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Published online on March 29, 2007, 10.1073/pnas.0701614104
PNAS | April 10, 2007 | vol. 104 | no. 15 | 6305-6310


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BIOLOGICAL SCIENCES / GENETICS
Discovering transcriptional regulatory regions in Drosophila by a nonalignment method for phylogenetic footprinting

Alona Sosinsky*,{dagger},{ddagger}, Barry Honig*,{dagger},{ddagger},§, Richard S. Mann{dagger}, and Andrea Califano{ddagger}

*Howard Hughes Medical Institute, {dagger}Department of Biochemistry and Molecular Biophysics, Department of Biomedical Informatics, and {ddagger}Center for Computational Biology and Bioinformatics, Columbia University, 1130 Nicholas Avenue, New York, NY 10032

Contributed by Barry Honig, February 22, 2007 (received for review October 13, 2006)

The functional annotation of the nonprotein-coding DNA of eukaryotic genomes is a problem of central importance. Phylogenetic footprinting methods, which attempt to identify functional regulatory regions by comparing orthologous genomic sequences of evolutionarily related species, have shown promising results. The main advantage of this class of approaches is that they do not require any knowledge of the regulating transcription factors. Here we describe a method called Enhancer Detection using only Genomic Information (EDGI), which integrates a traditional motif-discovery algorithm with a local permutation-clustering algorithm. Together, they can identify large regulatory elements (e.g., enhancers) as evolutionarily conserved order-independent clusters of short conserved motifs. We show that EDGI can distinguish between established sets of known enhancers and nonenhancers with 88% accuracy, rivaling predictions by methods that rely on the knowledge of the regulating transcription factors and their DNA-binding specificities. We tested EDGI's performance on a set of Drosophila genomes. Our results demonstrate that comparative genomic analysis of multiple closely related species has substantial power to identify key functional elements without additional biological knowledge.

enhancer discovery | regulatory sequence evolution | regulatory sequence prediction | transcription regulation | comparative genomics


Author contributions: A.S., B.H., R.S.M., and A.C. designed research; A.S., B.H., R.S.M., and A.C. performed research; A.S., B.H., R.S.M., and A.C. analyzed data; and A.S., B.H., R.S.M., and A.C. wrote the paper.

The authors declare no conflict of interest.

This article contains supporting information online at www.pnas.org/cgi/content/full/0701614104/DC1.

§To whom correspondence should be addressed. E-mail: bh6{at}columbia.edu

© 2007 by The National Academy of Sciences of the USA


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