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Distinguishing between convergent evolution and violation of the molecular clock for three taxa

Mitchell, JD, Sumner, JG ORCID: 0000-0001-9820-0235 and Holland, BR ORCID: 0000-0002-4628-7938 2018 , 'Distinguishing between convergent evolution and violation of the molecular clock for three taxa' , Systematic Biology , pp. 1-11 , doi: https://doi.org/10.1093/sysbio/syy038.

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Abstract

We give a non-technical introduction to convergence–divergence models, a new modeling approach for phylogenetic data that allows for the usual divergence of lineages after lineage-splitting but also allows for taxa to converge, i.e. become more similar over time. By examining the 3-taxon case in some detail, we illustrate that phylogeneticists have been “spoiled” in the sense of not having to think about the structural parameters in their models by virtue of the strong assumption that evolution is tree-like. We show that there are not always good statistical reasons to prefer the usual class of tree-like models over more general convergence–divergence models. Specifically, we show many 3-taxon data sets can be equally well explained by supposing violation of the molecular clock due to change in the rate of evolution along different edges, or by keeping the assumption of a constant rate of evolution but instead assuming that evolution is not a purely divergent process. Given the abundance of evidence that evolution is not strictly tree-like, our discussion is an illustration that as phylogeneticists we need to think clearly about the structural form of the models we use. For cases with four taxa, we show that there will be far greater ability to distinguish models with convergence from non-clock-like tree models.

Item Type: Article
Authors/Creators:Mitchell, JD and Sumner, JG and Holland, BR
Keywords: akaike information criterion, convergence–divergence models, distinguishability, identifiability, likelihood, molecular clock, phylogeny
Journal or Publication Title: Systematic Biology
Publisher: Taylor & Francis Inc
ISSN: 1063-5157
DOI / ID Number: https://doi.org/10.1093/sysbio/syy038
Copyright Information:

Copyright 2018 The Authors

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