Interactions between genetic variation and cellular environment in skeletal muscle gene expression

Taylor, D. Leland; Knowles, David A.; Scott, Laura J.; Ramirez, Andrea H.; Casale, Francesco Paolo; Wolford, Brooke N.; Guan, Li; Varshney, Arushi; Albanus, Ricardo D’Oliveira; Parker, Stephen C. J.; Narisu, Narisu; Chines, Peter S.; Erdos, Michael R.; Welch, Ryan; Kinnunen, Leena; Saramies, Jouko; Sundvall, Jouko; Lakka, Timo A.; Laakso, Markku; Tuomilehto, Jaakko; Koistinen, Heikki A.; Stegle, Oliver; Boehnke, Michael; Birney, Ewan; Collins, Francis S.

doi:10.1371/journal.pone.0195788

Cited by 19 publications

(10 citation statements)

References 64 publications

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“…While GxE interactions on human phenotype have been difficult to assess, GxE interactions in relation to gene expression have been studied under various contexts [8,[12][13][14][15][63][64][65]. Overlapping these effects with TF-eQTLs as in our analysis, or even performing TF-eQTL analysis in the environmental exposure datasets themselves, provides mechanistic hypotheses of how environmental effects impact genetic control of gene expression and phenotype.…”

Section: Discussionmentioning

confidence: 99%

Transcription factor regulation of eQTL activity across individuals and tissues

Flynn

Tsu

Kasela

et al. 2021

Preprint

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Tens of thousands of genetic variants associated with gene expression ( cis -eQTLs) have been discovered in the human population. These eQTLs are active in various tissues and contexts, but the molecular mechanisms of eQTL variability are poorly understood, hindering our understanding of genetic regulation across biological contexts. Since many eQTLs are believed to act by altering transcription factor (TF) binding affinity, we hypothesized that analyzing eQTL effect size as a function of TF level may allow discovery of mechanisms of eQTL variability. Using GTEx Consortium eQTL data from 49 tissues, we analyzed the interaction between eQTL effect size and TF level across tissues and across individuals within specific tissues and generated a list of 6,262 TF-eQTL interactions across 1,598 genes that are supported by at least two lines of evidence. These TF-eQTLs were enriched for various TF binding measures, supporting with orthogonal evidence that these eQTLs are regulated by the implicated TFs. We also found that our TF-eQTLs tend to overlap genes with gene-by-environment regulatory effects and to colocalize with GWAS loci, implying that our approach can help to elucidate mechanisms of context-specificity and trait associations. Finally, we highlight an interesting example of IKZF1 TF regulation of an APBB1IP gene eQTL that colocalizes with a GWAS signal for blood cell traits. Together, our findings provide candidate TF mechanisms for a large number of eQTLs and offer a generalizable approach for researchers to discover TF regulators of genetic variant effects in additional QTL datasets.

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Section: Discussionmentioning

confidence: 99%

Transcription factor regulation of eQTL activity across individuals and tissues

Flynn

Tsu

Kasela

et al. 2021

Preprint

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“…Response QTL mapping studies not only uncovered context-specific functional genetic variants, but also uncovered the importance of personalized genomic characterizations in the study of environmental risk for human health (e.g. (Moyerbrailean et al, 2016; Mangravite et al, 2013; Knowles et al, 2018; Taylor et al, 2018; Knowles et al, 2017; Nedelec et al, 2016; Barreiro et al, 2011; Maranville et al, 2011)). Overall, our understanding of the role of genetic variation in modulating the RNA-processing response to environmental perturbations is still quite limited.…”

Section: Genetic Regulation Of Rna Processingmentioning

confidence: 99%

“…Response eQTL mapping studies have demonstrated that genetic variation can modulate gene regulatory responses to environmental perturbations, such that the regulatory potential of a variant is unveiled only within a specific environmental context. Response QTL mapping studies not only uncovered context-specific functional genetic variants, but also uncovered the importance of personalized genomic characterizations in the study of environmental risk for human health (e.g., Barreiro et al, 2012;Knowles et al, 2017Knowles et al, , 2018Mangravite et al, 2013;Maranville et al, 2011;Moyerbrailean et al, 2016;Nedelec et al, 2016;Taylor et al, 2018). Overall, our understanding of the role of genetic variation in modulating the RNA processing response to environmental perturbations is still quite limited.…”

Section: Genetic Regulation Of Rna Processingmentioning

confidence: 99%

Environmental influences on RNA processing: Biochemical, molecular and genetic regulators of cellular response

