Algorithms for extracting structured motifs using a suffix tree with an application to promoter and regulatory site consensus identification

Laurent Marsan and Marie-France Sagot
Journal of Computational Biology, 7:345-360, 2000

The paper introduces two exact algorithms for extracting conserved structured motifs from a set of DNA sequences. Structured motifs may be described as an ordered collection of p >= 1 "boxes" (each box corresponding to one part of the structured motif), p substitution rates (one for each box) and p-1 intervals of distance (one for each pair of successive boxes in the collection). The contents of the boxes - that is, the motifs themselves -- are unknown at the start of the algorithm. This is precisely what the algorithms are meant to find. A suffix tree is used for finding such motifs. The algorithms are efficient enough to be able to infer site consensi, such as, for instance, promoter sequences or regulatory sites, from a set of unaligned sequences corresponding to the non coding regions upstream from all genes of a genome. In particular, both algorithms time complexity scales linearly with N^2 * n where n is the average length of the sequences and N their number. An application to the identification of promoter and regulatory consensus sequences in bacterial genomes is shown.

key words: structured motif extraction, promoter and regulatory site, consensus, model, suffix tree

Paper in postscript format
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