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Predicting Response to Selection on a Quantitative Trait: A Comparison between Models for Mixed-mating Populations

✍ Scribed by JOHN K. KELLY; SCOTT WILLIAMSON


Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
258 KB
Volume
207
Category
Article
ISSN
0022-5193

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✦ Synopsis


Two di!erent theoretical frameworks have been developed to predict response to selection in a mixed mating population (in which reproduction occurs by a mixture of outcrossing and self-fertilization). The genotypic covariance model (GCM) and the structured linear model (SLM) rely on the same assumptions regarding quantitative trait inheritance, but use di!erent genetic summary statistics. Here, we demonstrate the algebraic relationships between the various genetic metrics used in each theory. This is accomplished by reformulating the GCM in terms of the Wright}Kempthorne equation. We use stochastic simulations to investigate the relative accuracy of each theory for a range of sel"ng rates. The SLM is generally more accurate than the GCM, the most pronounced di!erences emerging in simulations with inbreeding depression for "tness. In fact, with strong inbreeding depression and high sel"ng rates, evolution can occur opposite the direction predicted by the GCM. The simulations also indicate that direct application of random mating models to partially sel"ng populations can produce very inaccurate predictions if quantitative trait loci exhibit dominance.