{"data":[{"id":65,"strategy":"Bulk RNA-seq","height":null,"isolationSource":null,"type":"1","dataSource":"NCBI","projectId":"GSE135897","bioProject":"PRJNA560505","releaseDate":"Aug 01 2020","sampleNumber":30,"caseDetail":"HLG,HMG,HSG,LLG,LMG,LSG","controlDetail":"-","featureTag":null,"tissue":"Oocyte","cellLine":null,"cellType":"Granulosa cells","disease":"Normal","developmentStage":null,"species":"Capra hircus","projectName":"Single-cell RNA-seq of the goat ovarian granulosa cells samples from high and low fertility groups","summary":"The goal of this study was designe to search for the granulosa cells contribution on fertility. Single-cell RNA-seq of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth). And each group was divided into three subgroup based in the size of follicles: large, medium, and small follicles.","overallDesign":"Single-cell RNA-seq of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth). And each group was divided into three subgroup based in the size of follicles: large, medium, and small follicles.","pmid":"33624340","submissionDate":"Aug 19 2019","updateDate":"Aug 01 2020","lastModified":"2021-06-27 00:08:44","createDate":"2021-06-27 00:08:44","datasetIds":"GEND000331","protocol":null,"sequencing":null,"isFeatured":0,"relDate":"2020-08-01 00:00:00","publications":[{"id":685,"pmid":"34344973","title":"Transcriptome profile of goat folliculogenesis reveals the interaction of oocyte and granulosa cell in correlation with different fertility population.","author":"Li S, Wang J, Zhang H, Ma D, Zhao M, Li N, Men Y, Zhang Y, Chu H, Lei C, Shen W, Othman OE, Zhao Y, Min L.","journal":"Scientific reports","journalAbbr":"Sci Rep","pubYear":2021,"pubMonth":"8","issue":"1","volume":"11","abst":"To understand the molecular and genetic mechanisms related to the litter size in one species of two different populations (high litter size and low litter size), we performed RNA-seq for the oocytes and granulosa cells (GCs) at different developmental stages of follicle, and identified the interaction of genes from both sides of follicle (oocyte and GCs) and the ligand-receptor pairs from these two sides. Our data were very comprehensive to uncover the difference between these two populations regarding the folliculogenesis. First, we identified a set of potential genes in oocyte and GCs as the marker genes which can be used to determine the goat fertility capability and ovarian reserve ability. The data showed that GRHPR, GPR84, CYB5A and ERAL1 were highly expressed in oocyte while JUNB, SCN2A, MEGE8, ZEB2, EGR1and PRRC2A were highly expressed in GCs. We found more functional genes were expressed in oocytes and GCs in high fertility group (HL) than that in low fertility group (LL). We uncovered that ligand-receptor pairs in Notch signaling pathway and transforming growth factor-β (TGF-β) superfamily pathways played important roles in goat folliculogenesis for the different fertility population. Moreover, we discovered that the correlations of the gene expression in oocytes and GCs at different stages in the two populations HL and LL were different, too. All the data reflected the gene expression landscape in oocytes and GCs which was correlated well with the fertility capability.","doi":"10.1038/s41598-021-95215-z","citations":0,"citationDate":"2022-08-26","pageInfo":null,"authorInstitution":null,"firstPubDate":"2021-08-03","type":"Research Support, Non-U.S. Gov't,research-article,Journal Article","keyword":null,"correspondingAuthor":null,"country":null,"lastModified":"2022-08-26 15:46:15","createTime":"2022-08-26 15:46:15","genDatasets":[{"id":235,"datasetId":"GEND000331","pairedDatasetId":"GEND000331","dataSource":"NCBI","visual":null,"height":null,"isolationSource":null,"projectId":"GSE135897","bioProjectId":"PRJNA560505","coverage":"3.939711247","mappingQuality":"0.9271","maxSequencingLength":"-","maxReplicate":"1","baseline":"Yes","rnaType":"poly(A)+ RNA","genetic":"-","phenotype":"-","environment":"-","spatio":"Tissue","temporal":"Development","sampleNumber":30,"species":"Capra hircus","datasetName":"Single-cell RNA-seq of the goat ovarian granulosa cells samples from high and low fertility groups","strategy":"Bulk RNA-seq","lastModified":"2021-06-27 00:09:48","createDate":"2021-06-27 00:09:48","pmid":"34344973","kingdom":"Animalia","type":"1","caseDetail":"HLG,HMG,HSG,LLG,LMG,LSG","controlDetail":"-","tissue":"Oocyte","cellType":"Granulosa cells","cellLine":null,"disease":"Normal","developmentStage":null,"theme":null,"datasetQuality":"High","cellNumber":0,"speciesId":6,"aiReady":1}],"species":[]}]},{"id":66,"strategy":"Bulk