Submitted on June 25, 2008
Accepted on May 1, 2009

Diversity and Complexity in DNA Recognition by Transcription Factors

Gwenael Badis ¹, Michael F. Berger ², Anthony A. Philippakis ³, Shaheynoor Talukder ⁴, Andrew R. Gehrke ⁵, Savina A. Jaeger ⁵, Esther T. Chan ⁶, Genita Metzler ⁷, Anastasia Vedenko ⁸, Xiaoyu Chen ¹, Hanna Kuznetsov ⁷, Chi-Fong Wang ⁹, David Coburn ¹, Daniel E. Newburger ⁵, Quaid Morris ¹⁰, Timothy R. Hughes ^11*, Martha L. Bulyk ^12*

¹ Banting and Best Department of Medical Research, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.
² Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA.; Committee on Higher Degrees in Biophysics, Harvard University, Cambridge, MA 02138, USA.
³ Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA.; Harvard-MIT Division of Health Sciences and Technology (HST), Harvard Medical School, Boston, MA 02115, USA.; Committee on Higher Degrees in Biophysics, Harvard University, Cambridge, MA 02138, USA.
⁴ Banting and Best Department of Medical Research, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.; Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.
⁵ Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA.
⁶ Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.
⁷ Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
⁸ Department of Biology, Wellesley College, Wellesley, MA 02481, USA.
⁹ Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
¹⁰ Banting and Best Department of Medical Research, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.; Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.; Department of Computer Science, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.; Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.
¹¹ Banting and Best Department of Medical Research, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.; Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.; Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College Street, Toronto, ON, Canada M5S 3E1.
¹² Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA.; Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA.; Harvard-MIT Division of Health Sciences and Technology (HST), Harvard Medical School, Boston, MA 02115, USA.; Committee on Higher Degrees in Biophysics, Harvard University, Cambridge, MA 02138, USA.

^* To whom correspondence should be addressed.
Timothy R. Hughes , E-mail: t.hughes{at}utoronto.ca
Martha L. Bulyk , E-mail: mlbulyk{at}receptor.med.harvard.edu

These authors contributed equally to this work.

Sequence preferences of DNA-binding proteins are a primary mechanism by which cells interpret the genome. Despite these proteins’ central importance in physiology, development, and evolution, comprehensive DNA-binding specificities have been determined experimentally for 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 evolution of transcriptional regulatory networks.