Transcription factor family‐specific DNA shape readout revealed by quantitative specificity models

Abstract

Transcription factors ( TF s) achieve DNA ‐binding specificity through contacts with functional groups of bases (base readout) and readout of structural properties of the double helix (shape readout). Currently, it remains unclear whether DNA shape readout is utilized by only a few selected TF families, or whether this mechanism is used extensively by most TF families. We resequenced data from previously published HT ‐ SELEX experiments, the most extensive mammalian TF – DNA binding data available to date. Using these data, we demonstrated the contributions of DNA shape readout across diverse TF families and its importance in core motif‐flanking regions. Statistical machine‐learning models combined with feature‐selection techniques helped to reveal the nucleotide position‐dependent DNA shape readout in TF ‐binding sites and the TF family‐specific position dependence. Based on these results, we proposed novel DNA shape logos to visualize the DNA shape preferences of TF s. Overall, this work suggests a way of obtaining mechanistic insights into TF – DNA binding without relying on experimentally solved all‐atom structures. image The role of DNA shape in transcription factor ( TF )‐binding specificity is explored using a TF – DNA binding dataset covering more than 400 mammalian TF s. DNA shape readout is important for many TF families and improves binding specificity models. The largest protein– DNA binding dataset derived from HT ‐ SELEX experiments covering more than 400 mammalian TF s is analyzed. DNA shape readout plays an important role in DNA ‐binding specificities of TF s across many protein families. DNA shape in regions immediately flanking the core‐binding site is generally recognized upon TF binding. Feature selection based on DNA sequencing data alone can provide structural insights into TF – DNA readout mechanisms.