@article {Taylor105429, author = {D. Leland Taylor and David A. Knowles and Laura J. Scott and Andrea H. Ramirez and Franceso Paolo Casale and Brooke N. Wolford and Li Guan and Arushi Varshney and Ricardo Oliveira Albanus and Stephen C.J. Parker and Narisu Narisu and Peter S. Chines and Michael R. Erdos and Ryan P. Welch and Leena Kinnunen and Jouko Saramies and Jouko Sundvall and Timo A. Lakka and Markku Laakso and Jaakko Tuomilehto and Heikki A. Koistinen and Oliver Stegle and Michael Boehnke and Ewan Birney and Francis S. Collins}, title = {Interactions between genetic variation and cellular environment in skeletal muscle gene expression}, elocation-id = {105429}, year = {2017}, doi = {10.1101/105429}, publisher = {Cold Spring Harbor Laboratory}, abstract = {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 interaction quantitative trait loci (iQTLs) 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.}, URL = {https://www.biorxiv.org/content/early/2017/02/03/105429}, eprint = {https://www.biorxiv.org/content/early/2017/02/03/105429.full.pdf}, journal = {bioRxiv} }