Using hexamers to predict cis-regulatory modules in Drosophila

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.

　 本文给出了一种基于简单数理统计的，在基因组中预测顺式调节基本单元的方法。该算法与预测TFBS的算法是异曲同工的。对于TFBS的预测这一领域还不熟悉的朋友，可以以这篇文章作为入门或者窗口，因为该篇文章思路清晰、简单易懂，并且为同领域的其他算法提供了索引。对于TFBS预测有一定背景的同行，不妨浏览这篇文章，毕竟如此简单易行的生物信息学算法能发表在影响因子5.42的杂志上是值得同志们思考，同时也令人欢欣鼓舞的。

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