Literature DB >> 17628149

Gene promoter scan methodology for identifying and classifying coregulated promoters.

Igor Zwir1, Oscar Harari, Eduardo A Groisman.   

Abstract

A critical challenge of the postgenomic era is to understand how genes are differentially regulated. Genetic and genomic approaches have been used successfully to assign genes to distinct regulatory networks in both prokaryotes and eukaryotes. However, little is known about what determines the differential expression of genes within a particular network, even when it involves a single transcription factor. The fact that coregulated genes may be differentially expressed suggests that subtle differences in the shared cis-acting regulatory elements are likely to be significant. This chapter describes a method, termed gene promoter scan (GPS), that discriminates among coregulated promoters by simultaneously considering a variety of cis-acting regulatory features. Application of this method to the PhoP/PhoQ two-component regulatory system of Escherichia coli and Salmonella enterica uncovered novel members of the PhoP regulon, as well as regulatory interactions that had not been discovered using previous approaches. The predictions made by GPS were validated experimentally to establish that the PhoP protein uses multiple mechanisms to control gene transcription and is a central element in a highly connected network.

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Year:  2007        PMID: 17628149      PMCID: PMC3755887          DOI: 10.1016/S0076-6879(06)22018-4

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  51 in total

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Journal:  Nat Genet       Date:  2000-05       Impact factor: 38.330

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Journal:  Science       Date:  1997-09-05       Impact factor: 47.728

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Journal:  EMBO J       Date:  2000-04-17       Impact factor: 11.598

8.  The phosphatase activity is the target for Mg2+ regulation of the sensor protein PhoQ in Salmonella.

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Journal:  J Biol Chem       Date:  2000-07-28       Impact factor: 5.157

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Journal:  Proc Int Conf Intell Syst Mol Biol       Date:  1995

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Journal:  Nature       Date:  2000-08-31       Impact factor: 49.962

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  1 in total

1.  Profile analysis and prediction of tissue-specific CpG island methylation classes.

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Journal:  BMC Bioinformatics       Date:  2009-04-21       Impact factor: 3.169

  1 in total

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