http://192.168.164.12:81/ricewiki/api.php?action=feedcontributions&feedformat=atom&user=Rice2012 2026-05-25T12:08:26Z User contributions MediaWiki 1.30.0 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=IC4R001-GWAS-2011-21829395&diff=270093 2016-06-21T08:38:51Z

<p>Rice2012: /* The Background of This Project */</p> <hr /> <div>== Project Title ==<br /> ''' Genetic Architecture of Aluminum Tolerance in Rice( Oryza sativa ) Determined through Genome-Wide Association Analysis and QTL Mapping '''<br /> <br /> ==The Background of This Project==<br /> * While rice (Oryza sativa) is significantly more Al tolerant than other cereals, no genes underlying Al tolerance in rice have been reported. Using genome-wide association(GWA) and bi-parental QTL mapping, we investigated the genetic architecture of Al tolerance in rice. Japonica varieties were twice as Al tolerant as indica and aus varieties. Overall, 57% of the phenotypic variation was correlated with subpopulation, consistent with observations that different genes and genomic regions were associated with Al tolerance in different subpopulations. Four regions identified by GWA co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified quantitative trait loci(QTL). Haplotype and sequence analysis around the candidate gene, Nrat1, identified a susceptible haplotype explaining 40% of the Al tolerance variation within the aus subpopulation and three non-synonymous mutations within Nrat1 that were predictive of Al sensitivity. Using Indica 6 Japonica mapping populations, we identified QTLs associated with transgressive variation where alleles from a susceptible indica or aus parent enhanced Al tolerance in a tolerant japonica background. This work demonstrates the importance of subpopulation in interpreting and manipulating complex traits in rice and provides a roadmap for breeders aiming to capture genetic value from phenotypically inferior lines.<br /> <br /> ==Plant Culture &amp; Treatment==<br /> * Plants were grown hydroponically in a growth chamber as described by Famoso et al. [8]. Al tolerance was determined based on relative root growth (RRG) after three days in Al (160 m M Al 3+ ) or control solution. The hydroponic solution used in this study was chemically designed and optimized for rice Al tolerance screening; for a detailed comparison of the phenotypic procedures employed in this work compared to previously published rice Al tolerance work see Famoso et al. (2010). To obtain uniform seedlings, 80 seeds were germinated and the 30 most uniform seedlings were visually selected and transferred to a control hydroponic solution for a 24 hour adjustment period. After the 24 hour adjustment period, root length was measured with a ruler and the 20 most uniform seedlings were selected and distributed to fresh control solution (0 uM Al 3+ ) or Al treatment solution (160 uM Al 3+ ). Plants were grown in their respective treatments for ,72 hours and the total root system growth was quantified using an imaging and root quantification system as described by Famoso et al.(2010). The mean total root growth was calculated for Al treated and control plants and RRG was calculated as mean growth (Al)/mean growth (control). The 373 genotypes screened for Al tolerance and used in the association analysis are part of a set of 400 O. sativa genotypes that have been genotyped with 44,000 SNPs as described by Zhao et al. [65].<br /> <br /> ==Research Findings==<br /> * Two immortalized QTL mapping populations were analyzed for Al tolerance. One consisted of 134 recombinant inbred lines (RIL) derived from the cross IR64/Azucena , and the other was comprised of 78 backcross inbred lines (BIL) derived from the cross Nipponbare/Kasalath//Nipponbare. These popula- tions were used to evaluate Al tolerance using three different indices of relative root growth (RRG), (1) longest root growth (LRG-RRG), (2) primary root growth (PGR-RRG) and total root growth (TRG-RRG) (see Materials and Methods for details). The phenotypic distribution was approximately normal for each population, no matter which root screening index was used. The QTL mapping populations allowed us to determine which of the three root evaluation methods would be most useful for evaluating the diversity panel as a whole.&lt;br&gt;&lt;br&gt;<br /> <br /> == Labs working on this Project ==<br /> * Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America<br /> * Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America<br /> * Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, US Department of Agriculture, Cornell University, Ithaca, New York, United States of America<br /> <br /> ==Corresponding Author==<br /> ''' Susan R. McCouch'''(srm4@cornell.edu)</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=IC4R001-GWAS-2011-21829395&diff=270092 2016-06-21T08:38:42Z

<p>Rice2012: /* Plant Culture &amp; Treatment */</p> <hr /> <div>== Project Title ==<br /> ''' Genetic Architecture of Aluminum Tolerance in Rice( Oryza sativa ) Determined through Genome-Wide Association Analysis and QTL Mapping '''<br /> <br /> ==The Background of This Project==<br /> While rice (Oryza sativa) is significantly more Al tolerant than other cereals, no genes underlying Al tolerance in rice have been reported. Using genome-wide association(GWA) and bi-parental QTL mapping, we investigated the genetic architecture of Al tolerance in rice. Japonica varieties were twice as Al tolerant as indica and aus varieties. Overall, 57% of the phenotypic variation was correlated with subpopulation, consistent with observations that different genes and genomic regions were associated with Al tolerance in different subpopulations. Four regions identified by GWA co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified quantitative trait loci(QTL). Haplotype and sequence analysis around the candidate gene, Nrat1, identified a susceptible haplotype explaining 40% of the Al tolerance variation within the aus subpopulation and three non-synonymous mutations within Nrat1 that were predictive of Al sensitivity. Using Indica 6 Japonica mapping populations, we identified QTLs associated with transgressive variation where alleles from a susceptible indica or aus parent enhanced Al tolerance in a tolerant japonica background. This work demonstrates the importance of subpopulation in interpreting and manipulating complex traits in rice and provides a roadmap for breeders aiming to capture genetic value from phenotypically inferior lines.<br /> <br /> ==Plant Culture &amp; Treatment==<br /> * Plants were grown hydroponically in a growth chamber as described by Famoso et al. [8]. Al tolerance was determined based on relative root growth (RRG) after three days in Al (160 m M Al 3+ ) or control solution. The hydroponic solution used in this study was chemically designed and optimized for rice Al tolerance screening; for a detailed comparison of the phenotypic procedures employed in this work compared to previously published rice Al tolerance work see Famoso et al. (2010). To obtain uniform seedlings, 80 seeds were germinated and the 30 most uniform seedlings were visually selected and transferred to a control hydroponic solution for a 24 hour adjustment period. After the 24 hour adjustment period, root length was measured with a ruler and the 20 most uniform seedlings were selected and distributed to fresh control solution (0 uM Al 3+ ) or Al treatment solution (160 uM Al 3+ ). Plants were grown in their respective treatments for ,72 hours and the total root system growth was quantified using an imaging and root quantification system as described by Famoso et al.(2010). The mean total root growth was calculated for Al treated and control plants and RRG was calculated as mean growth (Al)/mean growth (control). The 373 genotypes screened for Al tolerance and used in the association analysis are part of a set of 400 O. sativa genotypes that have been genotyped with 44,000 SNPs as described by Zhao et al. [65].<br /> <br /> ==Research Findings==<br /> * Two immortalized QTL mapping populations were analyzed for Al tolerance. One consisted of 134 recombinant inbred lines (RIL) derived from the cross IR64/Azucena , and the other was comprised of 78 backcross inbred lines (BIL) derived from the cross Nipponbare/Kasalath//Nipponbare. These popula- tions were used to evaluate Al tolerance using three different indices of relative root growth (RRG), (1) longest root growth (LRG-RRG), (2) primary root growth (PGR-RRG) and total root growth (TRG-RRG) (see Materials and Methods for details). The phenotypic distribution was approximately normal for each population, no matter which root screening index was used. The QTL mapping populations allowed us to determine which of the three root evaluation methods would be most useful for evaluating the diversity panel as a whole.&lt;br&gt;&lt;br&gt;<br /> <br /> == Labs working on this Project ==<br /> * Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America<br /> * Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America<br /> * Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, US Department of Agriculture, Cornell University, Ithaca, New York, United States of America<br /> <br /> ==Corresponding Author==<br /> ''' Susan R. McCouch'''(srm4@cornell.edu)</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=IC4R001-GWAS-2011-21829395&diff=270091 2016-06-21T08:38:21Z

<p>Rice2012: /* Plant Culture &amp; Treatment */</p> <hr /> <div>== Project Title ==<br /> ''' Genetic Architecture of Aluminum Tolerance in Rice( Oryza sativa ) Determined through Genome-Wide Association Analysis and QTL Mapping '''<br /> <br /> ==The Background of This Project==<br /> While rice (Oryza sativa) is significantly more Al tolerant than other cereals, no genes underlying Al tolerance in rice have been reported. Using genome-wide association(GWA) and bi-parental QTL mapping, we investigated the genetic architecture of Al tolerance in rice. Japonica varieties were twice as Al tolerant as indica and aus varieties. Overall, 57% of the phenotypic variation was correlated with subpopulation, consistent with observations that different genes and genomic regions were associated with Al tolerance in different subpopulations. Four regions identified by GWA co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified quantitative trait loci(QTL). Haplotype and sequence analysis around the candidate gene, Nrat1, identified a susceptible haplotype explaining 40% of the Al tolerance variation within the aus subpopulation and three non-synonymous mutations within Nrat1 that were predictive of Al sensitivity. Using Indica 6 Japonica mapping populations, we identified QTLs associated with transgressive variation where alleles from a susceptible indica or aus parent enhanced Al tolerance in a tolerant japonica background. This work demonstrates the importance of subpopulation in interpreting and manipulating complex traits in rice and provides a roadmap for breeders aiming to capture genetic value from phenotypically inferior lines.<br /> <br /> ==Plant Culture &amp; Treatment==<br /> Plants were grown hydroponically in a growth chamber as described by Famoso et al. [8]. Al tolerance was determined based on relative root growth (RRG) after three days in Al (160 m M Al 3+ ) or control solution. The hydroponic solution used in this study was chemically designed and optimized for rice Al tolerance screening; for a detailed comparison of the phenotypic procedures employed in this work compared to previously published rice Al tolerance work see Famoso et al. (2010). To obtain uniform seedlings, 80 seeds were germinated and the 30 most uniform seedlings were visually selected and transferred to a control hydroponic solution for a 24 hour adjustment period. After the 24 hour adjustment period, root length was measured with a ruler and the 20 most uniform seedlings were selected and distributed to fresh control solution (0 uM Al 3+ ) or Al treatment solution (160 uM Al 3+ ). Plants were grown in their respective treatments for ,72 hours and the total root system growth was quantified using an imaging and root quantification system as described by Famoso et al.(2010). The mean total root growth was calculated for Al treated and control plants and RRG was calculated as mean growth (Al)/mean growth (control). The 373 genotypes screened for Al tolerance and used in the association analysis are part of a set of 400 O. sativa genotypes that have been genotyped with 44,000 SNPs as described by Zhao et al. [65].<br /> <br /> ==Research Findings==<br /> * Two immortalized QTL mapping populations were analyzed for Al tolerance. One consisted of 134 recombinant inbred lines (RIL) derived from the cross IR64/Azucena , and the other was comprised of 78 backcross inbred lines (BIL) derived from the cross Nipponbare/Kasalath//Nipponbare. These popula- tions were used to evaluate Al tolerance using three different indices of relative root growth (RRG), (1) longest root growth (LRG-RRG), (2) primary root growth (PGR-RRG) and total root growth (TRG-RRG) (see Materials and Methods for details). The phenotypic distribution was approximately normal for each population, no matter which root screening index was used. The QTL mapping populations allowed us to determine which of the three root evaluation methods would be most useful for evaluating the diversity panel as a whole.&lt;br&gt;&lt;br&gt;<br /> <br /> == Labs working on this Project ==<br /> * Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America<br /> * Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America<br /> * Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, US Department of Agriculture, Cornell University, Ithaca, New York, United States of America<br /> <br /> ==Corresponding Author==<br /> ''' Susan R. McCouch'''(srm4@cornell.edu)</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=IC4R001-GWAS-2011-21829395&diff=270090 2016-06-21T08:38:03Z

<p>Rice2012: /* Plant Culture &amp; Treatment */</p> <hr /> <div>== Project Title ==<br /> ''' Genetic Architecture of Aluminum Tolerance in Rice( Oryza sativa ) Determined through Genome-Wide Association Analysis and QTL Mapping '''<br /> <br /> ==The Background of This Project==<br /> While rice (Oryza sativa) is significantly more Al tolerant than other cereals, no genes underlying Al tolerance in rice have been reported. Using genome-wide association(GWA) and bi-parental QTL mapping, we investigated the genetic architecture of Al tolerance in rice. Japonica varieties were twice as Al tolerant as indica and aus varieties. Overall, 57% of the phenotypic variation was correlated with subpopulation, consistent with observations that different genes and genomic regions were associated with Al tolerance in different subpopulations. Four regions identified by GWA co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified quantitative trait loci(QTL). Haplotype and sequence analysis around the candidate gene, Nrat1, identified a susceptible haplotype explaining 40% of the Al tolerance variation within the aus subpopulation and three non-synonymous mutations within Nrat1 that were predictive of Al sensitivity. Using Indica 6 Japonica mapping populations, we identified QTLs associated with transgressive variation where alleles from a susceptible indica or aus parent enhanced Al tolerance in a tolerant japonica background. This work demonstrates the importance of subpopulation in interpreting and manipulating complex traits in rice and provides a roadmap for breeders aiming to capture genetic value from phenotypically inferior lines.<br /> <br /> ==Plant Culture &amp; Treatment==<br /> Plants were grown hydroponically in a growth chamber as described by Famoso et al. [8]. Al tolerance was determined based on relative root growth (RRG) after three days in Al (160 m M Al 3+ ) or control solution. The hydroponic solution used in this study was chemically designed and optimized for rice Al tolerance screening; for a detailed comparison of the phenotypic procedures employed in this work compared to previously published rice Al tolerance work see Famoso et al. (2010). To obtain uniform seedlings, 80 seeds were germinated and the 30 most uniform seedlings were visually selected and transferred to a control hydroponic solution for a 24 hour adjustment period. After the 24 hour adjustment period, root length was measured with a ruler and the 20 most uniform seedlings were selected and distributed to fresh control solution (0 uM Al 3+ ) or Al treatment solution (160 uM Al 3+ ). Plants were grown in their respective treatments for ,72 hours and the total root system growth was quantified using an imaging and root quantification system as described by Famoso et al.(2010). The mean total root growth was calculated for Al treated and control plants and RRG was calculated as mean growth (Al)/mean growth (control). The 373 genotypes screened for Al tolerance and used in the association analysis are part of a set of 400 O. sativa genotypes that have been genotyped with 44,000 SNPs as described by Zhao et al. [65].<br /> [[File: IC4R-Epigenomic-overview-1.png|right|thumb|870px|'''Figure 1. Models of epigenetic mark changes over genes induced by environmental signals (A), and transposons induced by stresses in rice (B).''']]<br /> <br /> ==Research Findings==<br /> * Two immortalized QTL mapping populations were analyzed for Al tolerance. One consisted of 134 recombinant inbred lines (RIL) derived from the cross IR64/Azucena , and the other was comprised of 78 backcross inbred lines (BIL) derived from the cross Nipponbare/Kasalath//Nipponbare. These popula- tions were used to evaluate Al tolerance using three different indices of relative root growth (RRG), (1) longest root growth (LRG-RRG), (2) primary root growth (PGR-RRG) and total root growth (TRG-RRG) (see Materials and Methods for details). The phenotypic distribution was approximately normal for each population, no matter which root screening index was used. The QTL mapping populations allowed us to determine which of the three root evaluation methods would be most useful for evaluating the diversity panel as a whole.&lt;br&gt;&lt;br&gt;<br /> <br /> == Labs working on this Project ==<br /> * Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America<br /> * Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America<br /> * Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, US Department of Agriculture, Cornell University, Ithaca, New York, United States of America<br /> <br /> ==Corresponding Author==<br /> ''' Susan R. McCouch'''(srm4@cornell.edu)</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=IC4R001-GWAS-2011-21829395&diff=270089 2016-06-21T08:37:53Z

<p>Rice2012: /* Plant Culture &amp; Treatment */</p> <hr /> <div>== Project Title ==<br /> ''' Genetic Architecture of Aluminum Tolerance in Rice( Oryza sativa ) Determined through Genome-Wide Association Analysis and QTL Mapping '''<br /> <br /> ==The Background of This Project==<br /> While rice (Oryza sativa) is significantly more Al tolerant than other cereals, no genes underlying Al tolerance in rice have been reported. Using genome-wide association(GWA) and bi-parental QTL mapping, we investigated the genetic architecture of Al tolerance in rice. Japonica varieties were twice as Al tolerant as indica and aus varieties. Overall, 57% of the phenotypic variation was correlated with subpopulation, consistent with observations that different genes and genomic regions were associated with Al tolerance in different subpopulations. Four regions identified by GWA co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified quantitative trait loci(QTL). Haplotype and sequence analysis around the candidate gene, Nrat1, identified a susceptible haplotype explaining 40% of the Al tolerance variation within the aus subpopulation and three non-synonymous mutations within Nrat1 that were predictive of Al sensitivity. Using Indica 6 Japonica mapping populations, we identified QTLs associated with transgressive variation where alleles from a susceptible indica or aus parent enhanced Al tolerance in a tolerant japonica background. This work demonstrates the importance of subpopulation in interpreting and manipulating complex traits in rice and provides a roadmap for breeders aiming to capture genetic value from phenotypically inferior lines.<br /> <br /> ==Plant Culture &amp; Treatment==<br /> Plants were grown hydroponically in a growth chamber as described by Famoso et al. [8]. Al tolerance was determined based on relative root growth (RRG) after three days in Al (160 m M Al 3+ ) or control solution. The hydroponic solution used in this study was chemically designed and optimized for rice Al tolerance screening; for a detailed comparison of the phenotypic procedures employed in this work compared to previously published rice Al tolerance work see Famoso et al. (2010). To obtain uniform seedlings, 80 seeds were germinated and the 30 most uniform seedlings were visually selected and transferred to a control hydroponic solution for a 24 hour adjustment period. After the 24 hour adjustment period, root length was measured with a ruler and the 20 most uniform seedlings were selected and distributed to fresh control solution (0 uM Al 3+ ) or Al treatment solution (160 uM Al 3+ ). Plants were grown in their respective treatments for ,72 hours and the total root system growth was quantified using an imaging and root quantification system as described by Famoso et al.(2010). The mean total root growth was calculated for Al treated and control plants and RRG was calculated as mean growth (Al)/mean growth (control). The 373 genotypes screened for Al tolerance and used in the association analysis are part of a set of 400 O. sativa genotypes that have been genotyped with 44,000 SNPs as described by Zhao et al. [65].<br /> [[File: IC4R-Epigenomic-overview-1.png|left|thumb|870px|'''Figure 1. Models of epigenetic mark changes over genes induced by environmental signals (A), and transposons induced by stresses in rice (B).''']]<br /> <br /> ==Research Findings==<br /> * Two immortalized QTL mapping populations were analyzed for Al tolerance. One consisted of 134 recombinant inbred lines (RIL) derived from the cross IR64/Azucena , and the other was comprised of 78 backcross inbred lines (BIL) derived from the cross Nipponbare/Kasalath//Nipponbare. These popula- tions were used to evaluate Al tolerance using three different indices of relative root growth (RRG), (1) longest root growth (LRG-RRG), (2) primary root growth (PGR-RRG) and total root growth (TRG-RRG) (see Materials and Methods for details). The phenotypic distribution was approximately normal for each population, no matter which root screening index was used. The QTL mapping populations allowed us to determine which of the three root evaluation methods would be most useful for evaluating the diversity panel as a whole.&lt;br&gt;&lt;br&gt;<br /> <br /> == Labs working on this Project ==<br /> * Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America<br /> * Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America<br /> * Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, US Department of Agriculture, Cornell University, Ithaca, New York, United States of America<br /> <br /> ==Corresponding Author==<br /> ''' Susan R. McCouch'''(srm4@cornell.edu)</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=IC4R001-GWAS-2011-21829395&diff=270088 2016-06-21T08:37:45Z

<p>Rice2012: /* Plant Culture &amp; Treatment */</p> <hr /> <div>== Project Title ==<br /> ''' Genetic Architecture of Aluminum Tolerance in Rice( Oryza sativa ) Determined through Genome-Wide Association Analysis and QTL Mapping '''<br /> <br /> ==The Background of This Project==<br /> While rice (Oryza sativa) is significantly more Al tolerant than other cereals, no genes underlying Al tolerance in rice have been reported. Using genome-wide association(GWA) and bi-parental QTL mapping, we investigated the genetic architecture of Al tolerance in rice. Japonica varieties were twice as Al tolerant as indica and aus varieties. Overall, 57% of the phenotypic variation was correlated with subpopulation, consistent with observations that different genes and genomic regions were associated with Al tolerance in different subpopulations. Four regions identified by GWA co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified quantitative trait loci(QTL). Haplotype and sequence analysis around the candidate gene, Nrat1, identified a susceptible haplotype explaining 40% of the Al tolerance variation within the aus subpopulation and three non-synonymous mutations within Nrat1 that were predictive of Al sensitivity. Using Indica 6 Japonica mapping populations, we identified QTLs associated with transgressive variation where alleles from a susceptible indica or aus parent enhanced Al tolerance in a tolerant japonica background. This work demonstrates the importance of subpopulation in interpreting and manipulating complex traits in rice and provides a roadmap for breeders aiming to capture genetic value from phenotypically inferior lines.<br /> <br /> ==Plant Culture &amp; Treatment==<br /> Plants were grown hydroponically in a growth chamber as described by Famoso et al. [8]. Al tolerance was determined based on relative root growth (RRG) after three days in Al (160 m M Al 3+ ) or control solution. The hydroponic solution used in this study was chemically designed and optimized for rice Al tolerance screening; for a detailed comparison of the phenotypic procedures employed in this work compared to previously published rice Al tolerance work see Famoso et al. (2010). To obtain uniform seedlings, 80 seeds were germinated and the 30 most uniform seedlings were visually selected and transferred to a control hydroponic solution for a 24 hour adjustment period. After the 24 hour adjustment period, root length was measured with a ruler and the 20 most uniform seedlings were selected and distributed to fresh control solution (0 uM Al 3+ ) or Al treatment solution (160 uM Al 3+ ). Plants were grown in their respective treatments for ,72 hours and the total root system growth was quantified using an imaging and root quantification system as described by Famoso et al.(2010). The mean total root growth was calculated for Al treated and control plants and RRG was calculated as mean growth (Al)/mean growth (control). The 373 genotypes screened for Al tolerance and used in the association analysis are part of a set of 400 O. sativa genotypes that have been genotyped with 44,000 SNPs as described by Zhao et al. [65].<br /> [[File: IC4R-Epigenomic-overview-1.png|center|thumb|870px|'''Figure 1. Models of epigenetic mark changes over genes induced by environmental signals (A), and transposons induced by stresses in rice (B).''']]<br /> <br /> ==Research Findings==<br /> * Two immortalized QTL mapping populations were analyzed for Al tolerance. One consisted of 134 recombinant inbred lines (RIL) derived from the cross IR64/Azucena , and the other was comprised of 78 backcross inbred lines (BIL) derived from the cross Nipponbare/Kasalath//Nipponbare. These popula- tions were used to evaluate Al tolerance using three different indices of relative root growth (RRG), (1) longest root growth (LRG-RRG), (2) primary root growth (PGR-RRG) and total root growth (TRG-RRG) (see Materials and Methods for details). The phenotypic distribution was approximately normal for each population, no matter which root screening index was used. The QTL mapping populations allowed us to determine which of the three root evaluation methods would be most useful for evaluating the diversity panel as a whole.&lt;br&gt;&lt;br&gt;<br /> <br /> == Labs working on this Project ==<br /> * Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America<br /> * Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America<br /> * Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, US Department of Agriculture, Cornell University, Ithaca, New York, United States of America<br /> <br /> ==Corresponding Author==<br /> ''' Susan R. McCouch'''(srm4@cornell.edu)</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=IC4R001-GWAS-2011-21829395&diff=270087 2016-06-21T08:36:56Z

<p>Rice2012: /* Research Findings */</p> <hr /> <div>== Project Title ==<br /> ''' Genetic Architecture of Aluminum Tolerance in Rice( Oryza sativa ) Determined through Genome-Wide Association Analysis and QTL Mapping '''<br /> <br /> ==The Background of This Project==<br /> While rice (Oryza sativa) is significantly more Al tolerant than other cereals, no genes underlying Al tolerance in rice have been reported. Using genome-wide association(GWA) and bi-parental QTL mapping, we investigated the genetic architecture of Al tolerance in rice. Japonica varieties were twice as Al tolerant as indica and aus varieties. Overall, 57% of the phenotypic variation was correlated with subpopulation, consistent with observations that different genes and genomic regions were associated with Al tolerance in different subpopulations. Four regions identified by GWA co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified quantitative trait loci(QTL). Haplotype and sequence analysis around the candidate gene, Nrat1, identified a susceptible haplotype explaining 40% of the Al tolerance variation within the aus subpopulation and three non-synonymous mutations within Nrat1 that were predictive of Al sensitivity. Using Indica 6 Japonica mapping populations, we identified QTLs associated with transgressive variation where alleles from a susceptible indica or aus parent enhanced Al tolerance in a tolerant japonica background. This work demonstrates the importance of subpopulation in interpreting and manipulating complex traits in rice and provides a roadmap for breeders aiming to capture genetic value from phenotypically inferior lines.<br /> <br /> ==Plant Culture &amp; Treatment==<br /> Plants were grown hydroponically in a growth chamber as described by Famoso et al. [8]. Al tolerance was determined based on relative root growth (RRG) after three days in Al (160 m M Al 3+ ) or control solution. The hydroponic solution used in this study was chemically designed and optimized for rice Al tolerance screening; for a detailed comparison of the phenotypic procedures employed in this work compared to previously published rice Al tolerance work see Famoso et al. (2010). To obtain uniform seedlings, 80 seeds were germinated and the 30 most uniform seedlings were visually selected and transferred to a control hydroponic solution for a 24 hour adjustment period. After the 24 hour adjustment period, root length was measured with a ruler and the 20 most uniform seedlings were selected and distributed to fresh control solution (0 uM Al 3+ ) or Al treatment solution (160 uM Al 3+ ). Plants were grown in their respective treatments for ,72 hours and the total root system growth was quantified using an imaging and root quantification system as described by Famoso et al.(2010). The mean total root growth was calculated for Al treated and control plants and RRG was calculated as mean growth (Al)/mean growth (control). The 373 genotypes screened for Al tolerance and used in the association analysis are part of a set of 400 O. sativa genotypes that have been genotyped with 44,000 SNPs as described by Zhao et al. [65].<br /> <br /> ==Research Findings==<br /> * Two immortalized QTL mapping populations were analyzed for Al tolerance. One consisted of 134 recombinant inbred lines (RIL) derived from the cross IR64/Azucena , and the other was comprised of 78 backcross inbred lines (BIL) derived from the cross Nipponbare/Kasalath//Nipponbare. These popula- tions were used to evaluate Al tolerance using three different indices of relative root growth (RRG), (1) longest root growth (LRG-RRG), (2) primary root growth (PGR-RRG) and total root growth (TRG-RRG) (see Materials and Methods for details). The phenotypic distribution was approximately normal for each population, no matter which root screening index was used. The QTL mapping populations allowed us to determine which of the three root evaluation methods would be most useful for evaluating the diversity panel as a whole.&lt;br&gt;&lt;br&gt;<br /> <br /> == Labs working on this Project ==<br /> * Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America<br /> * Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America<br /> * Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, US Department of Agriculture, Cornell University, Ithaca, New York, United States of America<br /> <br /> ==Corresponding Author==<br /> ''' Susan R. McCouch'''(srm4@cornell.edu)</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270086 2016-06-21T08:31:49Z

