Skip Navigation



Nucleic Acids Research Advance Access published online on April 25, 2008
Nucleic Acids Research, doi:10.1093/nar/gkn135
This Article
Right arrow Full Text Freely available
Right arrow Print PDF (377K) Freely available
Right arrow Screen PDF (396K) Freely available
Right arrow Supplementary Data
Right arrowOA All Versions of this Article:
36/10/3332    most recent
gkn135v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Commercial Re-use Guidelines
for Open Access NAR Content
Google Scholar
Right arrow Articles by Sinoquet, C.
Right arrow Articles by Braun, F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sinoquet, C.
Right arrow Articles by Braun, F.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2008 The Author(s)
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.

Computational Biology

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

Christine Sinoquet1,*, Sylvain Demey1 and Frédérique Braun2

1Computer 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 and 2Inserm U601, Cancerology Research Department, University of Nantes, 9 quai Moncousu, 44093 Nantes Cedex 01, France

*To whom correspondence should be addressed. Tel: +33(0)25112 5805; Fax: +33(0)25112 5815; Email: christine.sinoquet{at}univ-nantes.fr

Received December 22, 2007. Revised February 20, 2008. Accepted March 10, 2008.

This article compares 32 bacterial genomes with respect to their high transcription potentialities. The {sigma}70 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 {sigma}70 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 {sigma}70-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.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 J. Bacteriol.Home page
J. Collado-Vides, H. Salgado, E. Morett, S. Gama-Castro, V. Jimenez-Jacinto, I. Martinez-Flores, A. Medina-Rivera, L. Muniz-Rascado, M. Peralta-Gil, and A. Santos-Zavaleta
Bioinformatics Resources for the Study of Gene Regulation in Bacteria
J. Bacteriol., January 1, 2009; 191(1): 23 - 31.
[Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.