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Nucleic Acids Research Advance Access published online on March 10, 2008
Nucleic Acids Research, doi:10.1093/nar/gkn048
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Genomics

A systematic characterization of factors that regulate Drosophila segmentation via a bacterial one-hybrid system

Marcus B. Noyes1,2, Xiangdong Meng1, Atsuya Wakabayashi1, Saurabh Sinha4, Michael H. Brodsky1,3 and Scot A. Wolfe1,2,*

1Program in Gene Function and Expression, 2Department of Biochemistry and Molecular Pharmacology, 3Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605 and 4Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA

*To whom correspondence should be addressed. Tel: +1 508 856 3953; Fax: +1 508 856 5460; Email: scot.wolfe{at}umassmed.edu

Correspondence may also be addressed to Michael H. Brodsky. Tel: +1 508 856 1640; Fax +1 508 856 5460; Email: michael.brodsky{at}umassmed.edu

Received December 21, 2007. Revised January 22, 2008. Accepted January 24, 2008.

Specificity data for groups of transcription factors (TFs) in a common regulatory network can be used to computationally identify the location of cis-regulatory modules in a genome. The primary limitation for this type of analysis is the paucity of specificity data that is available for the majority of TFs. We describe an omega-based bacterial one-hybrid system that provides a rapid method for characterizing DNA-binding specificities on a genome-wide scale. Using this system, 35 members of the Drosophila melanogaster segmentation network have been characterized, including representative members of all of the major classes of DNA-binding domains. A suite of web-based tools was created that uses this binding site dataset and phylogenetic comparisons to identify cis-regulatory modules throughout the fly genome. These tools allow specificities for any combination of factors to be used to perform rapid local or genome-wide searches for cis-regulatory modules. The utility of these factor specificities and tools is demonstrated on the well-characterized segmentation network. By incorporating specificity data on an additional 66 factors that we have characterized, our tools utilize ~14% of the predicted factors within the fly genome and provide an important new community resource for the identification of cis-regulatory modules.


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