title: Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes.
abstract: This article compares 32 bacterial genomes with respect to their high transcription potentialities. The sigma70 promoter has been widely studied for Escherichia coli model and a consensus is known. Since transcriptional regulations are known to compensate for promoter weakness (i.e. when the promoter similarity with regard to the consensus is rather low), predicting functional promoters is a hard task. Instead, the research work presented here comes within the scope of investigating potentially high ORF expression, in relation with three criteria: (i) high similarity to the sigma70 consensus (namely, the consensus variant appropriate for each genome), (ii) transcription strength reinforcement through a supplementary binding site--the upstream promoter (UP) element--and (iii) enhancement through an optimal Shine-Dalgarno (SD) sequence. We show that in the AT-rich Firmicutes' genomes, frequencies of potentially strong sigma70-like promoters are exceptionally high. Besides, though they contain a low number of strong promoters (SPs), some genomes may show a high proportion of promoters harbouring an UP element. Putative SPs of lesser quality are more frequently associated with an UP element than putative strong promoters of better quality. A meaningful difference is statistically ascertained when comparing bacterial genomes with similarly AT-rich genomes generated at random; the difference is the highest for Firmicutes. Comparing some Firmicutes genomes with similarly AT-rich Proteobacteria genomes, we confirm the Firmicutes specificity. We show that this specificity is neither explained by AT-bias nor genome size bias; neither does it originate in the abundance of optimal SD sequences, a typical and significant feature of Firmicutes more thoroughly analysed in our study.
authors.affiliation: Computer Science Institute of Nantes-Atlantic (Lina), U.M.R. C.N.R.S. 6241, University of Nantes, 2 rue de la Houssinière, BP 92208, 44322 Nantes Cedex, France. christine.sinoquet@univ-nantes.fr
authors.forename: Christine
authors.initials: C
authors.lastname: Sinoquet
authors.forename: Sylvain
authors.initials: S
authors.lastname: Demey
authors.forename: Frédérique
authors.initials: F
authors.lastname: Braun
mesh_terms: D020856:AT Rich Sequence; D001483:Base Sequence; D019295:Computational Biology; D016384:Consensus Sequence; D012321:DNA-Directed RNA Polymerases / Q000378:metabolism*; D003627:Data Interpretation, Statistical; D004742:Enhancer Elements, Genetic; D004926:Escherichia coli / Q000235:genetics; D016680:Genome, Bacterial; D023281:Genomics; D016366:Open Reading Frames; D011401:Promoter Regions, Genetic; D012808:Sigma Factor / Q000378:metabolism*; D020124:Thermotoga maritima / Q000235:genetics; D014158:Transcription, Genetic
chemical_list: D012808:Sigma Factor; C081775:RNA polymerase sigma 70; D012321:DNA-Directed RNA Polymerases