Literature DB >> 10705431

Genes regulated cooperatively by one or more transcription factors and their identification in whole eukaryotic genomes.

A Wagner1.   

Abstract

MOTIVATION: The question addressed here is how cooperative interactions among transcription factors (TFs), a very frequent phenomenon in eukaryotic transcriptional regulation, can be used to identify genes that are regulated by one or more TFs with known DNA binding specificities. Cooperativity may be homotypic, involving binding of only one transcription factor to multiple sites in a gene's regulatory region. It may also be heterotypic, involving binding of more than one TF. Both types of cooperativity have in common that the binding sites for the respective TFs form tightly linked 'clusters', groups of binding sites often more closely associated than expected by chance alone.
RESULTS: A statistical technique suitable for the identification of statistically significant homotypic or heterotypic TF binding site clusters in whole eukaryotic genomes is presented. It can be used to identify genes likely to be regulated by the TFs. Application of the technique is illustrated with two transcription factors involved in the cell cycle and mating control of the yeast Saccharomyces cerevisiae, indicating that the results obtained are biologically meaningful. This rapid and inexpensive computational method of generating hypotheses about gene regulation thus generates information that may be used to guide subsequent costly and laborious experimental approaches, and that may aid in the assignment of biological functions to putative open reading frames.

Entities:  

Mesh:

Substances:

Year:  1999        PMID: 10705431     DOI: 10.1093/bioinformatics/15.10.776

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  56 in total

1.  Exploiting transcription factor binding site clustering to identify cis-regulatory modules involved in pattern formation in the Drosophila genome.

Authors:  Benjamin P Berman; Yutaka Nibu; Barret D Pfeiffer; Pavel Tomancak; Susan E Celniker; Michael Levine; Gerald M Rubin; Michael B Eisen
Journal:  Proc Natl Acad Sci U S A       Date:  2002-01-22       Impact factor: 11.205

2.  rVista for comparative sequence-based discovery of functional transcription factor binding sites.

Authors:  Gabriela G Loots; Ivan Ovcharenko; Lior Pachter; Inna Dubchak; Edward M Rubin
Journal:  Genome Res       Date:  2002-05       Impact factor: 9.043

3.  Homotypic regulatory clusters in Drosophila.

Authors:  Alexander P Lifanov; Vsevolod J Makeev; Anna G Nazina; Dmitri A Papatsenko
Journal:  Genome Res       Date:  2003-04       Impact factor: 9.043

Review 4.  In silico identification of metazoan transcriptional regulatory regions.

Authors:  Wyeth W Wasserman; William Krivan
Journal:  Naturwissenschaften       Date:  2003-03-27

5.  Identifying cooperativity among transcription factors controlling the cell cycle in yeast.

Authors:  Nilanjana Banerjee; Michael Q Zhang
Journal:  Nucleic Acids Res       Date:  2003-12-01       Impact factor: 16.971

6.  Statistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences.

Authors:  Martin C Frith; John L Spouge; Ulla Hansen; Zhiping Weng
Journal:  Nucleic Acids Res       Date:  2002-07-15       Impact factor: 16.971

7.  A motif co-occurrence approach for genome-wide prediction of transcription-factor-binding sites in Escherichia coli.

Authors:  Martha L Bulyk; Abigail M McGuire; Nobuhisa Masuda; George M Church
Journal:  Genome Res       Date:  2004-02       Impact factor: 9.043

8.  Cluster-Buster: Finding dense clusters of motifs in DNA sequences.

Authors:  Martin C Frith; Michael C Li; Zhiping Weng
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

9.  Comprehensive quantitative analyses of the effects of promoter sequence elements on mRNA transcription.

Authors:  Michal Lapidot; Yitzhak Pilpel
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

10.  Predicting transcription factor synergism.

Authors:  Sridhar Hannenhalli; Samuel Levy
Journal:  Nucleic Acids Res       Date:  2002-10-01       Impact factor: 16.971

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.