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High-throughput allele-specific expression across 250 environmental conditions
Gene-by-environment (GxE) interactions determine common disease risk factors and biomedically relevant complex traits. However, quantifying how the environment modulates genetic effects on human quantitative phenotypes presents unique challenges. Environmental covariates are complex and difficult to...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131815/ https://www.ncbi.nlm.nih.gov/pubmed/27934696 http://dx.doi.org/10.1101/gr.209759.116 |
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author | Moyerbrailean, Gregory A. Richards, Allison L. Kurtz, Daniel Kalita, Cynthia A. Davis, Gordon O. Harvey, Chris T. Alazizi, Adnan Watza, Donovan Sorokin, Yoram Hauff, Nancy Zhou, Xiang Wen, Xiaoquan Pique-Regi, Roger Luca, Francesca |
author_facet | Moyerbrailean, Gregory A. Richards, Allison L. Kurtz, Daniel Kalita, Cynthia A. Davis, Gordon O. Harvey, Chris T. Alazizi, Adnan Watza, Donovan Sorokin, Yoram Hauff, Nancy Zhou, Xiang Wen, Xiaoquan Pique-Regi, Roger Luca, Francesca |
author_sort | Moyerbrailean, Gregory A. |
collection | PubMed |
description | Gene-by-environment (GxE) interactions determine common disease risk factors and biomedically relevant complex traits. However, quantifying how the environment modulates genetic effects on human quantitative phenotypes presents unique challenges. Environmental covariates are complex and difficult to measure and control at the organismal level, as found in GWAS and epidemiological studies. An alternative approach focuses on the cellular environment using in vitro treatments as a proxy for the organismal environment. These cellular environments simplify the organism-level environmental exposures to provide a tractable influence on subcellular phenotypes, such as gene expression. Expression quantitative trait loci (eQTL) mapping studies identified GxE interactions in response to drug treatment and pathogen exposure. However, eQTL mapping approaches are infeasible for large-scale analysis of multiple cellular environments. Recently, allele-specific expression (ASE) analysis emerged as a powerful tool to identify GxE interactions in gene expression patterns by exploiting naturally occurring environmental exposures. Here we characterized genetic effects on the transcriptional response to 50 treatments in five cell types. We discovered 1455 genes with ASE (FDR < 10%) and 215 genes with GxE interactions. We demonstrated a major role for GxE interactions in complex traits. Genes with a transcriptional response to environmental perturbations showed sevenfold higher odds of being found in GWAS. Additionally, 105 genes that indicated GxE interactions (49%) were identified by GWAS as associated with complex traits. Examples include GIPR–caffeine interaction and obesity and include LAMP3–selenium interaction and Parkinson disease. Our results demonstrate that comprehensive catalogs of GxE interactions are indispensable to thoroughly annotate genes and bridge epidemiological and genome-wide association studies. |
format | Online Article Text |
id | pubmed-5131815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-51318152016-12-19 High-throughput allele-specific expression across 250 environmental conditions Moyerbrailean, Gregory A. Richards, Allison L. Kurtz, Daniel Kalita, Cynthia A. Davis, Gordon O. Harvey, Chris T. Alazizi, Adnan Watza, Donovan Sorokin, Yoram Hauff, Nancy Zhou, Xiang Wen, Xiaoquan Pique-Regi, Roger Luca, Francesca Genome Res Research Gene-by-environment (GxE) interactions determine common disease risk factors and biomedically relevant complex traits. However, quantifying how the environment modulates genetic effects on human quantitative phenotypes presents unique challenges. Environmental covariates are complex and difficult to measure and control at the organismal level, as found in GWAS and epidemiological studies. An alternative approach focuses on the cellular environment using in vitro treatments as a proxy for the organismal environment. These cellular environments simplify the organism-level environmental exposures to provide a tractable influence on subcellular phenotypes, such as gene expression. Expression quantitative trait loci (eQTL) mapping studies identified GxE interactions in response to drug treatment and pathogen exposure. However, eQTL mapping approaches are infeasible for large-scale analysis of multiple cellular environments. Recently, allele-specific expression (ASE) analysis emerged as a powerful tool to identify GxE interactions in gene expression patterns by exploiting naturally occurring environmental exposures. Here we characterized genetic effects on the transcriptional response to 50 treatments in five cell types. We discovered 1455 genes with ASE (FDR < 10%) and 215 genes with GxE interactions. We demonstrated a major role for GxE interactions in complex traits. Genes with a transcriptional response to environmental perturbations showed sevenfold higher odds of being found in GWAS. Additionally, 105 genes that indicated GxE interactions (49%) were identified by GWAS as associated with complex traits. Examples include GIPR–caffeine interaction and obesity and include LAMP3–selenium interaction and Parkinson disease. Our results demonstrate that comprehensive catalogs of GxE interactions are indispensable to thoroughly annotate genes and bridge epidemiological and genome-wide association studies. Cold Spring Harbor Laboratory Press 2016-12 /pmc/articles/PMC5131815/ /pubmed/27934696 http://dx.doi.org/10.1101/gr.209759.116 Text en © 2016 Moyerbrailean et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Moyerbrailean, Gregory A. Richards, Allison L. Kurtz, Daniel Kalita, Cynthia A. Davis, Gordon O. Harvey, Chris T. Alazizi, Adnan Watza, Donovan Sorokin, Yoram Hauff, Nancy Zhou, Xiang Wen, Xiaoquan Pique-Regi, Roger Luca, Francesca High-throughput allele-specific expression across 250 environmental conditions |
title | High-throughput allele-specific expression across 250 environmental conditions |
title_full | High-throughput allele-specific expression across 250 environmental conditions |
title_fullStr | High-throughput allele-specific expression across 250 environmental conditions |
title_full_unstemmed | High-throughput allele-specific expression across 250 environmental conditions |
title_short | High-throughput allele-specific expression across 250 environmental conditions |
title_sort | high-throughput allele-specific expression across 250 environmental conditions |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131815/ https://www.ncbi.nlm.nih.gov/pubmed/27934696 http://dx.doi.org/10.1101/gr.209759.116 |
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