<p>Rice2012: /* References */</p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Metabolomics]]'''==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[Metabolomics|'''(More...)''']]<br /> <br /> =='''[[Phenomics]]'''==<br /> [[File:IC4R-Phenomics-overview-3.png|right|thumb|97px]] <br /> * Phenomics is an area of biology concerned with the measurement of phenomes—the physical and biochemical traits of organisms—as they change in response to genetic mutation and environmental influences. It is used in functional genomics, pharmaceutical research, metabolic engineering and increasingly in phylogenetics. Plant phenomics is the study of plant growth, performance and composition. Forward phenomics uses phenotyping tools to 'sieve' collections of germplasm for valuable traits. The sieve or screen could be high-throughput and fully automated and low resolution, [[Phenomics|'''(More...)''']]<br /> <br /> =='''References'''==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref5&quot;&gt;<br /> McGettigan, Paul A. &quot;Transcriptomics in the RNA-seq era.&quot; Current opinion in chemical biology 17.1 (2013): 4-11.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref6&quot;&gt;<br /> Piétu, Geneviève, et al. &quot;The Genexpress IMAGE knowledge base of the human brain transcriptome: a prototype integrated resource for functional and computational genomics.&quot; Genome research 9.2 (1999): 195-209.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref7&quot;&gt;<br /> Velculescu, Victor E., et al. &quot;Characterization of the yeast transcriptome.&quot; Cell 88.2 (1997): 243-251.<br /> &lt;/ref&gt;<br /> <br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270082 2016-06-21T08:07:45Z

<p>Rice2012: /* Interactomics */</p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Metabolomics]]'''==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[Metabolomics|'''(More...)''']]<br /> <br /> =='''[[Phenomics]]'''==<br /> [[File:IC4R-Phenomics-overview-3.png|right|thumb|97px]] <br /> * Phenomics is an area of biology concerned with the measurement of phenomes—the physical and biochemical traits of organisms—as they change in response to genetic mutation and environmental influences. It is used in functional genomics, pharmaceutical research, metabolic engineering and increasingly in phylogenetics. Plant phenomics is the study of plant growth, performance and composition. Forward phenomics uses phenotyping tools to 'sieve' collections of germplasm for valuable traits. The sieve or screen could be high-throughput and fully automated and low resolution, [[Phenomics|'''(More...)''']]<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref5&quot;&gt;<br /> McGettigan, Paul A. &quot;Transcriptomics in the RNA-seq era.&quot; Current opinion in chemical biology 17.1 (2013): 4-11.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref6&quot;&gt;<br /> Piétu, Geneviève, et al. &quot;The Genexpress IMAGE knowledge base of the human brain transcriptome: a prototype integrated resource for functional and computational genomics.&quot; Genome research 9.2 (1999): 195-209.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref7&quot;&gt;<br /> Velculescu, Victor E., et al. &quot;Characterization of the yeast transcriptome.&quot; Cell 88.2 (1997): 243-251.<br /> &lt;/ref&gt;<br /> <br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270080 2016-06-21T08:03:00Z

<p>Rice2012: /* References */</p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Metabolomics]]'''==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[Metabolomics|'''(More...)''']]<br /> <br /> =='''[[Interactomics]]'''==<br /> <br /> =='''[[Phenomics]]'''==<br /> [[File:IC4R-Phenomics-overview-3.png|right|thumb|97px]] <br /> * Phenomics is an area of biology concerned with the measurement of phenomes—the physical and biochemical traits of organisms—as they change in response to genetic mutation and environmental influences. It is used in functional genomics, pharmaceutical research, metabolic engineering and increasingly in phylogenetics. Plant phenomics is the study of plant growth, performance and composition. Forward phenomics uses phenotyping tools to 'sieve' collections of germplasm for valuable traits. The sieve or screen could be high-throughput and fully automated and low resolution, [[Phenomics|'''(More...)''']]<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref5&quot;&gt;<br /> McGettigan, Paul A. &quot;Transcriptomics in the RNA-seq era.&quot; Current opinion in chemical biology 17.1 (2013): 4-11.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref6&quot;&gt;<br /> Piétu, Geneviève, et al. &quot;The Genexpress IMAGE knowledge base of the human brain transcriptome: a prototype integrated resource for functional and computational genomics.&quot; Genome research 9.2 (1999): 195-209.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref7&quot;&gt;<br /> Velculescu, Victor E., et al. &quot;Characterization of the yeast transcriptome.&quot; Cell 88.2 (1997): 243-251.<br /> &lt;/ref&gt;<br /> <br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270079 2016-06-21T07:55:03Z

<p>Rice2012: </p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Metabolomics]]'''==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[Metabolomics|'''(More...)''']]<br /> <br /> =='''[[Interactomics]]'''==<br /> <br /> =='''[[Phenomics]]'''==<br /> [[File:IC4R-Phenomics-overview-3.png|right|thumb|97px]] <br /> * Phenomics is an area of biology concerned with the measurement of phenomes—the physical and biochemical traits of organisms—as they change in response to genetic mutation and environmental influences. It is used in functional genomics, pharmaceutical research, metabolic engineering and increasingly in phylogenetics. Plant phenomics is the study of plant growth, performance and composition. Forward phenomics uses phenotyping tools to 'sieve' collections of germplasm for valuable traits. The sieve or screen could be high-throughput and fully automated and low resolution, [[Phenomics|'''(More...)''']]<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Main_Page&diff=270078 2016-06-21T07:51:29Z

<p>Rice2012: </p> <hr /> <div>__NOTITLE__<br /> __NOTOC__<br /> __NOEDITSECTION__<br /> &lt;!-----------------title---------------------&gt;<br /> {|style=&quot;width:100%; margin-top:10px; background-color:#f6f6f6; border:1px solid #d2d2d2; margin-bottom: 10px;&quot;<br /> |style=&quot;width:50%; text-align:center; white-space:nowrap; color:#000&quot;|<br /> &lt;div style=&quot;font-size:180%; border:none; margin:0; padding:.5em; color:#000;&quot;&gt;Welcome to RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%&quot;&gt;[[:Category:Genes |86,216]] rice genes inside&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%; color:#492;&quot;&gt;'''Contribute your efforts, further our knowledge.'''&lt;/div&gt;<br /> <br /> |style=&quot;width:18%;|<br /> *&lt;span class=plainlinks&gt;[[:Category:Genes|Genes]]&lt;/span&gt;<br /> *[[RiceWiki:GeneFamilies|Gene Families]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Chromosomes|Chromosomes]]<br /> *[[RiceWiki:Databases|Databases]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Genome_Browser|Genome Browser]]<br /> *[[RiceWiki:Templates|Templates]]<br /> |}<br /> <br /> &lt;!---------------welcome Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f1f1f1; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Introduction&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;{{:RiceWiki:Summary}}&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.2em 0.5em;text-align:center&quot;&gt;''Nothing great is ever accomplished in isolation. – Yo-Yo Ma''&lt;/div&gt;<br /> ----<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> {|<br /> |<br /> *Featured genes: [[Os01g0883800]], [[Os02g0170300]], [[Os03g0149100]], [[Os08g0162100]]<br /> *Stress-related genes: [[RiceWiki:Stress|a list of stress-related genes]]<br /> *Genes to be curated: [[RiceWiki:TBC|a list of genes to be curated]]<br /> |<br /> *Curated genes: More than [[Curated Genes|''' 500 Rice Genes''']] have been curated.<br /> *'''[[Omics Knowledge Portal for Rice]]''': Sharing and Integrating the precious omics knowledge for rice.<br /> *Contribution score: [[Special:AuthorReward |quantified contributions]] by [http://www.ncbi.nlm.nih.gov/pubmed/23732274 ''AuthorReward'']<br /> |<br /> *Literature: [http://literature.ic4r.org 31527] rice-related publications associated with rice genes<br /> *Transcriptome: gene expression profiles at 22 developmental stages and tissue types based on RNA-Seq<br /> *Variations: SNPs and INDELs (under collection)<br /> |}<br /> &lt;/div&gt;<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;RiceWiki Award Winners in 2014&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:2014Award1.JPG|right|thumb|200px|link=RiceWiki:Awards]]<br /> *2014 Outstanding Award: SHI Junchao (侍骏超), Contribution Score: 190.164, Award: an iPad mini with Retina Display<br /> *2014 Excellent Award: HUANG Huasheng (黄华生), Contribution Score: 189.713, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: SONG Yafeng (宋亚凤), Contribution Score: 64.476, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: PAN Wenbo (潘文波), Contribution Score: 52.352, Award: XiaoMi Portable WiFi <br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part one----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------Rice Genome Overview------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent; width:30%;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Genome Overview&lt;/div&gt;<br /> &lt;div style=&quot;padding:1em 0em 0em 0em; text-align:center;&quot;&gt;[[image:RiceG.jpg]]&lt;/div&gt;<br /> == ==<br /> &lt;div style=&quot;padding:0.2em 0.5em;&quot;&gt;<br /> ====[[:Category:Japonica Genes | ''Oryza sativa Japonica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Japonica Chromosome 1|'''1''']].<br /> [[:category:Japonica Chromosome 2|'''2''']].<br /> [[:category:Japonica Chromosome 3|'''3''']].<br /> [[:category:Japonica Chromosome 4|'''4''']].<br /> [[:category:Japonica Chromosome 5|'''5''']].<br /> [[:category:Japonica Chromosome 6|'''6''']].<br /> [[:category:Japonica Chromosome 7|'''7''']].<br /> [[:category:Japonica Chromosome 8|'''8''']].<br /> [[:category:Japonica Chromosome 9|'''9''']].<br /> [[:category:Japonica Chromosome 10|'''10''']].<br /> [[:category:Japonica Chromosome 11|'''11''']].<br /> [[:category:Japonica Chromosome 12|'''12''']].<br /> [[:category:Japonica_Mitochondrion|'''Mt''']].<br /> [[:category:Japonica_Plastid|'''Pd''']]<br /> <br /> ====[[:Category:Indica Genes | ''Oryza sativa Indica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Indica Chromosome 1|'''1''']].<br /> [[:category:Indica Chromosome 2|'''2''']].<br /> [[:category:Indica Chromosome 3|'''3''']].<br /> [[:category:Indica Chromosome 4|'''4''']].<br /> [[:category:Indica Chromosome 5|'''5''']].<br /> [[:category:Indica Chromosome 6|'''6''']].<br /> [[:category:Indica Chromosome 7|'''7''']].<br /> [[:category:Indica Chromosome 8|'''8''']].<br /> [[:category:Indica Chromosome 9|'''9''']].<br /> [[:category:Indica Chromosome 10|'''10''']].<br /> [[:category:Indica Chromosome 11|'''11''']].<br /> [[:category:Indica Chromosome 12|'''12''']]<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Rice----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Story&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:Damifan.jpg|right|120px|margin: 5px|]]<br /> *As an important food<br /> :Rice is the seed of the monocot plants ''Oryza sativa'' (Asian rice) or ''Oryza glaberrima'' (African rice). As a cereal grain, it is the most important staple food for a large part of the world's human population, especially in East Asia, Southeast Asia, South Asia, the Middle East, and the West Indies. It is the grain with the third-highest worldwide production, after maize (corn) and wheat, according to data for 2010 [http://en.wikipedia.org/wiki/Rice (Full article...)].&lt;br&gt;<br /> *As a biological model<br /> :Rice is also a model organism for the biological study of the grass family of crops and other plants. The two most common rice cultivars, ''indica'' and ''japonica'', were completely sequenced in 2002. The genome sequences of domesticated rice provide a solid foundation for integrating biological information, including genetics, gene expression, development, physiology and evolution.&lt;/div&gt;<br /> ----<br /> {|style=&quot;border:none; background-color:transparent; width:100%&quot; <br /> |-style=&quot;background:transcript; color:black&quot; align=&quot;left&quot; valign=&quot;top&quot;<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Recent Modified Genes&lt;/div&gt; {{StatisticsActivity:type=edits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Highly Accessed Genes&lt;/div&gt; {{StatisticsActivity:type=visits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Most Annotated Genes&lt;/div&gt; {{StatisticsActivity:type=contributes|count = 10}}<br /> |}<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f4f4f4; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Publications&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/26519466 Information Commons for Rice (IC4R)] (2016) ''Nucleic Acids Research'', 44(D1):D1172-D1180.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/24136999 RiceWiki: a wiki-based database for community curation of rice genes] (2014) ''Nucleic Acids Research'', 42(D1),D1222-D1228.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/23732274 AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification] (2013) ''Bioinformatics'', 29(14):1837-1839.<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part two----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> &lt;!------------- Participating----------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:42%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Joining RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;<br /> * RiceWiki allows any user to view and search but only registered users can add and edit content. <br /> * To become a registered user, please email the RiceWiki Team at [mailto:ricewiki@big.ac.cn ricewiki@big.ac.cn] to tell us your preferred login name, real name, research interests, etc., and we will set up an account for you.<br /> * Please also spread this news to any one who might be of interest. [[File:Ppt_ico.gif | link=File:CommunityCuration-RiceWiki.pptx]]&lt;/div&gt;<br /> <br /> &lt;!-------------Lab Information--------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:33%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;About Us&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;Our group works in the field of [http://cbb.big.ac.cn Computational Biology and Bioinformatics] (CBB), currently with a particular focus on building biological knowledge wikis in aid of community curation of massive biological knowledge.<br /> &lt;/div&gt;<br /> <br /> &lt;!------------Visitor Statistics-------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Visitor Statistics&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;text-align:center&quot;&gt;<br /> &lt;htmlet nocache=&quot;yes&quot;&gt;earth&lt;/htmlet&gt;<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------Reward Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:60%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;[[RiceWiki:Awards|2015 RiceWiki Community Curation Awards]]&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> <br /> 为鼓励更多科研人员和学生参与水稻基因的审编工作，促进我国面向生物大数据的基础性研究人才培养，RiceWiki对符合参选资格条件的个人给予奖励，具体方法如下：<br /> <br /> # 本条例的有关奖项按年度进行评奖。<br /> # 参选资格条件：在2015年（即2015年1月1日至2015年12月31日）参与审编工作的个人（不包括RiceWiki团队中成员），其在本年度的总贡献值（Contribution Score）大于或等于50分（[[Special:AuthorReward | 用户贡献值查询]]）。<br /> # 符合上述参选资格条件的个人将在2016年1月集中进行评审。<br /> # 通过评审且贡献值最高的个人，免费获赠[http://www.mi.com/mipad 小米平板]及荣誉证书；凡是通过评审的个人，免费获赠[http://www.mi.com/wifi 小米随身]WiFi及荣誉证书。<br /> # 上述获奖信息将在RiceWiki网站进行公示。 <br /> <br /> 本条例的解释权属RiceWiki团队。<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------register Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------English------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:50%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;致全体参与者&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> *群体审编（Community Curation）是生物大数据整合和相关文献信息集成的重要方法之一（相关信息：[http://www.biocurator.org/what.shtml 国际生物审编协会]；[http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18769432/ Big data: The future of biocuration]）。<br /> *水稻是我国最重要的经济农作物之一，其数据知识库的建立可有利推动我国水稻的科学研究与应用转化，并影响国内其它相关领域的基础研究。<br /> *我国长期缺乏一个在国际上有一定影响力的数据库/中心，美国有NCBI，欧洲有EBI......<br /> *但是，你们现在所作的一点一滴正在改变这个现状，我们正在朝向建立面向我国重大需求且不同于现今国际生物数据中心的方向前进！<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Chinese----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;注册 &amp; 编辑&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * 请发送电子邮件至ricewiki(AT)big.ac.cn，并提供您的注册用户名（英文）、邮件地址(确保邮箱名正确)和真实姓名。<br /> * 您查收来自ricewiki(AT)big.ac.cn的邮件，里面有您的密码，请尽快登录并修改个人密码。如果两天内没有收到邮件，请检查垃圾邮箱。<br /> * 如果您确实没收到来自ricewiki(AT)big.ac.cn的邮件，请再次发送邮件联系ricewiki(AT)big.ac.cn。<br /> * 当多人在同一时间编辑同一页面时，会发生编辑冲突。建议每次编辑一小段内容并查看编辑历史。详细信息请查看：http://en.wikipedia.org/wiki/Help:Edit_conflict<br /> &lt;/div&gt;<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=File:IC4R-Phenomics-overview-3.png&diff=270077 2016-06-21T07:51:02Z

<p>Rice2012: </p> <hr /> <div></div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=File:IC4R-Phenomics-overview-2.png&diff=270076 2016-06-21T07:50:53Z

<p>Rice2012: </p> <hr /> <div></div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=File:IC4R-Phenomics-overview-1.png&diff=270075 2016-06-21T07:50:44Z

<p>Rice2012: </p> <hr /> <div></div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Phenomics&diff=270074 2016-06-21T07:50:24Z

<p>Rice2012: Created page with &quot;== What is Phenomics ?== '''Figure1. Plant phenomics is the study of plant growth, performance and composition''' * Ph...&quot;</p> <hr /> <div>== What is Phenomics ?==<br /> [[File:IC4R-Phenomics-overview-1.png|thumb|right|227px|'''Figure1. Plant phenomics is the study of plant growth, performance and composition''']]<br /> * Phenomics is an area of biology concerned with the measurement of phenomes—the physical and biochemical traits of organisms—as they change in response to genetic mutation and environmental influences. It is used in functional genomics, pharmaceutical research, metabolic engineering and increasingly in phylogenetics. Plant phenomics is the study of plant growth, performance and composition. <br /> *Forward phenomics uses phenotyping tools to 'sieve' collections of germplasm for valuable traits. The sieve or screen could be high-throughput and fully automated and low resolution, followed by higher-resolution, lower throughput measurements. Screens might include abiotic or biotic stress challenges and must be reproducible and of physiological relevance. Reverse phenomics is the detailed dissection of traits shown to be of value to reveal mechanistic understanding and allow exploitation of this mechanism in new approaches. This can involve reduction of a physiological trait to biochemical or biophysical processes and ultimately a gene or genes.<br /> <br /> ==Using plant phenomics to close the 'gene to genotype' loop==<br /> * An impressive array of tools is now available for high-throughput phenotyping and the approaches described above can be used in many different ways to facilitate the process of trait identification, gene identification and genotype development necessary to produce a new crop variety. Examples of how phenomics can be used to develop a crop genotype or variety with tolerance to a particular type of drought are presented in Figure 2.<br /> * In this scheme, phenomics features at a number of levels. ‘Forward’ phenomics can be used to identify pheno- typic, and thus genetic, variation in particular traits of interest (1 in Figure 2), for traits indicated as important and validated to be important by physiological studies (‘reverse phenomics’) of plants with differing drought tolerance (2 in Figure 2). This genetic approach can take the form of a large genotype screen using a bi-parental or multi-parent population, or by direct analysis of a ‘diversity panel’ of lines for analysis by association genetics. As discussed above, accurate, cost-effective 1 , high-throughput phenotyping is pivotal to fine mapping of traits, regardless of the genetic approach for producing allelic recombination or assessing variation by re-sequencing technologies.<br /> * Phenomics is also essential for good quality reverse genetic studies, to test hypotheses regarding the role of particular genes in the function of a plant (4 in Figure 2), and to test the effects of altering patterns, levels or alleles of target genes on the traits of germplasm (5 in Figure 2) and the drought tolerance of the resultant crop.<br /> [[File: IC4R-Phenomics-overview-3.png|center|thumb|970px|'''Figure 2. From plant phenotyping to phenomics. Plant phenotyping can be performed at multiple organizational levels, ranging from the field and canopy, to the whole-plant, organ, tissue, and cellular level (and eventually subcellular level). Phenotypic traits of interest can be categorized as physiological, structural, or performance-related. Plant phenotyping is the quantitative or qualitative investigation of these traits at any organizational level, in a given genomic expression state and a given environment. This is shown as a single column of yellow cubes, which could be positioned anywhere in the overall cube. A phenome corresponds to all possible phenotypes under different environmental conditions of a given genotype, represented by the combination of yellow and red cubes. Genomic expression states cover the complete range of available plant genetic resources (e.g., overexpresssion lines, mutants, natural accessions, and segregating populations). Plant phenomics could be considered as the study of phenomes of multiple genomic expression states, represented by the combination of yellow, red, and blue cubes. Light-colored cubes illustrate the (in principle) infinite possibilities of environmental conditions and genomic expression states. Notably, plant phenotypes can be assessed at specific times during development, or alternatively in a dynamic manner''']]<br /> <br /> ==Plant phenotyping is a complex matter involving a plethora of systems and tools==<br /> * 'Phenomics' has been proposed as a novel discipline in biology and involves the gathering of high-dimensional phenotypic data at multiple levels of organization, to progress towards the full characterization of the complete set of phenotypes of a genome, in analogy with whole genome sequencing [1]. This ultimate aim will of course remain hypothetical; however, current and future developments in plant phenotyping and phenomics may benefit from the consideration of dimensionality, together with throughput and resolution, because our comprehension of plant process- es in general, and the genotype–phenotype relationship in particular, is far from complete (Box 1). Plant phenotypes are inherently complex because they result from the interaction of genotypes with a multitude of environmental factors. This interaction influences on the one hand the developmental program and growth of plants, which can be described by means of structural traits, and, on the other hand, plant functioning, described by means of physiological traits (Figure 1). Both the structural and physiological traits eventually determine plant performance in terms of biomass and yield. Phenotypic traits at different organizational.<br /> [[File: IC4R-Phenomics-overview-2.png|center|thumb|970px|'''Figure 2. Closing the gene to genotype loop with phenomics.''']]<br /> <br /> ==Projects List==<br /> <br /> {|class=&quot;wikitable sortable&quot; style=&quot;width:100%;text-align:center&quot;<br /> |-<br /> !Project Title<br /> !Species<br /> !Published years<br /> !Academic Journal<br /> !RiceWiki Project ID<br /> |-<br /> |'''A phenomics approach detected differential epigenetic growth regulation between inbreds and their hybrid in Oryza sativa'''<br /> |''Oryza sativa''<br /> |2010<br /> |Mol Breeding<br /> |[[IC4R001-Phenomics-2010-X63158156]]<br /> |-<br /> |'''Phenomics of rice early vigour and drought response: Are sugar related and morphogenetic traits relevant?'''<br /> |''Oryza sativa''<br /> |2012<br /> |Rice<br /> |[[IC4R002-Phenomics-2012-24279832]]<br /> |-<br /> |'''A rice phenomics study—phenotype scoring and seed propagation of a T-DNA insertion-induced rice mutant population'''<br /> |''Oryza sativa''<br /> |2007<br /> |Plant Mol Biol<br /> |[[IC4R003-Phenomics-2007-17701278]]<br /> |-<br /> |'''Integrating Image-Based Phenomics and Associatio Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice'''<br /> |''Oryza sativa''<br /> |2015<br /> |Plant Physiology<br /> |[[IC4R004-Phenomics-2015-26111541]]<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270073 2016-06-21T07:50:09Z

<p>Rice2012: /* Phenomics */</p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Metabolomics]]'''==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[Metabolomics|'''(More...)''']]<br /> <br /> ==[[Interactomics]]==<br /> <br /> =='''[[Phenomics]]'''==<br /> [[File:IC4R-Phenomics-overview-3.png|right|thumb|97px]] <br /> * Phenomics is an area of biology concerned with the measurement of phenomes—the physical and biochemical traits of organisms—as they change in response to genetic mutation and environmental influences. It is used in functional genomics, pharmaceutical research, metabolic engineering and increasingly in phylogenetics. Plant phenomics is the study of plant growth, performance and composition. Forward phenomics uses phenotyping tools to 'sieve' collections of germplasm for valuable traits. The sieve or screen could be high-throughput and fully automated and low resolution, [[Phenomics|'''(More...)''']]<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270071 2016-06-21T07:31:03Z

<p>Rice2012: /* Epigenomic Studies in Rice */</p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Metabolomics]]'''==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[Metabolomics|'''(More...)''']]<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270070 2016-06-21T07:30:25Z

<p>Rice2012: /* Metabolomics */</p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]<br /> <br /> =='''[[Metabolomics]]'''==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[Metabolomics|'''(More...)''']]<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270069 2016-06-21T07:30:06Z

<p>Rice2012: /* Metabolomics */</p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]<br /> <br /> ==[[Metabolomics]]==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[Metabolomics|'''(More...)''']]<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270068 2016-06-21T07:29:44Z

