Computational detection of cis-regulatory modules

Motivation: The transcriptional regulation of a metazoan gene depends on the cooperative action of multiple transcription factors that bind to cis-regulatory modules (CRMs) located in the neighborhood of the gene. By integrating multiple signals, CRMs confer an organism specific spatial and temporal rate of transcription. Results: Based on the hypothesis that genes that are needed in exactly the same conditions might share similar regulatory switches, we have developed a novel methodology to find CRMs in a set of coexpressed or coregulated genes. The ModuleSearcher algorithm finds for a given gene set the best scoring combination of transcription factor binding sites within a sequence window using an A* procedure for tree searching. To keep the level of noise low, we use DNA sequences that are most likely to contain functional cis-regulatory information, namely conserved regions between human and mouse orthologous genes. The ModuleScanner performs genomic searches with a predicted CRM or with a user-defined CRM known from the literature to find possible target genes. The validity of a set of putative targets is checked using Gene Ontology annotations. We demonstrate the use and effectiveness of the ModuleSearcher and ModuleScanner algorithms and test their specificity and sensitivity on semi- artificial data. Next, we search for a module in a cluster of gene expression profiles of human cell cycle genes.