Affiliation:
1. Department of Human Genetics, University of Utah School of Medicine , Salt Lake City, UT 84112, USA
Abstract
Abstract
The genetic regulation of gene expression varies greatly across tissue-type and individuals and can be strongly influenced by the environment. Many variants, under healthy control conditions, may be silent or even have the opposite effect under diseased stress conditions. This study uses an in vivo mouse model to investigate how the effect of genetic variation changes with cellular stress across different tissues. Endoplasmic reticulum stress occurs when misfolded proteins accumulate in the endoplasmic reticulum. This triggers the unfolded protein response, a large transcriptional response which attempts to restore homeostasis. This transcriptional response, despite being a conserved, basic cellular process, is highly variable across different genetic backgrounds, making it an ideal system to study the dynamic effects of genetic variation. In this study, we sought to better understand how genetic variation alters expression across tissues, in the presence and absence of endoplasmic reticulum stress. The use of different mouse strains and their F1s allow us to also identify context-specific cis- and trans- regulatory variation underlying variable transcriptional responses. We found hundreds of genes that respond to endoplasmic reticulum stress in a tissue- and/or genotype-dependent manner. The majority of the regulatory effects we identified were acting in cis-, which in turn, contribute to the variable endoplasmic reticulum stress- and tissue-specific transcriptional response. This study demonstrates the need for incorporating environmental stressors across multiple different tissues in future studies to better elucidate the effect of any particular genetic factor in basic biological pathways, like the endoplasmic reticulum stress response.
Funder
NIH NIGMS R35
Glenn Award from the Glenn Foundation for Medical Research, and the University of Utah Mario R Capecchi Endowed Chair in Genetics
NIH, Interdisciplinary Training Grant T32 Program in Computational Approaches to Diabetes and Metabolism Research
Publisher
Oxford University Press (OUP)
Subject
Genetics (clinical),Genetics,Molecular Biology
Cited by
3 articles.
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