GenomeTrafac: a whole genome resource for the detection of transcription factor binding site clusters associated with conventional and microRNA encoding genes conserved between mouse and human gene orthologs

Nucleic Acids Res. 2007 Jan;35(Database issue):D116-21. doi: 10.1093/nar/gkl1011. Epub 2006 Dec 18.


Transcriptional cis-regulatory control regions frequently are found within non-coding DNA segments conserved across multi-species gene orthologs. Adopting a systematic gene-centric pipeline approach, we report here the development of a web-accessible database resource--GenomeTraFac ( allows genome-wide detection and characterization of compositionally similar cis-clusters that occur in gene orthologs between any two genomes for both microRNA genes as well as conventional RNA-encoding genes. Each ortholog gene pair can be scanned to visualize overall conserved sequence regions, and within these, the relative density of conserved cis-element motif clusters form graph peak structures. The results of these analyses can be mined en masse to identify most frequently represented cis-motifs in a list of genes. The system also provides a method for rapid evaluation and visualization of gene model-consistency between orthologs, and facilitates consideration of the potential impact of sequence variation in conserved non-coding regions to impact complex cis-element structures. Using the mouse and human genomes via the NCBI Reference Sequence database and the Sanger Institute miRBase, the system demonstrated the ability to identify validated transcription factor targets within promoter and distal genomic regulatory regions of both conventional and microRNA genes.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Base Sequence
  • Binding Sites
  • Computer Graphics
  • Conserved Sequence
  • Databases, Nucleic Acid*
  • Genomics
  • Humans
  • Internet
  • Mice
  • MicroRNAs / genetics*
  • Regulatory Elements, Transcriptional*
  • Transcription Factors / metabolism*
  • User-Computer Interface


  • MicroRNAs
  • Transcription Factors