Academic Commons


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.


Also Published In

Proceedings of the National Academy of Sciences
Academic Commons provides global access to research and scholarship produced at Columbia University, Barnard College, Teachers College, Union Theological Seminary and Jewish Theological Seminary. Academic Commons is managed by the Columbia University Libraries.