title: The cross-species prediction of bacterial promoters using a support vector machine.
abstract: Due to degeneracy of the observed binding sites, the in silico prediction of bacterial sigma(70)-like promoters remains a challenging problem. A large number of sigma(70)-like promoters has been biologically identified in only two species, Escherichia coli and Bacillus subtilis. In this paper we investigate the issues that arise when searching for promoters in other species using an ensemble of SVM classifiers trained on E. coli promoters. DNA sequences are represented using a tagged mismatch string kernel. The major benefit of our approach is that it does not require a prior definition of the typical -35 and -10 hexamers. This gives the SVM classifiers the freedom to discover other features relevant to the prediction of promoters. We use our approach to predict sigma(A) promoters in B. subtilis and sigma(66) promoters in Chlamydia trachomatis. We extended the analysis to identify specific regulatory features of gene sets in C. trachomatis having different expression profiles. We found a strong -35 hexamer and TGN/-10 associated with a set of early expressed genes. Our analysis highlights the advantage of using TSS-PREDICT as a starting point for predicting promoters in species where few are known.
authors.affiliation: School of Life Sciences, Faculty of Science, Queensland University of Queensland, Brisbane, Queensland, Australia.
authors.forename: Michael
authors.initials: M
authors.lastname: Towsey
authors.forename: Peter
authors.initials: P
authors.lastname: Timms
authors.forename: James
authors.initials: J
authors.lastname: Hogan
authors.forename: Sarah A
authors.initials: SA
authors.lastname: Mathews
mesh_terms: D001185:Artificial Intelligence; D001412:Bacillus subtilis / Q000235:genetics; D001419:Bacteria / Q000235:genetics*; D001483:Base Sequence; D001665:Binding Sites / Q000235:genetics; D002692:Chlamydia trachomatis / Q000235:genetics; D002874:Chromosome Mapping / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D004926:Escherichia coli / Q000235:genetics; D020869:Gene Expression Profiling; D008969:Molecular Sequence Data; D011401:Promoter Regions, Genetic / Q000235:genetics*; D050436:Regulatory Elements, Transcriptional / Q000235:genetics; D012808:Sigma Factor / Q000235:genetics; D024363:Transcription Initiation Site
chemical_list: D012808:Sigma Factor