Using hexamers to predict cis-regulatory motifs in Drosophila

Bob Y Chan and Dennis Kibler

School of Information and Computer Science, University of California, Irvine, Irvine, California, USA

author email corresponding author email

BMC Bioinformatics 2005, 6:262doi:10.1186/1471-2105-6-262


Published:	27 October 2005

Abstract

Background

Cis-regulatory modules (CRMs) are short stretches of DNA that help regulate gene expression in higher eukaryotes. They have been found up to 1 megabase away from the genes they regulate and can be located upstream, downstream, and even within their target genes. Due to the difficulty of finding CRMs using biological and computational techniques, even well-studied regulatory systems may contain CRMs that have not yet been discovered.

Results

We present a simple, efficient method (HexDiff) based only on hexamer frequencies of known CRMs and non-CRM sequence to predict novel CRMs in regulatory systems. On a data set of 16 gap and pair-rule genes containing 52 known CRMs, predictions made by HexDiff had a higher correlation with the known CRMs than several existing CRM prediction algorithms: Ahab, Cluster Buster, MSCAN, MCAST, and LWF. After combining the results of the different algorithms, 10 putative CRMs were identified and are strong candidates for future study. The hexamers used by HexDiff to distinguish between CRMs and non-CRM sequence were also analyzed and were shown to be enriched in regulatory elements.

Conclusion

HexDiff provides an efficient and effective means for finding new CRMs based on known CRMs, rather than known binding sites.