Project description:Lay Description The aim of the Genotype-Tissue Expression (GTEx) Project is to increase our understanding of how changes in our genes affect human health and disease with the ultimate goal of improving health care for future generations. It was launched in 2010 as a two-year pilot project supported by the Office of the Director, National Institutes of Health (NIH). GTEx will create a database that researchers can use to study how inherited changes in genes lead to common diseases. GTEx researchers are studying genes in different tissues obtained from many different people. The GTEx project also includes a study to explore the effectiveness of the GTEx donor consent process - this study will help ensure that the consent process and other aspects of the project effectively address the concerns and expectations of participants in the study. GTEx is a pioneering project that uses state-of-the-art protocols for obtaining and storing a large range of organs and tissues and for testing them in the lab. Until now, no project has analyzed genetic variation and expression in as many tissues in such a large population as planned for GTEx. Scientific Description Understanding the role of variation in the human genome is crucial to elucidating genetic contributions to human health and disease. Despite the results of genome-wide association studies (GWAS) documenting strong statistical associations between genetic variation and human traits, the functional role for most of these variants is largely unexplained. Nearly 90% of these GWAS-implicated sites lie outside of protein-coding sequences, suggesting that these variants might regulate gene expression. The goal of the Genotype-Tissue Expression (GTEx) project is to establish a resource database in which to study the relationship between genetic variation and gene expression in reference/non-diseased tissues. The ultimate resource would include up to 1,000 post-mortem donors with several dozen tissues from each, a resource large enough to study both cis- and trans- gene expression quantitative trait loci (eQTLs). Some tissue will also be banked for additional molecular analyses. GTEx was funded as a 2-year pilot project by the NIH Common Fund (CF), and will assess the feasibility of collecting high-quality RNA from multiple tissues from healthy donors. The project will collect and analyze RNA levels in 30 or more different human tissues from 160 postmortem donors and 5 tissues from a similar number of surgical controls. Each donor will be characterized for germline genetic variation through dense genotyping arrays. By treating RNA expression levels as quantitative traits, eQTLs will be identified as sites containing genetic variation that correlate with changes in RNA expression. Such eQTLs have been associated with 4%-12% of expressed human genes, and with common complex human diseases, including obesity, atherosclerosis, type 2 diabetes, Crohn's disease, and asthma. Additionally, few studies have examined the tissue specificity of eQTLs. The GTEx project will thus serve as a resource database and tissue bank for many future studies, especially for understanding the functional basis of inherited susceptibility to disease. It is anticipated that GTEx data will be made available through dbGaP on a periodic basis as it is generated.

Project description:Methylation of cytosines in CpG dinucleotides is an epigenetic mechanism with essential roles in mammalian development. To explore its functions in cellular differentiation, unbiased analysis of CpG methylation by whole genome bisulfite sequencing (WGBS) has been used to characterize epigenetic differences among different human tissues and cell types. Meanwhile, human interindividual variation in DNA methylation that is not cell-type specific has attracted relatively little attention. Systemic interindividual epigenetic variation is important, however, because like genetic variation it is a potential determinant of phenotypic variation and can be assessed in any easily obtainable DNA sample. Since systemic epigenetic variants originate in the preimplantation embryo, their establishment can be influenced by periconceptional environment, and potentially provide information about lifetime risks relevant to global health, obesity, and cancer. We elucidated systemic interindividual variation in CpG methylation in the human genome. We studied brain, heart, and thyroid tissues (representing all three germ layer lineages) from each of 10 donors in the NIH Gene-Tissue Expression (<a href="./study.cgi?study_id=phs000424">GTEx</a>) project. We performed deep whole genome bisulfite sequencing for these 30 samples, achieving a sequencing depth of over 50x coverage per sample. We identified 9,926 correlated regions of systemic interindividual variation (CoRSIVs). These regions, comprising just 0.1% of the human genome, often correlate with one another over long genomic distances, are associated with transposable elements and subtelomeric regions, conserved across various human ethnic groups, and particularly sensitive to periconceptional environment. While genetic variation appears to influence methylation at most CoRSIVs, many show no evidence of genetic influence, suggestive of 'pure' epigenetic variation. At CoRSIVs, interindividual variation in DNA methylation in an easily biopsied tissue predicts expression in other tissues, and genes associated with these loci are implicated in a range of human disorders. In addition to charting a previously unrecognized molecular level of human individuality, this atlas of human CoRSIVs provides a resource for future population-based investigations into how interindividual epigenetic variation modulates risk of disease.

Project description:BACKGROUND: The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering. RESULTS: QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative cis-drivers of gene expression programs in skeletal muscle as COQ4 (SSC1), LOC100513192 (SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests cis-causing genetic polymorphims affecting gene expression levels, with (e.g. COQ4) or without (e.g. LOC100513192) potential pleiotropic effects that affect the expression of other genes (cluster of trans-eQTLs). CONCLUSION: Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential.

Project description:BACKGROUND: The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering. RESULTS: QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative cis-drivers of gene expression programs in skeletal muscle as COQ4 (SSC1), LOC100513192 (SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests cis-causing genetic polymorphims affecting gene expression levels, with (e.g. COQ4) or without (e.g. LOC100513192) potential pleiotropic effects that affect the expression of other genes (cluster of trans-eQTLs). CONCLUSION: Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential. A wide genomic project was designed to combine genetic and transcriptome analysis. This project involved about 1,000 F2 pigs from 15 half-sib families to identify QTL for meat quality traits (Cherel et al., unpublished data). In this study, we focused on one family of 57 half sib F2 pigs. Total RNA was isolated from each of the 57 muscle samples using a commercial kit, and controlled for quality and concentration using an AGILENT 2100 bioanalyzer. cDNA was synthesized and labelled from 5 Âµg total RNA by simultaneous reverse transcription of mRNA using SuperScriptTM II RNase H- Reverse Transcriptase and 33P-deoxy-CTP. Each muscle sample mRNA was hybridized at 68Â°C during 24 h to one array. The arrays were then exposed to radioisotopic-sensitive imaging plates that were scanned thereafter with a phosphor imaging system at a 25 Âµm resolution. Hybridization images were quantified using a semi-automated software through a grid process with a fixed spot diameter. The output was then subjected to the data analysis process.

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	dbGaPEx2.1.5.xsd	Other
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	Study_Report.phs000424.GTEx.v1.p1.MULTI.pdf	Pdf
	manifest_phs000424.GTEx.v1.p1.c1.GRU.pdf	Pdf

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Genotype-Tissue Expression (GTEx)

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