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Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes

This article compares 32 bacterial genomes with respect to their high transcription potentialities. The σ70 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 si...

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Autores principales: Sinoquet, Christine, Demey, Sylvain, Braun, Frédérique
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2425493/
https://www.ncbi.nlm.nih.gov/pubmed/18440978
http://dx.doi.org/10.1093/nar/gkn135
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author Sinoquet, Christine
Demey, Sylvain
Braun, Frédérique
author_facet Sinoquet, Christine
Demey, Sylvain
Braun, Frédérique
author_sort Sinoquet, Christine
collection PubMed
description This article compares 32 bacterial genomes with respect to their high transcription potentialities. The σ70 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 σ70 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 σ70-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.
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spelling pubmed-24254932008-06-12 Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes Sinoquet, Christine Demey, Sylvain Braun, Frédérique Nucleic Acids Res Computational Biology This article compares 32 bacterial genomes with respect to their high transcription potentialities. The σ70 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 σ70 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 σ70-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. Oxford University Press 2008-06 2008-04-25 /pmc/articles/PMC2425493/ /pubmed/18440978 http://dx.doi.org/10.1093/nar/gkn135 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Sinoquet, Christine
Demey, Sylvain
Braun, Frédérique
Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes
title Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes
title_full Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes
title_fullStr Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes
title_full_unstemmed Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes
title_short Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes
title_sort large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2425493/
https://www.ncbi.nlm.nih.gov/pubmed/18440978
http://dx.doi.org/10.1093/nar/gkn135
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