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Deriving structure from evolution: metazoan segmentation.

Paul François1, Vincent Hakim, Eric D Siggia

  • 1Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 10065, USA.

Molecular Systems Biology
|December 20, 2007
PubMed
Summary
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Evolutionary developmental biology reveals how segmentation evolves. In silico models show regulatory networks can develop segmentation, mimicking insect and vertebrate development through incremental functional additions.

Area of Science:

  • Evolutionary developmental biology
  • Computational biology
  • Systems biology

Background:

  • Segmentation is a fundamental trait in metazoan evolution.
  • Understanding the evolution of segmentation is key to evolutionary developmental biology.
  • Both static (insect) and sequential (vertebrate) segmentation mechanisms are widespread.

Purpose of the Study:

  • To computationally evolve regulatory networks that produce segmentation.
  • To investigate the evolutionary pathways for different modes of segmentation.
  • To explore the potential interconversion between segmentation mechanisms.

Main Methods:

  • In silico evolution of regulatory networks using mutation and selection.
  • Simulating segmentation controlled by static and moving gradients.

Related Experiment Videos

  • Analyzing evolved network structures and their functional properties.

    • Main Results:

    • Static gradient segmentation evolved a cascade of adjacent repressors, similar to gap genes.
    • Sequential segmentation evolved via a constrained path into a 'clock and wavefront' model.
    • The evolved 'clock and wavefront' model incorporates a bistable system driven by an autonomous clock.

    Conclusions:

    • Complex traits like segmentation can evolve through the gradual addition of functions.
    • Early evolutionary stages of different segmentation modes are functionally similar.
    • Simulations suggest a possible evolutionary route for interconverting segmentation mechanisms.