Bayesian Estimation of Species Divergence Times Using Correlated Quantitative Characters

被引:18
|
作者
Alvarez-Carretero, Sandra [1 ]
Goswami, Anjali [2 ,3 ]
Yang, Ziheng [2 ]
Dos Reis, Mario [1 ]
机构
[1] Queen Mary Univ London, Sch Biol & Chem Sci, Mile End Rd, London E1 4NS, England
[2] UCL, Dept Genet Evolut & Environm, Gower St, London WC1E 6BT, England
[3] Nat Hist Museum, Dept Life Sci, Cromwell Rd, London SW7 5DB, England
基金
英国生物技术与生命科学研究理事会; 美国国家科学基金会;
关键词
Bayesian inference; continuous morphological characters; divergence times; geometric morphometrics; molecular clock; phylogeny; Procrustes alignment; PHYLOGENETIC ANALYSIS; MOLECULAR CLOCK; LIKELIHOOD-ESTIMATION; EVOLUTIONARY TREES; TERMINAL TAXA; R PACKAGE; FOSSIL; CARNIVORA; DISCRETE; MODELS;
D O I
10.1093/sysbio/syz015
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Discrete morphological data have been widely used to study species evolution, but the use of quantitative (or continuous) morphological characters is less common. Here, we implement a Bayesian method to estimate species divergence times using quantitative characters. Quantitative character evolution is modeled using Brownian diffusion with character correlation and character variation within populations. Through simulations, we demonstrate that ignoring the population variation (or population "noise") and the correlation among characters leads to biased estimates of divergence times and rate, especially if the correlation and population noise are high. We apply our new method to the analysis of quantitative characters (cranium landmarks) and molecular data from carnivoran mammals. Our results show that time estimates are affected by whether the correlations and population noise are accounted for or ignored in the analysis. The estimates are also affected by the type of data analyzed, with analyses of morphological characters only, molecular data only, or a combination of both; showing noticeable differences among the time estimates. Rate variation of morphological characters among the carnivoran species appears to be very high, with Bayesian model selection indicating that the independent-rates model fits the morphological data better than the autocorrelated-rates model. We suggest that using morphological continuous characters, together with molecular data, can bring a new perspective to the study of species evolution. Our new model is implemented in the MCMCtree computer program for Bayesian inference of divergence times.
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页码:967 / 986
页数:20
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