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Related Experiment Videos

The mutation matrix and the evolution of evolvability.

Adam G Jones1, Stevan J Arnold, Reinhard Bürger

  • 1Department of Biology, 3258 TAMU, Texas A&M University, College Station, Texas 77843, USA. agjones@tamu.edu

Evolution; International Journal of Organic Evolution
|April 19, 2007
PubMed
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Evolvability, the capacity for evolution, can itself evolve. Quantitative genetics shows that the mutational correlation (r(mu)) evolves, influencing genetic constraints and stabilizing the G-matrix over time.

Area of Science:

  • Evolutionary Biology
  • Quantitative Genetics

Background:

  • Evolvability is a central concept in evolutionary theory, unifying diverse disciplines.
  • Quantitative genetics offers a framework to study evolvability using the G-matrix (standing genetic variance) and M-matrix (mutation effects).
  • The G-matrix governs immediate response to selection, while the M-matrix influences the production of adaptive variants.

Purpose of the Study:

  • To explore the evolution of evolvability by analyzing the evolution of the mutational correlation, r(mu).
  • To investigate how the M-matrix evolves and its impact on genetic constraints and G-matrix stability.
  • To understand the interplay between selection, mutation, and genetic drift in shaping evolvability.

Main Methods:

  • Analytical theory and simulation-based models were employed.

Related Experiment Videos

  • A diploid, sexually reproducing population of finite size under stabilizing selection on a two-trait phenotype was modeled.
  • The mutational correlation (r(mu)) was treated as a quantitative trait influenced by multiple additive loci.

    • Main Results:

    • The mutational correlation (r(mu)) evolves in response to selection, despite not directly affecting fitness.
    • Mutational variance shows a weak tendency to align the M-matrix with the adaptive landscape but is affected by genetic drift.
    • Disruptive selection favors extreme values of r(mu) (-1 and +1), though drift counteracts this tendency.

    Conclusions:

    • Evolvability can evolve in natural systems, aligning the G-matrix, M-matrix, and adaptive landscape.
    • An evolving M-matrix generally enhances the stability of the G-matrix, suggesting previous studies may overestimate G-matrix instability.
    • Evolutionary processes can lead to increased stability of the G-matrix over time.