Accurate and sensitive quantification of protein-DNA binding affinity.

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Proceedings of the National Academy of Sciences of the United States of America. 2018 Apr 02;115(16):E3692-701. doi: 10.1073/pnas.1714376115

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Accurate and sensitive quantification of protein-DNA binding affinity. Stern Lab

Rastogi C, Rube HT, Kribelbauer JF, Crocker J, Loker RE, Martini GD, Laptenko O, Freed-Pastor WA, Prives C, Stern DL, Mann RS, Bussemaker HJ

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Abstract

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.

PMID: 29610332 [PubMed - indexed for MEDLINE]

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Accurate and sensitive quantification of protein-DNA binding affinity.

Abstract

PMID: 29610332 [PubMed - indexed for MEDLINE]

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