Literature DB >> 12364607

Predicting transcription factor synergism.

Sridhar Hannenhalli1, Samuel Levy.   

Abstract

Transcriptional regulation is mediated by a battery of transcription factor (TF) proteins, that form complexes involving protein-protein and protein-DNA interactions. Individual TFs bind to their cognate cis-elements or transcription factor-binding sites (TFBS). TFBS are organized on the DNA proximal to the gene in groups confined to a few hundred base pair regions. These groups are referred to as modules. Various modules work together to provide the combinatorial regulation of gene transcription in response to various developmental and environmental conditions. The sets of modules constitute a promoter model. Determining the TFs that preferentially work in concert as part of a module is an essential component of understanding transcriptional regulation. The TFs that act synergistically in such a fashion are likely to have their cis-elements co-localized on the genome at specific distances apart. We exploit this notion to predict TF pairs that are likely to be part of a transcriptional module on the human genome sequence. The computational method is validated statistically, using known interacting pairs extracted from the literature. There are 251 TFBS pairs up to 50 bp apart and 70 TFBS pairs up to 200 bp apart that score higher than any of the known synergistic pairs. Further investigation of 50 pairs randomly selected from each of these two sets using PubMed queries provided additional supporting evidence from the existing biological literature suggesting TF synergism for these novel pairs.

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Year:  2002        PMID: 12364607      PMCID: PMC140535          DOI: 10.1093/nar/gkf535

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  54 in total

1.  A specific lysine in c-Jun is required for transcriptional repression by E1A and is acetylated by p300.

Authors:  R G Vries; M Prudenziati; C Zwartjes; M Verlaan; E Kalkhoven; A Zantema
Journal:  EMBO J       Date:  2001-11-01       Impact factor: 11.598

2.  Detection of cis-element clusters in higher eukaryotic DNA.

Authors:  M C Frith; U Hansen; Z Weng
Journal:  Bioinformatics       Date:  2001-10       Impact factor: 6.937

3.  Identifying target sites for cooperatively binding factors.

Authors:  D GuhaThakurta; G D Stormo
Journal:  Bioinformatics       Date:  2001-07       Impact factor: 6.937

4.  Identification and functional modelling of DNA sequence elements of transcription.

Authors:  T Werner
Journal:  Brief Bioinform       Date:  2000-11       Impact factor: 11.622

5.  Identifying regulatory networks by combinatorial analysis of promoter elements.

Authors:  Y Pilpel; P Sudarsanam; G M Church
Journal:  Nat Genet       Date:  2001-10       Impact factor: 38.330

6.  Functional promoter modules can be detected by formal models independent of overall nucleotide sequence similarity.

Authors:  A Klingenhoff; K Frech; K Quandt; T Werner
Journal:  Bioinformatics       Date:  1999-03       Impact factor: 6.937

7.  Estrogen regulation of cyclin D1 gene expression in ZR-75 breast cancer cells involves multiple enhancer elements.

Authors:  E Castro-Rivera; I Samudio; S Safe
Journal:  J Biol Chem       Date:  2001-06-15       Impact factor: 5.157

8.  Recognition of NFATp/AP-1 composite elements within genes induced upon the activation of immune cells.

Authors:  A Kel; O Kel-Margoulis; V Babenko; E Wingender
Journal:  J Mol Biol       Date:  1999-05-07       Impact factor: 5.469

9.  Enrichment of regulatory signals in conserved non-coding genomic sequence.

Authors:  S Levy; S Hannenhalli; C Workman
Journal:  Bioinformatics       Date:  2001-10       Impact factor: 6.937

10.  Cloning and characterization of the promoters of the maxiK channel alpha and beta subunits.

Authors:  P D Dhulipala; M I Kotlikoff
Journal:  Biochim Biophys Acta       Date:  1999-02-16
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  41 in total

Review 1.  In silico identification of metazoan transcriptional regulatory regions.

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

2.  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

3.  Distribution of NF-kappaB-binding sites across human chromosome 22.

Authors:  Rebecca Martone; Ghia Euskirchen; Paul Bertone; Stephen Hartman; Thomas E Royce; Nicholas M Luscombe; John L Rinn; F Kenneth Nelson; Perry Miller; Mark Gerstein; Sherman Weissman; Michael Snyder
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-03       Impact factor: 11.205

4.  Distance preferences in the arrangement of binding motifs and hierarchical levels in organization of transcription regulatory information.

Authors:  Vsevolod J Makeev; Alexander P Lifanov; Anna G Nazina; Dmitri A Papatsenko
Journal:  Nucleic Acids Res       Date:  2003-10-15       Impact factor: 16.971

5.  Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes.

Authors:  Gabriel Kreiman
Journal:  Nucleic Acids Res       Date:  2004-05-20       Impact factor: 16.971

6.  Regulatory potential scores from genome-wide three-way alignments of human, mouse, and rat.

Authors:  Diana Kolbe; James Taylor; Laura Elnitski; Pallavi Eswara; Jia Li; Webb Miller; Ross Hardison; Francesca Chiaromonte
Journal:  Genome Res       Date:  2004-04       Impact factor: 9.043

Review 7.  Charting gene regulatory networks: strategies, challenges and perspectives.

Authors:  Gong-Hong Wei; De-Pei Liu; Chih-Chuan Liang
Journal:  Biochem J       Date:  2004-07-01       Impact factor: 3.857

8.  Recent computational approaches to understand gene regulation: mining gene regulation in silico.

Authors:  I Abnizova; T Subhankulova; Wr Gilks
Journal:  Curr Genomics       Date:  2007-04       Impact factor: 2.236

9.  The dilemma of choosing the ideal permutation strategy while estimating statistical significance of genome-wide enrichment.

Authors:  Subhajyoti De; Brent S Pedersen; Katerina Kechris
Journal:  Brief Bioinform       Date:  2013-08-16       Impact factor: 11.622

10.  In silico analysis of promoter regions from cold-induced genes in rice (Oryza sativa L.) and Arabidopsis thaliana reveals the importance of combinatorial control.

Authors:  Angelica Lindlöf; Marcus Bräutigam; Aakash Chawade; Olof Olsson; Björn Olsson
Journal:  Bioinformatics       Date:  2009-03-25       Impact factor: 6.937

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