Neutral Genetic Diversity in Mixed Mating Systems

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<jats:p>Background/Objectives: Systems of reproduction differ with respect to the magnitude of neutral genetic diversity maintained in a population. In particular, the partitioning of reproductive organisms into mating types and regular inbreeding have long been recognized as key factors that influence effective population number. Here, a range of reproductive systems are compared with respect to the maintenance of neutral genetic diversity. This study addresses full gonochorism, full hermaphroditism, androdioecy (male and hermaphroditic reproductives), and gynodioecy (female and hermaphroditic reproductives). Methods: Coalescence theory is used to determine the level of diversity maintained under each mating system considered. Results: For each mating system, the nature of the dependence of the level of neutral diversity on inbreeding depression, sex-specific viability, and other factors is described. In particular, the models account for the effects of sex-specific viability on the evolutionarily stable sex ratio and the collective contribution of each mating type (sex) to the offspring generation. Conclusions: Within the context of conservation biology, population genetic and quantitative genetic theory has addressed the determination of the target minimum effective population size. In contrast, this study proposes and explores a summary statistic (a ratio of effective numbers) as a means of characterizing the context in which evolution occurs.</jats:p>

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10.3390/genes15121635

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Uyenoyama, Marcy K (n.d.). Neutral Genetic Diversity in Mixed Mating Systems. Genes, 15(12). pp. 1635–1635. 10.3390/genes15121635 Retrieved from https://hdl.handle.net/10161/31815.

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Scholars@Duke

Uyenoyama

Marcy K. Uyenoyama

Professor of Biology

Marcy Uyenoyama studies mechanisms of evolutionary change at the molecular and population levels. Among the questions under study include the prediction and detection of the effects of natural selection on genomic structure. A major area of research addresses the development of maximum-likelihood and Bayesian methods for inferring evolutionary processes from the pattern of molecular variation. Evolutionary processes currently under study include characterization of population structure across genomes.


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