Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence

Kinney, J. B., Murugan, A., Callan, C. G., Cox, E. C. (2010) Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proceedings of the National Academy of Sciences of the United States of America, 107 (20). pp. 9158-9163. ISSN 0027-8424

URL: http://www.ncbi.nlm.nih.gov/pubmed/20439748
DOI: 10.1073/pnas.1004290107

Abstract

Cells use protein-DNA and protein-protein interactions to regulate transcription. A biophysical understanding of this process has, however, been limited by the lack of methods for quantitatively characterizing the interactions that occur at specific promoters and enhancers in living cells. Here we show how such biophysical information can be revealed by a simple experiment in which a library of partially mutated regulatory sequences are partitioned according to their in vivo transcriptional activities and then sequenced en masse. Computational analysis of the sequence data produced by this experiment can provide precise quantitative information about how the regulatory proteins at a specific arrangement of binding sites work together to regulate transcription. This ability to reliably extract precise information about regulatory biophysics in the face of experimental noise is made possible by a recently identified relationship between likelihood and mutual information. Applying our experimental and computational techniques to the Escherichia coli lac promoter, we demonstrate the ability to identify regulatory protein binding sites de novo, determine the sequence-dependent binding energy of the proteins that bind these sites, and, importantly, measure the in vivo interaction energy between RNA polymerase and a DNA-bound transcription factor. Our approach provides a generally applicable method for characterizing the biophysical basis of transcriptional regulation by a specified regulatory sequence. The principles of our method can also be applied to a wide range of other problems in molecular biology.

Item Type: Paper
Uncontrolled Keywords: gene regulation lac promoter mutual information thermodynamic models parallel tempering Monte Carlo ESCHERICHIA-COLI DNA-BINDING GENOMIC PROMOTERS ACTIVATOR PROTEIN LACTOSE OPERON REPRESSOR SPECIFICITY POLYMERASE ELEMENTS MODELS
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > transcription
bioinformatics > genomics and proteomics > annotation > sequence annotation
bioinformatics > genomics and proteomics > analysis and processing > Sequence Data Processing
bioinformatics > genomics and proteomics > Mapping and Rendering > Sequence Rendering
bioinformatics > computational biology
CSHL Authors:
Communities: CSHL labs > Kinney lab
CSHL Cancer Center Program > Gene Regulation and Cell Proliferation
Depositing User: CSHL Librarian
Date Deposited: 04 Oct 2011 13:36
Last Modified: 13 Oct 2015 14:49
PMCID: PMC2889059
Related URLs:
URI: http://repository.cshl.edu/id/eprint/15453

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