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Multinomial-sampling models for random genetic drift

T Nagylaki1

  • 1Department of Ecology and Evolution, University of Chicago, Illinois 60637, USA.

Genetics
|February 1, 1997
PubMed
Summary
This summary is machine-generated.

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This study presents three models for multinomial genotype sampling in finite populations. Findings show multinomial genotype sampling generally differs from multinomial gene sampling, challenging the Wright-Fisher model in some cases.

Area of Science:

  • Population genetics
  • Mathematical biology
  • Evolutionary genetics

Background:

  • Finite population models are crucial for understanding genetic drift.
  • The Wright-Fisher model is a standard but has limitations.
  • Multinomial sampling of genotypes is biologically relevant.

Purpose of the Study:

  • To derive and compare models of multinomial genotype sampling.
  • To investigate the relationship between genotype and gene sampling.
  • To evaluate the accuracy of the Wright-Fisher model under different sampling schemes.

Main Methods:

  • Derivation of three distinct models for multinomial genotype sampling.
  • Analysis of discrete, nonoverlapping generations with random mating.
  • Consideration of monoecious and dioecious populations, with autosomal or X-linked loci.

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  • Inclusion of arbitrary mutation and viability selection, excluding fertility differences.

    • Main Results:

    • Multinomial genotype sampling does not generally reduce to multinomial gene sampling.
    • In monoecious populations, the Wright-Fisher model is recovered only with multiplicative viabilities.
    • In dioecious populations, this reduction does not occur even with pure random drift.
    • The Wright-Fisher model is often a good approximation for large populations despite potential biological inaccuracies.

    Conclusions:

    • The assumption of multinomial gene sampling (Wright-Fisher) may be biologically unrealistic.
    • Distinct derivations highlight the complexities of genetic drift and sampling.
    • Careful consideration of sampling mechanisms is needed for accurate population genetic modeling.