Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs

<p>Abstract</p> <p>Background</p> <p>In bacteria, sigma factors and other transcriptional regulatory proteins recognize DNA patterns upstream of their target genes and interact with RNA polymerase to control transcription. As a consequence of evolution, DNA sequences re...

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Main Authors: Gaudreau Luc, Rodrigue Sébastien, Jacques Pierre-Étienne, Goulet Jean, Brzezinski Ryszard
Format: Article
Language:English
Published: BMC 2006-10-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/7/423
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spelling doaj-a2a9a365296d41c59f426de09f50fd802020-11-24T21:36:24ZengBMCBMC Bioinformatics1471-21052006-10-017142310.1186/1471-2105-7-423Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairsGaudreau LucRodrigue SébastienJacques Pierre-ÉtienneGoulet JeanBrzezinski Ryszard<p>Abstract</p> <p>Background</p> <p>In bacteria, sigma factors and other transcriptional regulatory proteins recognize DNA patterns upstream of their target genes and interact with RNA polymerase to control transcription. As a consequence of evolution, DNA sequences recognized by transcription factors are thought to be enriched in intergenic regions (IRs) and depleted from coding regions of prokaryotic genomes.</p> <p>Results</p> <p>In this work, we report that genomic distribution of transcription factors binding sites is biased towards IRs, and that this bias is conserved amongst bacterial species. We further take advantage of this observation to develop an algorithm that can efficiently identify promoter boxes by a distribution-dependent approach rather than a direct sequence comparison approach. This strategy, which can easily be combined with other methodologies, allowed the identification of promoter sequences in ten species and can be used with any annotated bacterial genome, with results that rival with current methodologies. Experimental validations of predicted promoters also support our approach.</p> <p>Conclusion</p> <p>Considering that complete genomic sequences of over 1000 bacteria will soon be available and that little transcriptional information is available for most of them, our algorithm constitutes a promising tool for the prediction of promoter sequences. Importantly, our methodology could also be adapted to identify DNA sequences recognized by other regulatory proteins.</p> http://www.biomedcentral.com/1471-2105/7/423
collection DOAJ
language English
format Article
sources DOAJ
author Gaudreau Luc
Rodrigue Sébastien
Jacques Pierre-Étienne
Goulet Jean
Brzezinski Ryszard
spellingShingle Gaudreau Luc
Rodrigue Sébastien
Jacques Pierre-Étienne
Goulet Jean
Brzezinski Ryszard
Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs
BMC Bioinformatics
author_facet Gaudreau Luc
Rodrigue Sébastien
Jacques Pierre-Étienne
Goulet Jean
Brzezinski Ryszard
author_sort Gaudreau Luc
title Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs
title_short Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs
title_full Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs
title_fullStr Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs
title_full_unstemmed Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs
title_sort detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2006-10-01
description <p>Abstract</p> <p>Background</p> <p>In bacteria, sigma factors and other transcriptional regulatory proteins recognize DNA patterns upstream of their target genes and interact with RNA polymerase to control transcription. As a consequence of evolution, DNA sequences recognized by transcription factors are thought to be enriched in intergenic regions (IRs) and depleted from coding regions of prokaryotic genomes.</p> <p>Results</p> <p>In this work, we report that genomic distribution of transcription factors binding sites is biased towards IRs, and that this bias is conserved amongst bacterial species. We further take advantage of this observation to develop an algorithm that can efficiently identify promoter boxes by a distribution-dependent approach rather than a direct sequence comparison approach. This strategy, which can easily be combined with other methodologies, allowed the identification of promoter sequences in ten species and can be used with any annotated bacterial genome, with results that rival with current methodologies. Experimental validations of predicted promoters also support our approach.</p> <p>Conclusion</p> <p>Considering that complete genomic sequences of over 1000 bacteria will soon be available and that little transcriptional information is available for most of them, our algorithm constitutes a promising tool for the prediction of promoter sequences. Importantly, our methodology could also be adapted to identify DNA sequences recognized by other regulatory proteins.</p>
url http://www.biomedcentral.com/1471-2105/7/423
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