Identifying genetic regulatory variants that affect transcription factor activity

Cell Genom. 2023 Aug 18;3(9):100382. doi: 10.1016/j.xgen.2023.100382. eCollection 2023 Sep 13.

Abstract

Genetic variants affecting gene expression levels in humans have been mapped in the Genotype-Tissue Expression (GTEx) project. Trans-acting variants impacting many genes simultaneously through a shared transcription factor (TF) are of particular interest. Here, we developed a generalized linear model (GLM) to estimate protein-level TF activity levels in an individual-specific manner from GTEx RNA sequencing (RNA-seq) profiles. It uses observed differential gene expression after TF perturbation as a predictor and, by analyzing differential expression within pairs of neighboring genes, controls for the confounding effect of variation in chromatin state along the genome. We inferred genotype-specific activities for 55 TFs across 49 tissues. Subsequently performing genome-wide association analysis on this virtual trait revealed TF activity quantitative trait loci (aQTLs) that, as a set, are enriched for functional features. Altogether, the set of tools we introduce here highlights the potential of genetic association studies for cellular endophenotypes based on a network-based multi-omics approach. The transparent peer review record is available.

Keywords: RNA-seq data; aQTL; beta-binomial distribution; gene regulation; generalized linear model; genetic variation; genome-wide association; quantitative trait locus; trans-acting genetic variation; transcription factor activity; transcription factor perturbation signatures.