Literature DB >> 12603015

Genome-wide analysis of bacterial promoter regions.

Eleazar Eskin1, Uri Keich, Mikhail S Gelfand, Pavel A Pevzner.   

Abstract

Identifying prokaryotic promoter sequences is notoriously difficult and for most sequenced bacterial genomes the promoter sequences are still unknown. Since experimental analysis trails behind sequencing, genome-wide computational promoter discovery is often the only realistic way to discover these sequences in newly sequenced bacterial genomes. However, genome-wide samples for promoter discovery may be very large and corrupted complicating promoter discovery. We discuss three aspects of genome-wide promoter discovery: sample generation, signal finding algorithms, and scoring signals. We applied our new MITRA algorithm to analyze samples of divergent and convergent genes in 20 bacterial genomes and found strong putative dyad signals in 17 out of the 20 genomes. Moreover, in 12 out of 20 genomes the found signals are identical or similar to the known regulatory patterns (Pribnow-Gilbert boxes and CRP binding sites). Since many of putative signals correspond to previously known elements of bacterial transcriptional regulation, the remaining discovered signals are good candidates for unknown regulatory elements.

Mesh:

Substances:

Year:  2003        PMID: 12603015

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  10 in total

1.  Stress-induced DNA duplex destabilization (SIDD) in the E. coli genome: SIDD sites are closely associated with promoters.

Authors:  Huiquan Wang; Michiel Noordewier; Craig J Benham
Journal:  Genome Res       Date:  2004-08       Impact factor: 9.043

2.  Structure and evolution of gene regulatory networks in microbial genomes.

Authors:  Sarath Chandra Janga; J Collado-Vides
Journal:  Res Microbiol       Date:  2007-10-15       Impact factor: 3.992

3.  Development of an efficient expression system for Flavobacterium strains.

Authors:  Shicheng Chen; Michael G Kaufman; Michael Bagdasarian; Adam K Bates; Edward D Walker
Journal:  Gene       Date:  2010-03-03       Impact factor: 3.688

4.  EXMOTIF: efficient structured motif extraction.

Authors:  Yongqiang Zhang; Mohammed J Zaki
Journal:  Algorithms Mol Biol       Date:  2006-11-16       Impact factor: 1.405

5.  Integrated computational and experimental analysis of the neuroendocrine transcriptome in genetic hypertension identifies novel control points for the cardiometabolic syndrome.

Authors:  Ryan S Friese; Chun Ye; Caroline M Nievergelt; Andrew J Schork; Nitish R Mahapatra; Fangwen Rao; Philip S Napolitan; Jill Waalen; Georg B Ehret; Patricia B Munroe; Geert W Schmid-Schönbein; Eleazar Eskin; Daniel T O'Connor
Journal:  Circ Cardiovasc Genet       Date:  2012-06-05

6.  Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs.

Authors:  Pierre-Etienne Jacques; Sébastien Rodrigue; Luc Gaudreau; Jean Goulet; Ryszard Brzezinski
Journal:  BMC Bioinformatics       Date:  2006-10-02       Impact factor: 3.169

7.  Genome2D: a visualization tool for the rapid analysis of bacterial transcriptome data.

Authors:  Richard J S Baerends; Wiep Klaas Smits; Anne de Jong; Leendert W Hamoen; Jan Kok; Oscar P Kuipers
Journal:  Genome Biol       Date:  2004-04-05       Impact factor: 13.583

8.  Triad pattern algorithm for predicting strong promoter candidates in bacterial genomes.

Authors:  Michael Dekhtyar; Amelie Morin; Vehary Sakanyan
Journal:  BMC Bioinformatics       Date:  2008-05-09       Impact factor: 3.169

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

Authors:  Christine Sinoquet; Sylvain Demey; Frédérique Braun
Journal:  Nucleic Acids Res       Date:  2008-04-25       Impact factor: 16.971

10.  SIGffRid: a tool to search for sigma factor binding sites in bacterial genomes using comparative approach and biologically driven statistics.

Authors:  Fabrice Touzain; Sophie Schbath; Isabelle Debled-Rennesson; Bertrand Aigle; Gregory Kucherov; Pierre Leblond
Journal:  BMC Bioinformatics       Date:  2008-01-31       Impact factor: 3.169

  10 in total

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