Abstract
Bayesian methods for molecular clock dating of species divergences have been greatly developed during the past decade. Advantages of the methods include the use of relaxed-clock models to describe evolutionary rate variation in the branches of a phylogenetic tree and the use of flexible fossil calibration densities to describe the uncertainty in node ages. The advent of next-generation sequencing technologies has led to a flood of genome-scale datasets for organisms belonging to all domains in the tree of life. Thus, a new era has begun where dating the tree of life using genome-scale data is now within reach. In this protocol, we explain how to use the computer program MCMCTree to perform Bayesian inference of divergence times using genome-scale datasets. We use a ten-species primate phylogeny, with a molecular alignment of over three million base pairs, as an exemplar on how to carry out the analysis. We pay particular attention to how to set up the analysis and the priors and how to diagnose the MCMC algorithm used to obtain the posterior estimates of divergence times and evolutionary rates.
Highlights
The molecular clock hypothesis, which states that the rate of molecular evolution is approximately constant with time, provides a powerful way to estimate the times of divergence of species in a phylogeny
Several statistical inference methodologies have been developed for molecular clock dating analyses; during the past decade, the Bayesian method has emerged as the method of choice [4, 5], and several Bayesian inference software packages exist to carry out this type of analysis [6–10]
Bayesian inference is well suited for divergence time estimation because it allows the natural integration of information from the fossil record with information from molecular sequences to estimate node ages, or geological times of divergence, of a species phylogeny [6, 11]
Summary
The molecular clock hypothesis, which states that the rate of molecular evolution is approximately constant with time, provides a powerful way to estimate the times of divergence of species in a phylogeny. Several statistical inference methodologies have been developed for molecular clock dating analyses; during the past decade, the Bayesian method has emerged as the method of choice [4, 5], and several Bayesian inference software packages exist to carry out this type of analysis [6–10] In this protocol, we will explain how to use the computer program MCMCTree to estimate times of species divergences using genome-scale datasets within the Bayesian inference. Bayesian inference is well suited for divergence time estimation because it allows the natural integration of information from the fossil record (in the form of prior statistical distributions describing the ages of nodes in a phylogeny) with information from molecular sequences to estimate node ages, or geological times of divergence, of a species phylogeny [6, 11] Another advantage of the Bayesian clock dating method is that relaxed-clock models, which allow for violations of the molecular clock, can be implemented as the prior on the evolutionary rates for the branches in the phylogeny [6]. For general introductions to Bayesian statistics and Bayesian molecular clock dating, the reader may consult [20, 21]
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