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Mutation, Gene Flow, and Genetic Drift01:09

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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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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
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Updated: Mar 11, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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What drives parallel evolution?: How population size and mutational variation contribute to repeated evolution.

Susan F Bailey1, François Blanquart2, Thomas Bataillon1

  • 1Bioinformatics Research Centre, University of Aarhus, Aarhus, Denmark.

Bioessays : News and Reviews in Molecular, Cellular and Developmental Biology
|November 19, 2016
PubMed
Summary

Parallel evolution, the repeated evolution of traits, is influenced by population size. Mutation rate variation across the genome also significantly impacts parallel evolution, not just selection alone.

Keywords:
bacteriaevolve and resequence experimentexperimental evolutionmutationparallel evolutionselection yeast

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Area of Science:

  • Evolutionary Biology
  • Genetics
  • Microbial Evolution

Background:

  • Parallel evolution describes the independent evolution of similar traits in distinct populations.
  • Understanding the genetic underpinnings of parallel evolution is crucial for evolutionary theory.

Purpose of the Study:

  • To dissect the gene-level drivers of parallel evolution using experimental evolution.
  • To quantify the contributions of mutation and selection heterogeneity to parallel evolution.

Main Methods:

  • Evolve-and-resequence experiments were conducted with bacteria and yeast.
  • A meta-analysis was performed on existing data.
  • A modeling approach was developed to estimate heterogeneity contributions.

Main Results:

  • Parallel evolution is often rare, but its probability increases with population size.
  • Mutation heterogeneity contributes significantly (10-45%) to variation in parallel evolution.
  • Selection alone does not fully explain parallel evolution; mutation rate variation is key.

Conclusions:

  • Parallel evolution is a complex phenomenon driven by both selection and mutation rate heterogeneity.
  • Future theories of parallel evolution must integrate genomic mutation rate information.
  • This study provides an empirically grounded framework for studying parallel evolution.