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Molecular evolution in large genetic networks: does connectivity equal constraint?

Matthew W Hahn1, Gavin C Conant, Andreas Wagner

  • 1Department of Biology, Box 90338, Duke University, Durham, NC 27708, USA. mwhahn@ ucdavis.edu

Journal of Molecular Evolution
|March 26, 2004
PubMed
Summary
This summary is machine-generated.

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Power-law distributions in genetic networks may not confer robustness against mutations. Highly connected proteins in E. coli and yeast networks show little correlation with evolutionary constraints, challenging previous hypotheses.

Area of Science:

  • Systems Biology
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Genetic networks exhibit power-law distributions in protein interaction numbers.
  • This broad-tailed distribution has been hypothesized to provide robustness against mutations.
  • Highly connected proteins are predicted to be under stronger evolutionary constraint.

Purpose of the Study:

  • To evaluate the hypothesis that broad-tailed distributions in genetic networks confer mutational robustness.
  • To test the prediction that highly connected proteins experience more severe evolutionary constraints.

Main Methods:

  • Analysis of two genetic networks: E. coli core intermediary metabolism and yeast protein-interaction network.
  • Correlation analysis between protein connectivity and evolutionary rate (amino acid substitution rates).

Related Experiment Videos

  • Function-specific analysis of correlations within the yeast protein-interaction network.

    • Main Results:

    • No significant correlation found between protein connectivity and evolutionary rate in the E. coli metabolic network.
    • Only a weak correlation observed in the yeast protein-interaction network.
    • Significant correlations in yeast were function-specific, primarily involving cell cycle and transcription genes.

    Conclusions:

    • The hypothesis that power-laws in cellular networks confer mutational robustness is not supported by the findings.
    • Highly connected proteins can tolerate amino acid substitutions similarly to other proteins.
    • Conflicting results in literature may stem from differences in datasets and reference taxa used.