Literature DB >> 12603036

Whole genome human/mouse phylogenetic footprinting of potential transcription regulatory signals.

E Cheremushkin1, A Kel.   

Abstract

UNLABELLED: Phylogenetic footprinting is an efficient approach for revealing potential transcription factor binding sites in promoter sequences. The idea is based on an assumption that functional sites in promoters should evolve much slower then other regions that do not bear any conservative function. Therefore, potential transcription factor (TF) binding sites that are found in the evolutionally conservative regions of promoters have more chances to be considered as "real" sites. The most difficult step of the phylogenetic footprinting is alignment of promoter sequences between different organisms (fe. human and mouse). The conventional alignment methods often can not align promoters due to the high level of sequence variability. We have developed a new alignment method that takes into account similarity in distribution of potential binding sites (motif-based alignment). This method has been used effectively for promoter alignment and for revealing new potential binding sites for various transcription factors. We made a systematic phylogenetic footprinting of human/mouse conserved non-coding sequences (CNS). 60 thousand potential binding sites were revealed in human and mouse genomes. We have developed a database of the predicted potential TF binding sites. AVAILABILITY: http://compel.bionet.nsc.ru/FunSite/footprint/; www.gene-regulation.com/.

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Year:  2003        PMID: 12603036     DOI: 10.1142/9789812776303_0028

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


  4 in total

1.  CONREAL: conserved regulatory elements anchored alignment algorithm for identification of transcription factor binding sites by phylogenetic footprinting.

Authors:  Eugene Berezikov; Victor Guryev; Ronald H A Plasterk; Edwin Cuppen
Journal:  Genome Res       Date:  2003-12-12       Impact factor: 9.043

2.  The mouse kinome: discovery and comparative genomics of all mouse protein kinases.

Authors:  Sean Caenepeel; Glen Charydczak; Sucha Sudarsanam; Tony Hunter; Gerard Manning
Journal:  Proc Natl Acad Sci U S A       Date:  2004-08-02       Impact factor: 11.205

3.  Prediction of protein-DNA interactions of transcription factors linking proteomics and transcriptomics data.

Authors:  Yu Kondrakhin; T Valeev; R Sharipov; I Yevshin; F Kolpakov; A Kel
Journal:  EuPA Open Proteom       Date:  2016-09-15

4.  Genome wide prediction of HNF4alpha functional binding sites by the use of local and global sequence context.

Authors:  Alexander E Kel; Monika Niehof; Volker Matys; Rüdiger Zemlin; Jürgen Borlak
Journal:  Genome Biol       Date:  2008-02-21       Impact factor: 13.583

  4 in total

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