Academic Journal
Interactions between genetic variation and cellular environment in skeletal muscle gene expression.
| Title: | Interactions between genetic variation and cellular environment in skeletal muscle gene expression. |
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| Authors: | D Leland Taylor, David A Knowles, Laura J Scott, Andrea H Ramirez, Francesco Paolo Casale, Brooke N Wolford, Li Guan, Arushi Varshney, Ricardo D'Oliveira Albanus, Stephen C J Parker, Narisu Narisu, Peter S Chines, Michael R Erdos, Ryan P Welch, Leena Kinnunen, Jouko Saramies, Jouko Sundvall, Timo A Lakka, Markku Laakso, Jaakko Tuomilehto, Heikki A Koistinen, Oliver Stegle, Michael Boehnke, Ewan Birney, Francis S Collins |
| Source: | PLoS ONE, Vol 13, Iss 4, p e0195788 (2018) |
| Publisher Information: | Public Library of Science (PLoS), 2018. |
| Publication Year: | 2018 |
| Collection: | LCC:Medicine LCC:Science |
| Subject Terms: | Medicine, Science |
| More Details: | From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1932-6203 |
| Relation: | http://europepmc.org/articles/PMC5901994?pdf=render; https://doaj.org/toc/1932-6203 |
| DOI: | 10.1371/journal.pone.0195788 |
| Access URL: | https://doaj.org/article/0de5691bc69c48a5a92bbc0b581ecb65 |
| Accession Number: | edsdoj.0de5691bc69c48a5a92bbc0b581ecb65 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 19326203 |
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| DOI: | 10.1371/journal.pone.0195788 |
| Published in: | PLoS ONE |
| Language: | English |