Systematic Dissection of Sequence Features Affecting the Binding Specificity of a Pioneer Factor Reveals Binding Synergy Between FOXA1 and AP-1

Abstract

Despite the unique ability of pioneer transcription factors (PFs) to target nucleosomal sites in closed chromatin, they only bind a small fraction of their genomic motifs. The underlying mechanism of this selectivity is not well understood. Here, we design a high-throughput assay called ChIP-ISO to systematically dissect sequence features affecting the binding specificity of a classic PF, FOXA1. Combining ChIP-ISO within vitroand neural network analyses, we find that 1) FOXA1 binding is strongly affected by co-binding TFs AP-1 and CEBPB, 2) FOXA1 and AP-1 show binding cooperativityin vitro, 3) FOXA1’s binding is determined more by local sequences than chromatin context, including eu-/heterochromatin, and 4) AP-1 is partially responsible for differential binding of FOXA1 in different cell types. Our study presents a framework for elucidating genetic rules underlying PF binding specificity and reveals a mechanism for context-specific regulation of its binding.

Interpretable deep learning reveals the sequence rules of Hippo signaling

“…Here, we hypothesized that this TF cooperativity is DNA sequence-driven and thus can be studied by measuring the binding of TFs on DNA and identifying the underlying sequence rules using interpretable deep learning. During training, deep learning models accurately learn sequence rules within genomic regions in an inherently combinatorial manner de novo until they can predict the data from sequence alone 15–21 . The key step is then to interrogate the model and extract the learned sequence rules using interpretation tools 15 .…”