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The infinitesimal model with dominance.

Nicholas H Barton1, Alison M Etheridge2, Amandine Véber3

  • 1Institute of Science and Technology, Am Campus I, A-3400 Klosterneuberg, Austria.

Genetics
|July 14, 2023
PubMed
Summary
This summary is machine-generated.

The infinitesimal model for quantitative trait inheritance is extended to include dominance effects. This robust model, grounded in Mendelian genetics, accurately predicts trait inheritance patterns with increasing numbers of genetic loci.

Keywords:
dominanceinfinitesimal model

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Area of Science:

  • Quantitative genetics
  • Statistical genetics
  • Population genetics

Background:

  • The classical infinitesimal model simplifies quantitative trait inheritance.
  • It assumes genetic components follow a normal distribution around parental averages.
  • Previous work justified this model for additive Mendelian factors.

Purpose of the Study:

  • To extend the infinitesimal model to incorporate dominance effects.
  • To provide a theoretical justification for the model under Mendelian inheritance with dominance.
  • To analyze the distribution of genetic and environmental components in families.

Main Methods:

  • Defining the model using classical quantitative genetics terms.
  • Justifying the model as a limit of Mendelian inheritance as the number of loci (M) approaches infinity.
  • Utilizing probabilities of identity by descent (IBD) for variance component analysis.

Main Results:

  • The infinitesimal model is extended to include first-order dominance effects.
  • Two-, three-, and four-way identities are required for variance component analysis with dominance.
  • Shared and residual genetic components are asymptotically normally distributed with an error of order 1/M.

Conclusions:

  • The infinitesimal model provides a robust framework for quantitative trait inheritance, even with dominance.
  • The model's validity is supported by its derivation from Mendelian inheritance with a large number of loci.
  • The findings have implications for understanding complex trait variation and genetic architecture.