<p>Rice2012: /* Metabolomics */</p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]<br /> <br /> ==[[Metabolomics]]==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, [[RNA-Seq Studies in Rice|'''(More...)''']]<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Metabolomics&diff=270067 2016-06-21T07:28:22Z

<p>Rice2012: /* Projects List */</p> <hr /> <div>==What is Metabolomics ?==<br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles.&lt;ref name=&quot;ref1&quot;/&gt; The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes.[2] mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to provide a better understanding of cellular biology.&lt;br&gt;&lt;br&gt;<br /> [[File: IC4R-Metabolomics-overview-1.png|center|thumb|970px|'''Figure 1. Integrated functional genomics. The effects of gene perturbations are evaluated at multiple levels including the transcriptome, proteome, and metabolome. Changes in the metabolome occur as a consequence of those changes in the transcriptome that result in changes in the levels or catalytic activities of enzymes. Therefore, metabolome analysis is a valuable tool for inferring gene function.''']]<br /> * Advances in mass spectrometry have enabled the analysis of cellular proteins and metabolites (proteome and metabolome respectively) on a scale previously unimaginable. The cumulative utilization of these technologies has advanced the fields of functional genomics (Holtorf et al., 2002; Oliver et al., 2002; Somerville and Somerville, 1999) and systems biology (Ideker et al., 2001; Kitano, 2000). Both fields comprise traditional molecular biology, enzymology and bio- chemistry; however, the predominant difference from previous approaches is the significantly larger scale upon which they are conducted.<br /> <br /> ==Limitations of metabolomics ==<br /> * The major limitation of metabolomics is its current inability to comprehensively profile all of the metabolome. This inability is directly related to the chemical complexity of the metabolome, the biological variance inherent in most living organisms, and the dynamic range limitations of most instrumental approaches. In many ways, this is similar to the situation of the Human Genome Project in 1990, when the technological means to sequence genomes were not yet available.<br /> ==Metabolome technologies==<br /> * It is generally accepted that a single analytical technique will not provide sufficient visualization of the metabolome and, therefore, multiple technologies are needed for a comprehensive view (Hall et al., 2002; Sumner et al., 2002). Accordingly, many analytical technologies have been enlisted to profile the metabolome. Methods based on infrared spectroscopy (IR) (Oliver et al., 1998), nuclear magnetic resonance (NMR(Bligny and Douce, 2001; Ratcliffe and Shachar-Hill,2001; Roberts, 2000), thin layer chromatography (TLC) (Tweeddale et al., 1998), HPLC with ultraviolet and photodiode array detection (LC/UV/PDA) (Fraser et al., 2000), capillary electrophoresis coupled to ultravio- let absorbance detection (CE/UV) (Baggett et al., 2002), capillary electrophoresis coupled to laser induced fluorescence detection (CE/LIF) (Arlt et al., 2001), capillary electrophoresis coupled to mass spectrometry (CE/MS) (Soga et al., 2002), gas chromatography-mass spectrometry (GC/MS), liquid chromatography-mass spectro- metry (LC/MS) (Huhman and Sumner, 2002), liquid chromatography tandem mass spectrometry (LC/MS/ MS) (Huhman and Sumner, 2002), Fourier transform ion cyclotron mass spectrometry (FTMS) (Aharoni et al., 2002), HPLC coupled with both mass spectrometry and nuclear magnetic resonance detection (LC/NMR/ MS) (Bailey et al., 2000a), and LC/NMR/MS/MS (Bai- ley et al., 2000b) have all been used.<br /> ==Projects List==<br /> <br /> {|class=&quot;wikitable sortable&quot; style=&quot;width:100%;text-align:center&quot;<br /> |-<br /> !Project Title<br /> !Species<br /> !Published years<br /> !Academic Journal<br /> !RiceWiki Project ID<br /> |-<br /> |'''Genetic analysis of the metabolome exemplified using a rice population'''<br /> |''Oryza sativa''<br /> |2013<br /> |Proceedings of the National Academy of Sciences<br /> |'''[[IC4R001-Metabolomics-2013-24259710]]'''<br /> |-<br /> |'''Folate fortification of rice by metabolic engineering'''<br /> |''Oryza sativa L. ssp. Japnoica''<br /> |2007<br /> |Nature Biotechnology<br /> |'''[[IC4R002-Metabolomics-2007-17934451]]'''<br /> |-<br /> |'''Characterization of Volatile Aroma Compounds in Cooked Black Rice'''<br /> |''Oryza sativa''<br /> |2007<br /> |Journal of Agricultural and Food Chemistry <br /> |'''[[IC4R003-Metabolomics-2007-18081248]]'''<br /> |-<br /> |'''A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress'''<br /> |''Oryza sativa''<br /> |2015<br /> |Analytical Biochemistry<br /> |'''[[IC4R004-Metabolomics-2015-25766578]]'''<br /> |-<br /> |'''Metabolomic screening applied to rice FOX Arabidopsis lines leads to the identification of a gene-changing nitrogen metabolism.'''<br /> |''Oryza sativa L. ssp. japonica''<br /> |2010<br /> |Molecular Plant<br /> |'''[[IC4R005-Metabolomics-2010-20085895]]'''<br /> |-<br /> |'''Application of a metabolomic method combining one-dimensional and two-dimensional gas chromatography-time-of-flight/mass spectrometry to metabolic phenotyping of natural variants in rice'''<br /> |''Oryza sativa L.''<br /> |2007<br /> |Journal of Chromatography B<br /> |'''[[IC4R006-Metabolomics-2007-17556050]]'''<br /> |-<br /> |'''Metabolic profiling of transgenic rice with cryIAc and sck genes: An evaluation of unintended effects at metabolic level by using GC-FID and GC–MS'''<br /> |''Oryza sativa L.''<br /> |2009<br /> |Journal of Chromatography B<br /> |'''[[IC4R007-Metabolomics-2009-19233746]]'''<br /> |}<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/Epigenome<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Metabolomics&diff=270066 2016-06-21T07:27:44Z

<p>Rice2012: /* What is Metabolomics ? */</p> <hr /> <div>==What is Metabolomics ?==<br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles.&lt;ref name=&quot;ref1&quot;/&gt; The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes.[2] mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to provide a better understanding of cellular biology.&lt;br&gt;&lt;br&gt;<br /> [[File: IC4R-Metabolomics-overview-1.png|center|thumb|970px|'''Figure 1. Integrated functional genomics. The effects of gene perturbations are evaluated at multiple levels including the transcriptome, proteome, and metabolome. Changes in the metabolome occur as a consequence of those changes in the transcriptome that result in changes in the levels or catalytic activities of enzymes. Therefore, metabolome analysis is a valuable tool for inferring gene function.''']]<br /> * Advances in mass spectrometry have enabled the analysis of cellular proteins and metabolites (proteome and metabolome respectively) on a scale previously unimaginable. The cumulative utilization of these technologies has advanced the fields of functional genomics (Holtorf et al., 2002; Oliver et al., 2002; Somerville and Somerville, 1999) and systems biology (Ideker et al., 2001; Kitano, 2000). Both fields comprise traditional molecular biology, enzymology and bio- chemistry; however, the predominant difference from previous approaches is the significantly larger scale upon which they are conducted.<br /> <br /> ==Limitations of metabolomics ==<br /> * The major limitation of metabolomics is its current inability to comprehensively profile all of the metabolome. This inability is directly related to the chemical complexity of the metabolome, the biological variance inherent in most living organisms, and the dynamic range limitations of most instrumental approaches. In many ways, this is similar to the situation of the Human Genome Project in 1990, when the technological means to sequence genomes were not yet available.<br /> ==Metabolome technologies==<br /> * It is generally accepted that a single analytical technique will not provide sufficient visualization of the metabolome and, therefore, multiple technologies are needed for a comprehensive view (Hall et al., 2002; Sumner et al., 2002). Accordingly, many analytical technologies have been enlisted to profile the metabolome. Methods based on infrared spectroscopy (IR) (Oliver et al., 1998), nuclear magnetic resonance (NMR(Bligny and Douce, 2001; Ratcliffe and Shachar-Hill,2001; Roberts, 2000), thin layer chromatography (TLC) (Tweeddale et al., 1998), HPLC with ultraviolet and photodiode array detection (LC/UV/PDA) (Fraser et al., 2000), capillary electrophoresis coupled to ultravio- let absorbance detection (CE/UV) (Baggett et al., 2002), capillary electrophoresis coupled to laser induced fluorescence detection (CE/LIF) (Arlt et al., 2001), capillary electrophoresis coupled to mass spectrometry (CE/MS) (Soga et al., 2002), gas chromatography-mass spectrometry (GC/MS), liquid chromatography-mass spectro- metry (LC/MS) (Huhman and Sumner, 2002), liquid chromatography tandem mass spectrometry (LC/MS/ MS) (Huhman and Sumner, 2002), Fourier transform ion cyclotron mass spectrometry (FTMS) (Aharoni et al., 2002), HPLC coupled with both mass spectrometry and nuclear magnetic resonance detection (LC/NMR/ MS) (Bailey et al., 2000a), and LC/NMR/MS/MS (Bai- ley et al., 2000b) have all been used.<br /> ==Projects List==<br /> <br /> {|class=&quot;wikitable sortable&quot; style=&quot;width:100%;text-align:center&quot;<br /> |-<br /> !Project Title<br /> !Species<br /> !Published years<br /> !Academic Journal<br /> !RiceWiki Project ID<br /> |-<br /> |'''Genetic analysis of the metabolome exemplified using a rice population'''<br /> |''Oryza sativa''<br /> |2013<br /> |Proceedings of the National Academy of Sciences<br /> |[[IC4R001-Metabolomics-2013-24259710]]<br /> |-<br /> |'''Folate fortification of rice by metabolic engineering'''<br /> |''Oryza sativa L. ssp. Japnoica''<br /> |2007<br /> |Nature Biotechnology<br /> |[[IC4R002-Metabolomics-2007-17934451]]<br /> |-<br /> |'''Characterization of Volatile Aroma Compounds in Cooked Black Rice'''<br /> |''Oryza sativa''<br /> |2007<br /> |Journal of Agricultural and Food Chemistry <br /> |[[IC4R003-Metabolomics-2007-18081248]]<br /> |-<br /> |'''A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress'''<br /> |''Oryza sativa''<br /> |2015<br /> |Analytical Biochemistry<br /> |[[IC4R004-Metabolomics-2015-25766578]]<br /> |-<br /> |'''Metabolomic screening applied to rice FOX Arabidopsis lines leads to the identification of a gene-changing nitrogen metabolism.'''<br /> |''Oryza sativa L. ssp. japonica''<br /> |2010<br /> |Molecular Plant<br /> |[[IC4R005-Metabolomics-2010-20085895]]<br /> |-<br /> |'''Application of a metabolomic method combining one-dimensional and two-dimensional gas chromatography-time-of-flight/mass spectrometry to metabolic phenotyping of natural variants in rice'''<br /> |''Oryza sativa L.''<br /> |2007<br /> |Journal of Chromatography B<br /> |[[IC4R006-Metabolomics-2007-17556050]]<br /> |-<br /> |'''Metabolic profiling of transgenic rice with cryIAc and sck genes: An evaluation of unintended effects at metabolic level by using GC-FID and GC–MS'''<br /> |''Oryza sativa L.''<br /> |2009<br /> |Journal of Chromatography B<br /> |[[IC4R007-Metabolomics-2009-19233746]]<br /> |}<br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/Epigenome<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Metabolomics&diff=270065 2016-06-21T07:27:35Z

<p>Rice2012: /* What is Metabolomics ? */</p> <hr /> <div>==What is Metabolomics ?==<br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles.&lt;ref name=&quot;ref1&quot;/&gt; The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes.[2] mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to provide a better understanding of cellular biology.<br /> [[File: IC4R-Metabolomics-overview-1.png|center|thumb|970px|'''Figure 1. Integrated functional genomics. The effects of gene perturbations are evaluated at multiple levels including the transcriptome, proteome, and metabolome. Changes in the metabolome occur as a consequence of those changes in the transcriptome that result in changes in the levels or catalytic activities of enzymes. Therefore, metabolome analysis is a valuable tool for inferring gene function.''']]<br /> * Advances in mass spectrometry have enabled the analysis of cellular proteins and metabolites (proteome and metabolome respectively) on a scale previously unimaginable. The cumulative utilization of these technologies has advanced the fields of functional genomics (Holtorf et al., 2002; Oliver et al., 2002; Somerville and Somerville, 1999) and systems biology (Ideker et al., 2001; Kitano, 2000). Both fields comprise traditional molecular biology, enzymology and bio- chemistry; however, the predominant difference from previous approaches is the significantly larger scale upon which they are conducted.&lt;br&gt;&lt;br&gt;<br /> <br /> ==Limitations of metabolomics ==<br /> * The major limitation of metabolomics is its current inability to comprehensively profile all of the metabolome. This inability is directly related to the chemical complexity of the metabolome, the biological variance inherent in most living organisms, and the dynamic range limitations of most instrumental approaches. In many ways, this is similar to the situation of the Human Genome Project in 1990, when the technological means to sequence genomes were not yet available.<br /> ==Metabolome technologies==<br /> * It is generally accepted that a single analytical technique will not provide sufficient visualization of the metabolome and, therefore, multiple technologies are needed for a comprehensive view (Hall et al., 2002; Sumner et al., 2002). Accordingly, many analytical technologies have been enlisted to profile the metabolome. Methods based on infrared spectroscopy (IR) (Oliver et al., 1998), nuclear magnetic resonance (NMR(Bligny and Douce, 2001; Ratcliffe and Shachar-Hill,2001; Roberts, 2000), thin layer chromatography (TLC) (Tweeddale et al., 1998), HPLC with ultraviolet and photodiode array detection (LC/UV/PDA) (Fraser et al., 2000), capillary electrophoresis coupled to ultravio- let absorbance detection (CE/UV) (Baggett et al., 2002), capillary electrophoresis coupled to laser induced fluorescence detection (CE/LIF) (Arlt et al., 2001), capillary electrophoresis coupled to mass spectrometry (CE/MS) (Soga et al., 2002), gas chromatography-mass spectrometry (GC/MS), liquid chromatography-mass spectro- metry (LC/MS) (Huhman and Sumner, 2002), liquid chromatography tandem mass spectrometry (LC/MS/ MS) (Huhman and Sumner, 2002), Fourier transform ion cyclotron mass spectrometry (FTMS) (Aharoni et al., 2002), HPLC coupled with both mass spectrometry and nuclear magnetic resonance detection (LC/NMR/ MS) (Bailey et al., 2000a), and LC/NMR/MS/MS (Bai- ley et al., 2000b) have all been used.<br /> ==Projects List==<br /> <br /> {|class=&quot;wikitable sortable&quot; style=&quot;width:100%;text-align:center&quot;<br /> |-<br /> !Project Title<br /> !Species<br /> !Published years<br /> !Academic Journal<br /> !RiceWiki Project ID<br /> |-<br /> |'''Genetic analysis of the metabolome exemplified using a rice population'''<br /> |''Oryza sativa''<br /> |2013<br /> |Proceedings of the National Academy of Sciences<br /> |[[IC4R001-Metabolomics-2013-24259710]]<br /> |-<br /> |'''Folate fortification of rice by metabolic engineering'''<br /> |''Oryza sativa L. ssp. Japnoica''<br /> |2007<br /> |Nature Biotechnology<br /> |[[IC4R002-Metabolomics-2007-17934451]]<br /> |-<br /> |'''Characterization of Volatile Aroma Compounds in Cooked Black Rice'''<br /> |''Oryza sativa''<br /> |2007<br /> |Journal of Agricultural and Food Chemistry <br /> |[[IC4R003-Metabolomics-2007-18081248]]<br /> |-<br /> |'''A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress'''<br /> |''Oryza sativa''<br /> |2015<br /> |Analytical Biochemistry<br /> |[[IC4R004-Metabolomics-2015-25766578]]<br /> |-<br /> |'''Metabolomic screening applied to rice FOX Arabidopsis lines leads to the identification of a gene-changing nitrogen metabolism.'''<br /> |''Oryza sativa L. ssp. japonica''<br /> |2010<br /> |Molecular Plant<br /> |[[IC4R005-Metabolomics-2010-20085895]]<br /> |-<br /> |'''Application of a metabolomic method combining one-dimensional and two-dimensional gas chromatography-time-of-flight/mass spectrometry to metabolic phenotyping of natural variants in rice'''<br /> |''Oryza sativa L.''<br /> |2007<br /> |Journal of Chromatography B<br /> |[[IC4R006-Metabolomics-2007-17556050]]<br /> |-<br /> |'''Metabolic profiling of transgenic rice with cryIAc and sck genes: An evaluation of unintended effects at metabolic level by using GC-FID and GC–MS'''<br /> |''Oryza sativa L.''<br /> |2009<br /> |Journal of Chromatography B<br /> |[[IC4R007-Metabolomics-2009-19233746]]<br /> |}<br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/Epigenome<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Metabolomics&diff=270064 2016-06-21T07:27:20Z

<p>Rice2012: Created page with &quot;==What is Metabolomics ?== * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the uniqu...&quot;</p> <hr /> <div>==What is Metabolomics ?==<br /> * Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the &quot;systematic study of the unique chemical fingerprints that specific cellular processes leave behind&quot;, the study of their small-molecule metabolite profiles.&lt;ref name=&quot;ref1&quot;/&gt; The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes.[2] mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to provide a better understanding of cellular biology.<br /> [[File: IC4R-Metabolomics-overview-1.png|center|thumb|970px|'''Figure 1. Integrated functional genomics. The effects of gene perturbations are evaluated at multiple levels including the transcriptome, proteome, and metabolome. Changes in the metabolome occur as a consequence of those changes in the transcriptome that result in changes in the levels or catalytic activities of enzymes. Therefore, metabolome analysis is a valuable tool for inferring gene function.''']]<br /> * Advances in mass spectrometry have enabled the analysis of cellular proteins and metabolites (proteome and metabolome respectively) on a scale previously unimaginable. The cumulative utilization of these technologies has advanced the fields of functional genomics (Holtorf et al., 2002; Oliver et al., 2002; Somerville and Somerville, 1999) and systems biology (Ideker et al., 2001; Kitano, 2000). Both fields comprise traditional molecular biology, enzymology and bio- chemistry; however, the predominant difference from previous approaches is the significantly larger scale upon which they are conducted.<br /> ==Limitations of metabolomics ==<br /> * The major limitation of metabolomics is its current inability to comprehensively profile all of the metabolome. This inability is directly related to the chemical complexity of the metabolome, the biological variance inherent in most living organisms, and the dynamic range limitations of most instrumental approaches. In many ways, this is similar to the situation of the Human Genome Project in 1990, when the technological means to sequence genomes were not yet available.<br /> ==Metabolome technologies==<br /> * It is generally accepted that a single analytical technique will not provide sufficient visualization of the metabolome and, therefore, multiple technologies are needed for a comprehensive view (Hall et al., 2002; Sumner et al., 2002). Accordingly, many analytical technologies have been enlisted to profile the metabolome. Methods based on infrared spectroscopy (IR) (Oliver et al., 1998), nuclear magnetic resonance (NMR(Bligny and Douce, 2001; Ratcliffe and Shachar-Hill,2001; Roberts, 2000), thin layer chromatography (TLC) (Tweeddale et al., 1998), HPLC with ultraviolet and photodiode array detection (LC/UV/PDA) (Fraser et al., 2000), capillary electrophoresis coupled to ultravio- let absorbance detection (CE/UV) (Baggett et al., 2002), capillary electrophoresis coupled to laser induced fluorescence detection (CE/LIF) (Arlt et al., 2001), capillary electrophoresis coupled to mass spectrometry (CE/MS) (Soga et al., 2002), gas chromatography-mass spectrometry (GC/MS), liquid chromatography-mass spectro- metry (LC/MS) (Huhman and Sumner, 2002), liquid chromatography tandem mass spectrometry (LC/MS/ MS) (Huhman and Sumner, 2002), Fourier transform ion cyclotron mass spectrometry (FTMS) (Aharoni et al., 2002), HPLC coupled with both mass spectrometry and nuclear magnetic resonance detection (LC/NMR/ MS) (Bailey et al., 2000a), and LC/NMR/MS/MS (Bai- ley et al., 2000b) have all been used.<br /> ==Projects List==<br /> <br /> {|class=&quot;wikitable sortable&quot; style=&quot;width:100%;text-align:center&quot;<br /> |-<br /> !Project Title<br /> !Species<br /> !Published years<br /> !Academic Journal<br /> !RiceWiki Project ID<br /> |-<br /> |'''Genetic analysis of the metabolome exemplified using a rice population'''<br /> |''Oryza sativa''<br /> |2013<br /> |Proceedings of the National Academy of Sciences<br /> |[[IC4R001-Metabolomics-2013-24259710]]<br /> |-<br /> |'''Folate fortification of rice by metabolic engineering'''<br /> |''Oryza sativa L. ssp. Japnoica''<br /> |2007<br /> |Nature Biotechnology<br /> |[[IC4R002-Metabolomics-2007-17934451]]<br /> |-<br /> |'''Characterization of Volatile Aroma Compounds in Cooked Black Rice'''<br /> |''Oryza sativa''<br /> |2007<br /> |Journal of Agricultural and Food Chemistry <br /> |[[IC4R003-Metabolomics-2007-18081248]]<br /> |-<br /> |'''A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress'''<br /> |''Oryza sativa''<br /> |2015<br /> |Analytical Biochemistry<br /> |[[IC4R004-Metabolomics-2015-25766578]]<br /> |-<br /> |'''Metabolomic screening applied to rice FOX Arabidopsis lines leads to the identification of a gene-changing nitrogen metabolism.'''<br /> |''Oryza sativa L. ssp. japonica''<br /> |2010<br /> |Molecular Plant<br /> |[[IC4R005-Metabolomics-2010-20085895]]<br /> |-<br /> |'''Application of a metabolomic method combining one-dimensional and two-dimensional gas chromatography-time-of-flight/mass spectrometry to metabolic phenotyping of natural variants in rice'''<br /> |''Oryza sativa L.''<br /> |2007<br /> |Journal of Chromatography B<br /> |[[IC4R006-Metabolomics-2007-17556050]]<br /> |-<br /> |'''Metabolic profiling of transgenic rice with cryIAc and sck genes: An evaluation of unintended effects at metabolic level by using GC-FID and GC–MS'''<br /> |''Oryza sativa L.''<br /> |2009<br /> |Journal of Chromatography B<br /> |[[IC4R007-Metabolomics-2009-19233746]]<br /> |}<br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/Epigenome<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=File:IC4R-Metabolomics-overview-1.png&diff=270063 2016-06-21T07:26:51Z

<p>Rice2012: </p> <hr /> <div></div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270062 2016-06-21T07:26:27Z

<p>Rice2012: </p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]<br /> <br /> ==[[Metabolomics]]==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]] <br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=270061 2016-06-21T07:25:17Z

<p>Rice2012: </p> <hr /> <div>=='''What is Omics?'''==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ''omics'' technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> =='''The Omics Knowledge Portal for Rice'''==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;, and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[lncRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-lncRNA-overview-1.png|right|thumb|97px]]<br /> * Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.[[lncRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[Microarray Related Studies in Rice]]'''===<br /> [[File:IC4R-Microarray-overview-2.png|right|thumb|97px]]<br /> * A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.[[Microarray Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Proteomic Studies in Rice]]'''==<br /> [[File:IC4R-Proteomics-overview-2.png|right|thumb|97px]]<br /> Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,[[Proteomic Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Genome-Wide Association Studies in Rice]]'''==<br /> [[File:IC4R-GWAS-overview-2.png|right|thumb|97px]]<br /> * A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.[[Genome-Wide Association Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''[[Epigenomic Studies in Rice]]'''==<br /> [[File:IC4R-Metabolomics-overview-1.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]<br /> <br /> ==[[Metabolomics]]==<br /> [[File:IC4R-Epigenomic-overview-2.png|right|thumb|97px]]<br /> * An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.[[Epigenomic Studies in Rice|'''(More...)''']]<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=MiRNA-Seq_Related_Studies_in_Rice&diff=269975 2016-06-20T15:02:22Z

