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Hybrid Dysfunction: Population Genetic and Quantitative Genetic Perspectives

Authors: Benjamin M, Fitzpatrick;

Hybrid Dysfunction: Population Genetic and Quantitative Genetic Perspectives

Abstract

In the wake of seminal work by Dobzhansky and Muller, hybrid dysfunction is usually attributed to incompatible mutations in different genes arising in different populations. This Dobzhansky-Muller (D-M) model is among the most important contributions of theoretical population genetics. Here I make formal connections between the D-M model and the quantitative genetic interpretation of hybrid dysfunction as a combination of additive, dominance, and epistatic effects. Concerns over conceptual differences between the two approaches are unwarranted; the D-M model can be expressed as a special case of the statistical model developed for line-cross analysis in quantitative genetics. This unified theoretical framework encourages application of quantitative genetic methods to the study of speciation.

Related Organizations
Keywords

Genetics, Population, Models, Statistical, Quantitative Trait, Heritable, Models, Genetic, Hybridization, Genetic, Epistasis, Genetic

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
28
Top 10%
Top 10%
Top 10%
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