Genetic load, inbreeding depression, and hybrid vigor covary with population size: An empirical evaluation of theoretical predictions

57Citations
Citations of this article
126Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Reduced population size is thought to have strong consequences for evolutionary processes as it enhances the strength of genetic drift. In its interaction with selection, this is predicted to increase the genetic load, reduce inbreeding depression, and increase hybrid vigor, and in turn affect phenotypic evolution. Several of these predictions have been tested, but comprehensive studies controlling for confounding factors are scarce. Here, we show that populations of Daphnia magna, which vary strongly in genetic diversity, also differ in genetic load, inbreeding depression, and hybrid vigor in a way that strongly supports theoretical predictions. Inbreeding depression is positively correlated with genetic diversity (a proxy for Ne), and genetic load and hybrid vigor are negatively correlated with genetic diversity. These patterns remain significant after accounting for potential confounding factors and indicate that, in small populations, a large proportion of the segregation load is converted into fixed load. Overall, the results suggest that the nature of genetic variation for fitness-related traits differs strongly between large and small populations. This has large consequences for evolutionary processes in natural populations, such as selection on dispersal, breeding systems, ageing, and local adaptation.

Cite

CITATION STYLE

APA

Lohr, J. N., & Haag, C. R. (2015). Genetic load, inbreeding depression, and hybrid vigor covary with population size: An empirical evaluation of theoretical predictions. Evolution, 69(12), 3109–3122. https://doi.org/10.1111/evo.12802

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free