Measuring and Predicting Enhancer-Promoter Communication

Abstract

Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but it remains unclear which enhancers regulate which genes. A key bottleneck in understanding the regulatory wiring that connects noncoding regulatory elements to specific target genes has been that we have lacked scalable experimental approaches for perturbing enhancers in the genome and determining their effects on gene expression. To address this challenge, we developed new experimental approaches to systematically quantify the effects of enhancers regulating a gene of interest in a given cell type. Applying these approaches to dozens of genes uncovered complex networks of regulatory connections that could not be predicted by any existing approach. Strikingly, a simple equation based on a mechanistic model for enhancer function performed remarkably well at predicting the complex patterns of regulatory connections we observed in our datasets. This Activity-by-Contact (ABC) model involves multiplying measures of enhancer activity and enhancer-promoter 3D contacts, and can predict enhancer-gene connections based on chromatin state maps. Together, these experimental and computational approaches provide a systematic framework to understand gene regulation by enhancers and will catalyze efforts to interpret human genetic variation and manipulate gene expression for therapeutic purposes.