<p>Rice2012: /* Projects List */</p> <hr /> <div>== What is microRNA ==<br /> [[File:IC4R-miRNA-overview-2.png|thumb|right|397px|'''Figure 1. An overview of canonical miRNA biogenesis, with noncanonical routes.&lt;ref name=&quot;ref2&quot; /&gt;''']]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993 &lt;ref name=&quot;ref2&quot;/&gt;&lt;ref name=&quot;ref3&quot;/&gt;. Currently, it is well known that miRNAs are widely present in plants, animals and some viruses, and miRNAs are involved in regulating almost all biological and metabolic processes, such as stem cell maintenance and differentiation, organ development, signaling pathways, disease, and response to environmental stress&lt;ref name=&quot;ref2&quot; /&gt;&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt; .<br /> <br /> ==Biogenesis of plant miRNAs==<br /> * miRNAs are coded by miRNA genes. Although a majority of miRNAs are 21–23 nucleotides in length &lt;ref name=&quot;ref5&quot; /&gt;, miRNA genes are usually very long and it is not certain how long miRNA genes are. The majority of plant miRNA genesare predominantly located at intergenic regions; however, animal miRNA genes can be located anywhere in the genome, including coding sequences. Similar to protein coding genes, miRNA genes are also transcribed by RNA polymerase II (RNA Pol II) ; however, some miRNAs can be transcribed by RNA Pol III . The initial miRNA transcripts are called primary miRNAs (primiRNAs). RNA Pol II generates capped and polyadeny-lated pri-miRNAs in both plants and animals&lt;ref name=&quot;ref2&quot; /&gt;.<br /> * '''''Figure 1''''' describes An overview of canonical miRNA biogenesis, with noncanonical routes. miRNA biogenesis begins with transcription of MIR loci by RNA polymerase II. 21-nucleotide long canonical miRNAs are mostly processed by Dicer-like 1 (DCL1), while DCL2, DCL3, and DCL4 generate miRNAs of differing lengths. miRNA/miRNA* duplexes are methylated by HEN1 for stabilization, which may also contribute to the export. The export of miRNAs is generally attributed to HASTY, although this is challenged by hst mutants. In contrast to the canonical base-to-loop processing, miRNAs can also be processed from loop to base&lt;ref name=&quot;ref2&quot; /&gt;.<br /> <br /> ==Abiotic stresses induce the aberrant expression of miRNAs==<br /> * The role of miRNAs in plant response to abiotic stress was initially suggested after data gathered from miRNA target prediction, miRNA expression profile studies during plant response to abiotic stress, and surveys of NCBI expressed sequence tags (ESTs). In one of the earliest plant miRNA papers, Jones-Rhoades and Bartel &lt;ref name=&quot;ref5&quot; /&gt; predicted and validated that ATP sulphurylase (APS), the enzyme that catalyses the first step of inorganic sulphate assimilation, was one of the targets of miR395, which is responsive to sulphate levels in plants. Based on this initial result, they further analysed the response of miR395 to cellular sulphate levels. Their results showed that in comparison with plants growing under normal sulphate conditions (2 mM SO 42– ), miR395 was induced by &gt;100-fold under low sulphate treatment (0.02 mM SO 42– ), suggesting that miR395 is involved in sulphate uptake and metabolism in plants. At the same time, Sunkar and Zhu (2004) constructed small RNA libraries from Arabidopsis seedling samples treated with cold stress (0 °C for 24 h), salt stress (300 mM NaCl for 5 h), drought stress (dehydration for 10 h), and hormones [100 μM abscisic acid (ABA) for 3 h], as well as from the untreated controls.<br /> [[File: IC4R-miRNA-overview-1.png|center|thumb|970px|'''Figure 2. The miRNA–target gene network is involved in plant response to environmental abiotic stresses.''']]<br /> <br /> * The '''''Figure2''''' describes the miRNA–target gene network is involved in plant response to environmental abiotic stresses. Different stresses induced and/or inhibited the expression of individual miRNAs that target transcription factors and/or stress related genes. This network further regulates plant development as well as response to abiotic stress. Plant hormones are also involved in this process through directly/indirectly regulating the expression of miRNAs and their targets.<br /> <br /> ==miRNAs regulate plant leaf development and leaf morphology ==<br /> * To date, at least 5 miRNAs (miR156, miR159, miR165, miR166, and miR319) have been dem- onstrated to control the pattern and development of leaves in Arabidopsis, maize, and other plant species (Jung et al. 2009; Kanehira et al. 2010; Kim et al. 2009; Millar and Waterhouse 2005; Pant et al. 2008). These miRNAs regulate leaf development by targeting the homeodomain leucine zipper (HD-ZIP) and the TCP transcription factor genes. miR319, originally reported as miR159, is the first miRNA experimentally shown function during leaf devel- opment (Palatnik et al. 2003, 2007). Overexpression of miR319 resulted in jaw-D phenotypes, including uneven leaf shape and curvature (Palatnik et al. 2003). The reason is that miR319 targets the TCP transcription factor, which regulates leaf development. miR165/166 regulates the developmental polarity of the leaf by targeting the HD-ZIP genes PHAVOLUTA (PHV), PHABULOSA (PHB) and REVOLUTA (REV), whose accumulation alters in adaxial and abaxial regions (Kidner 2010; Rubio-Somoza and Weigel 2011; Williams et al. 2005). In addition to the conserved miRNAs, non-conserved miRNAs may also play roles in leaf development. One example is miR824 that has been reported to play a role in stomatal development (Kutter et al. 2007). Overexpression of one single miRNA, miR156, significantly increases leaf initiation and plant biomass in Arabidopsis (Schwab et al. 2005). This suggests a novel miRNA-based biotechnology for improvement of plant biomass for agriculture purposes and also for biofuel production.<br /> <br /> ==Projects List==<br /> <br /> {|class=&quot;wikitable sortable&quot; style=&quot;width:100%;text-align:center&quot;<br /> |-<br /> !Project Title<br /> !Species<br /> !Published years<br /> !Academic Journal<br /> !RiceWiki Project ID<br /> |-<br /> |'''Microarray-based analysis of cadmium-responsive microRNAs in rice (Oryza sativa) '''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''<br /> |2011<br /> |Journal of Experimental Botany<br /> |[[IC4R001-miRNA-2011-21362738]]<br /> |-<br /> |'''Deep sequencing on genome-wide scale reveals the unique composition and expression patterns of microRNAs in developing pollen of Oryza sativa'''<br /> |''Japnoica Oryza sativa cultivars''<br /> |2011<br /> |Genome Biology<br /> |[[IC4R002-miRNA-2011-21679406]]<br /> |-<br /> |'''Differential expression of the microRNAs in superior and inferior spikelets in rice (Oryza sativa)'''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''<br /> |2011<br /> |Journal of Experimental Botany<br /> |[[IC4R003-miRNA-2011-21791435]]<br /> |-<br /> |'''Identification and Expression Analysis of microRNAs at the Grain Filling Stage in Rice(Oryza sativa L.)via Deep Sequencing'''<br /> |''Oryza sativa''<br /> |2013<br /> |PLoS One<br /> |[[IC4R004-miRNA-2013-23469249]]<br /> |-<br /> |'''Identification of Novel Oryza sativa miRNAs in Deep Sequencing-Based Small RNA Libraries of Rice Infected with Rice Stripe Virus'''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''<br /> |2012<br /> |PLoS One<br /> |[[IC4R005-miRNA-2012-23071571]]<br /> |-<br /> |'''Differentially expressed microRNA cohorts in seed development may contribute to poor grain filling of inferior spikelets in rice'''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''<br /> |2014<br /> |BMC Plant Biology<br /> |[[IC4R006-miRNA-2014-25052585]]<br /> |-<br /> |'''Identification and characterization of salt responsive miRNA-SSR markers in rice (Oryza sativa)'''<br /> |''Oryza sativa''<br /> |2014<br /> |Gene<br /> |[[IC4R007-miRNA-2014-24315823]]<br /> |}<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/MicroRNA<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Sun, Guiling. &quot;MicroRNAs and their diverse functions in plants.&quot; Plant molecular biology 80.1 (2012): 17-36.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Lee, Rosalind C., Rhonda L. Feinbaum, and Victor Ambros. &quot;The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.&quot; Cell 75.5 (1993): 843-854.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Lewis, Benjamin P., Christopher B. Burge, and David P. Bartel. &quot;Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.&quot; cell 120.1 (2005): 15-20.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref5&quot;&gt;<br /> Bartel, David P. &quot;MicroRNAs: genomics, biogenesis, mechanism, and function.&quot; cell 116.2 (2004): 281-297.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=269974 2016-06-20T14:56:22Z

<p>Rice2012: /* miRNA-Seq Related Studies in Rice */</p> <hr /> <div>==What is Omics?==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ‘‘omics’’ technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> ==The Omics Knowledge Portal for Rice==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;. and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.[[miRNA-Seq Related Studies in Rice|'''(More...)''']]<br /> <br /> ===[[lncRNA-Seq Related Studies in Rice]]===<br /> ===[[Microarray Related Studies in Rice]]===<br /> <br /> ==[[Proteomic Studies in Rice]]==<br /> <br /> ==[[Genome-Wide Association Studies in Rice]]==<br /> <br /> ==[[Epigenomic Studies in Rice]]==<br /> <br /> ==[[Metabolomics]]==<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=File:IC4R-miRNA-overview-1.png&diff=269973 2016-06-20T14:55:25Z

<p>Rice2012: </p> <hr /> <div></div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=MiRNA-Seq_Related_Studies_in_Rice&diff=269971 2016-06-20T14:54:47Z

<p>Rice2012: Created page with &quot;== What is microRNA == [[File:IC4R-miRNA-overview-2.png|thumb|right|397px|'''Figure 1. An overview of canonical miRNA biogenesis, with noncanonical routes.&lt;ref name=&quot;ref2&quot; /&gt;'...&quot;</p> <hr /> <div>== What is microRNA ==<br /> [[File:IC4R-miRNA-overview-2.png|thumb|right|397px|'''Figure 1. An overview of canonical miRNA biogenesis, with noncanonical routes.&lt;ref name=&quot;ref2&quot; /&gt;''']]<br /> * microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993 &lt;ref name=&quot;ref2&quot;/&gt;&lt;ref name=&quot;ref3&quot;/&gt;. Currently, it is well known that miRNAs are widely present in plants, animals and some viruses, and miRNAs are involved in regulating almost all biological and metabolic processes, such as stem cell maintenance and differentiation, organ development, signaling pathways, disease, and response to environmental stress&lt;ref name=&quot;ref2&quot; /&gt;&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt; .<br /> <br /> ==Biogenesis of plant miRNAs==<br /> * miRNAs are coded by miRNA genes. Although a majority of miRNAs are 21–23 nucleotides in length &lt;ref name=&quot;ref5&quot; /&gt;, miRNA genes are usually very long and it is not certain how long miRNA genes are. The majority of plant miRNA genesare predominantly located at intergenic regions; however, animal miRNA genes can be located anywhere in the genome, including coding sequences. Similar to protein coding genes, miRNA genes are also transcribed by RNA polymerase II (RNA Pol II) ; however, some miRNAs can be transcribed by RNA Pol III . The initial miRNA transcripts are called primary miRNAs (primiRNAs). RNA Pol II generates capped and polyadeny-lated pri-miRNAs in both plants and animals&lt;ref name=&quot;ref2&quot; /&gt;.<br /> * '''''Figure 1''''' describes An overview of canonical miRNA biogenesis, with noncanonical routes. miRNA biogenesis begins with transcription of MIR loci by RNA polymerase II. 21-nucleotide long canonical miRNAs are mostly processed by Dicer-like 1 (DCL1), while DCL2, DCL3, and DCL4 generate miRNAs of differing lengths. miRNA/miRNA* duplexes are methylated by HEN1 for stabilization, which may also contribute to the export. The export of miRNAs is generally attributed to HASTY, although this is challenged by hst mutants. In contrast to the canonical base-to-loop processing, miRNAs can also be processed from loop to base&lt;ref name=&quot;ref2&quot; /&gt;.<br /> <br /> ==Abiotic stresses induce the aberrant expression of miRNAs==<br /> * The role of miRNAs in plant response to abiotic stress was initially suggested after data gathered from miRNA target prediction, miRNA expression profile studies during plant response to abiotic stress, and surveys of NCBI expressed sequence tags (ESTs). In one of the earliest plant miRNA papers, Jones-Rhoades and Bartel &lt;ref name=&quot;ref5&quot; /&gt; predicted and validated that ATP sulphurylase (APS), the enzyme that catalyses the first step of inorganic sulphate assimilation, was one of the targets of miR395, which is responsive to sulphate levels in plants. Based on this initial result, they further analysed the response of miR395 to cellular sulphate levels. Their results showed that in comparison with plants growing under normal sulphate conditions (2 mM SO 42– ), miR395 was induced by &gt;100-fold under low sulphate treatment (0.02 mM SO 42– ), suggesting that miR395 is involved in sulphate uptake and metabolism in plants. At the same time, Sunkar and Zhu (2004) constructed small RNA libraries from Arabidopsis seedling samples treated with cold stress (0 °C for 24 h), salt stress (300 mM NaCl for 5 h), drought stress (dehydration for 10 h), and hormones [100 μM abscisic acid (ABA) for 3 h], as well as from the untreated controls.<br /> [[File: IC4R-miRNA-overview-1.png|center|thumb|970px|'''Figure 2. The miRNA–target gene network is involved in plant response to environmental abiotic stresses.''']]<br /> <br /> * The '''''Figure2''''' describes the miRNA–target gene network is involved in plant response to environmental abiotic stresses. Different stresses induced and/or inhibited the expression of individual miRNAs that target transcription factors and/or stress related genes. This network further regulates plant development as well as response to abiotic stress. Plant hormones are also involved in this process through directly/indirectly regulating the expression of miRNAs and their targets.<br /> <br /> ==miRNAs regulate plant leaf development and leaf morphology ==<br /> * To date, at least 5 miRNAs (miR156, miR159, miR165, miR166, and miR319) have been dem- onstrated to control the pattern and development of leaves in Arabidopsis, maize, and other plant species (Jung et al. 2009; Kanehira et al. 2010; Kim et al. 2009; Millar and Waterhouse 2005; Pant et al. 2008). These miRNAs regulate leaf development by targeting the homeodomain leucine zipper (HD-ZIP) and the TCP transcription factor genes. miR319, originally reported as miR159, is the first miRNA experimentally shown function during leaf devel- opment (Palatnik et al. 2003, 2007). Overexpression of miR319 resulted in jaw-D phenotypes, including uneven leaf shape and curvature (Palatnik et al. 2003). The reason is that miR319 targets the TCP transcription factor, which regulates leaf development. miR165/166 regulates the developmental polarity of the leaf by targeting the HD-ZIP genes PHAVOLUTA (PHV), PHABULOSA (PHB) and REVOLUTA (REV), whose accumulation alters in adaxial and abaxial regions (Kidner 2010; Rubio-Somoza and Weigel 2011; Williams et al. 2005). In addition to the conserved miRNAs, non-conserved miRNAs may also play roles in leaf development. One example is miR824 that has been reported to play a role in stomatal development (Kutter et al. 2007). Overexpression of one single miRNA, miR156, significantly increases leaf initiation and plant biomass in Arabidopsis (Schwab et al. 2005). This suggests a novel miRNA-based biotechnology for improvement of plant biomass for agriculture purposes and also for biofuel production.<br /> <br /> ==Projects List==<br /> <br /> {|class=&quot;wikitable sortable&quot; style=&quot;width:100%;text-align:center&quot;<br /> |-<br /> !Project Title<br /> !Species<br /> !Published years<br /> !Academic Journal<br /> !RiceWiki Project ID<br /> |-<br /> |'''Microarray-based analysis of cadmium-responsive microRNAs in rice (Oryza sativa) '''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''<br /> |2011<br /> |Journal of Experimental Botany<br /> |[[IC4R001-miRNA-2011-21362738]]<br /> |-<br /> |'''Deep sequencing on genome-wide scale reveals the unique composition and expression patterns of microRNAs in developing pollen of Oryza sativa'''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''''Oryza sativa cultivars''<br /> |2011<br /> |Genome Biology<br /> |[[IC4R002-miRNA-2011-21679406]]<br /> |-<br /> |'''Differential expression of the microRNAs in superior and inferior spikelets in rice (Oryza sativa)'''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''<br /> |2011<br /> |Journal of Experimental Botany<br /> |[[IC4R003-miRNA-2011-21791435]]<br /> |-<br /> |'''Identification and Expression Analysis of microRNAs at the Grain Filling Stage in Rice(Oryza sativa L.)via Deep Sequencing'''<br /> |''Oryza sativa''<br /> |2013<br /> |PLoS One<br /> |[[IC4R004-miRNA-2013-23469249]]<br /> |-<br /> |'''Identification of Novel Oryza sativa miRNAs in Deep Sequencing-Based Small RNA Libraries of Rice Infected with Rice Stripe Virus'''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''<br /> |2012<br /> |PLoS One<br /> |[[IC4R005-miRNA-2012-23071571]]<br /> |-<br /> |'''Differentially expressed microRNA cohorts in seed development may contribute to poor grain filling of inferior spikelets in rice'''<br /> |''Oryza sativa'' L. ssp. ''Japnoica''<br /> |2014<br /> |BMC Plant Biology<br /> |[[IC4R006-miRNA-2014-25052585]]<br /> |-<br /> |'''Identification and characterization of salt responsive miRNA-SSR markers in rice (Oryza sativa)'''<br /> |''Oryza sativa''<br /> |2014<br /> |Gene<br /> |[[IC4R007-miRNA-2014-24315823]]<br /> |}<br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;<br /> https://en.wikipedia.org/wiki/MicroRNA<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Sun, Guiling. &quot;MicroRNAs and their diverse functions in plants.&quot; Plant molecular biology 80.1 (2012): 17-36.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Lee, Rosalind C., Rhonda L. Feinbaum, and Victor Ambros. &quot;The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.&quot; Cell 75.5 (1993): 843-854.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Lewis, Benjamin P., Christopher B. Burge, and David P. Bartel. &quot;Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.&quot; cell 120.1 (2005): 15-20.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref5&quot;&gt;<br /> Bartel, David P. &quot;MicroRNAs: genomics, biogenesis, mechanism, and function.&quot; cell 116.2 (2004): 281-297.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=269970 2016-06-20T14:54:25Z

<p>Rice2012: /* Transcriptomic Studies in Rice */</p> <hr /> <div>==What is Omics?==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ‘‘omics’’ technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> ==The Omics Knowledge Portal for Rice==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;. and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.&lt;br&gt;&lt;br&gt;<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years,[[miRNA-Seq Related Studies in Rice|'''(More...)''']]<br /> <br /> ===[[lncRNA-Seq Related Studies in Rice]]===<br /> ===[[Microarray Related Studies in Rice]]===<br /> <br /> ==[[Proteomic Studies in Rice]]==<br /> <br /> ==[[Genome-Wide Association Studies in Rice]]==<br /> <br /> ==[[Epigenomic Studies in Rice]]==<br /> <br /> ==[[Metabolomics]]==<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=269969 2016-06-20T14:54:04Z

<p>Rice2012: /* mRNA-Seq Related Studies in Rice */</p> <hr /> <div>==What is Omics?==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ‘‘omics’’ technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> ==The Omics Knowledge Portal for Rice==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;. and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years,[[miRNA-Seq Related Studies in Rice|'''(More...)''']]<br /> <br /> ===[[lncRNA-Seq Related Studies in Rice]]===<br /> ===[[Microarray Related Studies in Rice]]===<br /> <br /> ==[[Proteomic Studies in Rice]]==<br /> <br /> ==[[Genome-Wide Association Studies in Rice]]==<br /> <br /> ==[[Epigenomic Studies in Rice]]==<br /> <br /> ==[[Metabolomics]]==<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=File:IC4R-miRNA-overview-2.png&diff=269968 2016-06-20T14:53:27Z

<p>Rice2012: </p> <hr /> <div></div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=269967 2016-06-20T14:53:07Z

<p>Rice2012: /* Transcriptomic Studies in Rice */</p> <hr /> <div>==What is Omics?==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ‘‘omics’’ technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> ==The Omics Knowledge Portal for Rice==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;. and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]<br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-miRNA-overview-2.png|right|thumb|97px]]<br /> microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years,[[miRNA-Seq Related Studies in Rice|'''(More...)''']]<br /> <br /> ===[[lncRNA-Seq Related Studies in Rice]]===<br /> ===[[Microarray Related Studies in Rice]]===<br /> <br /> ==[[Proteomic Studies in Rice]]==<br /> <br /> ==[[Genome-Wide Association Studies in Rice]]==<br /> <br /> ==[[Epigenomic Studies in Rice]]==<br /> <br /> ==[[Metabolomics]]==<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Omics_Knowledge_Portal_for_Rice&diff=269966 2016-06-20T14:52:37Z

<p>Rice2012: /* Transcriptomic Studies in Rice */</p> <hr /> <div>==What is Omics?==<br /> * Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life.&lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt; It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics). Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. The main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields.&quot;&lt;br&gt;&lt;br&gt;<br /> <br /> * The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.&lt;ref name=&quot;ref3&quot; /&gt;&lt;ref name=&quot;ref4&quot; /&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> * Take the Model of &quot;Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&quot; from Jeongsik Kim (pulished in June 2016 ) '''(Figure 1)''' for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The ''Age/environment'' dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The ''Organization'' dimension refers to various analytic layers, including organelle, cell, organ, and organism. The ''Analysis'' dimension defines diverse high-throughput ‘‘omics’’ technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.&lt;ref name=&quot;ref4&quot;/&gt;&lt;br&gt;&lt;br&gt;<br /> <br /> ==The Omics Knowledge Portal for Rice==<br /> * In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. We invite concerned biologits all around the world to join this the portal to share the precious related knowledge.&lt;br&gt;&lt;br&gt;<br /> [[File:IC4R-Omics-Overview-1.png|center|thumb|1000px|'''Figure 1. Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence&lt;ref name=&quot;ref4&quot; /&gt;''']]<br /> <br /> ==[[Genome Sequencing Studies in Rice|'''Genomic Studies in Rice''']]==<br /> [[File:IC4R-Genome-overview-1.png|right|thumb|97px]]<br /> * The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.[[Genome Sequencing Studies in Rice|'''(More...)''']]&lt;br&gt;&lt;br&gt;<br /> <br /> =='''Transcriptomic Studies in Rice'''==<br /> * The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'&lt;ref name=&quot;ref5&quot; /&gt;. The term was first proposed by Charles Auffray in 1996&lt;ref name=&quot;ref6&quot; /&gt;. and first used in a scientific paper in 1997&lt;ref name=&quot;ref7&quot; /&gt;. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.<br /> ==='''[[mRNA-Seq Related Studies in Rice]]'''===<br /> [[File:IC4R-RNA-Seq-overview-1.png|right|thumb|97px]]<br /> * RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.[[mRNA-Seq Related Studies in Rice|'''(More...)''']]<br /> ==='''[[miRNA-Seq Related Studies in Rice]]'''===<br /> microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes.&lt;ref name=&quot;ref1&quot; /&gt; Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years,[[miRNA-Seq Related Studies in Rice|'''(More...)''']]<br /> <br /> ===[[lncRNA-Seq Related Studies in Rice]]===<br /> ===[[Microarray Related Studies in Rice]]===<br /> <br /> ==[[Proteomic Studies in Rice]]==<br /> <br /> ==[[Genome-Wide Association Studies in Rice]]==<br /> <br /> ==[[Epigenomic Studies in Rice]]==<br /> <br /> ==[[Metabolomics]]==<br /> <br /> ==[[Interactomics]]==<br /> <br /> ==[[Phenomics]]==<br /> <br /> ==References==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;https://en.wikipedia.org/wiki/Omics<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;<br /> Langridge, Peter, and Delphine Fleury. &quot;Making the most of ‘omics’ for crop breeding.&quot; Trends in biotechnology 29.1 (2011): 33-40.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;<br /> Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. &quot;Metabolo-proteomics to discover plant biotic stress resistance genes.&quot; Trends in Plant Science 18.9 (2013): 522-531.<br /> &lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;<br /> Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. &quot;Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research.&quot; Molecular Plant 9.6 (2016): 813-825.<br /> &lt;/ref&gt;<br /> &lt;/references&gt;</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=RiceWiki:TBC&diff=269798 2016-06-20T01:48:40Z

