TY - JOUR T1 - Transcription factor regulation of eQTL activity across individuals and tissues JF - bioRxiv DO - 10.1101/2021.07.20.453075 SP - 2021.07.20.453075 AU - Elise D. Flynn AU - Athena L. Tsu AU - Silva Kasela AU - Sarah Kim-Hellmuth AU - Francois Aguet AU - Kristin G. Ardlie AU - Harmen J. Bussemaker AU - Pejman Mohammadi AU - Tuuli Lappalainen Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/07/20/2021.07.20.453075.abstract N2 - 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.Author Summary Gene expression is regulated by local genomic sequence and can be affected by genetic variants. In the human population, tens of thousands of cis-regulatory variants have been discovered that are associated with altered gene expression across tissues, cell types, or environmental conditions. Understanding the molecular mechanisms of how these small changes in the genome sequence affect genome function would offer insight to the genetic regulatory code and how gene expression is controlled across tissues and environments. Current research efforts suggest that many regulatory variants’ effects on gene expression are mediated by them altering the binding of transcription factors, which are proteins that bind to DNA to regulate gene expression. Here, we exploit the natural variation of TF activity among 49 tissues and between 838 individuals to elucidate which TFs regulate which regulatory variants. We find 6,262 TF-eQTL interactions across 1,598 genes that are supported by at least two lines of evidence. We validate these interactions using functional genomic and experimental approaches, and we find indication that they may pinpoint mechanisms of environment-specific genetic regulatory effects and genetic variants associated to diseases and traits.Competing Interest StatementI have read the journal's policy and the authors of this manuscript have the following competing interests: TL advises Variant Bio, Goldfinch Bio, GlaxoSmithKline and has equity in Variant Bio. FA is an inventor on a patent application related to TensorQTL. ER -