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Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity

Uncovering the functional impact of genetic variation on gene expression is important in understanding tissue biology and the pathogenesis of complex traits. Despite large efforts to map expression quantitative trait loci (eQTLs) across many human tissues, our ability to translate those findings to...

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Autores principales: Arvanitis, Marios, Tayeb, Karl, Strober, Benjamin J., Battle, Alexis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874223/
https://www.ncbi.nlm.nih.gov/pubmed/35085493
http://dx.doi.org/10.1016/j.ajhg.2022.01.002
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author Arvanitis, Marios
Tayeb, Karl
Strober, Benjamin J.
Battle, Alexis
author_facet Arvanitis, Marios
Tayeb, Karl
Strober, Benjamin J.
Battle, Alexis
author_sort Arvanitis, Marios
collection PubMed
description Uncovering the functional impact of genetic variation on gene expression is important in understanding tissue biology and the pathogenesis of complex traits. Despite large efforts to map expression quantitative trait loci (eQTLs) across many human tissues, our ability to translate those findings to understanding human disease has been incomplete, and the majority of disease loci are not explained by association with expression of a target gene. Cell-type specificity and the presence of multiple independent causal variants for many eQTLs are potential confounders contributing to the apparent discrepancy with disease loci. In this study, we investigate the tissue specificity of genetic effects on gene expression and the overlap with disease loci while considering the presence of multiple causal variants within and across tissues. We find evidence of pervasive tissue specificity of eQTLs, often masked by linkage disequilibrium that misleads traditional meta-analytic approaches. We propose CAFEH (colocalization and fine-mapping in the presence of allelic heterogeneity), a Bayesian method that integrates genetic association data across multiple traits, incorporating linkage disequilibrium to identify causal variants. CAFEH outperforms previous approaches in colocalization and fine-mapping. Using CAFEH, we show that genes with highly tissue-specific genetic effects are under greater selection, enriched in differentiation and developmental processes, and more likely to be involved in human disease. Last, we demonstrate that CAFEH can efficiently leverage the widespread allelic heterogeneity in genetic regulation of gene expression to prioritize the target tissue in genome-wide association complex trait loci, thereby improving our ability to interpret complex trait genetics.
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spelling pubmed-88742232022-03-02 Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity Arvanitis, Marios Tayeb, Karl Strober, Benjamin J. Battle, Alexis Am J Hum Genet Article Uncovering the functional impact of genetic variation on gene expression is important in understanding tissue biology and the pathogenesis of complex traits. Despite large efforts to map expression quantitative trait loci (eQTLs) across many human tissues, our ability to translate those findings to understanding human disease has been incomplete, and the majority of disease loci are not explained by association with expression of a target gene. Cell-type specificity and the presence of multiple independent causal variants for many eQTLs are potential confounders contributing to the apparent discrepancy with disease loci. In this study, we investigate the tissue specificity of genetic effects on gene expression and the overlap with disease loci while considering the presence of multiple causal variants within and across tissues. We find evidence of pervasive tissue specificity of eQTLs, often masked by linkage disequilibrium that misleads traditional meta-analytic approaches. We propose CAFEH (colocalization and fine-mapping in the presence of allelic heterogeneity), a Bayesian method that integrates genetic association data across multiple traits, incorporating linkage disequilibrium to identify causal variants. CAFEH outperforms previous approaches in colocalization and fine-mapping. Using CAFEH, we show that genes with highly tissue-specific genetic effects are under greater selection, enriched in differentiation and developmental processes, and more likely to be involved in human disease. Last, we demonstrate that CAFEH can efficiently leverage the widespread allelic heterogeneity in genetic regulation of gene expression to prioritize the target tissue in genome-wide association complex trait loci, thereby improving our ability to interpret complex trait genetics. Elsevier 2022-02-03 2022-01-31 /pmc/articles/PMC8874223/ /pubmed/35085493 http://dx.doi.org/10.1016/j.ajhg.2022.01.002 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Arvanitis, Marios
Tayeb, Karl
Strober, Benjamin J.
Battle, Alexis
Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity
title Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity
title_full Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity
title_fullStr Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity
title_full_unstemmed Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity
title_short Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity
title_sort redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874223/
https://www.ncbi.nlm.nih.gov/pubmed/35085493
http://dx.doi.org/10.1016/j.ajhg.2022.01.002
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