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Center for Genomics and Bioinformatics (A.S., W.W.), Karolinska Institutet, 113 37 Stockholm, Sweden; Centre for Molecular Medicine and Therapeutics (W.W.W.), British Columbia Children’s and Women’s Hospitals, and Department of Medical Genetics (W.W.W.), University of British Columbia, Vancouver, Canada V5Z 4H4
Address all correspondence and requests for reprints to: Wyeth W. Wasserman, Centre for Molecular Medicine and Therapeutics, 3018-950 West 28th Avenue, Vancouver, British Columbia, Canada V5Z 4H4. E-mail: wyeth{at}cmmt.ubc.ca.
The nuclear receptor (NR) class of transcription factors controls critical regulatory events in key developmental processes, homeostasis maintenance, and medically important diseases and conditions. Identification of the members of a regulon controlled by a NR could provide an accelerated understanding of development and disease. New bioinformatics methods for the analysis of regulatory sequences are required to address the complex properties associated with known regulatory elements targeted by the receptors because the standard methods for binding site prediction fail to reflect the diverse target site configurations. We have constructed a flexible Hidden Markov Model framework capable of predicting NHR binding sites. The model allows for variable spacing and orientation of half-sites. In a genome-scale analysis enabled by the model, we show that NRs in Fugu rubripes have a significant cross-regulatory potential. The model is implemented in a web interface, freely available for academic researchers, available at http://mordor.cgb.ki.se/NHR-scan.
NURSA Molecule Pages Link:
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