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dc.contributor.authorBletsa, Magda
dc.contributor.authorSuchard, Marc A
dc.contributor.authorJi, Xiang
dc.contributor.authorGryseels, Sophie
dc.contributor.authorVrancken, Bram
dc.contributor.authorBaele, Guy
dc.contributor.authorWorobey, Michael
dc.contributor.authorLemey, Philippe
dc.date.accessioned2020-01-31T19:20:56Z
dc.date.available2020-01-31T19:20:56Z
dc.date.issued2019-09-05
dc.identifier.citationMagda Bletsa, Marc A Suchard, Xiang Ji, Sophie Gryseels, Bram Vrancken, Guy Baele, Michael Worobey, Philippe Lemey, Divergence dating using mixed effects clock modelling: An application to HIV-1, Virus Evolution, Volume 5, Issue 2, July 2019, vez036, https://doi.org/10.1093/ve/vez036en_US
dc.identifier.issn2057-1577
dc.identifier.pmid31720009
dc.identifier.doi10.1093/ve/vez036
dc.identifier.urihttp://hdl.handle.net/10150/636791
dc.description.abstractThe need to estimate divergence times in evolutionary histories in the presence of various sources of substitution rate variation has stimulated a rich development of relaxed molecular clock models. Viral evolutionary studies frequently adopt an uncorrelated clock model as a generic relaxed molecular clock process, but this may impose considerable estimation bias if discrete rate variation exists among clades or lineages. For HIV-1 group M, rate variation among subtypes has been shown to result in inconsistencies in time to the most recent common ancestor estimation. Although this calls into question the adequacy of available molecular dating methods, no solution to this problem has been offered so far. Here, we investigate the use of mixed effects molecular clock models, which combine both fixed and random effects in the evolutionary rate, to estimate divergence times. Using simulation, we demonstrate that this model outperforms existing molecular clock models in a Bayesian framework for estimating time-measured phylogenies in the presence of mixed sources of rate variation, while also maintaining good performance in simpler scenarios. By analysing a comprehensive HIV-1 group M complete genome data set we confirm considerable rate variation among subtypes that is not adequately modelled by uncorrelated relaxed clock models. The mixed effects clock model can accommodate this rate variation and results in a time to the most recent common ancestor of HIV-1 group M of 1920 (1915–25), which is only slightly earlier than the uncorrelated relaxed clock estimate for the same data set. The use of complete genome data appears to have a more profound impact than the molecular clock model because it reduces the credible intervals by 50 per cent relative to similar estimates based on short envelope gene sequences.en_US
dc.description.sponsorshipEuropean Research Council under the European UnionEuropean Research Council (ERC) [725422-ReservoirDOCS]; Wellcome TrustWellcome Trust [206298/Z/17/Z]; Special Research Fund, KU Leuven ('Bijzonder Onderzoeksfonds', KU Leuven) [OT/14/115]; Research Foundation - Flanders ('Fonds voor Wetenschappelijk Onderzoek - Vlaanderen')FWO [G066215N, G0D5117N, G0B9317N]; NSFNational Science Foundation (NSF) [DMS 1264153]; NIHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 AI107034, U19 AI135995]; FWOFWO; Interne Fondsen KU Leuven/Internal Funds KU Leuven [C14/18/094]; NIH/NIAIDUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Allergy & Infectious Diseases (NIAID) [R01AI084691]; David and Lucile Packard FoundationThe David & Lucile Packard Foundationen_US
dc.language.isoenen_US
dc.publisherOXFORD UNIV PRESSen_US
dc.rightsCopyright © The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.comen_US
dc.subjectBayesian inferenceen_US
dc.subjectHIVen_US
dc.subjectdivergence timeen_US
dc.subjectmixed effectsen_US
dc.subjectmolecular clocken_US
dc.titleDivergence dating using mixed effects clock modelling: An application to HIV-1en_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Dept Ecol & Evolutionary Biolen_US
dc.identifier.journalVIRUS EVOLUTIONen_US
dc.description.noteOpen access journalen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
dc.source.journaltitleVirus evolution
dc.source.volume5
dc.source.issue2
dc.source.beginpagevez036
dc.source.endpage
refterms.dateFOA2020-01-31T19:20:57Z
dc.source.countryEngland


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