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Evolution. 2001 May;55(5):859-68.

Predicting nuclear gene coalescence from mitochondrial data: the three-times rule.

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  • 1Department of Organismic and Evolutionary Biology, Harvard University, Cambridge Massachusetts 02138, USA. spalumbi@oeb.harvard.edu

Abstract

Coalescence theory predicts when genetic drift at nuclear loci will result in fixation of sequence differences to produce monophyletic gene trees. However, the theory is difficult to apply to particular taxa because it hinges on genetically effective population size, which is generally unknown. Neutral theory also predicts that evolution of monophyly will be four times slower in nuclear than in mitochondrial genes primarily because genetic drift is slower at nuclear loci. Variation in mitochondrial DNA (mtDNA) within and between species has been studied extensively, but can these mtDNA data be used to predict coalescence in nuclear loci? Comparison of neutral theories of coalescence of mitochondrial and nuclear loci suggests a simple rule of thumb. The "three-times rule" states that, on average, most nuclear loci will be monophyletic when the branch length leading to the mtDNA sequences of a species is three times longer than the average mtDNA sequence diversity observed within that species. A test using mitochondrial and nuclear intron data from seven species of whales and dolphins suggests general agreement with predictions of the three-times rule. We define the coalescence ratio as the mitochondrial branch length for a species divided by intraspecific mtDNA diversity. We show that species with high coalescence ratios show nuclear monophyly, whereas species with low ratios have polyphyletic nuclear gene trees. As expected, species with intermediate coalescence ratios show a variety of patterns. Especially at very high or low coalescence ratios, the three-times rule predicts nuclear gene patterns that can help detect the action of selection. The three-times rule may be useful as an empirical benchmark for evaluating evolutionary processes occurring at multiple loci.

PMID:
11430646
[PubMed - indexed for MEDLINE]

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