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Related Experiment Videos

Genome evolution reveals biochemical networks and functional modules.

Christian von Mering1, Evgeny M Zdobnov, Sophia Tsoka

  • 1European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69117 Heidelberg, Germany.

Proceedings of the National Academy of Sciences of the United States of America
|December 16, 2003
PubMed
Summary

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Genomic analysis reveals that gene order changes are constrained by function, enabling the prediction of protein network modules. These modules accurately identify metabolic pathways and predict new functions.

Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • Genome sequencing reveals significant inter-species variability in gene content and arrangement.
  • Gene dynamics (rearrangement, duplication, loss, horizontal transfer) are influenced by selective pressures from gene functional interactions.
  • Genomic constraints underpin comparative genomics techniques for predicting gene functional associations.

Purpose of the Study:

  • To demonstrate that integrating quantitative comparative genomic techniques across numerous genomes can reveal global functional modularity in protein networks.
  • To benchmark predicted modules against known metabolic pathways in Escherichia coli.
  • To identify novel protein and pathway functions through module analysis.

Main Methods:

  • Quantitative integration of comparative genomic techniques, including conserved gene neighborhood, gene fusion events, and phylogenetic distributions.

Related Experiment Videos

  • Application of these integrated methods to a large dataset of genomes.
  • Benchmarking of predicted functional modules against known metabolic pathways in Escherichia coli.

    • Main Results:

    • Detection of global modularity in functional protein networks, extending beyond individual gene function.
    • Accurate clustering of 74% of known metabolic enzymes into modules with high pathway specificity (84%).
    • Identification of hundreds of reliable functional predictions at both protein and pathway levels.

    Conclusions:

    • Functional modularity is an intrinsic feature of protein networks, encoded within present-day genomes.
    • Integrated comparative genomics provides a powerful approach for understanding higher-level functional organization in biological systems.
    • This approach facilitates the prediction of novel gene and pathway functions.