<p>Rice2012: </p> <hr /> <div>To be curated&lt;br&gt;<br /> '''Every Gene Has A Story ！'''<br /> {|class=&quot;wikitable&quot; style=&quot;width:90%;text-align:center&quot; <br /> |-<br /> !Gene name<br /> !RAP ID<br /> !MSU ID<br /> !Reference Title<br /> |- <br /> |''PLA2''<br /> |[[Os01g0907900]]<br /> |LOC_Os01g68000<br /> |A Regulator of Leaf Initiation and Maturation in Rice <br /> |-<br /> |''OsMADS15'' <br /> |[[Os07g0108900]]<br /> |LOC_Os07g01820<br /> |Involved with Reproductive Habit of Rice<br /> |-<br /> |''GS5'' <br /> |[[Os05g0158500]]<br /> |LOC_Os05g06660<br /> |A QLT located at chrosome 5 of rice which can control grain size by regulating grain width, filling and weight<br /> |-<br /> |''Hd17'' <br /> |[[Os06g0142600]]<br /> |LOC_Os06g05060<br /> |An important regulator which can promote rice flowering.<br /> |-<br /> |''ORF3'' <br /> |[[Os06g0212900]]<br /> |LOC_Os06g10990<br /> |A rice gene reported by Science which can regulate fertility in Indica-Japonica hybrids.<br /> |-<br /> |''OsFIE1'' <br /> |[[Os08g0137100]]<br /> |LOC_Os08g04270<br /> |Regulating for seed developement and grain filling.<br /> |-<br /> |''OsMADS15'' <br /> |[[Os07g0108900]]<br /> |LOC_Os07g01820<br /> |A Regulateor for Reproductive Habit in Rice<br /> |-<br /> |''DTH2'' <br /> |[[Os02g0724000]]<br /> |LOC_Os02g49230<br /> |A minor-effect quantitative trait locus that promotes heading under Long Day conditions.<br /> |-<br /> |''OsYSL2''<br /> ''OsYSL15''&lt;br&gt;<br /> ''OsYSL16''&lt;br&gt; <br /> |[[Os02g0649900]]&lt;br&gt;<br /> [[Os02g0650300]]&lt;br&gt;<br /> [[Os04g0542800]]<br /> |LOC_Os02g43370&lt;br&gt;<br /> LOC_Os02g43410&lt;br&gt;<br /> LOC_Os04g45900<br /> |As members of rice Yellow Stripe 1 gene family, these three genes has been regarded as transporters of metals, for example, iron and corpper in rice. <br /> |-<br /> |''OsIAA23'' <br /> |[[Os06g0597000]]<br /> |LOC_Os06g39590<br /> |It can regulate the postembryonic maintenance of the quiescent center (QC) in rice. The defeciency of OsIAA23 can cause the disintegration of the root cap and termination of root growth.<br /> |-<br /> |''OsRSS1'' <br /> |[[Os02g0606700]]<br /> |LOC_Os02g39390<br /> |This gene can contribute to the vigour of meristematic cells and viability under salinity conditions.<br /> |-<br /> |''OsTDL1A'' <br /> |[[Os12g0472500]]<br /> |LOC_Os12g28750<br /> |Regulating the development of flowers and limiting sporocyte numbers in rice.<br /> |-<br /> |''YSA'' <br /> |[[Os03g0597200]]<br /> |LOC_Os03g40020<br /> |The mutant of YSA can generate albino leaves before the three-leaf stage, then gradually turns green and recovers to normal green at the sixleaf stage.<br /> |-<br /> |''TH1'' <br /> |[[Os02g0811000]]<br /> |LOC_Os02g56610<br /> |The mutant of TH1 can exhibit obviously triangular hull with tortuous and slender palea.<br /> |-<br /> |''OsDIS1'' <br /> |[[Os03g0356414]]<br /> |LOC_Os03g24040<br /> |This gene is involved in the drought-stress signal transduction in rice<br /> |-<br /> |''SRL1'' <br /> |[[Os07g0102300]]<br /> |LOC_Os07g01240<br /> |This gene is involved in the regulation of leaf rolling.<br /> |-<br /> |''OsHDT1'' <br /> |[[Os05g0597100]]<br /> |LOC_Os05g51830<br /> |A histone deacetylase gene which is involed in flowering time control and innate immunity in rice.<br /> |-<br /> |''OsIRE1'' <br /> |[[Os07g0471000]]<br /> |LOC_Os07g28820<br /> |A stress sensors in the endoplasmic reticulum stress response of rice.<br /> |-<br /> |''OsSPL16'' <br /> |[[Os08g0531600]]<br /> |LOC_Os08g41940<br /> |Encoding a positive regulator of cell prolifertion which can pormote cell division and grain filling.<br /> |-<br /> |''DRO1'' <br /> |[[Os09g0439800]]<br /> |LOC_Os09g26840<br /> |Involved in cell elongation in the root tip that causes asymmetric root growth and downward bending of the root in response to gravity<br /> |-<br /> |''VYL'' <br /> |[[Os03g0411500]]<br /> |LOC_Os03g29810<br /> |The mutant of this gene produces chlorotic leaves throughout the entire growth period.<br /> |-<br /> |''MFS1'' <br /> |[[Os05g0497200]]<br /> |LOC_Os05g41760<br /> |The Mutant of this gene showed delayed transformation of spikelet meristems to floral meristems, which resulted in an extra hull-like organ and an elongated rachilla.<br /> |-<br /> |''OsHCI1'' <br /> |[[Os10g0445400]]<br /> |LOC_Os10g30850<br /> |With a RING finger protein, this gene was specifically induced by heat and cold stress treatments but not by salinity or dehydration<br /> |-<br /> |''OsMPS'' <br /> |[[Os02g0618400]]<br /> |LOC_Os02g40530<br /> |Over-expression of OsMPS reduces growth under non-stress conditions, while knockdown plants display increased biomass.<br /> |-<br /> |''OsCPK10'' <br /> |[[Os03g0788500]]<br /> |LOC_Os03g57450<br /> |Overexpression of this gene in Arabidopsis enhanced the resistance to infection with Pseudomonas syringae pv. tomato, associated with elevated expression of both SA- and JA-related defense genes.<br /> |-<br /> |''OsALS1'' <br /> |[[Os03g0755100]]<br /> |LOC_Os03g54790<br /> |Encoding a half-size ABC transporter that is a member of the TAP (transporter associated with antigen processing) sub-group.<br /> |-<br /> |''oni3'' <br /> |[[Os09g0363900]]<br /> |LOC_Os09g19930<br /> |This gene is required for avoiding organ fusions in rice.<br /> |-<br /> |''VYL'' <br /> |[[Os03g0411500]]<br /> |LOC_Os03g29810<br /> |The mutant of this gene produce produces chlorotic leaves throughout the entire growth period. <br /> |-<br /> |''OsRSS3'' <br /> |[[Os03g0411500]]<br /> |LOC_Os03g29810<br /> |This gene can regulate root cell elongation during adaptation to salinity.<br /> |-<br /> |''CAP1'' <br /> |[[Os02g0141300]]<br /> |LOC_Os02g04840<br /> |The cap1 heterozygous plant can produce equal numbers of normal and collapsed abnormal grains.<br /> |-<br /> |''OsAt10'' <br /> |[[Os06g0594600]]<br /> |LOC_Os06g39390<br /> |Overexpression of this gene can alters rice cell wall hydroxycinnamic acid Content and saccharification<br /> |-<br /> |''ONI1'' <br /> |[[Os03g0181500]]<br /> |LOC_Os03g08360<br /> |This gene is required for correct fatty acid composition and normal shoot development in rice.<br /> |-<br /> |''Cga1'' <br /> |[[Os02g0220400]]<br /> |LOC_Os02g12790<br /> |This gene can regulates chloroplast development and plant architecture<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Main_Page&diff=269674 2016-06-02T04:03:39Z

<p>Rice2012: </p> <hr /> <div>__NOTITLE__<br /> __NOTOC__<br /> __NOEDITSECTION__<br /> &lt;!-----------------title---------------------&gt;<br /> {|style=&quot;width:100%; margin-top:10px; background-color:#f6f6f6; border:1px solid #d2d2d2; margin-bottom: 10px;&quot;<br /> |style=&quot;width:50%; text-align:center; white-space:nowrap; color:#000&quot;|<br /> &lt;div style=&quot;font-size:180%; border:none; margin:0; padding:.5em; color:#000;&quot;&gt;Welcome to RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%&quot;&gt;[[:Category:Genes |86,216]] rice genes inside&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%; color:#492;&quot;&gt;'''Contribute your efforts, further our knowledge.'''&lt;/div&gt;<br /> <br /> |style=&quot;width:18%;|<br /> *&lt;span class=plainlinks&gt;[[:Category:Genes|Genes]]&lt;/span&gt;<br /> *[[RiceWiki:GeneFamilies|Gene Families]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Chromosomes|Chromosomes]]<br /> *[[RiceWiki:Databases|Databases]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Genome_Browser|Genome Browser]]<br /> *[[RiceWiki:Templates|Templates]]<br /> |}<br /> <br /> &lt;!---------------welcome Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f1f1f1; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Introduction&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;{{:RiceWiki:Summary}}&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.2em 0.5em;text-align:center&quot;&gt;''Nothing great is ever accomplished in isolation. – Yo-Yo Ma''&lt;/div&gt;<br /> ----<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> {|<br /> |<br /> *Featured genes: [[Os01g0883800]], [[Os02g0170300]], [[Os03g0149100]], [[Os08g0162100]]<br /> *Stress-related genes: [[RiceWiki:Stress|a list of stress-related genes]]<br /> *Genes to be curated: [[RiceWiki:TBC|a list of genes to be curated]]<br /> |<br /> *Curated genes: [[Special:CuratedGenes | {{StatisticsActivity:type=curatedgenecount}} curated genes]]<br /> *User list: [[Special:ListUsers| {{StatisticsActivity:type=usercount}} registered users]]<br /> *Contribution score: [[Special:AuthorReward |quantified contributions]] by [http://www.ncbi.nlm.nih.gov/pubmed/23732274 ''AuthorReward'']<br /> |<br /> *Literature: [http://literature.ic4r.org 31527] rice-related publications associated with rice genes<br /> *Transcriptome: gene expression profiles at 22 developmental stages and tissue types based on RNA-Seq<br /> *Variations: SNPs and INDELs (under collection)<br /> |}<br /> &lt;/div&gt;<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;RiceWiki Award Winners in 2014&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:2014Award1.JPG|right|thumb|200px|link=RiceWiki:Awards]]<br /> *2014 Outstanding Award: SHI Junchao (侍骏超), Contribution Score: 190.164, Award: an iPad mini with Retina Display<br /> *2014 Excellent Award: HUANG Huasheng (黄华生), Contribution Score: 189.713, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: SONG Yafeng (宋亚凤), Contribution Score: 64.476, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: PAN Wenbo (潘文波), Contribution Score: 52.352, Award: XiaoMi Portable WiFi <br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part one----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------Rice Genome Overview------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent; width:30%;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Genome Overview&lt;/div&gt;<br /> &lt;div style=&quot;padding:1em 0em 0em 0em; text-align:center;&quot;&gt;[[image:RiceG.jpg]]&lt;/div&gt;<br /> == ==<br /> &lt;div style=&quot;padding:0.2em 0.5em;&quot;&gt;<br /> ====[[:Category:Japonica Genes | ''Oryza sativa Japonica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Japonica Chromosome 1|'''1''']].<br /> [[:category:Japonica Chromosome 2|'''2''']].<br /> [[:category:Japonica Chromosome 3|'''3''']].<br /> [[:category:Japonica Chromosome 4|'''4''']].<br /> [[:category:Japonica Chromosome 5|'''5''']].<br /> [[:category:Japonica Chromosome 6|'''6''']].<br /> [[:category:Japonica Chromosome 7|'''7''']].<br /> [[:category:Japonica Chromosome 8|'''8''']].<br /> [[:category:Japonica Chromosome 9|'''9''']].<br /> [[:category:Japonica Chromosome 10|'''10''']].<br /> [[:category:Japonica Chromosome 11|'''11''']].<br /> [[:category:Japonica Chromosome 12|'''12''']].<br /> [[:category:Japonica_Mitochondrion|'''Mt''']].<br /> [[:category:Japonica_Plastid|'''Pd''']]<br /> <br /> ====[[:Category:Indica Genes | ''Oryza sativa Indica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Indica Chromosome 1|'''1''']].<br /> [[:category:Indica Chromosome 2|'''2''']].<br /> [[:category:Indica Chromosome 3|'''3''']].<br /> [[:category:Indica Chromosome 4|'''4''']].<br /> [[:category:Indica Chromosome 5|'''5''']].<br /> [[:category:Indica Chromosome 6|'''6''']].<br /> [[:category:Indica Chromosome 7|'''7''']].<br /> [[:category:Indica Chromosome 8|'''8''']].<br /> [[:category:Indica Chromosome 9|'''9''']].<br /> [[:category:Indica Chromosome 10|'''10''']].<br /> [[:category:Indica Chromosome 11|'''11''']].<br /> [[:category:Indica Chromosome 12|'''12''']]<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Rice----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Story&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:Damifan.jpg|right|120px|margin: 5px|]]<br /> *As an important food<br /> :Rice is the seed of the monocot plants ''Oryza sativa'' (Asian rice) or ''Oryza glaberrima'' (African rice). As a cereal grain, it is the most important staple food for a large part of the world's human population, especially in East Asia, Southeast Asia, South Asia, the Middle East, and the West Indies. It is the grain with the third-highest worldwide production, after maize (corn) and wheat, according to data for 2010 [http://en.wikipedia.org/wiki/Rice (Full article...)].&lt;br&gt;<br /> *As a biological model<br /> :Rice is also a model organism for the biological study of the grass family of crops and other plants. The two most common rice cultivars, ''indica'' and ''japonica'', were completely sequenced in 2002. The genome sequences of domesticated rice provide a solid foundation for integrating biological information, including genetics, gene expression, development, physiology and evolution.&lt;/div&gt;<br /> ----<br /> {|style=&quot;border:none; background-color:transparent; width:100%&quot; <br /> |-style=&quot;background:transcript; color:black&quot; align=&quot;left&quot; valign=&quot;top&quot;<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Recent Modified Genes&lt;/div&gt; {{StatisticsActivity:type=edits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Highly Accessed Genes&lt;/div&gt; {{StatisticsActivity:type=visits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Most Annotated Genes&lt;/div&gt; {{StatisticsActivity:type=contributes|count = 10}}<br /> |}<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f4f4f4; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Publications&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/24136999 RiceWiki: a wiki-based database for community curation of rice genes] (2014) ''Nucleic Acids Research'', 42(D1),D1222-D1228.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/23732274 AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification] (2013) ''Bioinformatics'', 29(14):1837-1839.<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part two----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> &lt;!------------- Participating----------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:42%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Joining RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;<br /> * RiceWiki allows any user to view and search but only registered users can add and edit content. <br /> * To become a registered user, please email the RiceWiki Team at [mailto:ricewiki@big.ac.cn ricewiki@big.ac.cn] to tell us your preferred login name, real name, research interests, etc., and we will set up an account for you.<br /> * Please also spread this news to any one who might be of interest. [[File:Ppt_ico.gif | link=File:CommunityCuration-RiceWiki.pptx]]&lt;/div&gt;<br /> <br /> &lt;!-------------Lab Information--------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:33%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;About Us&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;Our group works in the field of [http://cbb.big.ac.cn Computational Biology and Bioinformatics] (CBB), currently with a particular focus on building biological knowledge wikis in aid of community curation of massive biological knowledge.<br /> &lt;/div&gt;<br /> <br /> &lt;!------------Visitor Statistics-------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Visitor Statistics&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;text-align:center&quot;&gt;<br /> &lt;htmlet nocache=&quot;yes&quot;&gt;earth&lt;/htmlet&gt;<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------Reward Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:60%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;[[RiceWiki:Awards|2015 RiceWiki Community Curation Awards]]&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> <br /> 为鼓励更多科研人员和学生参与水稻基因的审编工作，促进我国面向生物大数据的基础性研究人才培养，RiceWiki对符合参选资格条件的个人给予奖励，具体方法如下：<br /> <br /> # 本条例的有关奖项按年度进行评奖。<br /> # 参选资格条件：在2015年（即2015年1月1日至2015年12月31日）参与审编工作的个人（不包括RiceWiki团队中成员），其在本年度的总贡献值（Contribution Score）大于或等于50分（[[Special:AuthorReward | 用户贡献值查询]]）。<br /> # 符合上述参选资格条件的个人将在2016年1月集中进行评审。<br /> # 通过评审且贡献值最高的个人，免费获赠[http://www.mi.com/mipad 小米平板]及荣誉证书；凡是通过评审的个人，免费获赠[http://www.mi.com/wifi 小米随身]WiFi及荣誉证书。<br /> # 上述获奖信息将在RiceWiki网站进行公示。 <br /> <br /> 本条例的解释权属RiceWiki团队。<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------register Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------English------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:50%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;致全体参与者&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> *群体审编（Community Curation）是生物大数据整合和相关文献信息集成的重要方法之一（相关信息：[http://www.biocurator.org/what.shtml 国际生物审编协会]；[http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18769432/ Big data: The future of biocuration]）。<br /> *水稻是我国最重要的经济农作物之一，其数据知识库的建立可有利推动我国水稻的科学研究与应用转化，并影响国内其它相关领域的基础研究。<br /> *我国长期缺乏一个在国际上有一定影响力的数据库/中心，美国有NCBI，欧洲有EBI......<br /> *但是，你们现在所作的一点一滴正在改变这个现状，我们正在朝向建立面向我国重大需求且不同于现今国际生物数据中心的方向前进！<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Chinese----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;注册 &amp; 编辑&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * 请发送电子邮件至ricewiki(AT)big.ac.cn，并提供您的注册用户名（英文）、邮件地址(确保邮箱名正确)和真实姓名。<br /> * 您查收来自ricewiki(AT)big.ac.cn的邮件，里面有您的密码，请尽快登录并修改个人密码。如果两天内没有收到邮件，请检查垃圾邮箱。<br /> * 如果您确实没收到来自ricewiki(AT)big.ac.cn的邮件，请再次发送邮件联系ricewiki(AT)big.ac.cn。<br /> * 当多人在同一时间编辑同一页面时，会发生编辑冲突。建议每次编辑一小段内容并查看编辑历史。详细信息请查看：http://en.wikipedia.org/wiki/Help:Edit_conflict<br /> &lt;/div&gt;<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Main_Page&diff=269673 2016-06-01T08:44:37Z

<p>Rice2012: </p> <hr /> <div>__NOTITLE__<br /> __NOTOC__<br /> __NOEDITSECTION__<br /> &lt;!-----------------title---------------------&gt;<br /> {|style=&quot;width:100%; margin-top:10px; background-color:#f6f6f6; border:1px solid #d2d2d2; margin-bottom: 10px;&quot;<br /> |style=&quot;width:50%; text-align:center; white-space:nowrap; color:#000&quot;|<br /> &lt;div style=&quot;font-size:180%; border:none; margin:0; padding:.5em; color:#000;&quot;&gt;Welcome to RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%&quot;&gt;[[:Category:Genes |86,216]] rice genes inside&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%; color:#492;&quot;&gt;'''Contribute your efforts, further our knowledge.'''&lt;/div&gt;<br /> <br /> |style=&quot;width:18%;|<br /> *&lt;span class=plainlinks&gt;[[:Category:Genes|Genes]]&lt;/span&gt;<br /> *[[RiceWiki:GeneFamilies|Gene Families]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Chromosomes|Chromosomes]]<br /> *[[RiceWiki:Databases|Databases]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Genome_Browser|Genome Browser]]<br /> *[[RiceWiki:Templates|Templates]]<br /> |}<br /> <br /> &lt;!---------------welcome Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f1f1f1; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Introduction&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;{{:RiceWiki:Summary}}&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.2em 0.5em;text-align:center&quot;&gt;''Nothing great is ever accomplished in isolation. – Yo-Yo Ma''&lt;/div&gt;<br /> ----<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> {|<br /> |<br /> *Featured genes: [[Os01g0883800]], [[Os02g0170300]], [[Os03g0149100]], [[Os08g0162100]]<br /> *Stress-related genes: [[RiceWiki:Stress|a list of stress-related genes]]<br /> *Genes to be curated: [[RiceWiki:TBC|a list of genes to be curated]]<br /> |<br /> *Curated genes: [[Special:CuratedGenes | {{StatisticsActivity:type=curatedgenecount}} curated genes]]<br /> *User list: [[Special:ListUsers| {{StatisticsActivity:type=usercount}} registered users]]<br /> *Contribution score: [[Special:AuthorReward |quantified contributions]] by [http://www.ncbi.nlm.nih.gov/pubmed/23732274 ''AuthorReward'']<br /> |<br /> *Literature: [http://literature.ic4r.org 31527] rice-related publications associated with rice genes<br /> *Transcriptome: gene expression profiles at 22 developmental stages and tissue types based on RNA-Seq<br /> *Variations: SNPs and INDELs (under collection)<br /> |}<br /> &lt;/div&gt;<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;RiceWiki Award Winners in 2014&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:2014Award1.JPG|right|thumb|200px|link=RiceWiki:Awards]]<br /> *2014 Outstanding Award: SHI Junchao (侍骏超), Contribution Score: 190.164, Award: an iPad mini with Retina Display<br /> *2014 Excellent Award: HUANG Huasheng (黄华生), Contribution Score: 189.713, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: SONG Yafeng (宋亚凤), Contribution Score: 64.476, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: PAN Wenbo (潘文波), Contribution Score: 52.352, Award: XiaoMi Portable WiFi <br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part one----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------Rice Genome Overview------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent; width:30%;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Genome Overview&lt;/div&gt;<br /> &lt;div style=&quot;padding:1em 0em 0em 0em; text-align:center;&quot;&gt;[[image:RiceG.jpg]]&lt;/div&gt;<br /> == ==<br /> &lt;div style=&quot;padding:0.2em 0.5em;&quot;&gt;<br /> ====[[:Category:Japonica Genes | ''Oryza sativa Japonica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Japonica Chromosome 1|'''1''']].<br /> [[:category:Japonica Chromosome 2|'''2''']].<br /> [[:category:Japonica Chromosome 3|'''3''']].<br /> [[:category:Japonica Chromosome 4|'''4''']].<br /> [[:category:Japonica Chromosome 5|'''5''']].<br /> [[:category:Japonica Chromosome 6|'''6''']].<br /> [[:category:Japonica Chromosome 7|'''7''']].<br /> [[:category:Japonica Chromosome 8|'''8''']].<br /> [[:category:Japonica Chromosome 9|'''9''']].<br /> [[:category:Japonica Chromosome 10|'''10''']].<br /> [[:category:Japonica Chromosome 11|'''11''']].<br /> [[:category:Japonica Chromosome 12|'''12''']].<br /> [[:category:Japonica_Mitochondrion|'''Mt''']].<br /> [[:category:Japonica_Plastid|'''Pd''']]<br /> <br /> ====[[:Category:Indica Genes | ''Oryza sativa Indica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Indica Chromosome 1|'''1''']].<br /> [[:category:Indica Chromosome 2|'''2''']].<br /> [[:category:Indica Chromosome 3|'''3''']].<br /> [[:category:Indica Chromosome 4|'''4''']].<br /> [[:category:Indica Chromosome 5|'''5''']].<br /> [[:category:Indica Chromosome 6|'''6''']].<br /> [[:category:Indica Chromosome 7|'''7''']].<br /> [[:category:Indica Chromosome 8|'''8''']].<br /> [[:category:Indica Chromosome 9|'''9''']].<br /> [[:category:Indica Chromosome 10|'''10''']].<br /> [[:category:Indica Chromosome 11|'''11''']].<br /> [[:category:Indica Chromosome 12|'''12''']]<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Rice----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Story&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:Damifan.jpg|right|120px|margin: 5px|]]<br /> *As an important food<br /> :Rice is the seed of the monocot plants ''Oryza sativa'' (Asian rice) or ''Oryza glaberrima'' (African rice). As a cereal grain, it is the most important staple food for a large part of the world's human population, especially in East Asia, Southeast Asia, South Asia, the Middle East, and the West Indies. It is the grain with the third-highest worldwide production, after maize (corn) and wheat, according to data for 2010 [http://en.wikipedia.org/wiki/Rice (Full article...)].&lt;br&gt;<br /> *As a biological model<br /> :Rice is also a model organism for the biological study of the grass family of crops and other plants. The two most common rice cultivars, ''indica'' and ''japonica'', were completely sequenced in 2002. The genome sequences of domesticated rice provide a solid foundation for integrating biological information, including genetics, gene expression, development, physiology and evolution.&lt;/div&gt;<br /> ----<br /> {|style=&quot;border:none; background-color:transparent; width:100%&quot; <br /> |-style=&quot;background:transcript; color:black&quot; align=&quot;left&quot; valign=&quot;top&quot;<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Recent Modified Genes&lt;/div&gt; {{StatisticsActivity:type=edits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Highly Accessed Genes&lt;/div&gt; {{StatisticsActivity:type=visits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Most Annotated Genes&lt;/div&gt; {{StatisticsActivity:type=contributes|count = 10}}<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f4f4f4; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Publications&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/24136999 RiceWiki: a wiki-based database for community curation of rice genes] (2014) ''Nucleic Acids Research'', 42(D1),D1222-D1228.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/23732274 AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification] (2013) ''Bioinformatics'', 29(14):1837-1839.<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part two----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> &lt;!------------- Participating----------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:42%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Joining RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;<br /> * RiceWiki allows any user to view and search but only registered users can add and edit content. <br /> * To become a registered user, please email the RiceWiki Team at [mailto:ricewiki@big.ac.cn ricewiki@big.ac.cn] to tell us your preferred login name, real name, research interests, etc., and we will set up an account for you.<br /> * Please also spread this news to any one who might be of interest. [[File:Ppt_ico.gif | link=File:CommunityCuration-RiceWiki.pptx]]&lt;/div&gt;<br /> <br /> &lt;!-------------Lab Information--------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:33%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;About Us&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;Our group works in the field of [http://cbb.big.ac.cn Computational Biology and Bioinformatics] (CBB), currently with a particular focus on building biological knowledge wikis in aid of community curation of massive biological knowledge.<br /> &lt;/div&gt;<br /> <br /> &lt;!------------Visitor Statistics-------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Visitor Statistics&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;text-align:center&quot;&gt;<br /> &lt;htmlet nocache=&quot;yes&quot;&gt;earth&lt;/htmlet&gt;<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------Reward Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:60%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;[[RiceWiki:Awards|2015 RiceWiki Community Curation Awards]]&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> <br /> 为鼓励更多科研人员和学生参与水稻基因的审编工作，促进我国面向生物大数据的基础性研究人才培养，RiceWiki对符合参选资格条件的个人给予奖励，具体方法如下：<br /> <br /> # 本条例的有关奖项按年度进行评奖。<br /> # 参选资格条件：在2015年（即2015年1月1日至2015年12月31日）参与审编工作的个人（不包括RiceWiki团队中成员），其在本年度的总贡献值（Contribution Score）大于或等于50分（[[Special:AuthorReward | 用户贡献值查询]]）。<br /> # 符合上述参选资格条件的个人将在2016年1月集中进行评审。<br /> # 通过评审且贡献值最高的个人，免费获赠[http://www.mi.com/mipad 小米平板]及荣誉证书；凡是通过评审的个人，免费获赠[http://www.mi.com/wifi 小米随身]WiFi及荣誉证书。<br /> # 上述获奖信息将在RiceWiki网站进行公示。 <br /> <br /> 本条例的解释权属RiceWiki团队。<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------register Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------English------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:50%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;致全体参与者&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> *群体审编（Community Curation）是生物大数据整合和相关文献信息集成的重要方法之一（相关信息：[http://www.biocurator.org/what.shtml 国际生物审编协会]；[http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18769432/ Big data: The future of biocuration]）。<br /> *水稻是我国最重要的经济农作物之一，其数据知识库的建立可有利推动我国水稻的科学研究与应用转化，并影响国内其它相关领域的基础研究。<br /> *我国长期缺乏一个在国际上有一定影响力的数据库/中心，美国有NCBI，欧洲有EBI......<br /> *但是，你们现在所作的一点一滴正在改变这个现状，我们正在朝向建立面向我国重大需求且不同于现今国际生物数据中心的方向前进！<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Chinese----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;注册 &amp; 编辑&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * 请发送电子邮件至ricewiki(AT)big.ac.cn，并提供您的注册用户名（英文）、邮件地址(确保邮箱名正确)和真实姓名。<br /> * 您查收来自ricewiki(AT)big.ac.cn的邮件，里面有您的密码，请尽快登录并修改个人密码。如果两天内没有收到邮件，请检查垃圾邮箱。<br /> * 如果您确实没收到来自ricewiki(AT)big.ac.cn的邮件，请再次发送邮件联系ricewiki(AT)big.ac.cn。<br /> * 当多人在同一时间编辑同一页面时，会发生编辑冲突。建议每次编辑一小段内容并查看编辑历史。详细信息请查看：http://en.wikipedia.org/wiki/Help:Edit_conflict<br /> &lt;/div&gt;<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Main_Page&diff=269672 2016-06-01T08:44:05Z

