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Related Concept Videos

Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Multiallelic polymorphism maintained under unpredictable migration and selection.

Noël Bonneuil1

  • 1Institut national d'études démographiques, 133, bld Davout, 75980 Paris cedex 20, France. bonneuil@ined.fr

Journal of Theoretical Biology
|October 18, 2011
PubMed
Summary
This summary is machine-generated.

This study explores protected polymorphism dynamics, defining it as C-viability kernel maintenance under changing conditions. It reveals how migration and selection influence polymorphism, offering insights into evolutionary stability.

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Area of Science:

  • Evolutionary Biology
  • Population Genetics
  • Mathematical Biology

Background:

  • Protected polymorphism is crucial for evolutionary adaptation.
  • Maintaining genetic diversity under dynamic environmental pressures is a key challenge.
  • Previous models often simplified time-dependent factors like selection and migration.

Purpose of the Study:

  • To address the problem of protected polymorphism under time-dependent selection and migration.
  • To reformulate this problem as a C-viability problem.
  • To compute the C-viability kernel for varying population structures and allele numbers.

Main Methods:

  • Utilizing the concept of the C-viability kernel to define the maintenance of polymorphism.
  • Modeling protected polymorphism as a C-viability problem.
  • Computing the C-viability kernel for systems with two and three demes and alleles under time-dependent, unpredictable selection and migration.

Main Results:

  • The C-viability kernel computation provides a framework for understanding dynamic polymorphism maintenance.
  • Results delineate the complex trade-offs between population isolation and migration.
  • Relative fitness values are shown to interact with migration patterns in determining polymorphism stability.

Conclusions:

  • Protected polymorphism can be dynamically maintained within defined constraints, even under unpredictable environmental changes.
  • The C-viability approach offers a comprehensive solution to the problem of protected polymorphism in time-varying conditions.
  • This study provides a full dimensionality answer to protected polymorphism in complex, time-varying scenarios.