Molecular and quantitative genetic divergence among populations of house mice with known evolutionary histories

Abstract

Evolutionary biologists have long been interested in the processes influencing population differentiation, but separating the effects of neutral and adaptive evolution has been an obstacle for studies of population subdivision. A recently developed method allows tests of whether disruptive (ie, spatially variable) or stabilizing (ie, spatially uniform) selection is influencing phenotypic differentiation among subpopulations. This method, referred to as the F ST vs Q ST comparison, separates the total additive genetic variance into within-and among-population components and evaluates this level of differentiation against a neutral hypothesis. Thus, levels of neutral molecular (F ST ) and quantitative genetic (Q ST ) divergence are compared to evaluate the effects of selection and genetic drift on phenotypic differentiation. Although the utility of such comparisons appears great, its accuracy has not yet been evaluated in populations with known evolutionary histories. In this study, F ST vs Q ST comparisons were evaluated using laboratory populations of house mice with known evolutionary histories. In this model system, the F ST vs Q ST comparisons between the selection groups should reveal quantitative trait differentiation consistent with disruptive selection, while the F ST vs Q ST comparisons among lines within the selection groups should suggest quantitative trait differentiation in agreement with drift. We find that F ST vs Q ST comparisons generally produce the correct evolutionary inference at each level in the population hierarchy. Additionally, we demonstrate that when strong selection is applied between populations Q ST increases relative to Q ST among populations diverging by drift. Finally, we show that the statistical properties of Q ST , a variance component ratio, need further investigation. Heredity (2005) 94, 518-525.

Adaptive Differentiation of Quantitative Traits in the Globally Distributed Weed, Wild Radish (Raphanus raphanistrum)

“…These latter two methods have been found to underestimate the variance of Q ST , while the simulation method (primarily used in our study) or a Bayesian approach produces the most accurate estimates (Morgan et al 2005;O'Hara and Merila 2005). Thus, it may be difficult to detect significant differences among F ST and Q ST based on additive variance without very large sample sizes.…”

The Effects of Dominance, Regular Inbreeding and Sampling Design on QST, an Estimator of Population Differentiation for Quantitative Traits

“…These experimental sampling designs are similar to those used in several studies estimating Q ST o , with total number of individuals at 1000 (e.g., Spitze 1993;Lynch et al 1999;Palo et al 2003;Morgan et al 2005). Often, however, the total number of individuals used to infer Q ST is ,1000 (e.g., Bonnin et al 1996;Petit et al 2001;Steinger et al 2002).…”

Bias and Precision in QST Estimates: Problems and Some Solutions

“…It does, however, estimate the bias. This method was used by Morgan et al (2005), who noted that it gave larger confidence intervals than the nonparametric bootstrap over individuals.…”

“…They are free from distributional assumptions, but it is unclear if they can be used for unbalanced data without modification. Bootstrapping over individuals has been used previously by Spitze (1993), Koskinen et al (2002), and Morgan et al (2005).…”

“…Q ST , then genetic drift is a plausible explanation for the observed degree of differentiation. However, these interpretations are subject to a number of restrictive assumptions (e.g., Merilä and Crnokrak 2001), and other potential problems and pitfalls with these comparisons have also surfaced (e.g., Crnokrak and Merilä 2002;Hendry 2002;Morgan et al 2005).…”