Rastogi, C., Rube, H.T., Kribelbauer, J.F., Crocker, J., Loker, R.E., Martini, G.D., Laptenko, O., Freed-Pastor, W.A., Prives, C., Stern, D.L., Mann, R.S., Bussemaker, H.J. (2018). Accurate and sensitive quantification of protein-DNA binding affinity.  Proc. Natl. Acad. Sci. U.S.A. 115(16): E3692--EE3701.

FBrf0239950

Research paper

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.

PMC5910815 (PMC) (EuropePMC)