Literature DB >> 18955146

Technical considerations in using DNA microarrays to define regulons.

Virgil A Rhodius1, Joseph T Wade.   

Abstract

Transcription is the major regulatory target of gene expression in bacteria, and is controlled by many regulatory proteins and RNAs. Microarrays are a powerful tool to study the regulation of transcription on a genomic scale. Here we describe the use of transcription profiling and ChIP-chip to study transcriptional regulation in bacteria. Transcription profiling determines the outcome of regulatory events whereas ChIP-chip identifies the protein-DNA interactions that determine these events. Together they can provide detailed information on transcriptional regulatory systems.

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Year:  2008        PMID: 18955146      PMCID: PMC2637246          DOI: 10.1016/j.ymeth.2008.10.017

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  43 in total

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3.  W-AlignACE: an improved Gibbs sampling algorithm based on more accurate position weight matrices learned from sequence and gene expression/ChIP-chip data.

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Journal:  Bioinformatics       Date:  2008-03-05       Impact factor: 6.937

Review 4.  Next-generation sequencing transforms today's biology.

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5.  Studies of the distribution of Escherichia coli cAMP-receptor protein and RNA polymerase along the E. coli chromosome.

Authors:  David C Grainger; Douglas Hurd; Marcus Harrison; Jolyon Holdstock; Stephen J W Busby
Journal:  Proc Natl Acad Sci U S A       Date:  2005-11-21       Impact factor: 11.205

6.  High-throughput identification of transcription start sites, conserved promoter motifs and predicted regulons.

Authors:  Patrick T McGrath; Honglak Lee; Li Zhang; Antonio A Iniesta; Alison K Hottes; Meng How Tan; Nathan J Hillson; Ping Hu; Lucy Shapiro; Harley H McAdams
Journal:  Nat Biotechnol       Date:  2007-04-01       Impact factor: 54.908

7.  The transition between transcriptional initiation and elongation in E. coli is highly variable and often rate limiting.

Authors:  Nikos B Reppas; Joseph T Wade; George M Church; Kevin Struhl
Journal:  Mol Cell       Date:  2006-12-08       Impact factor: 17.970

8.  Genetic reconstruction of a functional transcriptional regulatory network.

Authors:  Zhanzhi Hu; Patrick J Killion; Vishwanath R Iyer
Journal:  Nat Genet       Date:  2007-04-08       Impact factor: 38.330

9.  Elimination of laboratory ozone leads to a dramatic improvement in the reproducibility of microarray gene expression measurements.

Authors:  William S Branham; Cathy D Melvin; Tao Han; Varsha G Desai; Carrie L Moland; Adam T Scully; James C Fuscoe
Journal:  BMC Biotechnol       Date:  2007-02-12       Impact factor: 2.563

10.  Limitations and potentials of current motif discovery algorithms.

Authors:  Jianjun Hu; Bin Li; Daisuke Kihara
Journal:  Nucleic Acids Res       Date:  2005-09-02       Impact factor: 16.971

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  9 in total

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2.  Using DNA microarrays to assay part function.

Authors:  Virgil A Rhodius; Carol A Gross
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3.  Unexpected stress-reducing effect of PhaP, a poly(3-hydroxybutyrate) granule-associated protein, in Escherichia coli.

Authors:  Alejandra de Almeida; Mariela V Catone; Virgil A Rhodius; Carol A Gross; M Julia Pettinari
Journal:  Appl Environ Microbiol       Date:  2011-07-22       Impact factor: 4.792

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5.  Identification of HilD-regulated genes in Salmonella enterica serovar Typhimurium.

Authors:  Brianna L Petrone; Anne M Stringer; Joseph T Wade
Journal:  J Bacteriol       Date:  2013-12-27       Impact factor: 3.490

6.  Genome-scale analyses of Escherichia coli and Salmonella enterica AraC reveal noncanonical targets and an expanded core regulon.

Authors:  Anne M Stringer; Salvatore Currenti; Richard P Bonocora; Catherine Baranowski; Brianna L Petrone; Michael J Palumbo; Andrew A Reilly; Zhen Zhang; Ivan Erill; Joseph T Wade
Journal:  J Bacteriol       Date:  2013-11-22       Impact factor: 3.490

7.  Nanobody(R)-based chromatin immunoprecipitation/micro-array analysis for genome-wide identification of transcription factor DNA binding sites.

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8.  "Non-canonical protein-DNA interactions identified by ChIP are not artifacts": response.

Authors:  Daniel Schindler; Torsten Waldminghaus
Journal:  BMC Genomics       Date:  2013-09-22       Impact factor: 3.969

9.  Ethanolamine Signaling Promotes Salmonella Niche Recognition and Adaptation during Infection.

Authors:  Christopher J Anderson; David E Clark; Mazhar Adli; Melissa M Kendall
Journal:  PLoS Pathog       Date:  2015-11-13       Impact factor: 6.823

  9 in total

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