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Mello B , Tao Q , Barba-Montoya J , Kumar S
Molecular dating for phylogenies containing a mix of populations and species by using Bayesian and RelTime approaches
Mol Ecol Resour. 2021 Jan;21(1) :122-136
PMID: 32881388 PMCID: PMC8152102 URL: https://www.ncbi.nlm.nih.gov/pubmed/32881388
AbstractSimultaneous molecular dating of population and species divergences is essential in many biological investigations, including phylogeography, phylodynamics and species delimitation studies. In these investigations, multiple sequence alignments consist of both intra- and interspecies samples (mixed samples). As a result, the phylogenetic trees contain interspecies, interpopulation and within-population divergences. Bayesian relaxed clock methods are often employed in these analyses, but they assume the same tree prior for both inter- and intraspecies branching processes and require specification of a clock model for branch rates (independent vs. autocorrelated rates models). We evaluated the impact of a single tree prior on Bayesian divergence time estimates by analysing computer-simulated data sets. We also examined the effect of the assumption of independence of evolutionary rate variation among branches when the branch rates are autocorrelated. Bayesian approach with coalescent tree priors generally produced excellent molecular dates and highest posterior densities with high coverage probabilities. We also evaluated the performance of a non-Bayesian method, RelTime, which does not require the specification of a tree prior or a clock model. RelTime's performance was similar to that of the Bayesian approach, suggesting that it is also suitable to analyse data sets containing both populations and species variation when its computational efficiency is needed.
Notes1755-0998 Mello, Beatriz Orcid: 0000-0002-4511-2757 Tao, Qiqing Barba-Montoya, Jose Kumar, Sudhir Orcid: 0000-0002-9918-8212 233920/2014-5/Brazilian Research Council (CNPq)/ 409152/2018-8/Brazilian Research Council (CNPq)/ NNX16AJ30G/NASA/NASA/United States 1661218/Division of Biological Infrastructure/ 1932765/Division of Biological Infrastructure/ GM0126567-02/GM/NIGMS NIH HHS/United States Journal Article England Mol Ecol Resour. 2021 Jan;21(1):122-136. doi: 10.1111/1755-0998.13249. Epub 2020 Sep 16.