Graduate School of Biomedical Sciences; Program in Gene Function and Expression; Department of Biochemistry and Molecular Pharmacology; Program in Molecular Medicine
Life Sciences | Medicine and Health Sciences
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 approximately 14% of the predicted factors within the fly genome and provide an important new community resource for the identification of cis-regulatory modules.
DOI of Published Version
Nucleic Acids Res. 2008 May;36(8):2547-60. Epub 2008 Mar 10. Link to article on publisher's site
Nucleic acids research
Noyes MB, Meng X, Wakabayashi A, Sinha S, Brodsky MH, Wolfe SA. (2008). A systematic characterization of factors that regulate Drosophila segmentation via a bacterial one-hybrid system. Morningside Graduate School of Biomedical Sciences Student Publications. https://doi.org/10.1093/nar/gkn048. Retrieved from https://escholarship.umassmed.edu/gsbs_sp/1350