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Identification of functional links between genes using phylogenetic profiles.

Jie Wu1, Simon Kasif, Charles DeLisi

  • 1Department of Biomedical Engineering, USA Bioinformatics Graduate Program, Boston University, 44 Cummington St., Boston, MA, 02215, USA.

Bioinformatics (Oxford, England)
|August 13, 2003
PubMed
Summary

This study introduces a new phylogenetic profiling method to identify functional gene links. The approach significantly increases the number of detected functional gene relationships, including analogous genes.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Systems Biology

Background:

  • Phylogenetic profiling links genes based on shared occurrence patterns across species.
  • Identical profile requirements limit detection to strong functional links and miss analogous genes.

Purpose of the Study:

  • To develop a relaxed phylogenetic profiling method to identify a broader range of functional gene relationships.
  • To infer gene function with adjustable confidence levels.

Main Methods:

  • Developed a method to assess the probability of chance co-occurrence between gene profiles.
  • Applied the method to 2905 clusters of orthologous genes (COGs) from 44 microbial genomes.
  • Calculated significance based on the probability distribution of chance co-occurrences.

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Main Results:

  • Identified 8935 intrapathway gene pairs at 0.01 significance, a 30-fold increase over identical profile methods.
  • Linked approximately 65,000 interpathway gene pairs, significantly beyond chance expectations.
  • Successfully recovered metabolic networks, including the TCA cycle, demonstrating the method's efficacy.
  • Found functional correlation is symmetric with profile similarity, suggesting detection of analogous genes.

Conclusions:

  • The relaxed phylogenetic profiling method substantially enhances the discovery of functional gene links.
  • The approach effectively identifies both intrapathway and interpathway gene relationships, including analogous genes.
  • This method provides a powerful tool for reconstructing biological networks and inferring gene function.