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Related Experiment Videos

CREME: a framework for identifying cis-regulatory modules in human-mouse conserved segments.

Roded Sharan1, Ivan Ovcharenko, Asa Ben-Hur

  • 1International Computer Science Institute, 1947 Center St., Suite 600, Berkeley CA-94704, USA. roded@icsi.berkeley.edu

Bioinformatics (Oxford, England)
|July 12, 2003
PubMed
Summary

This study introduces CREME, a computational framework to identify clusters of transcription factor binding sites (cis-regulatory modules) in gene promoters. The tool helps uncover regulatory mechanisms controlling gene expression, particularly for cell cycle and stress response genes.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Transcription factor binding to regulatory sequences controls gene transcription.
  • Genes are often regulated by cooperative transcription factors organized in modular binding sites.
  • Understanding these cis-regulatory modules is key to deciphering gene regulation.

Purpose of the Study:

  • To develop a computational framework for identifying recurrent cis-regulatory modules in gene promoters.
  • To statistically evaluate the significance of these modules and their co-occurrences.
  • To apply this framework to identify regulatory modules in human and mouse genes.

Main Methods:

  • Utilized a database of known transcription factor binding site motifs and their genomic locations.

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  • Developed statistical tests to identify motifs with significant frequency differences in selected promoters compared to a background set.
  • Implemented a hashing algorithm to detect co-occurring motif clusters and novel statistical scores for significance evaluation.
  • Integrated methods into the CREME software suite with a visualization browser.

    • Main Results:

    • Applied CREME to human-mouse conserved promoter segments, focusing on cell cycle and stress response genes.
    • Identified cis-regulatory modules within these gene sets.
    • Validated biological significance by testing for gene co-expression and functional similarity.
    • Found that 5 out of 7 identified gene sets for cell cycle regulation were coherently expressed.
    • Observed that 4 out of 6 detected sets in stress response genes belonged to well-defined functional sub-categories.

    Conclusions:

    • The CREME framework effectively identifies statistically significant cis-regulatory modules.
    • The identified modules are biologically relevant, correlating with gene co-expression and shared function.
    • This approach advances the understanding of gene regulation, particularly for complex processes like cell cycle control and stress response.