Pai

Luca

2018

WIREs RNA

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RNA processing has emerged as a key mechanistic step in the regulation of the cellular response to environmental perturbation. Recent work has uncovered extensive remodeling of transcriptome composition upon environmental perturbation and linked the impacts of this molecular plasticity to health and disease outcomes. These isoform changes and their underlying mechanisms are varied-involving alternative sites of transcription initiation, alternative splicing, and alternative cleavage at the 3' end of the mRNA. The mechanisms and consequences of differential RNA processing have been characterized across a range of common environmental insults, including chemical stimuli, immune stimuli, heat stress, and cancer pathogenesis. In each case, there are perturbation-specific contributions of local (cis) regulatory elements or global (trans) factors and downstream consequences. Overall, it is clear that choices in isoform usage involve a balance between the usage of specific genetic elements (i.e., splice sites, polyadenylation sites) and the timing at which certain decisions are made (i.e., transcription elongation rate). Fine-tuned cellular responses to environmental perturbation are often dependent on the genetic makeup of the cell. Genetic analyses of interindividual variation in splicing have identified genetic effects on splicing that contribute to variation in complex traits. Finally, the increase in the number of tissue types and environmental conditions analyzed for RNA processing is paralleled by the need to develop appropriate analytical tools. The combination of large datasets, novel methods and conditions explored promises to provide a much greater understanding of the role of RNA processing response in human phenotypic variation. This article is categorized under: RNA Processing > RNA Editing and Modification RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Mechanisms RNA Processing > Splicing Regulation/Alternative Splicing.

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“…Despite being a conserved, basic cellular function, the ER stress response is subject to inter-individual variation in Drosophila, mouse, and humans [6][7][8][9]. It is only recently that we are beginning to appreciate the impact of genetic variation on the ER stress response.…”

Section: Introductionmentioning

confidence: 99%

“…It is only recently that we are beginning to appreciate the impact of genetic variation on the ER stress response. In Drosophila, we used natural genetic variation to demonstrate that susceptibility to ER stress is highly variable across strains and is associated with SNPs in both canonical and novel ER stress genes [6,7]. We also used mouse embryonic fibroblasts (MEFs) from inbred mouse strains to uncover a complex genetic architecture underlying the variable transcriptional response to ER stress among different genetic backgrounds [8].…”

Section: Introductionmentioning

confidence: 99%

The dynamic effect of regulatory genetic variation on thein vivoER stress transcriptional response

Russell

Chow

2021

Preprint

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Genotype x Environment (GxE) interactions occur when environmental conditions drastically change the effect of a genetic variant. In order to truly understand the effect of genetic variation, we need to incorporate multiple environments into our analyses. Many variants, under steady state conditions, may be silent or even have the opposite effect under stress conditions. This study uses an in vivo mouse model to investigate how the effect of genetic variation changes with tissue type and cellular stress. Endoplasmic reticulum (ER) stress occurs when misfolded proteins accumulate in the ER. This triggers the unfolded protein response (UPR), a large transcriptional response which attempts to return the cell to homeostasis. This transcriptional response, despite being a well conserved, basic cellular process, is highly variable across different genetic backgrounds, making it an ideal system to study GxE effects. In this study, we sought to better understand how genetic variation alters expression across tissues, in the presence and absence of ER stress. The use of different mouse strains and their F1s allow us to also identify context specific cis- and trans- regulatory mechanisms underlying variable transcriptional responses. We found hundreds of genes that respond to ER stress in a tissue- and/or genotype-dependent manner. Genotype-dependent ER stress-responsive genes are enriched for processes such as protein folding, apoptosis, and protein transport, indicating that some of the variability occurs in canonical ER stress factors. The majority of regulatory mechanisms underlying these variable transcriptional responses derive from cis- regulatory variation and are unique to a given tissue or ER stress state. This study demonstrates the need for incorporating multiple environments in future studies to better elucidate the effect of any particular genetic factor in basic biological pathways, like the ER stress response.

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Interactions between genetic variation and cellular environment in skeletal muscle gene expression

Cited by 19 publications

References 64 publications

Transcription factor regulation of eQTL activity across individuals and tissues

Transcription factor regulation of eQTL activity across individuals and tissues

Environmental influences on RNA processing: Biochemical, molecular and genetic regulators of cellular response

The dynamic effect of regulatory genetic variation on thein vivoER stress transcriptional response

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