Literature DB >> 29243391

Bayesian molecular dating: opening up the black box.

Lindell Bromham1, Sebastián Duchêne2,3, Xia Hua1, Andrew M Ritchie3, David A Duchêne1,3, Simon Y W Ho3.   

Abstract

Molecular dating analyses allow evolutionary timescales to be estimated from genetic data, offering an unprecedented capacity for investigating the evolutionary past of all species. These methods require us to make assumptions about the relationship between genetic change and evolutionary time, often referred to as a 'molecular clock'. Although initially regarded with scepticism, molecular dating has now been adopted in many areas of biology. This broad uptake has been due partly to the development of Bayesian methods that allow complex aspects of molecular evolution, such as variation in rates of change across lineages, to be taken into account. But in order to do this, Bayesian dating methods rely on a range of assumptions about the evolutionary process, which vary in their degree of biological realism and empirical support. These assumptions can have substantial impacts on the estimates produced by molecular dating analyses. The aim of this review is to open the 'black box' of Bayesian molecular dating and have a look at the machinery inside. We explain the components of these dating methods, the important decisions that researchers must make in their analyses, and the factors that need to be considered when interpreting results. We illustrate the effects that the choices of different models and priors can have on the outcome of the analysis, and suggest ways to explore these impacts. We describe some major research directions that may improve the reliability of Bayesian dating. The goal of our review is to help researchers to make informed choices when using Bayesian phylogenetic methods to estimate evolutionary rates and timescales.
© 2017 Cambridge Philosophical Society.

Keywords:  evolutionary models; model selection; molecular clocks; phylogenetics; priors; relaxed clocks

Mesh:

Year:  2017        PMID: 29243391     DOI: 10.1111/brv.12390

Source DB:  PubMed          Journal:  Biol Rev Camb Philos Soc        ISSN: 0006-3231


  27 in total

1.  A Simulation-Based Evaluation of Tip-Dating Under the Fossilized Birth-Death Process.

Authors:  Arong Luo; David A Duchêne; Chi Zhang; Chao-Dong Zhu; Simon Y W Ho
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Review 2.  Epidemiological inference from pathogen genomes: A review of phylodynamic models and applications.

Authors:  Leo A Featherstone; Joshua M Zhang; Timothy G Vaughan; Sebastian Duchene
Journal:  Virus Evol       Date:  2022-06-02

3.  Bayesian inference of ancestral dates on bacterial phylogenetic trees.

Authors:  Xavier Didelot; Nicholas J Croucher; Stephen D Bentley; Simon R Harris; Daniel J Wilson
Journal:  Nucleic Acids Res       Date:  2018-12-14       Impact factor: 16.971

4.  Molecular and morphological clocks for estimating evolutionary divergence times.

Authors:  Jose Barba-Montoya; Qiqing Tao; Sudhir Kumar
Journal:  BMC Ecol Evol       Date:  2021-05-12

5.  Divergence-time estimates for hominins provide insight into encephalization and body mass trends in human evolution.

Authors:  Hans P Püschel; Ornella C Bertrand; Joseph E O'Reilly; René Bobe; Thomas A Püschel
Journal:  Nat Ecol Evol       Date:  2021-04-01       Impact factor: 19.100

6.  Phylogenomics indicates the "living fossil" Isoetes diversified in the Cenozoic.

Authors:  Daniel Wood; Guillaume Besnard; David J Beerling; Colin P Osborne; Pascal-Antoine Christin
Journal:  PLoS One       Date:  2020-06-18       Impact factor: 3.240

7.  Phylogenomic history of enigmatic pygmy perches: implications for biogeography, taxonomy and conservation.

Authors:  Sean J Buckley; Fabricius M C B Domingos; Catherine R M Attard; Chris J Brauer; Jonathan Sandoval-Castillo; Ryan Lodge; Peter J Unmack; Luciano B Beheregaray
Journal:  R Soc Open Sci       Date:  2018-06-13       Impact factor: 2.963

8.  A comparison of methods for estimating substitution rates from ancient DNA sequence data.

Authors:  K Jun Tong; David A Duchêne; Sebastián Duchêne; Jemma L Geoghegan; Simon Y W Ho
Journal:  BMC Evol Biol       Date:  2018-05-16       Impact factor: 3.260

9.  Rates and Rocks: Strengths and Weaknesses of Molecular Dating Methods.

Authors:  Stéphane Guindon
Journal:  Front Genet       Date:  2020-05-27       Impact factor: 4.599

10.  Global Rate Variation in Bony Vertebrates.

Authors:  Naoko Takezaki
Journal:  Genome Biol Evol       Date:  2018-07-01       Impact factor: 3.416

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