RNA-seq","height":null,"isolationSource":null,"type":"1","dataSource":"NCBI","projectId":"GSE136005","bioProject":"PRJNA560927","releaseDate":"Aug 01 2020","sampleNumber":29,"caseDetail":"HLO,HMO,HSO,LLO,LMO,LSO","controlDetail":"-","featureTag":null,"tissue":"Oocyte","cellLine":null,"cellType":"Oocyte cells","disease":"Normal","developmentStage":null,"species":"Capra hircus","projectName":"Single-cell RNA-seq of the goat ovarian granulosa cells samples from high and low fertility groups","summary":"The goal of this study was designe to search for the granulosa cells contribution on fertility. Single-cell RNA-seq of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth). And each group was divided into three subgroup based in the size of follicles: large, medium, and small follicles.","overallDesign":"Single-cell RNA-seq of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth). And each group was divided into three subgroup based in the size of follicles: large, medium, and small follicles.","pmid":"33624340","submissionDate":"Aug 16 2019","updateDate":"Aug 01 2020","lastModified":"2021-06-27 00:08:44","createDate":"2021-06-27 00:08:44","datasetIds":"GEND000066","protocol":null,"sequencing":null,"isFeatured":0,"relDate":"2020-08-01 00:00:00","publications":[{"id":685,"pmid":"34344973","title":"Transcriptome profile of goat folliculogenesis reveals the interaction of oocyte and granulosa cell in correlation with different fertility population.","author":"Li S, Wang J, Zhang H, Ma D, Zhao M, Li N, Men Y, Zhang Y, Chu H, Lei C, Shen W, Othman OE, Zhao Y, Min L.","journal":"Scientific reports","journalAbbr":"Sci Rep","pubYear":2021,"pubMonth":"8","issue":"1","volume":"11","abst":"To understand the molecular and genetic mechanisms related to the litter size in one species of two different populations (high litter size and low litter size), we performed RNA-seq for the oocytes and granulosa cells (GCs) at different developmental stages of follicle, and identified the interaction of genes from both sides of follicle (oocyte and GCs) and the ligand-receptor pairs from these two sides. Our data were very comprehensive to uncover the difference between these two populations regarding the folliculogenesis. First, we identified a set of potential genes in oocyte and GCs as the marker genes which can be used to determine the goat fertility capability and ovarian reserve ability. The data showed that GRHPR, GPR84, CYB5A and ERAL1 were highly expressed in oocyte while JUNB, SCN2A, MEGE8, ZEB2, EGR1and PRRC2A were highly expressed in GCs. We found more functional genes were expressed in oocytes and GCs in high fertility group (HL) than that in low fertility group (LL). We uncovered that ligand-receptor pairs in Notch signaling pathway and transforming growth factor-β (TGF-β) superfamily pathways played important roles in goat folliculogenesis for the different fertility population. Moreover, we discovered that the correlations of the gene expression in oocytes and GCs at different stages in the two populations HL and LL were different, too. All the data reflected the gene expression landscape in oocytes and GCs which was correlated well with the fertility capability.","doi":"10.1038/s41598-021-95215-z","citations":0,"citationDate":"2022-08-26","pageInfo":null,"authorInstitution":null,"firstPubDate":"2021-08-03","type":"Research Support, Non-U.S. Gov't,research-article,Journal Article","keyword":null,"correspondingAuthor":null,"country":null,"lastModified":"2022-08-26 15:46:15","createTime":"2022-08-26 15:46:15","genDatasets":[{"id":235,"datasetId":"GEND000331","pairedDatasetId":"GEND000331","dataSource":"NCBI","visual":null,"height":null,"isolationSource":null,"projectId":"GSE135897","bioProjectId":"PRJNA560505","coverage":"3.939711247","mappingQuality":"0.9271","maxSequencingLength":"-","maxReplicate":"1","baseline":"Yes","rnaType":"poly(A)+ RNA","genetic":"-","phenotype":"-","environment":"-","spatio":"Tissue","temporal":"Development","sampleNumber":30,"species":"Capra hircus","datasetName":"Single-cell RNA-seq of the goat ovarian granulosa cells samples from high and low fertility groups","strategy":"Bulk RNA-seq","lastModified":"2021-06-27 00:09:48","createDate":"2021-06-27 00:09:48","pmid":"34344973","kingdom":"Animalia","type":"1","caseDetail":"HLG,HMG,HSG,LLG,LMG,LSG","controlDetail":"-","tissue":"Oocyte","cellType":"Granulosa cells","cellLine":null,"disease":"Normal","developmentStage":null,"theme":null,"datasetQuality":"High","cellNumber":0,"speciesId":6,"aiReady":1}],"species":[]}]},{"id":75,"strategy":"Bulk RNA-seq","height":null,"isolationSource":null,"type":"1","dataSource":"NCBI","projectId":"GSE66242","bioProject":"PRJNA276799","releaseDate":"Sep 06 