Discovery and information-theoretic characterization of transcription factor binding sites that act cooperatively

TL;DR

This paper introduces a probabilistic model for transcription factor binding sites that accounts for cooperative interactions with nearby sites, improving prediction accuracy and quantifying information content in DNA sequences.

Contribution

It develops conditional PWMs based on flanking sequences, revealing cooperative binding patterns and enhancing detection of transcription factor sites.

Findings

Dorsal sites with Twist cooperation contain about 0.5 bits of information.

Conditional models outperform traditional PWMs in predicting binding sites.

Cooperative binding sites exhibit measurable information content.

Abstract

Transcription factor binding to the surface of DNA regulatory regions is one of the primary causes of regulating gene expression levels. A probabilistic approach to model protein-DNA interactions at the sequence level is through Position Weight Matrices (PWMs) that estimate the joint probability of a DNA binding site sequence by assuming positional independence within the DNA sequence. Here we construct conditional PWMs that depend on the motif signatures in the flanking DNA sequence, by conditioning known binding site loci on the presence or absence of additional binding sites in the flanking sequence of each site's locus. Pooling known sites with similar flanking sequence patterns allows for the estimation of the conditional distribution function over the binding site sequences. We apply our model to the Dorsal transcription factor binding sites active in patterning the Dorsal-Ventral axis of Drosophila development. We find that those binding sites that cooperate with nearby Twist sites on average contain about 0.5 bits of information about the presence of Twist transcription factor binding sites in the flanking sequence. We also find that Dorsal binding site detectors conditioned on flanking sequence information make better predictions about what is a Dorsal site relative to background DNA than detection without information about flanking sequence features.