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Title | Genetic effects on gene expression across human tissues. |
Publication Type | Journal Article |
Year of Publication | 2017 |
Authors | Battle, A, Brown, CD, Engelhardt, BE, Montgomery, SB |
Corporate Authors | GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, Lead analysts:, Laboratory, Data Analysis &Coordinating Center (LDACC):, NIH program management:, Biospecimen collection:, Pathology:, eQTL manuscript working group: |
Journal | Nature |
Volume | 550 |
Issue | 7675 |
Pagination | 204-213 |
Date Published | 2017 10 11 |
ISSN | 1476-4687 |
Keywords | Alleles, Chromosomes, Human, Disease, Female, Gene Expression Profiling, Gene Expression Regulation, Genetic Variation, Genome, Human, Genotype, Humans, Male, Organ Specificity, Quantitative Trait Loci |
Abstract | Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease. |
DOI | 10.1038/nature24277 |
Alternate Journal | Nature |
PubMed ID | 29022597 |
PubMed Central ID | PMC5776756 |
Grant List | P30 AG010124 / AG / NIA NIH HHS / United States U41 HG002371 / HG / NHGRI NIH HHS / United States R01 MH101782 / MH / NIMH NIH HHS / United States R01 MH109905 / MH / NIMH NIH HHS / United States R01 MH106842 / MH / NIMH NIH HHS / United States T15 LM007033 / LM / NLM NIH HHS / United States T32 HG000044 / HG / NHGRI NIH HHS / United States R01 MH101822 / MH / NIMH NIH HHS / United States T32 HG003284 / HG / NHGRI NIH HHS / United States U01 HG007436 / HG / NHGRI NIH HHS / United States R01 MH101820 / MH / NIMH NIH HHS / United States U54 HG007990 / HG / NHGRI NIH HHS / United States U01 HG007591 / HG / NHGRI NIH HHS / United States |