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dc.creatorTao, Q
dc.creatorBarba-Montoya, J
dc.creatorHuuki, LA
dc.creatorDurnan, MK
dc.creatorKumar, S
dc.date.accessioned2020-12-15T21:26:09Z
dc.date.available2020-12-15T21:26:09Z
dc.date.issued2020-06-01
dc.identifier.issn0737-4038
dc.identifier.issn1537-1719
dc.identifier.doihttp://dx.doi.org/10.34944/dspace/4475
dc.identifier.other32119075 (pubmed)
dc.identifier.urihttp://hdl.handle.net/20.500.12613/4493
dc.description.abstract© The Author(s) 2020. The conventional wisdom in molecular evolution is to apply parameter-rich models of nucleotide and amino acid substitutions for estimating divergence times. However, the actual extent of the difference between time estimates produced by highly complex models compared with those from simple models is yet to be quantified for contemporary data sets that frequently contain sequences from many species and genes. In a reanalysis of many large multispecies alignments from diverse groups of taxa, we found that the use of the simplest models can produce divergence time estimates and credibility intervals similar to those obtained from the complex models applied in the original studies. This result is surprising because the use of simple models underestimates sequence divergence for all the data sets analyzed. We found three fundamental reasons for the observed robustness of time estimates to model complexity in many practical data sets. First, the estimates of branch lengths and node-to-tip distances under the simplest model show an approximately linear relationship with those produced by using the most complex models applied on data sets with many sequences. Second, relaxed clock methods automatically adjust rates on branches that experience considerable underestimation of sequence divergences, resulting in time estimates that are similar to those from complex models. And, third, the inclusion of even a few good calibrations in an analysis can reduce the difference in time estimates from simple and complex models. The robustness of time estimates to model complexity in these empirical data analyses is encouraging, because all phylogenomics studies use statistical models that are oversimplified descriptions of actual evolutionary substitution processes.
dc.format.extent1819-1831
dc.language.isoen
dc.relation.haspartMolecular Biology and Evolution
dc.relation.isreferencedbyOxford University Press (OUP)
dc.rightsCC BY
dc.subjectmolecular dating
dc.subjectsubstitution model
dc.subjectrelaxed clock
dc.subjectphylogenomics
dc.subjectRelTime
dc.titleRelative efficiencies of simple and complex substitution models in estimating divergence times in phylogenomics
dc.typeArticle
dc.type.genreJournal Article
dc.relation.doi10.1093/molbev/msaa049
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
dc.creator.orcidKumar, Sudhir|0000-0002-9918-8212
dc.date.updated2020-12-15T21:26:05Z
refterms.dateFOA2020-12-15T21:26:10Z


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