Precise physical models of protein-DNA interaction from high-throughput data

Kinney, J. B., Tkacik, G., Callan, C. G. (January 2007) Precise physical models of protein-DNA interaction from high-throughput data. Proc Natl Acad Sci U S A, 104 (2). pp. 501-6. ISSN 0027-8424 (Print)0027-8424 (Linking)

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URL: http://www.ncbi.nlm.nih.gov/pubmed/17197415
DOI: 10.1073/pnas.0609908104

Abstract

A cell's ability to regulate gene transcription depends in large part on the energy with which transcription factors (TFs) bind their DNA regulatory sites. Obtaining accurate models of this binding energy is therefore an important goal for quantitative biology. In this article, we present a principled likelihood-based approach for inferring physical models of TF-DNA binding energy from the data produced by modern high-throughput binding assays. Central to our analysis is the ability to assess the relative likelihood of different model parameters given experimental observations. We take a unique approach to this problem and show how to compute likelihood without any explicit assumptions about the noise that inevitably corrupts such measurements. Sampling possible choices for model parameters according to this likelihood function, we can then make probabilistic predictions for the identities of binding sites and their physical binding energies. Applying this procedure to previously published data on the Saccharomyces cerevisiae TF Abf1p, we find models of TF binding whose parameters are determined with remarkable precision. Evidence for the accuracy of these models is provided by an astonishing level of phylogenetic conservation in the predicted energies of putative binding sites. Results from in vivo and in vitro experiments also provide highly consistent characterizations of Abf1p, a result that contrasts with a previous analysis of the same data.

Item Type: Paper
Uncontrolled Keywords: Binding Sites Biophysical Phenomena Biophysics DNA/ chemistry/ metabolism DNA, Fungal/chemistry/metabolism DNA-Binding Proteins/chemistry/metabolism Likelihood Functions Models, Chemical Protein Array Analysis Protein Binding Saccharomyces cerevisiae/metabolism Saccharomyces cerevisiae Proteins/chemistry/metabolism Thermodynamics Transcription Factors/ chemistry/ metabolism
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification
physics > biophysics
CSHL Authors:
Communities: CSHL labs > Kinney lab
Depositing User: Matt Covey
Date: 9 January 2007
Date Deposited: 30 Apr 2015 19:26
Last Modified: 09 Nov 2017 16:01
PMCID: PMC1766414
Related URLs:
URI: http://repository.cshl.edu/id/eprint/31366

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