Limited overlap of eQTLs and GWAS hits due to systematic differences in discovery

Mostafavi, Hakhamanesh; Spence, Jeffrey P.; Naqvi, Sahin; Pritchard, Jonathan K.

doi:10.1101/2022.05.07.491045

Cited by 87 publications

(97 citation statements)

References 109 publications

(157 reference statements)

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“…Our findings contrast with several recent studies on humans where regulatory variants such as eQTL contribute a small part to phenotypic variation 9,10,19 . Our analysis supporting the direct role of regulatory variants in shaping complex traits has several differences from previous studies which may have led to our different conclusions.…”

Section: Discussioncontrasting

confidence: 99%

Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Xiang

Fang

Liu

et al. 2022

Preprint

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Many quantitative trait loci (QTL) are located in non-coding genomic regions. Therefore, QTL are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription so QTL changing gene expression (eQTL) or RNA splicing (sQTL) are expected to significantly contribute to phenotypic variations. Here, we quantify the contribution of eQTL and sQTL detected from 16 tissues (N~5,000) to 37 complex traits of ~120k cattle. Using Bayesian methods, we show that including more regulatory variants in the model explains larger proportions of heritability. Across traits, cis and trans eQTL and sQTL detected from 16 tissues jointly explain ~70% (SE=0.5%) of heritability, 44% more than expected from the same number of random variants, where trans e/sQTL contribute 24% (14% more than expected). Multi-tissue cis and trans e/sQTL also explain 71% (SE=0.3%) of heritability for the metabolome, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.

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Section: Discussioncontrasting

confidence: 99%

Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Xiang

Fang

Liu

et al. 2022

Preprint

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“…From the 1st to the 5th quintiles of constraint, rare variant enrichments decayed from a median of 4.5x to 0.3x, while common variant enrichments declined from a lower maximum (2.1x) to a similar minimum (0.5x) ( Figure 4C ). These observations are consistent with the expected effect of negative selection, which prevents both coding and regulatory variants affecting highly constrained genes from becoming common in the population, thereby limiting the magnitude of common variant enrichments 19,22,35,36 (see Discussion).…”

Section: Resultssupporting

confidence: 83%

Polygenic architecture of rare coding variation across 400,000 exomes

Weiner

Nadig

Jagadeesh

et al. 2022

Preprint

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Both common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have discovered thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare-variant associations in hundreds of genes. However, rare-variant genetic architecture is not well characterized, and the relationship between common- and rare- variant architecture is unclear. Here, we quantify the heritability explained by gene-wise burden of rare coding variants and compare the genetic architecture of common and rare variation across 22 common traits and diseases in 400,000 UK Biobank exomes. Rare coding variants (AF = 1e-6 - 1e-3) explain 1.3% (SE = 0.03%) of phenotypic variance on average - much less than common variants - and most burden heritability is explained by ultra-rare loss-of-function variants (AF = 1e-6 - 1e-5). Common and rare variants implicate the same cell types, with similar enrichments, and they have pleiotropic effects on the same pairs of traits, with similar genetic correlations. They partially colocalize at individual genes and loci, but not to the same extent: burden heritability is strongly concentrated in a limited number of significant genes (median: 6 genes explaining 19% of h2), while common-variant heritability is much more polygenic. Burden heritability is also more strongly concentrated in constrained genes (median enrichment: 4.5x vs. 2.1x for common variants), indicating that negative selection affects common- and rare-variant architecture differently. Finally, we find that burden heritability for schizophrenia and bipolar disorder is especially high (3.8% and 3.6%). Our results show that there are a tractable number of large-effect genes to discover by studying rare variants, that common and rare associations are mechanistically convergent, and that rare coding variants will contribute only modestly to missing heritability and population risk stratification.

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“…However, the eQTL data provide only weak evidence that GWAS hits affect GATA3 expression in T cells (Supplementary Table 1). One possible explanation is that power to detect eQTLs is limited by the modest effects of common variants on gene expression and by the relatively small sample sizes of eQTL studies in relevant cell types 19 .…”

Section: Main Textmentioning

confidence: 99%

Deletion mapping of regulatory elements for GATA3 reveals a distal T helper 2 cell enhancer involved in allergic diseases

Chen

Fiaux

Sen

et al. 2022

Preprint

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The GATA3 gene is essential for T cell differentiation and is surrounded by risk variants for immune traits. Interpretation of these variants is challenging because the regulatory landscape of GATA3 is complex with dozens of potential enhancers spread across a large topological associating domain (TAD) and gene expression quantitative trait locus (eQTL) studies provide limited evidence for variant function. Here, we perform a tiling deletion screen in Jurkat T cells to identify 23 candidate regulatory elements. Using small deletions in primary T helper 2 (Th2) cells, we validate the function of five of these elements, two of which contain risk variants for asthma and allergic diseases. We fine-map genome-wide association study (GWAS) signals in a distal regulatory element, 1 Mb downstream, to identify 14 candidate causal variants. Small deletions spanning candidate rs725861 decrease GATA3 expression in Th2 cells suggesting a causal mechanism for this variant in allergic diseases. Our study demonstrates the power of integrating GWAS signals with deletion mapping and identifies critical regulatory sequences for GATA3.

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Limited overlap of eQTLs and GWAS hits due to systematic differences in discovery

Cited by 87 publications

References 109 publications

Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Polygenic architecture of rare coding variation across 400,000 exomes

Deletion mapping of regulatory elements for GATA3 reveals a distal T helper 2 cell enhancer involved in allergic diseases

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