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SUBSTITUTION PROCESSES IN MOLECULAR EVOLUTION. II. EXCHANGEABLE MODELS FROM POPULATION GENETICS.

John H Gillespie1

  • 1Section of Evolution and Ecology, University of California, Davis, California, 95616.

Evolution; International Journal of Organic Evolution
|June 1, 2017
PubMed
Summary
This summary is machine-generated.

Computer simulations reveal that substitution rates are insensitive to selection strength under balancing selection. Origination and fixation processes in molecular evolution exhibit complex patterns, challenging current models.

Keywords:
Molecular evolutionSAS-CFFnatural selectionneutral-allele theoryoverdominancepoint processsubstitution processunderdominance

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Area of Science:

  • Population genetics
  • Molecular evolution
  • Computational biology

Background:

  • Substitution processes in population genetics involve mutation origination and fixation.
  • Existing models combine population genetics (e.g., neutral, overdominance) with gene models (infinite-sites, no-recombination).

Purpose of the Study:

  • To investigate substitution processes using computer simulations.
  • To analyze origination and fixation patterns under various population genetics models.
  • To assess the compatibility of these models with protein evolution.

Main Methods:

  • Computer simulations of substitution processes.
  • Integration of population genetics models (symmetrical-neutral, overdominance, underdominance, TIM, SAS-CFF) with the infinite-sites, no-recombination gene model.
  • Introduction and application of Sawyer processes to model origination events.

Main Results:

  • Substitution rate is largely insensitive to selection strength under strong balancing selection.
  • Origination processes show regularity (overdominance, TIM, SAS-CFF) or clustering (underdominance).
  • Fixation processes are complex, featuring bursts of multiple fixations, and are approximated.

Conclusions:

  • Protein evolution is difficult to reconcile with current models without additional time-scale perturbations.
  • Sawyer processes provide a framework for understanding origination patterns.
  • Fixation processes exhibit more complexity than origination processes.