2017","sampleNumber":27,"caseDetail":"2000m,3000m,600m","controlDetail":"2000m,3000m,600m","featureTag":null,"tissue":"Heart,Lung,Muscle","cellLine":null,"cellType":null,"disease":null,"developmentStage":null,"species":"Capra hircus","projectName":"Transcriptomic analysis provides insights into the high-altitude adaptation in domestic goats","summary":"Domestic goats distributed in a wide range of habitats and have evolved genetic adaptations to their local environmental conditions. The goal of this study s to investigate the dramatic gene expression changes of goats that are shaped by high altitude adaptation.","overallDesign":"RNA-seq on 27 samples from the three tissues (heart, lung and skeletal muscle) in three indigenous populations residing in distinct altitudes (600 m, 2,000 m and 3,000 m)","pmid":"29149296","submissionDate":"Feb 24 2015","updateDate":"Aug 01 2019","lastModified":"2021-06-27 00:08:44","createDate":"2021-06-27 00:08:44","datasetIds":"GEND000163","protocol":null,"sequencing":null,"isFeatured":0,"relDate":"2017-09-06 00:00:00","publications":[{"id":277,"pmid":"29149296","title":"Comparative transcriptomics of 5 high-altitude vertebrates and their low-altitude relatives.","author":"Tang Q, Gu Y, Zhou X, Jin L, Guan J, Liu R, Li J, Long K, Tian S, Che T, Hu S, Liang Y, Yang X, Tao X, Zhong Z, Wang G, Chen X, Li D, Ma J, Wang X, Mai M, Jiang A, Luo X, Lv X, Gladyshev VN, Li X, Li M.","journal":"GigaScience","journalAbbr":"Gigascience","pubYear":2017,"pubMonth":"12","issue":"12","volume":"6","abst":"<h4>Background</h4>Species living at high altitude are subject to strong selective pressures due to inhospitable environments (e.g., hypoxia, low temperature, high solar radiation, and lack of biological production), making these species valuable models for comparative analyses of local adaptation. Studies that have examined high-altitude adaptation have identified a vast array of rapidly evolving genes that characterize the dramatic phenotypic changes in high-altitude animals. However, how high-altitude environment shapes gene expression programs remains largely unknown.<h4>Findings</h4>We generated a total of 910 Gb of high-quality RNA-seq data for 180 samples derived from 6 tissues of 5 agriculturally important high-altitude vertebrates (Tibetan chicken, Tibetan pig, Tibetan sheep, Tibetan goat, and yak) and their cross-fertile relatives living in geographically neighboring low-altitude regions. Of these, ∼75% reads could be aligned to their respective reference genomes, and on average ∼60% of annotated protein coding genes in each organism showed FPKM expression values greater than 0.5. We observed a general concordance in topological relationships between the nucleotide alignments and gene expression-based trees. Tissue and species accounted for markedly more variance than altitude based on either the expression or the alternative splicing patterns. Cross-species clustering analyses showed a tissue-dominated pattern of gene expression and a species-dominated pattern for alternative splicing. We also identified numerous differentially expressed genes that could potentially be involved in phenotypic divergence shaped by high-altitude adaptation.<h4>Conclusions</h4>These data serve as a valuable resource for examining the convergence and divergence of gene expression changes between species as they adapt or acclimatize to high-altitude environments.","doi":"10.1093/gigascience/gix105","citations":15,"citationDate":"2021-06-29","pageInfo":null,"authorInstitution":"Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China.","firstPubDate":"2017-12-01","type":"Comparative Study,Research Support, Non-U.S. Gov't,research-article,Journal Article","keyword":"Alternative splicing,Gene Expression,Comparative Transcriptomics,High-altitude Vertebrates","correspondingAuthor":"Mingzhou Li","country":"China","lastModified":"2021-06-29 22:53:42","createTime":"2021-06-29 22:53:42","genDatasets":[{"id":149,"datasetId":"GEND000163","pairedDatasetId":"GEND000163","dataSource":"NCBI","visual":null,"height":null,"isolationSource":null,"projectId":"GSE66242","bioProjectId":"PRJNA276799","coverage":"1.39450921","mappingQuality":"0.9829","maxSequencingLength":"196","maxReplicate":"3","baseline":"No","rnaType":"poly(A)+ RNA","genetic":"-","phenotype":"-","environment":"Abiotic stress","spatio":"Tissue","temporal":"-","sampleNumber":27,"species":"Capra hircus","datasetName":"Transcriptomic analysis provides insights into the high-altitude adaptation in domestic goats","strategy":"Bulk RNA-seq","lastModified":"2021-06-27 00:09:48","createDate":"2021-06-27 