Genetic determinants of enhancer function

Abstract

Sequence variation in enhancers, a class of cis-regulatory elements (CREs) that control cell type-specific gene transcription, contributes significantly to phenotypic variation within human populations, including the risk of developing diseases. Enhancers are short DNA sequences (~200 bp) composed of multiple binding sites (~4-10 bp each) for transcription factors (TFs). The transcriptional regulatory activity of an enhancer is encoded by the type, number, and distribution of TF-binding sites present. Active enhancers in different cell types generally lack shared, stereotypical sequence features and TF binding preferences are often not fully captured from in vitro binding assays. Therefore, the sequence determinants of TF binding to enhancers and the relationship between TF binding and enhancer activity in the native genomic context remain poorly understood. Hence, it remains difficult to reliably predict in silico the effect of any given sequence variant on enhancer function without a direct sequence-to-function relationship for well-defined cell or tissue types. To address this gap in knowledge, I generated allele-specific maps of TF binding and enhancer activity in fibroblasts derived from a panel of F1-hybrid mice, which contain a higher frequency of sequence variants than observed between maternal and paternal alleles of human cells. I identified thousands of enhancers that exhibit significant differences in TF binding and/or enhancer activity between alleles and I used these loci to define features of sequence variants that are most likely to impact enhancer function. My dataset demonstrates a critical role for AP-1 TFs at many fibroblast enhancers, reveals a hierarchical relationship between AP-1 and TEAD TFs, and delineates the nature of sequence variants that contribute to AP-1 binding. These data described herein represents one of the most comprehensive assessments to date on the impact of sequence variation on enhancer function in chromatin, with implications for pinpointing functional cis-regulatory variation in human populations.