<p>Rice2012: </p> <hr /> <div>__NOTITLE__<br /> __NOTOC__<br /> __NOEDITSECTION__<br /> &lt;!-----------------title---------------------&gt;<br /> {|style=&quot;width:100%; margin-top:10px; background-color:#f6f6f6; border:1px solid #d2d2d2; margin-bottom: 10px;&quot;<br /> |style=&quot;width:50%; text-align:center; white-space:nowrap; color:#000&quot;|<br /> &lt;div style=&quot;font-size:180%; border:none; margin:0; padding:.5em; color:#000;&quot;&gt;Welcome to RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%&quot;&gt;[[:Category:Genes |86,216]] rice genes inside&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%; color:#492;&quot;&gt;'''Contribute your efforts, further our knowledge.'''&lt;/div&gt;<br /> <br /> |style=&quot;width:18%;|<br /> *&lt;span class=plainlinks&gt;[[:Category:Genes|Genes]]&lt;/span&gt;<br /> *[[RiceWiki:GeneFamilies|Gene Families]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Chromosomes|Chromosomes]]<br /> *[[RiceWiki:Databases|Databases]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Genome_Browser|Genome Browser]]<br /> *[[RiceWiki:Templates|Templates]]<br /> |}<br /> <br /> &lt;!---------------welcome Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f1f1f1; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Introduction&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;{{:RiceWiki:Summary}}&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.2em 0.5em;text-align:center&quot;&gt;''Nothing great is ever accomplished in isolation. – Yo-Yo Ma''&lt;/div&gt;<br /> ----<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> {|<br /> |<br /> *Featured genes: [[Os01g0883800]], [[Os02g0170300]], [[Os03g0149100]], [[Os08g0162100]]<br /> *Stress-related genes: [[RiceWiki:Stress|a list of stress-related genes]]<br /> *Genes to be curated: [[RiceWiki:TBC|a list of genes to be curated]]<br /> |<br /> *Curated genes: [[Special:CuratedGenes | {{StatisticsActivity:type=curatedgenecount}} curated genes]]<br /> *User list: [[Special:ListUsers| {{StatisticsActivity:type=usercount}} registered users]]<br /> *Contribution score: [[Special:AuthorReward |quantified contributions]] by [http://www.ncbi.nlm.nih.gov/pubmed/23732274 ''AuthorReward'']<br /> |<br /> *Literature: [http://literature.ic4r.org 31527] rice-related publications associated with rice genes<br /> *Transcriptome: gene expression profiles at 22 developmental stages and tissue types based on RNA-Seq<br /> *Variations: SNPs and INDELs (under collection)<br /> |}<br /> &lt;/div&gt;<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;RiceWiki Award Winners in 2014&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:2014Award1.JPG|right|thumb|200px|link=RiceWiki:Awards]]<br /> *2014 Outstanding Award: SHI Junchao (侍骏超), Contribution Score: 190.164, Award: an iPad mini with Retina Display<br /> *2014 Excellent Award: HUANG Huasheng (黄华生), Contribution Score: 189.713, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: SONG Yafeng (宋亚凤), Contribution Score: 64.476, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: PAN Wenbo (潘文波), Contribution Score: 52.352, Award: XiaoMi Portable WiFi <br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part one----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------Rice Genome Overview------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent; width:30%;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Genome Overview&lt;/div&gt;<br /> &lt;div style=&quot;padding:1em 0em 0em 0em; text-align:center;&quot;&gt;[[image:RiceG.jpg]]&lt;/div&gt;<br /> == ==<br /> &lt;div style=&quot;padding:0.2em 0.5em;&quot;&gt;<br /> ====[[:Category:Japonica Genes | ''Oryza sativa Japonica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Japonica Chromosome 1|'''1''']].<br /> [[:category:Japonica Chromosome 2|'''2''']].<br /> [[:category:Japonica Chromosome 3|'''3''']].<br /> [[:category:Japonica Chromosome 4|'''4''']].<br /> [[:category:Japonica Chromosome 5|'''5''']].<br /> [[:category:Japonica Chromosome 6|'''6''']].<br /> [[:category:Japonica Chromosome 7|'''7''']].<br /> [[:category:Japonica Chromosome 8|'''8''']].<br /> [[:category:Japonica Chromosome 9|'''9''']].<br /> [[:category:Japonica Chromosome 10|'''10''']].<br /> [[:category:Japonica Chromosome 11|'''11''']].<br /> [[:category:Japonica Chromosome 12|'''12''']].<br /> [[:category:Japonica_Mitochondrion|'''Mt''']].<br /> [[:category:Japonica_Plastid|'''Pd''']]<br /> <br /> ====[[:Category:Indica Genes | ''Oryza sativa Indica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Indica Chromosome 1|'''1''']].<br /> [[:category:Indica Chromosome 2|'''2''']].<br /> [[:category:Indica Chromosome 3|'''3''']].<br /> [[:category:Indica Chromosome 4|'''4''']].<br /> [[:category:Indica Chromosome 5|'''5''']].<br /> [[:category:Indica Chromosome 6|'''6''']].<br /> [[:category:Indica Chromosome 7|'''7''']].<br /> [[:category:Indica Chromosome 8|'''8''']].<br /> [[:category:Indica Chromosome 9|'''9''']].<br /> [[:category:Indica Chromosome 10|'''10''']].<br /> [[:category:Indica Chromosome 11|'''11''']].<br /> [[:category:Indica Chromosome 12|'''12''']]<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Rice----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Story&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:Damifan.jpg|right|120px|margin: 5px|]]<br /> *As an important food<br /> :Rice is the seed of the monocot plants ''Oryza sativa'' (Asian rice) or ''Oryza glaberrima'' (African rice). As a cereal grain, it is the most important staple food for a large part of the world's human population, especially in East Asia, Southeast Asia, South Asia, the Middle East, and the West Indies. It is the grain with the third-highest worldwide production, after maize (corn) and wheat, according to data for 2010 [http://en.wikipedia.org/wiki/Rice (Full article...)].&lt;br&gt;<br /> *As a biological model<br /> :Rice is also a model organism for the biological study of the grass family of crops and other plants. The two most common rice cultivars, ''indica'' and ''japonica'', were completely sequenced in 2002. The genome sequences of domesticated rice provide a solid foundation for integrating biological information, including genetics, gene expression, development, physiology and evolution.&lt;/div&gt;<br /> ----<br /> {|-style=&quot;border:none; background-color:transparent; width:100%&quot; <br /> |style=&quot;background:transcript; color:black&quot; align=&quot;left&quot; valign=&quot;top&quot;<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Recent Modified Genes&lt;/div&gt; {{StatisticsActivity:type=edits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Highly Accessed Genes&lt;/div&gt; {{StatisticsActivity:type=visits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Most Annotated Genes&lt;/div&gt; {{StatisticsActivity:type=contributes|count = 10}}<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f4f4f4; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Publications&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/24136999 RiceWiki: a wiki-based database for community curation of rice genes] (2014) ''Nucleic Acids Research'', 42(D1),D1222-D1228.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/23732274 AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification] (2013) ''Bioinformatics'', 29(14):1837-1839.<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part two----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> &lt;!------------- Participating----------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:42%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Joining RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;<br /> * RiceWiki allows any user to view and search but only registered users can add and edit content. <br /> * To become a registered user, please email the RiceWiki Team at [mailto:ricewiki@big.ac.cn ricewiki@big.ac.cn] to tell us your preferred login name, real name, research interests, etc., and we will set up an account for you.<br /> * Please also spread this news to any one who might be of interest. [[File:Ppt_ico.gif | link=File:CommunityCuration-RiceWiki.pptx]]&lt;/div&gt;<br /> <br /> &lt;!-------------Lab Information--------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:33%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;About Us&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;Our group works in the field of [http://cbb.big.ac.cn Computational Biology and Bioinformatics] (CBB), currently with a particular focus on building biological knowledge wikis in aid of community curation of massive biological knowledge.<br /> &lt;/div&gt;<br /> <br /> &lt;!------------Visitor Statistics-------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Visitor Statistics&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;text-align:center&quot;&gt;<br /> &lt;htmlet nocache=&quot;yes&quot;&gt;earth&lt;/htmlet&gt;<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------Reward Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:60%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;[[RiceWiki:Awards|2015 RiceWiki Community Curation Awards]]&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> <br /> 为鼓励更多科研人员和学生参与水稻基因的审编工作，促进我国面向生物大数据的基础性研究人才培养，RiceWiki对符合参选资格条件的个人给予奖励，具体方法如下：<br /> <br /> # 本条例的有关奖项按年度进行评奖。<br /> # 参选资格条件：在2015年（即2015年1月1日至2015年12月31日）参与审编工作的个人（不包括RiceWiki团队中成员），其在本年度的总贡献值（Contribution Score）大于或等于50分（[[Special:AuthorReward | 用户贡献值查询]]）。<br /> # 符合上述参选资格条件的个人将在2016年1月集中进行评审。<br /> # 通过评审且贡献值最高的个人，免费获赠[http://www.mi.com/mipad 小米平板]及荣誉证书；凡是通过评审的个人，免费获赠[http://www.mi.com/wifi 小米随身]WiFi及荣誉证书。<br /> # 上述获奖信息将在RiceWiki网站进行公示。 <br /> <br /> 本条例的解释权属RiceWiki团队。<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------register Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------English------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:50%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;致全体参与者&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> *群体审编（Community Curation）是生物大数据整合和相关文献信息集成的重要方法之一（相关信息：[http://www.biocurator.org/what.shtml 国际生物审编协会]；[http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18769432/ Big data: The future of biocuration]）。<br /> *水稻是我国最重要的经济农作物之一，其数据知识库的建立可有利推动我国水稻的科学研究与应用转化，并影响国内其它相关领域的基础研究。<br /> *我国长期缺乏一个在国际上有一定影响力的数据库/中心，美国有NCBI，欧洲有EBI......<br /> *但是，你们现在所作的一点一滴正在改变这个现状，我们正在朝向建立面向我国重大需求且不同于现今国际生物数据中心的方向前进！<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Chinese----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;注册 &amp; 编辑&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * 请发送电子邮件至ricewiki(AT)big.ac.cn，并提供您的注册用户名（英文）、邮件地址(确保邮箱名正确)和真实姓名。<br /> * 您查收来自ricewiki(AT)big.ac.cn的邮件，里面有您的密码，请尽快登录并修改个人密码。如果两天内没有收到邮件，请检查垃圾邮箱。<br /> * 如果您确实没收到来自ricewiki(AT)big.ac.cn的邮件，请再次发送邮件联系ricewiki(AT)big.ac.cn。<br /> * 当多人在同一时间编辑同一页面时，会发生编辑冲突。建议每次编辑一小段内容并查看编辑历史。详细信息请查看：http://en.wikipedia.org/wiki/Help:Edit_conflict<br /> &lt;/div&gt;<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Main_Page&diff=269671 2016-06-01T08:43:43Z

<p>Rice2012: </p> <hr /> <div>__NOTITLE__<br /> __NOTOC__<br /> __NOEDITSECTION__<br /> &lt;!-----------------title---------------------&gt;<br /> {|style=&quot;width:100%; margin-top:10px; background-color:#f6f6f6; border:1px solid #d2d2d2; margin-bottom: 10px;&quot;<br /> |style=&quot;width:50%; text-align:center; white-space:nowrap; color:#000&quot;|<br /> &lt;div style=&quot;font-size:180%; border:none; margin:0; padding:.5em; color:#000;&quot;&gt;Welcome to RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%&quot;&gt;[[:Category:Genes |86,216]] rice genes inside&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%; color:#492;&quot;&gt;'''Contribute your efforts, further our knowledge.'''&lt;/div&gt;<br /> <br /> |style=&quot;width:18%;|<br /> *&lt;span class=plainlinks&gt;[[:Category:Genes|Genes]]&lt;/span&gt;<br /> *[[RiceWiki:GeneFamilies|Gene Families]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Chromosomes|Chromosomes]]<br /> *[[RiceWiki:Databases|Databases]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Genome_Browser|Genome Browser]]<br /> *[[RiceWiki:Templates|Templates]]<br /> |}<br /> <br /> &lt;!---------------welcome Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f1f1f1; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Introduction&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;{{:RiceWiki:Summary}}&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.2em 0.5em;text-align:center&quot;&gt;''Nothing great is ever accomplished in isolation. – Yo-Yo Ma''&lt;/div&gt;<br /> ----<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> {|<br /> |<br /> *Featured genes: [[Os01g0883800]], [[Os02g0170300]], [[Os03g0149100]], [[Os08g0162100]]<br /> *Stress-related genes: [[RiceWiki:Stress|a list of stress-related genes]]<br /> *Genes to be curated: [[RiceWiki:TBC|a list of genes to be curated]]<br /> |<br /> *Curated genes: [[Special:CuratedGenes | {{StatisticsActivity:type=curatedgenecount}} curated genes]]<br /> *User list: [[Special:ListUsers| {{StatisticsActivity:type=usercount}} registered users]]<br /> *Contribution score: [[Special:AuthorReward |quantified contributions]] by [http://www.ncbi.nlm.nih.gov/pubmed/23732274 ''AuthorReward'']<br /> |<br /> *Literature: [http://literature.ic4r.org 31527] rice-related publications associated with rice genes<br /> *Transcriptome: gene expression profiles at 22 developmental stages and tissue types based on RNA-Seq<br /> *Variations: SNPs and INDELs (under collection)<br /> |}<br /> &lt;/div&gt;<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;RiceWiki Award Winners in 2014&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:2014Award1.JPG|right|thumb|200px|link=RiceWiki:Awards]]<br /> *2014 Outstanding Award: SHI Junchao (侍骏超), Contribution Score: 190.164, Award: an iPad mini with Retina Display<br /> *2014 Excellent Award: HUANG Huasheng (黄华生), Contribution Score: 189.713, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: SONG Yafeng (宋亚凤), Contribution Score: 64.476, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: PAN Wenbo (潘文波), Contribution Score: 52.352, Award: XiaoMi Portable WiFi <br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part one----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------Rice Genome Overview------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent; width:30%;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Genome Overview&lt;/div&gt;<br /> &lt;div style=&quot;padding:1em 0em 0em 0em; text-align:center;&quot;&gt;[[image:RiceG.jpg]]&lt;/div&gt;<br /> == ==<br /> &lt;div style=&quot;padding:0.2em 0.5em;&quot;&gt;<br /> ====[[:Category:Japonica Genes | ''Oryza sativa Japonica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Japonica Chromosome 1|'''1''']].<br /> [[:category:Japonica Chromosome 2|'''2''']].<br /> [[:category:Japonica Chromosome 3|'''3''']].<br /> [[:category:Japonica Chromosome 4|'''4''']].<br /> [[:category:Japonica Chromosome 5|'''5''']].<br /> [[:category:Japonica Chromosome 6|'''6''']].<br /> [[:category:Japonica Chromosome 7|'''7''']].<br /> [[:category:Japonica Chromosome 8|'''8''']].<br /> [[:category:Japonica Chromosome 9|'''9''']].<br /> [[:category:Japonica Chromosome 10|'''10''']].<br /> [[:category:Japonica Chromosome 11|'''11''']].<br /> [[:category:Japonica Chromosome 12|'''12''']].<br /> [[:category:Japonica_Mitochondrion|'''Mt''']].<br /> [[:category:Japonica_Plastid|'''Pd''']]<br /> <br /> ====[[:Category:Indica Genes | ''Oryza sativa Indica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Indica Chromosome 1|'''1''']].<br /> [[:category:Indica Chromosome 2|'''2''']].<br /> [[:category:Indica Chromosome 3|'''3''']].<br /> [[:category:Indica Chromosome 4|'''4''']].<br /> [[:category:Indica Chromosome 5|'''5''']].<br /> [[:category:Indica Chromosome 6|'''6''']].<br /> [[:category:Indica Chromosome 7|'''7''']].<br /> [[:category:Indica Chromosome 8|'''8''']].<br /> [[:category:Indica Chromosome 9|'''9''']].<br /> [[:category:Indica Chromosome 10|'''10''']].<br /> [[:category:Indica Chromosome 11|'''11''']].<br /> [[:category:Indica Chromosome 12|'''12''']]<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Rice----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Story&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:Damifan.jpg|right|120px|margin: 5px|]]<br /> *As an important food<br /> :Rice is the seed of the monocot plants ''Oryza sativa'' (Asian rice) or ''Oryza glaberrima'' (African rice). As a cereal grain, it is the most important staple food for a large part of the world's human population, especially in East Asia, Southeast Asia, South Asia, the Middle East, and the West Indies. It is the grain with the third-highest worldwide production, after maize (corn) and wheat, according to data for 2010 [http://en.wikipedia.org/wiki/Rice (Full article...)].&lt;br&gt;<br /> *As a biological model<br /> :Rice is also a model organism for the biological study of the grass family of crops and other plants. The two most common rice cultivars, ''indica'' and ''japonica'', were completely sequenced in 2002. The genome sequences of domesticated rice provide a solid foundation for integrating biological information, including genetics, gene expression, development, physiology and evolution.&lt;/div&gt;<br /> ----<br /> {|style=&quot;border:none; background-color:transparent; width:100%&quot; <br /> |style=&quot;background:transcript; color:black&quot; align=&quot;left&quot; valign=&quot;top&quot;<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Recent Modified Genes&lt;/div&gt; {{StatisticsActivity:type=edits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Highly Accessed Genes&lt;/div&gt; {{StatisticsActivity:type=visits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Most Annotated Genes&lt;/div&gt; {{StatisticsActivity:type=contributes|count = 10}}<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f4f4f4; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Publications&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/24136999 RiceWiki: a wiki-based database for community curation of rice genes] (2014) ''Nucleic Acids Research'', 42(D1),D1222-D1228.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/23732274 AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification] (2013) ''Bioinformatics'', 29(14):1837-1839.<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part two----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> &lt;!------------- Participating----------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:42%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Joining RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;<br /> * RiceWiki allows any user to view and search but only registered users can add and edit content. <br /> * To become a registered user, please email the RiceWiki Team at [mailto:ricewiki@big.ac.cn ricewiki@big.ac.cn] to tell us your preferred login name, real name, research interests, etc., and we will set up an account for you.<br /> * Please also spread this news to any one who might be of interest. [[File:Ppt_ico.gif | link=File:CommunityCuration-RiceWiki.pptx]]&lt;/div&gt;<br /> <br /> &lt;!-------------Lab Information--------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:33%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;About Us&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;Our group works in the field of [http://cbb.big.ac.cn Computational Biology and Bioinformatics] (CBB), currently with a particular focus on building biological knowledge wikis in aid of community curation of massive biological knowledge.<br /> &lt;/div&gt;<br /> <br /> &lt;!------------Visitor Statistics-------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Visitor Statistics&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;text-align:center&quot;&gt;<br /> &lt;htmlet nocache=&quot;yes&quot;&gt;earth&lt;/htmlet&gt;<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------Reward Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:60%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;[[RiceWiki:Awards|2015 RiceWiki Community Curation Awards]]&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> <br /> 为鼓励更多科研人员和学生参与水稻基因的审编工作，促进我国面向生物大数据的基础性研究人才培养，RiceWiki对符合参选资格条件的个人给予奖励，具体方法如下：<br /> <br /> # 本条例的有关奖项按年度进行评奖。<br /> # 参选资格条件：在2015年（即2015年1月1日至2015年12月31日）参与审编工作的个人（不包括RiceWiki团队中成员），其在本年度的总贡献值（Contribution Score）大于或等于50分（[[Special:AuthorReward | 用户贡献值查询]]）。<br /> # 符合上述参选资格条件的个人将在2016年1月集中进行评审。<br /> # 通过评审且贡献值最高的个人，免费获赠[http://www.mi.com/mipad 小米平板]及荣誉证书；凡是通过评审的个人，免费获赠[http://www.mi.com/wifi 小米随身]WiFi及荣誉证书。<br /> # 上述获奖信息将在RiceWiki网站进行公示。 <br /> <br /> 本条例的解释权属RiceWiki团队。<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------register Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------English------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:50%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;致全体参与者&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> *群体审编（Community Curation）是生物大数据整合和相关文献信息集成的重要方法之一（相关信息：[http://www.biocurator.org/what.shtml 国际生物审编协会]；[http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18769432/ Big data: The future of biocuration]）。<br /> *水稻是我国最重要的经济农作物之一，其数据知识库的建立可有利推动我国水稻的科学研究与应用转化，并影响国内其它相关领域的基础研究。<br /> *我国长期缺乏一个在国际上有一定影响力的数据库/中心，美国有NCBI，欧洲有EBI......<br /> *但是，你们现在所作的一点一滴正在改变这个现状，我们正在朝向建立面向我国重大需求且不同于现今国际生物数据中心的方向前进！<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Chinese----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;注册 &amp; 编辑&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * 请发送电子邮件至ricewiki(AT)big.ac.cn，并提供您的注册用户名（英文）、邮件地址(确保邮箱名正确)和真实姓名。<br /> * 您查收来自ricewiki(AT)big.ac.cn的邮件，里面有您的密码，请尽快登录并修改个人密码。如果两天内没有收到邮件，请检查垃圾邮箱。<br /> * 如果您确实没收到来自ricewiki(AT)big.ac.cn的邮件，请再次发送邮件联系ricewiki(AT)big.ac.cn。<br /> * 当多人在同一时间编辑同一页面时，会发生编辑冲突。建议每次编辑一小段内容并查看编辑历史。详细信息请查看：http://en.wikipedia.org/wiki/Help:Edit_conflict<br /> &lt;/div&gt;<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Main_Page&diff=269670 2016-06-01T08:42:08Z

