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Related Experiment Videos

Identification of putative plant cold responsive regulatory elements by gene expression profiling and a pattern

Joel Kreps1, Paul Budworth, Steve Goff

  • 1Torrey Mesa Research Institute, 3115 Merryfield Row, San Diego, CA 92121, USA.

Plant Biotechnology Journal
|December 15, 2006
PubMed
Summary
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A new algorithm, GBSSR, identifies gene regulatory elements by analyzing gene expression data. It finds over-represented DNA sequences in co-expressed genes, aiding in understanding gene regulation and identifying novel elements.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Understanding gene regulation is crucial for deciphering complex biological processes.
  • Identifying cis-regulatory elements is key to understanding gene expression control.
  • Existing methods may rely on statistical assumptions or be computationally intensive.

Purpose of the Study:

  • To develop a novel algorithm, GBSSR, for identifying putative cis-regulatory elements.
  • To analyze co-expressed gene groups from gene chip expression profiling.
  • To facilitate the study of transcriptional factors, quantitative trait loci, and gene regulatory networks.

Main Methods:

  • Developed the GBSSR (Gene Bootstrap Sequence Sampling and Retrieval) algorithm.
  • Employed extensive bootstrap sampling across a whole genome's promoters.

Related Experiment Videos

  • Enumerated frequency distributions of 6-15 bp DNA strings without statistical assumptions.
  • Applied the algorithm to analyze co-expressed gene groups.

    • Main Results:

    • Identified known cold-responsive elements in a plant system as top candidates.
    • Discovered potentially novel cis-regulatory elements.
    • Demonstrated the algorithm's ability to find over-represented sequences in co-expressed gene sets.
    • A typical analysis of 40 genes takes approximately 7 days on a 32-CPU Linux cluster.

    Conclusions:

    • GBSSR is an effective tool for discovering cis-regulatory elements from gene expression data.
    • The algorithm aids in understanding gene regulatory networks and identifying novel regulatory sequences.
    • GBSSR offers a statistically assumption-free approach to sequence analysis in genomics.