Reports

Diversity and Complexity in DNA Recognition by Transcription Factors

Gwenael Badis,^1,* Michael F. Berger,^2,3,* Anthony A. Philippakis,^2,3,4,* Shaheynoor Talukder,^1,5,* Andrew R. Gehrke,^2,* Savina A. Jaeger,^2,* Esther T. Chan,^5,* Genita Metzler,⁶ Anastasia Vedenko,⁷ Xiaoyu Chen,¹ Hanna Kuznetsov,⁶ Chi-Fong Wang,⁸ David Coburn,¹ Daniel E. Newburger,² Quaid Morris,^1,5,9,10 Timothy R. Hughes,^1,5,10, Martha L. Bulyk^2,3,4,11,

Sequence preferences of DNA binding proteins are a primary mechanism by which cells interpret the genome. Despite the central importance of these proteins in physiology, development, and evolution, comprehensive DNA binding specificities have been determined experimentally for only a few proteins. Here, we used microarrays containing all 10–base pair sequences to examine the binding specificities of 104 distinct mouse DNA binding proteins representing 22 structural classes. Our results reveal a complex landscape of binding, with virtually every protein analyzed possessing unique preferences. Roughly half of the proteins each recognized multiple distinctly different sequence motifs, challenging our molecular understanding of how proteins interact with their DNA binding sites. This complexity in DNA recognition may be important in gene regulation and in the evolution of transcriptional regulatory networks.

¹ Banting and Best Department of Medical Research, University of Toronto, Toronto, ON M5S 3E1, Canada.
² Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA.
³ Committee on Higher Degrees in Biophysics, Harvard University, Cambridge, MA 02138, USA.
⁴ Harvard–Massachusetts Institute of Technology (MIT) Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA.
⁵ Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada.
⁶ Department of Biology, MIT, Cambridge, MA 02139, USA.
⁷ Department of Biology, Wellesley College, Wellesley, MA 02481, USA.
⁸ Department of Physics, MIT, Cambridge, MA 02139, USA.
⁹ Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4, Canada.
¹⁰ Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada.
¹¹ Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA.

^* These authors contributed equally to this work.

To whom correspondence should be addressed. E-mail: t.hughes{at}utoronto.ca (T.R.H.); mlbulyk{at}receptor.med.harvard.edu (M.L.B.)

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Quantitative cell array screening to identify regulators of gene expression.

P. Kainth and B. Andrews (2009)
Brief Funct Genomic Proteomic
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JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles.

E. Portales-Casamar, S. Thongjuea, A. T. Kwon, D. Arenillas, X. Zhao, E. Valen, D. Yusuf, B. Lenhard, W. W. Wasserman, and A. Sandelin (2009)
Nucleic Acids Res.
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Distinguishing direct versus indirect transcription factor-DNA interactions.

R. Gordan, A. J. Hartemink, and M. L. Bulyk (2009)
Genome Res. 19, 2090-2100
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Bind-n-Seq: high-throughput analysis of in vitro protein-DNA interactions using massively parallel sequencing.

A. Zykovich, I. Korf, and D. J. Segal (2009)
Nucleic Acids Res.
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Exhaustive Search for Over-represented DNA Sequence Motifs with CisFinder.

A. A. Sharov and M. S.H. Ko (2009)
DNA Res 16, 261-273
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Analysis of a complete DNA-protein affinity landscape.

W. Rowe, M. Platt, D. C. Wedge, P. J. Day, D. B. Kell, and J. Knowles (2009)
J R Soc Interface
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