Further observations on the evolution of additive genetic variation with mutation

Area of Science:

• Population Genetics
• Quantitative Genetics
• Evolutionary Biology

Background:

• Neutral quantitative traits are influenced by genes with additive effects, mutation, and genetic drift.
• Comparing mutation models is crucial for understanding genetic variance in populations.

Purpose of the Study:

• To compare the Lynch and Hill (LH) and Cockerham and Tachida (CT) mutation models.
• To evaluate their performance in predicting genetic variances within and between replicate small populations.
• To assess their utility for populations founded from different initial states.

Main Methods:

• Mathematical modeling of genetic variances (within-population, sigma w2, and between-population, sigma b2).
• Analysis of replicate small populations initiated from near-fixed or large equilibrium founder populations.
• Formulation for monoecious populations adapted for separate sexes using effective population size.

Main Results:

• Both LH and CT models yield similar predictions for within-population genetic variance (sigma w2).
• The models diverge in predicting between-population genetic variance (sigma b2) only after extended evolutionary time.
• The CT model accommodates populations founded from large equilibrium populations, providing additive variance insights.
• Both models offer estimations of the average mutation rate.

Conclusions:

• The LH and CT mutation models are largely congruent for short-to-medium evolutionary timescales.
• The CT model offers broader applicability, including large founder populations and insights into additive variance.
• Both models provide valuable information on mutation rates in quantitative genetics studies.