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Related Experiment Videos

Evolution of spatial expression pattern.

Louise J Johnson1, John F Y Brookfield

  • 1Institute of Genetics, University of Nottingham, Queens Medical Centre, Nottingham NG7 2UH, UK.

Evolution & Development
|February 27, 2004
PubMed
Summary
This summary is machine-generated.

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Gene expression patterns evolve rapidly through transcription factor networks. Network complexity has minimal impact on evolvability, with both simple and complex systems facing evolutionary dead ends.

Area of Science:

  • Developmental biology
  • Evolutionary systems biology
  • Computational biology

Background:

  • Understanding how precise morphological patterns arise from gene expression is a key challenge in developmental biology.
  • Spatial gene expression patterns are established by interactions between transcription factors and DNA targets.
  • The evolution of gene regulatory networks (GRNs) underlying these patterns remains poorly understood.

Purpose of the Study:

  • To investigate the evolution of gene regulatory networks controlling spatial gene expression patterns.
  • To compare the evolvability of simple versus complex gene networks in achieving a target expression pattern.
  • To identify factors influencing the evolutionary trajectories and potential limitations of GRN evolution.

Main Methods:

Related Experiment Videos

  • Simulated the evolution of gene regulatory networks controlling spatial expression patterns along an embryo.
  • Varied network complexity by altering the number of genes and interactions.
  • Tracked the number of mutational events required to reach a target expression pattern.
  • Analyzed the occurrence of evolutionary 'dead ends' and pathways to escape them.

    • Main Results:

    • Gene expression patterns can evolve within a few hundred mutational events.
    • Increasing network complexity had a marginal effect on evolvability.
    • Both simple and complex networks demonstrated wide variation in evolutionary success.
    • Evolutionary 'dead ends' were observed, requiring combinations of deleterious mutations for resolution.

    Conclusions:

    • Evolvability of spatial gene expression patterns is achievable relatively quickly.
    • Network complexity is not the primary driver of evolvability in these systems.
    • Evolutionary constraints and contingent paths, including 'dead ends', are significant features of GRN evolution.