The GTEx Consortium atlas of genetic regulatory effects across human tissues

By F. Aguet, A. Barbeira, Rodrigo Bonazzola, Andrew Anand Brown, Stephane E. Castel, Brian Jo, S. Kasela, Sarah Kim-Hellmuth, Yanyu Liang, Meritxell Oliva and 42 more. Science, 2019

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The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e254b0ff90ed6992dbfbf63970552d29cde8efc8

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Citations in the corpus

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases (2020, background): “…higher precision than including all genes passing a global score threshold, consistent with the idea that a regulatory variant can affect the expression of multiple genes 33,35 , yet only a select few, perhaps often the most strongly regulated, have a direct effect on the complex trait of interest.”
Haplotype-resolved diverse human genomes and integrated analysis of structural variation (2021, background): “Genome-wide QTL scans can bridge the gap between molecular and clinical phenotypes and serve as a proxy for functional effects mediated by genetic variant classes ( 23 , 44 , 59 ).”
Mendelian randomization for cardiovascular diseases: principles and applications (2023, positive): “…one of these initial MR studies, 94 the researchers selected variants within ± 100 kb of the HMGCR and NPC1L1 genes that associated with LDL-C levels at a threshold of P 5.0 × 10 − 6 in the Global Lipids Genetics Consortium 101 as instrumental variables to predict the corresponding drug effects.”
The Nucleotide Transformer: Building and Evaluating Robust Foundation Models for Human Genomics (2024, result): “Our results also suggest that training on a diverse dataset, represented by the Multispecies 2.5B model, outperforms or matches the 1000G 2.5B model on several tasks derived from human-based assays (Fig.”