Functional transcription factor target discovery via compendia of binding and expression profiles

TL;DR

This study demonstrates that correlating TF binding and gene expression profiles across multiple conditions effectively identifies functional transcription factor targets, outperforming single-condition analyses and enabling cross-cell-type predictions.

Contribution

The paper introduces a method leveraging multi-condition binding and expression data to distinguish functional TF targets, improving accuracy over traditional single-condition approaches.

Findings

High correlation predicts functional TF targets.

Cross-cell-type correlation predicts targets in other cell types.

Time-course correlation identifies functional targets in specific tissues.

Abstract

Genome-wide experiments to map the DNA-binding locations of transcription-associated factors (TFs) have shown that the number of genes bound by a TF far exceeds the number of possible direct target genes. Distinguishing functional from non-functional binding is therefore a major challenge in the study of transcriptional regulation. We hypothesized that functional targets can be discovered by correlating binding and expression profiles across multiple experimental conditions. To test this hypothesis, we obtained ChIP-seq and RNA-seq data from matching cell types from the human ENCODE resource, considered promoter-proximal and distal cumulative regulatory models to map binding sites to genes, and used a combination of linear and non-linear measures to correlate binding and expression data. We found that a high degree of correlation between a gene's TF-binding and expression profiles was significantly more predictive of the gene being differentially expressed upon knockdown of that TF, compared to using binding sites in the cell type of interest only. Remarkably, TF targets predicted from correlation across a compendium of cell types were also predictive of functional targets in other cell types. Finally, correlation across a time course of ChIP-seq and RNA-seq experiments was also predictive of functional TF targets in that tissue.