00:09:48","pmid":"29149296","kingdom":"Animalia","type":"1","caseDetail":"2000m,3000m,600m","controlDetail":"2000m,3000m,600m","tissue":"Heart,Lung,Muscle","cellType":null,"cellLine":null,"disease":"Normal","developmentStage":null,"theme":null,"datasetQuality":"High","cellNumber":0,"speciesId":6,"aiReady":1}],"species":[]}]},{"id":790,"strategy":"scRNA 10x Genomics","height":null,"isolationSource":null,"type":"0","dataSource":"NCBI","projectId":"GSE135688","bioProject":"PRJNA559681","releaseDate":"Dec 01 2021","sampleNumber":2,"caseDetail":"High fertility,Low fertility","controlDetail":null,"featureTag":null,"tissue":"Ovary","cellLine":"-","cellType":"Ovarian granulosa cell","disease":"Normal","developmentStage":"-","species":"Capra hircus","projectName":"Single-cell RNA-seq (10x) of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth).","summary":"Single-cell RNA-seq (10x) of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth). The goal of this project is to explore the role of ovarian granulosa cells on the fertility of goat at single cell level. We would like to investigate the role of ovarian granulosa cells on the ovulation rate which indicates fertility. Therefore the ovarian granulosa cells from different population (hihg or low fertility groups animals) were analyzed.","overallDesign":"We totally analyzed ~12,000 single cell transcriptome profile from goat ovarian granulosa cells from the two groups.","pmid":"33624340","submissionDate":"Aug 10 2019","updateDate":"Dec 01 2021","lastModified":"2023-11-13 16:14:00","createDate":"2023-11-13 16:14:00","datasetIds":"GEND000566","protocol":null,"sequencing":null,"isFeatured":0,"relDate":"2021-12-01 00:00:00","publications":[]},{"id":791,"strategy":"snRNA-seq BGI","height":null,"isolationSource":null,"type":"0","dataSource":"NCBI","projectId":"GSE183300","bioProject":"PRJNA747757","releaseDate":"Sep 04 2021","sampleNumber":28,"caseDetail":"Duodenum,Esophagus,Eyelid,Heart,intestine,Kidney,Large,Liver,Lung,Rectum,Spleen,Stomach","controlDetail":null,"featureTag":null,"tissue":"Duodenum,Esophagus,Eyelid,Heart,intestine,Kidney,Large,Liver,Lung,Rectum,Spleen,Stomach","cellLine":"-","cellType":"-","disease":"Normal","developmentStage":"-","species":"Anas platyrhynchos; Columba livia; Canis lupus familiaris; Felis catus; Capra hircus; Manis javanica; Oryctolagus cuniculus; Mesocricetus auratus; Anolis carolinensis; Panthera tigris altaica","projectName":"Single cell atlas for mammals, reptiles and birds","summary":"The availability of viral entry factors is a prerequisite for the cross-species transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Large-scale single-cell screening on animal cells is a powerful tool to reveal the expression patterns of viral entry genes for different hosts. But such exploration for SARS-CoV-2 remained limited. Here, we presented the broadest pan-species single-nucleus RNA sequencing study to date, covering 11 representative species in pets (cat, dog, hamster, lizard), livestock (goat, rabbit), poultry (duck, pigeon) and wildlife (pangolin, tiger, deer), from which we investigated the co-expression of ACE2 and TMPRSS2. Notably, the proportion of SARS-CoV-2 putative target cells in cat was found considerably higher than that of other species investigated in this study, highlighting the necessity to carefully evaluate the role of cats during SARS-CoV-2 circulation. Furthermore, cross-species analysis of comparative lung cell atlas in mammals, reptiles and birds revealed core developmental programs, critical connectomes and conserved regulatory circuits among evolutionarily distant species. Additionally, we developed a user-friendly and freely accessible online platform named PANDORA for researchers to fully exploit the pan-species single cell atlas. Overall, our work provides a compendium of gene expression profiles for non-model animals, which could be employed to identify potential SARS-CoV-2 target cells and narrow down putative zoonotic reservoirs. Alternatively, our resources could also be utilized to illuminate the cellular and molecular mechanisms underlying animal tissue evolution.","overallDesign":"To investigate the expression of SARS-CoV-2 receptors ACE2 and TMPRSS2 from 11 representative species in pets (cat, dog, hamster, lizard), livestock (goat, rabbit), poultry (duck, pigeon) and wildlife (pangolin, tiger, deer).","pmid":"34873160","submissionDate":"Sep 02 2021","updateDate":"Jan 10 2022","lastModified":"2023-11-13 16:14:00","createDate":"2023-11-13 16:14:00","datasetIds":"GEND000567,GEND000568,GEND000569,GEND000570,GEND000571,GEND000572,GEND000573,GEND000574,GEND000575,GEND000576","protocol":null,"sequencing":null,"isFeatured":0,"relDate":"2021-09-04 00:00:00","publications":[]}]}