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Measuring Microbial Mutation Rates with the Fluctuation Assay
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Published on: November 28, 2019

Optimal mutation rates in dynamic environments: The Eigen model.

Mark Ancliff1, Jeong-Man Park

  • 1Department of Physics, The Catholic University of Korea, Bucheon, Gyeonggi-do, Korea.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 28, 2010
PubMed
Summary
This summary is machine-generated.

In dynamic environments, this study identifies survival mutation rates for the Eigen quasispecies model. The optimal mutation rate for population growth is lower than in the Crow-Kimura model, suggesting adaptive advantages.

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Area of Science:

  • Evolutionary dynamics
  • Theoretical biology
  • Population genetics

Background:

  • The Eigen quasispecies model describes evolution in molecular systems.
  • Dynamic environments pose challenges to species survival and adaptation.
  • Understanding mutation rate optima is crucial for evolutionary theory.

Purpose of the Study:

  • To analyze the Eigen quasispecies model under a dynamic, sharp-peak fitness environment.
  • To determine the critical mutation rates for quasispecies survival.
  • To calculate the optimal mutation rate for maximizing population growth.

Main Methods:

  • Mathematical modeling of the Eigen quasispecies model.
  • Analysis of an environment with periodically shifting fitness peaks.
  • Estimation of stationary states and population dynamics.

Main Results:

  • An asymptotic stationary state was found where population changes mirror environmental shifts.
  • Maximum and minimum mutation rates for quasispecies survival were estimated.
  • The optimal mutation rate in the Eigen model was found to be lower than in the Crow-Kimura model.

Conclusions:

  • The Eigen model predicts specific mutation rate ranges for survival in fluctuating environments.
  • A lower optimal mutation rate in the Eigen model compared to Crow-Kimura suggests different adaptive strategies.
  • Parallel mutation-replication processes may confer advantages in dynamic environments.