<p>Rice2012: </p> <hr /> <div>__NOTITLE__<br /> __NOTOC__<br /> __NOEDITSECTION__<br /> &lt;!-----------------title---------------------&gt;<br /> {|style=&quot;width:100%; margin-top:10px; background-color:#f6f6f6; border:1px solid #d2d2d2; margin-bottom: 10px;&quot;<br /> |style=&quot;width:50%; text-align:center; white-space:nowrap; color:#000&quot;|<br /> &lt;div style=&quot;font-size:180%; border:none; margin:0; padding:.5em; color:#000;&quot;&gt;Welcome to RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%&quot;&gt;[[:Category:Genes |86,216]] rice genes inside&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%; color:#492;&quot;&gt;'''Contribute your efforts, further our knowledge.'''&lt;/div&gt;<br /> <br /> |style=&quot;width:18%;|<br /> *&lt;span class=plainlinks&gt;[[:Category:Genes|Genes]]&lt;/span&gt;<br /> *[[RiceWiki:GeneFamilies|Gene Families]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Chromosomes|Chromosomes]]<br /> *[[RiceWiki:Databases|Databases]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Genome_Browser|Genome Browser]]<br /> *[[RiceWiki:Templates|Templates]]<br /> |}<br /> <br /> &lt;!---------------welcome Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f1f1f1; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Introduction&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;{{:RiceWiki:Summary}}&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.2em 0.5em;text-align:center&quot;&gt;''Nothing great is ever accomplished in isolation. – Yo-Yo Ma''&lt;/div&gt;<br /> ----<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> {|<br /> |<br /> *Featured genes: [[Os01g0883800]], [[Os02g0170300]], [[Os03g0149100]], [[Os08g0162100]]<br /> *Stress-related genes: [[RiceWiki:Stress|a list of stress-related genes]]<br /> *Genes to be curated: [[RiceWiki:TBC|a list of genes to be curated]]<br /> |<br /> *Curated genes: [[Special:CuratedGenes | {{StatisticsActivity:type=curatedgenecount}} curated genes]]<br /> *User list: [[Special:ListUsers| {{StatisticsActivity:type=usercount}} registered users]]<br /> *Contribution score: [[Special:AuthorReward |quantified contributions]] by [http://www.ncbi.nlm.nih.gov/pubmed/23732274 ''AuthorReward'']<br /> |<br /> *Literature: [http://literature.ic4r.org 31527] rice-related publications associated with rice genes<br /> *Transcriptome: gene expression profiles at 22 developmental stages and tissue types based on RNA-Seq<br /> *Variations: SNPs and INDELs (under collection)<br /> |}<br /> &lt;/div&gt;<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;RiceWiki Award Winners in 2014&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:2014Award1.JPG|right|thumb|200px|link=RiceWiki:Awards]]<br /> *2014 Outstanding Award: SHI Junchao (侍骏超), Contribution Score: 190.164, Award: an iPad mini with Retina Display<br /> *2014 Excellent Award: HUANG Huasheng (黄华生), Contribution Score: 189.713, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: SONG Yafeng (宋亚凤), Contribution Score: 64.476, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: PAN Wenbo (潘文波), Contribution Score: 52.352, Award: XiaoMi Portable WiFi <br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part one----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------Rice Genome Overview------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent; width:30%;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Genome Overview&lt;/div&gt;<br /> &lt;div style=&quot;padding:1em 0em 0em 0em; text-align:center;&quot;&gt;[[image:RiceG.jpg]]&lt;/div&gt;<br /> == ==<br /> &lt;div style=&quot;padding:0.2em 0.5em;&quot;&gt;<br /> ====[[:Category:Japonica Genes | ''Oryza sativa Japonica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Japonica Chromosome 1|'''1''']].<br /> [[:category:Japonica Chromosome 2|'''2''']].<br /> [[:category:Japonica Chromosome 3|'''3''']].<br /> [[:category:Japonica Chromosome 4|'''4''']].<br /> [[:category:Japonica Chromosome 5|'''5''']].<br /> [[:category:Japonica Chromosome 6|'''6''']].<br /> [[:category:Japonica Chromosome 7|'''7''']].<br /> [[:category:Japonica Chromosome 8|'''8''']].<br /> [[:category:Japonica Chromosome 9|'''9''']].<br /> [[:category:Japonica Chromosome 10|'''10''']].<br /> [[:category:Japonica Chromosome 11|'''11''']].<br /> [[:category:Japonica Chromosome 12|'''12''']].<br /> [[:category:Japonica_Mitochondrion|'''Mt''']].<br /> [[:category:Japonica_Plastid|'''Pd''']]<br /> <br /> ====[[:Category:Indica Genes | ''Oryza sativa Indica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Indica Chromosome 1|'''1''']].<br /> [[:category:Indica Chromosome 2|'''2''']].<br /> [[:category:Indica Chromosome 3|'''3''']].<br /> [[:category:Indica Chromosome 4|'''4''']].<br /> [[:category:Indica Chromosome 5|'''5''']].<br /> [[:category:Indica Chromosome 6|'''6''']].<br /> [[:category:Indica Chromosome 7|'''7''']].<br /> [[:category:Indica Chromosome 8|'''8''']].<br /> [[:category:Indica Chromosome 9|'''9''']].<br /> [[:category:Indica Chromosome 10|'''10''']].<br /> [[:category:Indica Chromosome 11|'''11''']].<br /> [[:category:Indica Chromosome 12|'''12''']]<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Rice----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Story&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:Damifan.jpg|right|120px|margin: 5px|]]<br /> *As an important food<br /> :Rice is the seed of the monocot plants ''Oryza sativa'' (Asian rice) or ''Oryza glaberrima'' (African rice). As a cereal grain, it is the most important staple food for a large part of the world's human population, especially in East Asia, Southeast Asia, South Asia, the Middle East, and the West Indies. It is the grain with the third-highest worldwide production, after maize (corn) and wheat, according to data for 2010 [http://en.wikipedia.org/wiki/Rice (Full article...)].&lt;br&gt;<br /> *As a biological model<br /> :Rice is also a model organism for the biological study of the grass family of crops and other plants. The two most common rice cultivars, ''indica'' and ''japonica'', were completely sequenced in 2002. The genome sequences of domesticated rice provide a solid foundation for integrating biological information, including genetics, gene expression, development, physiology and evolution.&lt;/div&gt;<br /> ----<br /> {|style=&quot;border:none; background-color:transparent; width:100%&quot; <br /> |- style=&quot;background:transcript; color:black&quot; align=&quot;left&quot; valign=&quot;top&quot;<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Recent Modified Genes&lt;/div&gt; {{StatisticsActivity:type=edits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Highly Accessed Genes&lt;/div&gt; {{StatisticsActivity:type=visits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Most Annotated Genes&lt;/div&gt; {{StatisticsActivity:type=contributes|count = 10}}<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f4f4f4; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Publications&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/24136999 RiceWiki: a wiki-based database for community curation of rice genes] (2014) ''Nucleic Acids Research'', 42(D1),D1222-D1228.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/23732274 AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification] (2013) ''Bioinformatics'', 29(14):1837-1839.<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part two----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> &lt;!------------- Participating----------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:42%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Joining RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;<br /> * RiceWiki allows any user to view and search but only registered users can add and edit content. <br /> * To become a registered user, please email the RiceWiki Team at [mailto:ricewiki@big.ac.cn ricewiki@big.ac.cn] to tell us your preferred login name, real name, research interests, etc., and we will set up an account for you.<br /> * Please also spread this news to any one who might be of interest. [[File:Ppt_ico.gif | link=File:CommunityCuration-RiceWiki.pptx]]&lt;/div&gt;<br /> <br /> &lt;!-------------Lab Information--------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:33%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;About Us&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;Our group works in the field of [http://cbb.big.ac.cn Computational Biology and Bioinformatics] (CBB), currently with a particular focus on building biological knowledge wikis in aid of community curation of massive biological knowledge.<br /> &lt;/div&gt;<br /> <br /> &lt;!------------Visitor Statistics-------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Visitor Statistics&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;text-align:center&quot;&gt;<br /> &lt;htmlet nocache=&quot;yes&quot;&gt;earth&lt;/htmlet&gt;<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------Reward Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:60%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;[[RiceWiki:Awards|2015 RiceWiki Community Curation Awards]]&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> <br /> 为鼓励更多科研人员和学生参与水稻基因的审编工作，促进我国面向生物大数据的基础性研究人才培养，RiceWiki对符合参选资格条件的个人给予奖励，具体方法如下：<br /> <br /> # 本条例的有关奖项按年度进行评奖。<br /> # 参选资格条件：在2015年（即2015年1月1日至2015年12月31日）参与审编工作的个人（不包括RiceWiki团队中成员），其在本年度的总贡献值（Contribution Score）大于或等于50分（[[Special:AuthorReward | 用户贡献值查询]]）。<br /> # 符合上述参选资格条件的个人将在2016年1月集中进行评审。<br /> # 通过评审且贡献值最高的个人，免费获赠[http://www.mi.com/mipad 小米平板]及荣誉证书；凡是通过评审的个人，免费获赠[http://www.mi.com/wifi 小米随身]WiFi及荣誉证书。<br /> # 上述获奖信息将在RiceWiki网站进行公示。 <br /> <br /> 本条例的解释权属RiceWiki团队。<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------register Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------English------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:50%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;致全体参与者&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> *群体审编（Community Curation）是生物大数据整合和相关文献信息集成的重要方法之一（相关信息：[http://www.biocurator.org/what.shtml 国际生物审编协会]；[http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18769432/ Big data: The future of biocuration]）。<br /> *水稻是我国最重要的经济农作物之一，其数据知识库的建立可有利推动我国水稻的科学研究与应用转化，并影响国内其它相关领域的基础研究。<br /> *我国长期缺乏一个在国际上有一定影响力的数据库/中心，美国有NCBI，欧洲有EBI......<br /> *但是，你们现在所作的一点一滴正在改变这个现状，我们正在朝向建立面向我国重大需求且不同于现今国际生物数据中心的方向前进！<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Chinese----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;注册 &amp; 编辑&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * 请发送电子邮件至ricewiki(AT)big.ac.cn，并提供您的注册用户名（英文）、邮件地址(确保邮箱名正确)和真实姓名。<br /> * 您查收来自ricewiki(AT)big.ac.cn的邮件，里面有您的密码，请尽快登录并修改个人密码。如果两天内没有收到邮件，请检查垃圾邮箱。<br /> * 如果您确实没收到来自ricewiki(AT)big.ac.cn的邮件，请再次发送邮件联系ricewiki(AT)big.ac.cn。<br /> * 当多人在同一时间编辑同一页面时，会发生编辑冲突。建议每次编辑一小段内容并查看编辑历史。详细信息请查看：http://en.wikipedia.org/wiki/Help:Edit_conflict<br /> &lt;/div&gt;<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Main_Page&diff=269669 2016-06-01T08:18:15Z

<p>Rice2012: </p> <hr /> <div>__NOTITLE__<br /> __NOTOC__<br /> __NOEDITSECTION__<br /> &lt;!-----------------title---------------------&gt;<br /> {|style=&quot;width:100%; margin-top:10px; background-color:#f6f6f6; border:1px solid #d2d2d2; margin-bottom: 10px;&quot;<br /> |style=&quot;width:50%; text-align:center; white-space:nowrap; color:#000&quot;|<br /> &lt;div style=&quot;font-size:180%; border:none; margin:0; padding:.5em; color:#000;&quot;&gt;Welcome to RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%&quot;&gt;[[:Category:Genes |86,216]] rice genes inside&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%; color:#492;&quot;&gt;'''Contribute your efforts, further our knowledge.'''&lt;/div&gt;<br /> <br /> |style=&quot;width:18%;|<br /> *&lt;span class=plainlinks&gt;[[:Category:Genes|Genes]]&lt;/span&gt;<br /> *[[RiceWiki:GeneFamilies|Gene Families]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Chromosomes|Chromosomes]]<br /> *[[RiceWiki:Databases|Databases]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Genome_Browser|Genome Browser]]<br /> *[[RiceWiki:Templates|Templates]]<br /> |}<br /> <br /> &lt;!---------------welcome Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f1f1f1; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Introduction&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;{{:RiceWiki:Summary}}&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.2em 0.5em;text-align:center&quot;&gt;''Nothing great is ever accomplished in isolation. – Yo-Yo Ma''&lt;/div&gt;<br /> ----<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> {|<br /> |<br /> *Featured genes: [[Os01g0883800]], [[Os02g0170300]], [[Os03g0149100]], [[Os08g0162100]]<br /> *Stress-related genes: [[RiceWiki:Stress|a list of stress-related genes]]<br /> *Genes to be curated: [[RiceWiki:TBC|a list of genes to be curated]]<br /> |<br /> *Curated genes: [[Special:CuratedGenes | {{StatisticsActivity:type=curatedgenecount}} curated genes]]<br /> *User list: [[Special:ListUsers| {{StatisticsActivity:type=usercount}} registered users]]<br /> *Contribution score: [[Special:AuthorReward |quantified contributions]] by [http://www.ncbi.nlm.nih.gov/pubmed/23732274 ''AuthorReward'']<br /> |<br /> *Literature: [http://literature.ic4r.org 31527] rice-related publications associated with rice genes<br /> *Transcriptome: gene expression profiles at 22 developmental stages and tissue types based on RNA-Seq<br /> *Variations: SNPs and INDELs (under collection)<br /> |}<br /> &lt;/div&gt;<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;RiceWiki Award Winners in 2014&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:2014Award1.JPG|right|thumb|200px|link=RiceWiki:Awards]]<br /> *2014 Outstanding Award: SHI Junchao (侍骏超), Contribution Score: 190.164, Award: an iPad mini with Retina Display<br /> *2014 Excellent Award: HUANG Huasheng (黄华生), Contribution Score: 189.713, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: SONG Yafeng (宋亚凤), Contribution Score: 64.476, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: PAN Wenbo (潘文波), Contribution Score: 52.352, Award: XiaoMi Portable WiFi <br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part one----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------Rice Genome Overview------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent; width:30%;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Genome Overview&lt;/div&gt;<br /> &lt;div style=&quot;padding:1em 0em 0em 0em; text-align:center;&quot;&gt;[[image:RiceG.jpg]]&lt;/div&gt;<br /> == ==<br /> &lt;div style=&quot;padding:0.2em 0.5em;&quot;&gt;<br /> ====[[:Category:Japonica Genes | ''Oryza sativa Japonica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Japonica Chromosome 1|'''1''']].<br /> [[:category:Japonica Chromosome 2|'''2''']].<br /> [[:category:Japonica Chromosome 3|'''3''']].<br /> [[:category:Japonica Chromosome 4|'''4''']].<br /> [[:category:Japonica Chromosome 5|'''5''']].<br /> [[:category:Japonica Chromosome 6|'''6''']].<br /> [[:category:Japonica Chromosome 7|'''7''']].<br /> [[:category:Japonica Chromosome 8|'''8''']].<br /> [[:category:Japonica Chromosome 9|'''9''']].<br /> [[:category:Japonica Chromosome 10|'''10''']].<br /> [[:category:Japonica Chromosome 11|'''11''']].<br /> [[:category:Japonica Chromosome 12|'''12''']].<br /> [[:category:Japonica_Mitochondrion|'''Mt''']].<br /> [[:category:Japonica_Plastid|'''Pd''']]<br /> <br /> ====[[:Category:Indica Genes | ''Oryza sativa Indica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Indica Chromosome 1|'''1''']].<br /> [[:category:Indica Chromosome 2|'''2''']].<br /> [[:category:Indica Chromosome 3|'''3''']].<br /> [[:category:Indica Chromosome 4|'''4''']].<br /> [[:category:Indica Chromosome 5|'''5''']].<br /> [[:category:Indica Chromosome 6|'''6''']].<br /> [[:category:Indica Chromosome 7|'''7''']].<br /> [[:category:Indica Chromosome 8|'''8''']].<br /> [[:category:Indica Chromosome 9|'''9''']].<br /> [[:category:Indica Chromosome 10|'''10''']].<br /> [[:category:Indica Chromosome 11|'''11''']].<br /> [[:category:Indica Chromosome 12|'''12''']]<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Rice----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Story&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:Damifan.jpg|right|120px|margin: 5px|]]<br /> *As an important food<br /> :Rice is the seed of the monocot plants ''Oryza sativa'' (Asian rice) or ''Oryza glaberrima'' (African rice). As a cereal grain, it is the most important staple food for a large part of the world's human population, especially in East Asia, Southeast Asia, South Asia, the Middle East, and the West Indies. It is the grain with the third-highest worldwide production, after maize (corn) and wheat, according to data for 2010 [http://en.wikipedia.org/wiki/Rice (Full article...)].&lt;br&gt;<br /> *As a biological model<br /> :Rice is also a model organism for the biological study of the grass family of crops and other plants. The two most common rice cultivars, ''indica'' and ''japonica'', were completely sequenced in 2002. The genome sequences of domesticated rice provide a solid foundation for integrating biological information, including genetics, gene expression, development, physiology and evolution.&lt;/div&gt;<br /> ----<br /> {|style=&quot;border:none; background-color:transparent; width:100%&quot; <br /> |- style=&quot;background:transcript; color:black&quot; align=&quot;left&quot; valign=&quot;top&quot;<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Recent Modified Genes&lt;/div&gt; <br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Highly Accessed Genes&lt;/div&gt; <br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Most Annotated Genes&lt;/div&gt; <br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f4f4f4; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Publications&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/24136999 RiceWiki: a wiki-based database for community curation of rice genes] (2014) ''Nucleic Acids Research'', 42(D1),D1222-D1228.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/23732274 AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification] (2013) ''Bioinformatics'', 29(14):1837-1839.<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part two----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> &lt;!------------- Participating----------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:42%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Joining RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;<br /> * RiceWiki allows any user to view and search but only registered users can add and edit content. <br /> * To become a registered user, please email the RiceWiki Team at [mailto:ricewiki@big.ac.cn ricewiki@big.ac.cn] to tell us your preferred login name, real name, research interests, etc., and we will set up an account for you.<br /> * Please also spread this news to any one who might be of interest. [[File:Ppt_ico.gif | link=File:CommunityCuration-RiceWiki.pptx]]&lt;/div&gt;<br /> <br /> &lt;!-------------Lab Information--------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:33%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;About Us&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;Our group works in the field of [http://cbb.big.ac.cn Computational Biology and Bioinformatics] (CBB), currently with a particular focus on building biological knowledge wikis in aid of community curation of massive biological knowledge.<br /> &lt;/div&gt;<br /> <br /> &lt;!------------Visitor Statistics-------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Visitor Statistics&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;text-align:center&quot;&gt;<br /> &lt;htmlet nocache=&quot;yes&quot;&gt;earth&lt;/htmlet&gt;<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------Reward Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:60%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;[[RiceWiki:Awards|2015 RiceWiki Community Curation Awards]]&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> <br /> 为鼓励更多科研人员和学生参与水稻基因的审编工作，促进我国面向生物大数据的基础性研究人才培养，RiceWiki对符合参选资格条件的个人给予奖励，具体方法如下：<br /> <br /> # 本条例的有关奖项按年度进行评奖。<br /> # 参选资格条件：在2015年（即2015年1月1日至2015年12月31日）参与审编工作的个人（不包括RiceWiki团队中成员），其在本年度的总贡献值（Contribution Score）大于或等于50分（[[Special:AuthorReward | 用户贡献值查询]]）。<br /> # 符合上述参选资格条件的个人将在2016年1月集中进行评审。<br /> # 通过评审且贡献值最高的个人，免费获赠[http://www.mi.com/mipad 小米平板]及荣誉证书；凡是通过评审的个人，免费获赠[http://www.mi.com/wifi 小米随身]WiFi及荣誉证书。<br /> # 上述获奖信息将在RiceWiki网站进行公示。 <br /> <br /> 本条例的解释权属RiceWiki团队。<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------register Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------English------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:50%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;致全体参与者&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> *群体审编（Community Curation）是生物大数据整合和相关文献信息集成的重要方法之一（相关信息：[http://www.biocurator.org/what.shtml 国际生物审编协会]；[http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18769432/ Big data: The future of biocuration]）。<br /> *水稻是我国最重要的经济农作物之一，其数据知识库的建立可有利推动我国水稻的科学研究与应用转化，并影响国内其它相关领域的基础研究。<br /> *我国长期缺乏一个在国际上有一定影响力的数据库/中心，美国有NCBI，欧洲有EBI......<br /> *但是，你们现在所作的一点一滴正在改变这个现状，我们正在朝向建立面向我国重大需求且不同于现今国际生物数据中心的方向前进！<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Chinese----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;注册 &amp; 编辑&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * 请发送电子邮件至ricewiki(AT)big.ac.cn，并提供您的注册用户名（英文）、邮件地址(确保邮箱名正确)和真实姓名。<br /> * 您查收来自ricewiki(AT)big.ac.cn的邮件，里面有您的密码，请尽快登录并修改个人密码。如果两天内没有收到邮件，请检查垃圾邮箱。<br /> * 如果您确实没收到来自ricewiki(AT)big.ac.cn的邮件，请再次发送邮件联系ricewiki(AT)big.ac.cn。<br /> * 当多人在同一时间编辑同一页面时，会发生编辑冲突。建议每次编辑一小段内容并查看编辑历史。详细信息请查看：http://en.wikipedia.org/wiki/Help:Edit_conflict<br /> &lt;/div&gt;<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Main_Page&diff=269668 2015-09-17T14:10:28Z

<p>Rice2012: </p> <hr /> <div>__NOTITLE__<br /> __NOTOC__<br /> __NOEDITSECTION__<br /> &lt;!-----------------title---------------------&gt;<br /> {|style=&quot;width:100%; margin-top:10px; background-color:#f6f6f6; border:1px solid #d2d2d2; margin-bottom: 10px;&quot;<br /> |style=&quot;width:50%; text-align:center; white-space:nowrap; color:#000&quot;|<br /> &lt;div style=&quot;font-size:180%; border:none; margin:0; padding:.5em; color:#000;&quot;&gt;Welcome to RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%&quot;&gt;[[:Category:Genes |86,216]] rice genes inside&lt;/div&gt;<br /> &lt;div style=&quot;padding:0em; font-size:100%; color:#492;&quot;&gt;'''Contribute your efforts, further our knowledge.'''&lt;/div&gt;<br /> <br /> |style=&quot;width:18%;|<br /> *&lt;span class=plainlinks&gt;[[:Category:Genes|Genes]]&lt;/span&gt;<br /> *[[RiceWiki:GeneFamilies|Gene Families]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Chromosomes|Chromosomes]]<br /> *[[RiceWiki:Databases|Databases]]<br /> |style=&quot;width:18%;|<br /> *[[RiceWiki:Genome_Browser|Genome Browser]]<br /> *[[RiceWiki:Templates|Templates]]<br /> |}<br /> <br /> &lt;!---------------welcome Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f1f1f1; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Introduction&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;{{:RiceWiki:Summary}}&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.2em 0.5em;text-align:center&quot;&gt;''Nothing great is ever accomplished in isolation. – Yo-Yo Ma''&lt;/div&gt;<br /> ----<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> {|<br /> |<br /> *Featured genes: [[Os01g0883800]], [[Os02g0170300]], [[Os03g0149100]], [[Os08g0162100]]<br /> *Stress-related genes: [[RiceWiki:Stress|a list of stress-related genes]]<br /> *Genes to be curated: [[RiceWiki:TBC|a list of genes to be curated]]<br /> |<br /> *Curated genes: [[Special:CuratedGenes | {{StatisticsActivity:type=curatedgenecount}} curated genes]]<br /> *User list: [[Special:ListUsers| {{StatisticsActivity:type=usercount}} registered users]]<br /> *Contribution score: [[Special:AuthorReward |quantified contributions]] by [http://www.ncbi.nlm.nih.gov/pubmed/23732274 ''AuthorReward'']<br /> |<br /> *Literature: [http://literature.ic4r.org 31527] rice-related publications associated with rice genes<br /> *Transcriptome: gene expression profiles at 22 developmental stages and tissue types based on RNA-Seq<br /> *Variations: SNPs and INDELs (under collection)<br /> |}<br /> &lt;/div&gt;<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;RiceWiki Award Winners in 2014&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:2014Award1.JPG|right|thumb|200px|link=RiceWiki:Awards]]<br /> *2014 Outstanding Award: SHI Junchao (侍骏超), Contribution Score: 190.164, Award: an iPad mini with Retina Display<br /> *2014 Excellent Award: HUANG Huasheng (黄华生), Contribution Score: 189.713, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: SONG Yafeng (宋亚凤), Contribution Score: 64.476, Award: XiaoMi Portable WiFi<br /> *2014 Excellent Award: PAN Wenbo (潘文波), Contribution Score: 52.352, Award: XiaoMi Portable WiFi <br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part one----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------Rice Genome Overview------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent; width:30%;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Genome Overview&lt;/div&gt;<br /> &lt;div style=&quot;padding:1em 0em 0em 0em; text-align:center;&quot;&gt;[[image:RiceG.jpg]]&lt;/div&gt;<br /> == ==<br /> &lt;div style=&quot;padding:0.2em 0.5em;&quot;&gt;<br /> ====[[:Category:Japonica Genes | ''Oryza sativa Japonica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Japonica Chromosome 1|'''1''']].<br /> [[:category:Japonica Chromosome 2|'''2''']].<br /> [[:category:Japonica Chromosome 3|'''3''']].<br /> [[:category:Japonica Chromosome 4|'''4''']].<br /> [[:category:Japonica Chromosome 5|'''5''']].<br /> [[:category:Japonica Chromosome 6|'''6''']].<br /> [[:category:Japonica Chromosome 7|'''7''']].<br /> [[:category:Japonica Chromosome 8|'''8''']].<br /> [[:category:Japonica Chromosome 9|'''9''']].<br /> [[:category:Japonica Chromosome 10|'''10''']].<br /> [[:category:Japonica Chromosome 11|'''11''']].<br /> [[:category:Japonica Chromosome 12|'''12''']].<br /> [[:category:Japonica_Mitochondrion|'''Mt''']].<br /> [[:category:Japonica_Plastid|'''Pd''']]<br /> <br /> ====[[:Category:Indica Genes | ''Oryza sativa Indica'' Group]]====<br /> '''Chromosome'''<br /> [[:category:Indica Chromosome 1|'''1''']].<br /> [[:category:Indica Chromosome 2|'''2''']].<br /> [[:category:Indica Chromosome 3|'''3''']].<br /> [[:category:Indica Chromosome 4|'''4''']].<br /> [[:category:Indica Chromosome 5|'''5''']].<br /> [[:category:Indica Chromosome 6|'''6''']].<br /> [[:category:Indica Chromosome 7|'''7''']].<br /> [[:category:Indica Chromosome 8|'''8''']].<br /> [[:category:Indica Chromosome 9|'''9''']].<br /> [[:category:Indica Chromosome 10|'''10''']].<br /> [[:category:Indica Chromosome 11|'''11''']].<br /> [[:category:Indica Chromosome 12|'''12''']]<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Rice----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #93ff93; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#deffde; border-bottom:1px solid #93ff93; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Rice Story&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> [[File:Damifan.jpg|right|120px|margin: 5px|]]<br /> *As an important food<br /> :Rice is the seed of the monocot plants ''Oryza sativa'' (Asian rice) or ''Oryza glaberrima'' (African rice). As a cereal grain, it is the most important staple food for a large part of the world's human population, especially in East Asia, Southeast Asia, South Asia, the Middle East, and the West Indies. It is the grain with the third-highest worldwide production, after maize (corn) and wheat, according to data for 2010 [http://en.wikipedia.org/wiki/Rice (Full article...)].&lt;br&gt;<br /> *As a biological model<br /> :Rice is also a model organism for the biological study of the grass family of crops and other plants. The two most common rice cultivars, ''indica'' and ''japonica'', were completely sequenced in 2002. The genome sequences of domesticated rice provide a solid foundation for integrating biological information, including genetics, gene expression, development, physiology and evolution.&lt;/div&gt;<br /> ----<br /> {|style=&quot;border:none; background-color:transparent; width:100%&quot; <br /> |- style=&quot;background:transcript; color:black&quot; align=&quot;left&quot; valign=&quot;top&quot;<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Recent Modified Genes&lt;/div&gt; {{StatisticsActivity:type=edits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Highly Accessed Genes&lt;/div&gt; {{StatisticsActivity:type=visits|count = 10}}<br /> |&lt;div style=&quot;font-size:110%; font-weight:bold;&quot;&gt;Most Annotated Genes&lt;/div&gt; {{StatisticsActivity:type=contributes|count = 10}}<br /> |}<br /> |}<br /> <br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #c6c6c6; background-color:transparent; width:100%;&quot;|<br /> &lt;div style=&quot;background:#f4f4f4; border-bottom:1px solid #c6c6c6; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Publications&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/24136999 RiceWiki: a wiki-based database for community curation of rice genes] (2014) ''Nucleic Acids Research'', 42(D1),D1222-D1228.<br /> * [http://www.ncbi.nlm.nih.gov/pubmed/23732274 AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification] (2013) ''Bioinformatics'', 29(14):1837-1839.<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!--------------main part two----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> &lt;!------------- Participating----------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:42%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Joining RiceWiki&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;<br /> * RiceWiki allows any user to view and search but only registered users can add and edit content. <br /> * To become a registered user, please email the RiceWiki Team at [mailto:ricewiki@big.ac.cn ricewiki@big.ac.cn] to tell us your preferred login name, real name, research interests, etc., and we will set up an account for you.<br /> * Please also spread this news to any one who might be of interest. [[File:Ppt_ico.gif | link=File:CommunityCuration-RiceWiki.pptx]]&lt;/div&gt;<br /> <br /> &lt;!-------------Lab Information--------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent; width:33%&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;About Us&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;&quot;&gt;Our group works in the field of [http://cbb.big.ac.cn Computational Biology and Bioinformatics] (CBB), currently with a particular focus on building biological knowledge wikis in aid of community curation of massive biological knowledge.<br /> &lt;/div&gt;<br /> <br /> &lt;!------------Visitor Statistics-------------&gt;<br /> |style=&quot;padding:0px 4px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #66B3FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #66B3FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;Visitor Statistics&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 1em;text-align:center&quot;&gt;<br /> &lt;htmlet nocache=&quot;yes&quot;&gt;earth&lt;/htmlet&gt;<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------Reward Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:60%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;[[RiceWiki:Awards|2015 RiceWiki Community Curation Awards]]&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> <br /> 为鼓励更多科研人员和学生参与水稻基因的审编工作，促进我国面向生物大数据的基础性研究人才培养，RiceWiki对符合参选资格条件的个人给予奖励，具体方法如下：<br /> <br /> # 本条例的有关奖项按年度进行评奖。<br /> # 参选资格条件：在2015年（即2015年1月1日至2015年12月31日）参与审编工作的个人（不包括RiceWiki团队中成员），其在本年度的总贡献值（Contribution Score）大于或等于50分（[[Special:AuthorReward | 用户贡献值查询]]）。<br /> # 符合上述参选资格条件的个人将在2016年1月集中进行评审。<br /> # 通过评审且贡献值最高的个人，免费获赠[http://www.mi.com/mipad 小米平板]及荣誉证书；凡是通过评审的个人，免费获赠[http://www.mi.com/wifi 小米随身]WiFi及荣誉证书。<br /> # 上述获奖信息将在RiceWiki网站进行公示。 <br /> <br /> 本条例的解释权属RiceWiki团队。<br /> &lt;/div&gt;<br /> |}<br /> <br /> &lt;!---------------register Box-----------------&gt;<br /> {|border=&quot;0&quot; cellspacing=&quot;0&quot; cellpadding=&quot;0&quot; style=&quot;margin:1em 0; background:transparent; width:100%;&quot;<br /> |-<br /> &lt;!-----------English------------&gt;<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent; width:50%;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;致全体参与者&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> *群体审编（Community Curation）是生物大数据整合和相关文献信息集成的重要方法之一（相关信息：[http://www.biocurator.org/what.shtml 国际生物审编协会]；[http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18769432/ Big data: The future of biocuration]）。<br /> *水稻是我国最重要的经济农作物之一，其数据知识库的建立可有利推动我国水稻的科学研究与应用转化，并影响国内其它相关领域的基础研究。<br /> *我国长期缺乏一个在国际上有一定影响力的数据库/中心，美国有NCBI，欧洲有EBI......<br /> *但是，你们现在所作的一点一滴正在改变这个现状，我们正在朝向建立面向我国重大需求且不同于现今国际生物数据中心的方向前进！<br /> &lt;/div&gt;<br /> <br /> &lt;!-----------------Chinese----------------------&gt;<br /> |style=&quot;padding:0px 5px;&quot;|<br /> |valign=&quot;top&quot; style=&quot;border:1px solid #ACD6FF; background-color:transparent;&quot;|<br /> &lt;div style=&quot;background:#ACD6FF; border-bottom:1px solid #ACD6FF; padding:0.2em 0.5em; font-size:125%; font-weight:bold;&quot;&gt;注册 &amp; 编辑&lt;/div&gt;<br /> &lt;div style=&quot;padding:0.5em 0.5em;&quot;&gt;<br /> * 请发送电子邮件至ricewiki(AT)big.ac.cn，并提供您的注册用户名（英文）、邮件地址(确保邮箱名正确)和真实姓名。<br /> * 您查收来自ricewiki(AT)big.ac.cn的邮件，里面有您的密码，请尽快登录并修改个人密码。如果两天内没有收到邮件，请检查垃圾邮箱。<br /> * 如果您确实没收到来自ricewiki(AT)big.ac.cn的邮件，请再次发送邮件联系ricewiki(AT)big.ac.cn。<br /> * 当多人在同一时间编辑同一页面时，会发生编辑冲突。建议每次编辑一小段内容并查看编辑历史。详细信息请查看：http://en.wikipedia.org/wiki/Help:Edit_conflict<br /> &lt;/div&gt;<br /> |}</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Os01g0883800&diff=269664 2015-09-08T04:34:34Z

