2018 Articles

Accurate and sensitive quantification of protein-DNA binding affinity

Rastogi, Chaitanya; Rube, Hans Tomas; Kribelbauer, Judith Franziska; Crocker, Justin; Loker, Ryan Edmund; Martini, Gabriella D.; Laptenko, Oleg; Freed-Pastor, William Allen; Prives, Carol L.; Stern, David L.; Mann, Richard S.; Bussemaker, Harmen J.

Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes.