The GTEx Consortium atlas of genetic regulatory effects across human tissues

Abstract

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.

Exploring the Limits of Combined Image/'omics Analysis for Non-cancer Histological Phenotypes

“…We consider this observation to be notable, as the complexity of pathway biology and the underlying driving tissues could quite conceivably result in alternate findings. Our findings offer a complementary counterpoint to the fact that the majority of general ("nondisease") expression QTLs are thought to be common across a variety of tissues (GTEx Consortium et al, 2020). The figure also shows the same type of plot for association of expression with imaging PCs 1-3, which sometimes roughly track the π 1 values from phenotype association.…”

“…The v8 release is available on the GTEx Portal (https://www.gtexportal.org/home/datasets). Gene read counts were normalized between samples using TMM, and genes were selected based on expression thresholds explained in GTEx Consortium et al (2020). To account for hidden batch effects in the gene expression data, GTEx implemented the Probabilistic Estimation of Expression Residuals (PEER) method (Stegle et al, 2010) to estimate a set of cofactors for each tissue type.…”

“…Arrows indicate the tissue with the highest π 1 for phenotype, in many instances coinciding with the phenotype tissue. Tissues used in the cross-tissue analysis are labeled using the same color scheme used by GTEx Consortium et al (2020).…”

“…The motivation for GTEx (Lonsdale et al, 2013) was that the expression quantitative trait locus dissection of disease pathology is best performed using expression in the same tissue manifesting the pathology. The expression QTL results from GTEx v8 (GTEx Consortium et al, 2020) provide incomplete support for this hypothesis, as a large proportion of significant eQTLs appear to be common across tissues, raising the possibility of analogous findings for histopathological designations. In other words, it is unclear whether expression should be measured in the same tissue as that providing the basis for diagnosis.…”

To Kill But Not Be Killed: Controlling the Activity of Mammalian Pore-Forming Proteins

“…The majority of the MAC components, similar to other serum proteins, are produced by hepatocytes in the liver (58). The exception is C7, which is expressed primarily extrahepatically as shown by the fact that, in liver transplant patients, as little as 10% of plasma C7 originated from the donor cells (59), compared to nearly 100% for C6 and C9 (60,61).…”