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Strategies for Partitioning Clock Models in Phylogenomic Dating: Application to the Angiosperm Evolutionary Timescale
Evolutionary timescales can be inferred from molecular sequence data using a Bayesian phylogenetic approach. In these methods, the molecular clock is often calibrated using fossil data. The uncertainty in these fossil calibrations is important because it determines the limiting posterior distributio...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5647803/ https://www.ncbi.nlm.nih.gov/pubmed/29036288 http://dx.doi.org/10.1093/gbe/evx198 |
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author | Foster, Charles S.P. Ho, Simon Y.W. |
author_facet | Foster, Charles S.P. Ho, Simon Y.W. |
author_sort | Foster, Charles S.P. |
collection | PubMed |
description | Evolutionary timescales can be inferred from molecular sequence data using a Bayesian phylogenetic approach. In these methods, the molecular clock is often calibrated using fossil data. The uncertainty in these fossil calibrations is important because it determines the limiting posterior distribution for divergence-time estimates as the sequence length tends to infinity. Here, we investigate how the accuracy and precision of Bayesian divergence-time estimates improve with the increased clock-partitioning of genome-scale data into clock-subsets. We focus on a data set comprising plastome-scale sequences of 52 angiosperm taxa. There was little difference among the Bayesian date estimates whether we chose clock-subsets based on patterns of among-lineage rate heterogeneity or relative rates across genes, or by random assignment. Increasing the degree of clock-partitioning usually led to an improvement in the precision of divergence-time estimates, but this increase was asymptotic to a limit presumably imposed by fossil calibrations. Our clock-partitioning approaches yielded highly precise age estimates for several key nodes in the angiosperm phylogeny. For example, when partitioning the data into 20 clock-subsets based on patterns of among-lineage rate heterogeneity, we inferred crown angiosperms to have arisen 198–178 Ma. This demonstrates that judicious clock-partitioning can improve the precision of molecular dating based on phylogenomic data, but the meaning of this increased precision should be considered critically. |
format | Online Article Text |
id | pubmed-5647803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-56478032017-10-25 Strategies for Partitioning Clock Models in Phylogenomic Dating: Application to the Angiosperm Evolutionary Timescale Foster, Charles S.P. Ho, Simon Y.W. Genome Biol Evol Research Article Evolutionary timescales can be inferred from molecular sequence data using a Bayesian phylogenetic approach. In these methods, the molecular clock is often calibrated using fossil data. The uncertainty in these fossil calibrations is important because it determines the limiting posterior distribution for divergence-time estimates as the sequence length tends to infinity. Here, we investigate how the accuracy and precision of Bayesian divergence-time estimates improve with the increased clock-partitioning of genome-scale data into clock-subsets. We focus on a data set comprising plastome-scale sequences of 52 angiosperm taxa. There was little difference among the Bayesian date estimates whether we chose clock-subsets based on patterns of among-lineage rate heterogeneity or relative rates across genes, or by random assignment. Increasing the degree of clock-partitioning usually led to an improvement in the precision of divergence-time estimates, but this increase was asymptotic to a limit presumably imposed by fossil calibrations. Our clock-partitioning approaches yielded highly precise age estimates for several key nodes in the angiosperm phylogeny. For example, when partitioning the data into 20 clock-subsets based on patterns of among-lineage rate heterogeneity, we inferred crown angiosperms to have arisen 198–178 Ma. This demonstrates that judicious clock-partitioning can improve the precision of molecular dating based on phylogenomic data, but the meaning of this increased precision should be considered critically. Oxford University Press 2017-09-25 /pmc/articles/PMC5647803/ /pubmed/29036288 http://dx.doi.org/10.1093/gbe/evx198 Text en © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/4.0/ 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.com |
spellingShingle | Research Article Foster, Charles S.P. Ho, Simon Y.W. Strategies for Partitioning Clock Models in Phylogenomic Dating: Application to the Angiosperm Evolutionary Timescale |
title | Strategies for Partitioning Clock Models in Phylogenomic Dating: Application to the Angiosperm Evolutionary Timescale |
title_full | Strategies for Partitioning Clock Models in Phylogenomic Dating: Application to the Angiosperm Evolutionary Timescale |
title_fullStr | Strategies for Partitioning Clock Models in Phylogenomic Dating: Application to the Angiosperm Evolutionary Timescale |
title_full_unstemmed | Strategies for Partitioning Clock Models in Phylogenomic Dating: Application to the Angiosperm Evolutionary Timescale |
title_short | Strategies for Partitioning Clock Models in Phylogenomic Dating: Application to the Angiosperm Evolutionary Timescale |
title_sort | strategies for partitioning clock models in phylogenomic dating: application to the angiosperm evolutionary timescale |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5647803/ https://www.ncbi.nlm.nih.gov/pubmed/29036288 http://dx.doi.org/10.1093/gbe/evx198 |
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