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Fluctuating selection models and McDonald-Kreitman type analyses.

Toni I Gossmann1, David Waxman2, Adam Eyre-Walker3

  • 1School of Life Sciences, University of Sussex, Brighton, United Kingdom ; Department of Animal and Plant Sciences, University of Sheffield, Sheffield, United Kingdom.

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Summary
This summary is machine-generated.

Environmental changes cause fluctuating selection, impacting adaptive evolution studies. Fluctuating selection provides genuine evidence of adaptation, though rates may be underestimated by current methods.

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Area of Science:

  • Population genetics
  • Evolutionary biology
  • Molecular evolution

Background:

  • Environmental changes can alter selection pressures on mutations over time.
  • Population genetic models often assume constant selection, which may not reflect reality.
  • McDonald-Kreitman (MK) style approaches are used to quantify adaptive evolution.

Purpose of the Study:

  • To investigate the impact of fluctuating selection on quantifying adaptive evolution.
  • To assess how fluctuating selection affects MK-style analyses.
  • To determine if fluctuating selection can mimic signals of adaptive evolution.

Main Methods:

  • Simulations of population genetic models with fluctuating selection.
  • Application of MK-style analytical frameworks to simulated data.
  • Comparison of results under fluctuating versus constant selection models.

Main Results:

  • Fluctuating selection can generate apparent evidence of adaptive evolution, even with zero average selection.
  • Mutations experiencing fluctuating selection tend to be positively selected on average.
  • MK-type approaches may underestimate the rate of adaptive evolution under fluctuating selection.

Conclusions:

  • The evidence for adaptive evolution detected under fluctuating selection is genuine, as advantageous mutations tend to fix.
  • Fluctuating selection models provide a more realistic framework for studying adaptation.
  • Current methods may require adjustments to accurately estimate adaptive evolution rates in dynamic environments.