<p>Rice2012: moved Sd-1 to Sd1 over redirect</p> <hr /> <div>The rice ''semidwarf-1 (sd1)'' gene is well known as the &quot;green revolution gene&quot; and controls the plant height of rice.<br /> <br /> == Annotated Information ==<br /> === Function ===<br /> [[File:Sd1-fig1.jpg|right|thumb|150px|''Semidwarf VS. normal-type rice plants at ripening (from reference &lt;ref name=&quot;ref3&quot; /&gt;).'']]<br /> <br /> This gene is originally derived from the Chinese cultivar Dee-Geo-Woo-Gen (DGWG). It encodes an oxidase enzyme involved in the biosynthesis of gibberellin, which is a plant growth hormone. The rice genome carries at least two GA20ox genes (GA20ox-1 and GA20ox-2). SD1 corresponds to GA20ox-2. Mutation of SD1 will cause a semi-dwarf phenotype of rice without seed yield being affected &lt;ref name=&quot;ref1&quot; /&gt;. It is not surprising that a rice semidwarfing gene encodes GA20-ox since successful production of semidwarf plants using antisense or overexpressed GA20-ox genes has been reported in Arabidopsis, Solanum dulcamara, potato, and lettuce &lt;ref name=&quot;ref3&quot; /&gt;.<br /> <br /> It is a key enzyme in the biosynthesis of gibberellin that catalyses the three steps GA53-&gt;GA44-&gt;GA19-&gt;GA20. Impaired GA 20-oxidase activity will cause elevated content of GA53, and reduced amount of G20&lt;ref name=&quot;ref3&quot; /&gt;. However, there is slight difference between different strains. The extent of GA1 is lower in Doongara (semi-dwarf rice strain) when compared with Kyeema (tall), while there is no significant difference between Calrose76 (semi-dwarf rice strain) and Calrose (tall). Calrose76 has lower contents of GA44 and of GA19 than Calrose, while there is no significant difference between Doongara (semi-dwarf rice strain) and Kyeema (tall) &lt;ref name=&quot;ref3&quot; /&gt;.<br /> <br /> '''GO assignment(s):''' [http://amigo.geneontology.org/amigo/term/GO:0005506 GO:0005506], [http://amigo.geneontology.org/amigo/term/GO:0016216 GO:0016216], [http://amigo.geneontology.org/amigo/term/GO:0017000 GO:0017000]<br /> <br /> === Mutation ===<br /> 'Dee-Geo-Woo-Gen' (semi-dwarf rice strain): A 383-base-pair deletion from the genome (A 280-bp deletion within the coding region), which induces a frameshift that creates a stop codon in SD1, may be related with the semi-dwarf phenotype &lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt;.<br /> <br /> Calrose76 (semi-dwarf rice strain): The DNA sequence of Calrose76 is identical to Calrose (tall) except for a C to T transition at position 798 that resulted in a change of the predicted amino acid leucine (Leu-266) in Calrose to phenylalanine in Calrose76 &lt;ref name=&quot;ref2&quot; /&gt;.<br /> <br /> It has been found that introgression of a chromosomal block containing the SD1 allele from tropical japonica is associated with a change in growth patterns in BHA1 (one weedy rice population) &lt;ref name=&quot;ref7&quot; /&gt;.<br /> <br /> === Expression ===<br /> This gene is strongly expressed in the leaf blade, stem and unopened flower, whereas GA20ox-1 is predominantly expressed in the unopened flower &lt;ref name=&quot;ref1&quot; /&gt;. <br /> <br /> Among the DGWG-type sd-1 mutants, IR24 and Habataki have little transcript of this gene, while Milyang 23 expresses a normal or greater amount of truncated transcript. No significant difference is observed between Calrose and its single-nucleotide-substitution mutant Calrose 76 &lt;ref name=&quot;ref3&quot; /&gt;.<br /> <br /> Analysis of the tissue- and stage-specificity of transcription of sd1 in Nipponbare revealed that this<br /> gene was expressed within 48 hr after sowing, as well as in 10-day-old plants, 30-day-old leaves, and flowering panicles; no transcription is detected in 24-hr-old seedlings or in 14-day-old roots. Transcript accumulates predominantly in adult leaves &lt;ref name=&quot;ref3&quot; /&gt;.<br /> <br /> {| class='wikitable' style=&quot;text-align:center&quot;<br /> |-<br /> ! | Primer<br /> ! | Forward primer<br /> ! | Reverse primer<br /> |-<br /> | rowspan=&quot;3&quot;|Gene amplication<br /> | | 5'-CAACTCACTCCCGCTCAACACAGC-3'<br /> | | 5'-TTTGAAATGCAATGTCGTCCACC-3' (used to amplify exon 1 &lt;ref name=&quot;ref2&quot; /&gt;)<br /> |-<br /> | | 5'-GCGCCAATGGGGTAATTAAAACG-3'<br /> | | 5'-GGCATTCCATTGTTTGTGATTGG-3' (used to amplify exon 2 &lt;ref name=&quot;ref2&quot; /&gt;)<br /> |-<br /> | | 5'-GTTTGTCCTTGTCGCGTTGCTCAG-3'<br /> | | 5'-TCTGTTCGTTCCGTTTCGTTCCG-3' (used to amplify exon 3 &lt;ref name=&quot;ref2&quot; /&gt;)<br /> |-<br /> | rowspan=&quot;2&quot;|RT-PCR<br /> | | 5'-CAACTCACTCCCGCTCAACACAGC-3'<br /> | | 5'-GTTCGTTCCGTTTCGGTTCCG-3' &lt;ref name=&quot;ref3&quot; /&gt;<br /> |-<br /> | | 5'-AGCTGGACATGCCCGTGGTC-3'<br /> | | 5'-TTGAGCTGCTGTCCGCGAAG-3' &lt;ref name=&quot;ref3&quot; /&gt;<br /> |}<br /> <br /> === Evolution ===<br /> This gene is conserved in ''Arabidopsis'' (47% identity) and pea (50% identity). GA20ox-2 shows 47.8% identity to<br /> GA20ox-1 in rice. There are at least three GA20-ox genes in Arabidopsis &lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt;.<br /> <br /> === Knowledge Extension ===<br /> <br /> [[File:Gibberellin SD1 RHT Signal.PNG|right|thumb|500px|''Gibberellin signalling pathway (from reference &lt;ref name=&quot;ref4&quot; /&gt;).'']]<br /> <br /> Except ''sd1'', another ‘green revolution’ gene named ''Rht1'', which encodes a GA signal suppressor DELLA protein. The deletion in the N-terminal region of the native RHT1 constitutively suppresses GA signaling, consequently resulting in a dominant semi-dwarf phenotype &lt;ref name=&quot;ref5&quot; /&gt;. Both sd1 and Rht1 are associated with GA pathway, indicating the importance of GA in the regulation of developmental processes and making it a prime target for improving crop yield &lt;ref name=&quot;ref4&quot; /&gt;. <br /> <br /> The wheat green-revolution gene Rht (for ‘reduced height’) &lt;ref name=&quot;ref5&quot; /&gt; is a gain-of-function allele caused by a mutation in a transcription factor that is associated with the gibberellin signalling pathway. As wheat has a hexaploid genome, it does not contain recessive alleles such as ''sd1'' in rice that might otherwise be used to produce a semi-dwarf strain of wheat. Although the genetic and biochemical functions of the rice SD1 and wheat RHT proteins are completely different (that is, recessive versus dominant, loss-of-function versus gain-offunction events, enzyme versus transcription factor, respectively), the products of both genes are linked with gibberellin malfunction &lt;ref name=&quot;ref1&quot; /&gt;.<br /> <br /> In rice, ''Slr1'' gene encodes the DELLA protein. Three semi-dominant dwarf mutants (''Slr1-d1'', ''Slr1-d2'' and ''Slr1-d3'') associated with this gene have been identified, which were caused by gain-of-function mutations in the N-terminal region of SLR1. These three mutants are responsive to GA at a reduced rate, with later SLRl degradation, and showing reduced interaction activity with GID1 (GA receptor) comparing with wild type rice &lt;ref name=&quot;ref6&quot; /&gt;.<br /> <br /> == Labs working on this gene ==<br /> *Bioscience Center, and Graduate School of Bioagricultural Science, Nagoya University, Nagoya 464-8601, Japan<br /> *Honda R&amp;D, Wako Research Center, Wako 351-0193, Japan<br /> *International Rice Research Institute, Manila, DAPO Box 7777, Philippines<br /> *BioResources Center, and Plant Molecular Biology Laboratory, Riken, Tsukuba 305-0074, Japan<br /> *Division of Plant Industry, Commonwealth Scientific and Industrial Research Organization, GPO Box 1600, Canberra ACT 2601, Australia<br /> *Plant Genome Center, 1-25-2 Kannondai, Tsukuba, Ibaraki 305-0856, Japan<br /> <br /> == References ==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;Sasaki A, Ashikari M, Ueguchi-Tanaka M, Itoh H, Nishimura A, et al. (2002) Green revolution: a mutant gibberellin-synthesis gene in rice. Nature 416: 701-702.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;Spielmeyer W, Ellis MH, Chandler PM (2002) Semidwarf (sd-1), &quot;green revolution&quot; rice, contains a defective gibberellin 20-oxidase gene. Proc Natl Acad Sci U S A 99: 9043-9048.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;Monna L, Kitazawa N, Yoshino R, Suzuki J, Masuda H, et al. (2002) Positional cloning of rice semidwarfing gene, sd-1: rice &quot;green revolution gene&quot; encodes a mutant enzyme involved in gibberellin synthesis. DNA Res 9: 11-17.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;Hedden P. (2003) The genes of the Green Revolution. Trends Genet 19: 5-9.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref5&quot;&gt;Peng J, Richards DE, Hartley NM, Murphy GP, Devos KM, et al. (1999) 'Green revolution' genes encode mutant gibberellin response modulators. Nature 400: 256-261.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref6&quot;&gt;Asano K, Hirano K, Ueguchi-Tanaka M, Angeles-Shim RB, Komura T, et al. (2009) Isolation and characterization of dominant dwarf mutants, ''Slr1-d'', in rice. Mol Genet Genomics 281: 223-231.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref7&quot;&gt;Reagon M, Thurber CS, Olsen KM, Jia Y, Caicedo AL (2011) The long and the short of it: SD1 polymorphism and the evolution of growth trait divergence in U.S. weedy rice. Mol Ecol 20: 3743-3756.&lt;/ref&gt;<br /> &lt;/references&gt;<br /> <br /> == Structured Information ==<br /> <br /> [[Category:Genes]]<br /> [[Category:Japonica mRNA]]<br /> [[Category:Oryza Sativa Japonica Group]]<br /> [[Category:Japonica Genes]]<br /> [[Category:Japonica Chromosome 1]]<br /> [[Category:Chromosome 1]]</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Sd-1&diff=269665 2015-09-08T04:34:34Z

<p>Rice2012: moved Sd-1 to Sd1 over redirect</p> <hr /> <div>#REDIRECT [[Sd1]]</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Talk:Os01g0883800&diff=269666 2015-09-08T04:34:34Z

<p>Rice2012: moved Talk:Sd-1 to Talk:Sd1 over redirect</p> <hr /> <div>Hi Guys,<br /> <br /> I suggest the information should be grouped into different sections, similar with the following.<br /> <br /> 1. One sentence summary<br /> <br /> 2. Annotated details<br /> <br /> 2.1 sub-section 1<br /> 2.2 sub-section 2<br /> ......<br /> 2.n sub-section n<br /> <br /> 3. Structured information<br /> Template table<br /> <br /> Here is my two cents. Any other ideas or comments?<br /> <br /> ZZ<br /> <br /> == NO citation of reference ==<br /> <br /> In the main body of the text, there is no place cite ref3. Please fix this. Thanks!</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Talk:Sd-1&diff=269667 2015-09-08T04:34:34Z

<p>Rice2012: moved Talk:Sd-1 to Talk:Sd1 over redirect</p> <hr /> <div>#REDIRECT [[Talk:Sd1]]</div>

Rice2012 https://ngdc.cncb.ac.cn/ricewiki/index.php?title=Os01g0883800&diff=269660 2015-09-08T04:33:58Z

<p>Rice2012: moved Sd1 to Sd-1</p> <hr /> <div>The rice ''semidwarf-1 (sd1)'' gene is well known as the &quot;green revolution gene&quot; and controls the plant height of rice.<br /> <br /> == Annotated Information ==<br /> === Function ===<br /> [[File:Sd1-fig1.jpg|right|thumb|150px|''Semidwarf VS. normal-type rice plants at ripening (from reference &lt;ref name=&quot;ref3&quot; /&gt;).'']]<br /> <br /> This gene is originally derived from the Chinese cultivar Dee-Geo-Woo-Gen (DGWG). It encodes an oxidase enzyme involved in the biosynthesis of gibberellin, which is a plant growth hormone. The rice genome carries at least two GA20ox genes (GA20ox-1 and GA20ox-2). SD1 corresponds to GA20ox-2. Mutation of SD1 will cause a semi-dwarf phenotype of rice without seed yield being affected &lt;ref name=&quot;ref1&quot; /&gt;. It is not surprising that a rice semidwarfing gene encodes GA20-ox since successful production of semidwarf plants using antisense or overexpressed GA20-ox genes has been reported in Arabidopsis, Solanum dulcamara, potato, and lettuce &lt;ref name=&quot;ref3&quot; /&gt;.<br /> <br /> It is a key enzyme in the biosynthesis of gibberellin that catalyses the three steps GA53-&gt;GA44-&gt;GA19-&gt;GA20. Impaired GA 20-oxidase activity will cause elevated content of GA53, and reduced amount of G20&lt;ref name=&quot;ref3&quot; /&gt;. However, there is slight difference between different strains. The extent of GA1 is lower in Doongara (semi-dwarf rice strain) when compared with Kyeema (tall), while there is no significant difference between Calrose76 (semi-dwarf rice strain) and Calrose (tall). Calrose76 has lower contents of GA44 and of GA19 than Calrose, while there is no significant difference between Doongara (semi-dwarf rice strain) and Kyeema (tall) &lt;ref name=&quot;ref3&quot; /&gt;.<br /> <br /> '''GO assignment(s):''' [http://amigo.geneontology.org/amigo/term/GO:0005506 GO:0005506], [http://amigo.geneontology.org/amigo/term/GO:0016216 GO:0016216], [http://amigo.geneontology.org/amigo/term/GO:0017000 GO:0017000]<br /> <br /> === Mutation ===<br /> 'Dee-Geo-Woo-Gen' (semi-dwarf rice strain): A 383-base-pair deletion from the genome (A 280-bp deletion within the coding region), which induces a frameshift that creates a stop codon in SD1, may be related with the semi-dwarf phenotype &lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt;.<br /> <br /> Calrose76 (semi-dwarf rice strain): The DNA sequence of Calrose76 is identical to Calrose (tall) except for a C to T transition at position 798 that resulted in a change of the predicted amino acid leucine (Leu-266) in Calrose to phenylalanine in Calrose76 &lt;ref name=&quot;ref2&quot; /&gt;.<br /> <br /> It has been found that introgression of a chromosomal block containing the SD1 allele from tropical japonica is associated with a change in growth patterns in BHA1 (one weedy rice population) &lt;ref name=&quot;ref7&quot; /&gt;.<br /> <br /> === Expression ===<br /> This gene is strongly expressed in the leaf blade, stem and unopened flower, whereas GA20ox-1 is predominantly expressed in the unopened flower &lt;ref name=&quot;ref1&quot; /&gt;. <br /> <br /> Among the DGWG-type sd-1 mutants, IR24 and Habataki have little transcript of this gene, while Milyang 23 expresses a normal or greater amount of truncated transcript. No significant difference is observed between Calrose and its single-nucleotide-substitution mutant Calrose 76 &lt;ref name=&quot;ref3&quot; /&gt;.<br /> <br /> Analysis of the tissue- and stage-specificity of transcription of sd1 in Nipponbare revealed that this<br /> gene was expressed within 48 hr after sowing, as well as in 10-day-old plants, 30-day-old leaves, and flowering panicles; no transcription is detected in 24-hr-old seedlings or in 14-day-old roots. Transcript accumulates predominantly in adult leaves &lt;ref name=&quot;ref3&quot; /&gt;.<br /> <br /> {| class='wikitable' style=&quot;text-align:center&quot;<br /> |-<br /> ! | Primer<br /> ! | Forward primer<br /> ! | Reverse primer<br /> |-<br /> | rowspan=&quot;3&quot;|Gene amplication<br /> | | 5'-CAACTCACTCCCGCTCAACACAGC-3'<br /> | | 5'-TTTGAAATGCAATGTCGTCCACC-3' (used to amplify exon 1 &lt;ref name=&quot;ref2&quot; /&gt;)<br /> |-<br /> | | 5'-GCGCCAATGGGGTAATTAAAACG-3'<br /> | | 5'-GGCATTCCATTGTTTGTGATTGG-3' (used to amplify exon 2 &lt;ref name=&quot;ref2&quot; /&gt;)<br /> |-<br /> | | 5'-GTTTGTCCTTGTCGCGTTGCTCAG-3'<br /> | | 5'-TCTGTTCGTTCCGTTTCGTTCCG-3' (used to amplify exon 3 &lt;ref name=&quot;ref2&quot; /&gt;)<br /> |-<br /> | rowspan=&quot;2&quot;|RT-PCR<br /> | | 5'-CAACTCACTCCCGCTCAACACAGC-3'<br /> | | 5'-GTTCGTTCCGTTTCGGTTCCG-3' &lt;ref name=&quot;ref3&quot; /&gt;<br /> |-<br /> | | 5'-AGCTGGACATGCCCGTGGTC-3'<br /> | | 5'-TTGAGCTGCTGTCCGCGAAG-3' &lt;ref name=&quot;ref3&quot; /&gt;<br /> |}<br /> <br /> === Evolution ===<br /> This gene is conserved in ''Arabidopsis'' (47% identity) and pea (50% identity). GA20ox-2 shows 47.8% identity to<br /> GA20ox-1 in rice. There are at least three GA20-ox genes in Arabidopsis &lt;ref name=&quot;ref1&quot; /&gt;&lt;ref name=&quot;ref2&quot; /&gt;.<br /> <br /> === Knowledge Extension ===<br /> <br /> [[File:Gibberellin SD1 RHT Signal.PNG|right|thumb|500px|''Gibberellin signalling pathway (from reference &lt;ref name=&quot;ref4&quot; /&gt;).'']]<br /> <br /> Except ''sd1'', another ‘green revolution’ gene named ''Rht1'', which encodes a GA signal suppressor DELLA protein. The deletion in the N-terminal region of the native RHT1 constitutively suppresses GA signaling, consequently resulting in a dominant semi-dwarf phenotype &lt;ref name=&quot;ref5&quot; /&gt;. Both sd1 and Rht1 are associated with GA pathway, indicating the importance of GA in the regulation of developmental processes and making it a prime target for improving crop yield &lt;ref name=&quot;ref4&quot; /&gt;. <br /> <br /> The wheat green-revolution gene Rht (for ‘reduced height’) &lt;ref name=&quot;ref5&quot; /&gt; is a gain-of-function allele caused by a mutation in a transcription factor that is associated with the gibberellin signalling pathway. As wheat has a hexaploid genome, it does not contain recessive alleles such as ''sd1'' in rice that might otherwise be used to produce a semi-dwarf strain of wheat. Although the genetic and biochemical functions of the rice SD1 and wheat RHT proteins are completely different (that is, recessive versus dominant, loss-of-function versus gain-offunction events, enzyme versus transcription factor, respectively), the products of both genes are linked with gibberellin malfunction &lt;ref name=&quot;ref1&quot; /&gt;.<br /> <br /> In rice, ''Slr1'' gene encodes the DELLA protein. Three semi-dominant dwarf mutants (''Slr1-d1'', ''Slr1-d2'' and ''Slr1-d3'') associated with this gene have been identified, which were caused by gain-of-function mutations in the N-terminal region of SLR1. These three mutants are responsive to GA at a reduced rate, with later SLRl degradation, and showing reduced interaction activity with GID1 (GA receptor) comparing with wild type rice &lt;ref name=&quot;ref6&quot; /&gt;.<br /> <br /> == Labs working on this gene ==<br /> *Bioscience Center, and Graduate School of Bioagricultural Science, Nagoya University, Nagoya 464-8601, Japan<br /> *Honda R&amp;D, Wako Research Center, Wako 351-0193, Japan<br /> *International Rice Research Institute, Manila, DAPO Box 7777, Philippines<br /> *BioResources Center, and Plant Molecular Biology Laboratory, Riken, Tsukuba 305-0074, Japan<br /> *Division of Plant Industry, Commonwealth Scientific and Industrial Research Organization, GPO Box 1600, Canberra ACT 2601, Australia<br /> *Plant Genome Center, 1-25-2 Kannondai, Tsukuba, Ibaraki 305-0856, Japan<br /> <br /> == References ==<br /> &lt;references&gt;<br /> &lt;ref name=&quot;ref1&quot;&gt;Sasaki A, Ashikari M, Ueguchi-Tanaka M, Itoh H, Nishimura A, et al. (2002) Green revolution: a mutant gibberellin-synthesis gene in rice. Nature 416: 701-702.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref2&quot;&gt;Spielmeyer W, Ellis MH, Chandler PM (2002) Semidwarf (sd-1), &quot;green revolution&quot; rice, contains a defective gibberellin 20-oxidase gene. Proc Natl Acad Sci U S A 99: 9043-9048.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref3&quot;&gt;Monna L, Kitazawa N, Yoshino R, Suzuki J, Masuda H, et al. (2002) Positional cloning of rice semidwarfing gene, sd-1: rice &quot;green revolution gene&quot; encodes a mutant enzyme involved in gibberellin synthesis. DNA Res 9: 11-17.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref4&quot;&gt;Hedden P. (2003) The genes of the Green Revolution. Trends Genet 19: 5-9.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref5&quot;&gt;Peng J, Richards DE, Hartley NM, Murphy GP, Devos KM, et al. (1999) 'Green revolution' genes encode mutant gibberellin response modulators. Nature 400: 256-261.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref6&quot;&gt;Asano K, Hirano K, Ueguchi-Tanaka M, Angeles-Shim RB, Komura T, et al. (2009) Isolation and characterization of dominant dwarf mutants, ''Slr1-d'', in rice. Mol Genet Genomics 281: 223-231.&lt;/ref&gt;<br /> &lt;ref name=&quot;ref7&quot;&gt;Reagon M, Thurber CS, Olsen KM, Jia Y, Caicedo AL (2011) The long and the short of it: SD1 polymorphism and the evolution of growth trait divergence in U.S. weedy rice. Mol Ecol 20: 3743-3756.&lt;/ref&gt;<br /> &lt;/references&gt;<br /> <br /> == Structured Information ==<br /> <br /> [[Category:Genes]]<br /> [[Category:Japonica mRNA]]<br /> [[Category:Oryza Sativa Japonica Group]]<br /> [[Category:Japonica Genes]]<br /> [[Category:Japonica Chromosome 1]]<br /> [[Category:Chromosome 1]]</div>

Rice2012