IC4R012-Metabolomics-2012-22229385 - Revision history

Guangyi: /* Research Findings */

2016-07-22T08:23:37Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T08:22:24Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T08:21:10Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T08:18:53Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T08:12:33Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T08:00:01Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T07:58:47Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T07:57:40Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T07:56:54Z

‎Research Findings

Guangyi: /* Research Findings */

2016-07-22T07:38:38Z

‎Research Findings

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 *Finally, a metabolome dataset containing m-trait data for 759 metabolite signals from 85 experimental lines for the 2005 and 2007 harvests was obtained. Among the metabolite signals,a total of 93 were identified by comparing their chromatographic behaviour with mass spectra of the standard compounds, and 38 metabolites were structurally annotated using MS and MS/MS spectral data (Matsuda et al., 2011)(Figure 1 and Table S1).
 <br>
-[[File:IC4R012-Metabolomics-2012-22229385-f1.png |center |thumb |10000px |'''''']]
+[[File:IC4R012-Metabolomics-2012-22229385-f1.png |center |thumb |10000px |''''''Figure 1. Rice grain metabolites annotated in this study.
 <br>
-[[File:IC4R012-Metabolomics-2012-22229385-t1.png |center |thumb |10000px |'''''']]
+Rice grain metabolites annotated in this study are represented in the simplified metabolic pathway. The colours of the nodes represent the methods used for analysis of that metabolite, i.e. GC-TOF-MS (yellow), CE-TOF-MS (blue), LC-IT-TOF-MS (green) and LC-Q-TOF-MS (red). The shape of the node represents the reliability of metabolite annotation. Rectangles indicate metabolites whose structure was identified by comparing their chromatographic behaviour and mass spectra with standard compounds. Diamonds indicate metabolites whose structure was determined by MS and MS/MS spectral data. Abbreviations for metabolites are defined in Table S1.'''''']]
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 *In this study, H2 was estimated using ANOVA by considering variation between the harvests of 2005 and 2007 as phenotypic variance derived from environmental factors. If quantitative traits are not affected by environmental factors, H2 should be close to 1. The distributions across all m-traits indicated that more than half of the m-traits have relatively low broad-sense heritability(H2 < 0.6) (Figure 2).

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 *In this study, H2 was estimated using ANOVA by considering variation between the harvests of 2005 and 2007 as phenotypic variance derived from environmental factors. If quantitative traits are not affected by environmental factors, H2 should be close to 1. The distributions across all m-traits indicated that more than half of the m-traits have relatively low broad-sense heritability(H2 < 0.6) (Figure 2).
 <br>
-[[File:IC4R012-Metabolomics-2012-22229385-f2.png |center |thumb |10000px |'''''']]
+[[File:IC4R012-Metabolomics-2012-22229385-f2.png |center |thumb |10000px |''''''Figure 2. Distribution of levels of broad-sense heritability of metabolic traits.Broad-sense heritability (H2) was estimated using one-way ANOVA by considering variations between the 2005 and 2007 harvests as phenotypic variance derived from environmental factors.'''''']]
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 *The annotated metabolite data showed that several groups of metabolites exhibited high heritability. Examples of such metabolites include lysophosphatidyl cholines,oryzanolsand flavone glycosides (Figure 3).

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 *The annotated metabolite data showed that several groups of metabolites exhibited high heritability. Examples of such metabolites include lysophosphatidyl cholines,oryzanolsand flavone glycosides (Figure 3).
 <br>
-[[File:IC4R012-Metabolomics-2012-22229385-f3.png |center |thumb |10000px |'''''']]
+[[File:IC4R012-Metabolomics-2012-22229385-f3.png |center |thumb |10000px |''''''Figure 3. Broad-sense heritability of rice grain metabolites.
 <br>
 *Figure 4 shows the genome-wide distribution of mQTLs. It is clear that mQTLs are unevenly distributed throughout the rice genome, and that there are several regions in which mQTLs are densely clustered.

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 *Figure 4 shows the genome-wide distribution of mQTLs. It is clear that mQTLs are unevenly distributed throughout the rice genome, and that there are several regions in which mQTLs are densely clustered.
 <br>
-[[File:IC4R012-Metabolomics-2012-22229385-f4.png |center |thumb |10000px |'''''']]
+[[File:IC4R012-Metabolomics-2012-22229385-f4.png |center |thumb |10000px |''''''Figure 4. Genome-wide distribution of mQTLs.Each row represents QTL mapping of single metabolic traits (m-traits). The results for a total of 758 m-traits are shown. Regions indicated in red or blue represent 1 ) LOD support intervals of detected mQTLs that positively affect the m-traits of Sasanishiki (red) and Habataki (blue) genotypes. The colours on the right of the panels indicate the various metabolome analysis pipelines, that is, CE-TOF-MS (blue), GC-TOF-MS (yellow), LC-IT-TOF-MS (green) and LC-Q-TOF-MS (red), used for analysis of metabolites.'''''']]
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 ==Research Findings==
 *Finally, a metabolome dataset containing m-trait data for 759 metabolite signals from 85 experimental lines for the 2005 and 2007 harvests was obtained. Among the metabolite signals,a total of 93 were identified by comparing their chromatographic behaviour with mass spectra of the standard compounds, and 38 metabolites were structurally annotated using MS and MS/MS spectral data (Matsuda et al., 2011)(Figure 1 and Table S1).
 <br>
 *In this study, H2 was estimated using ANOVA by considering variation between the harvests of 2005 and 2007 as phenotypic variance derived from environmental factors. If quantitative traits are not affected by environmental factors, H2 should be close to 1. The distributions across all m-traits indicated that more than half of the m-traits have relatively low broad-sense heritability(H2 < 0.6) (Figure 2).
 <br>
 *The annotated metabolite data showed that several groups of metabolites exhibited high heritability. Examples of such metabolites include lysophosphatidyl cholines,oryzanolsand flavone glycosides (Figure 3).
 <br>
 *Figure 4 shows the genome-wide distribution of mQTLs. It is clear that mQTLs are unevenly distributed throughout the rice genome, and that there are several regions in which mQTLs are densely clustered.
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 ==Labs working on this Project==

← Older revision		Revision as of 07:38, 22 July 2016
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	==Research Findings==		==Research Findings==
		+	*Finally, a metabolome dataset containing m-trait data for 759 metabolite signals from 85 experimental lines for the 2005 and
		+	2007 harvests was obtained. Among the metabolite signals,a total of 93 were identified by comparing their chromatographic behaviour with mass spectra of the standard compounds, and 38 metabolites were structurally annotated using MS and MS/MS spectral data (Matsuda et al., 2011)(Figure 1 and Table S1).
		+	<br>

	==Labs working on this Project==		==Labs working on this Project==