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Cis-regulatory modules (CRMs) composed of multiple transcription factorbinding sites (TFBSs) control gene expression in eukaryotic genomes.Comparative genomic studies have shown that these regulatory elements are moreconserved across species due to evolutionary constraints. We propose astatistical method to combine module structure and cross-species orthology inde novo motif discovery. We use a hidden Markov model (HMM) to capture themodule structure in each species and couple these HMMs through multiple-speciesalignment. Evolutionary models are incorporated to consider correlatedstructures among aligned sequence positions across different species. Based onour model, we develop a Markov chain Monte Carlo approach, MultiModule, todiscover CRMs and their component motifs simultaneously in groups oforthologous sequences from multiple species. Our method is tested on bothsimulated and biological data sets in mammals and Drosophila, where significantimprovement over other motif and module discovery methods is observed.

Coupling hidden Markov models for the discovery of Cis-regulatory modules in multiple species