A Comparison of Methods for Estimating Substitution Rates from Ancient DNA Sequence Data

Abstract

The estimation of evolutionary rates from ancient DNA sequences can be negatively affected by among-lineage rate variation and non-random sampling. Using a simulation study, we compared the performance of three phylogenetic methods for inferring evolutionary rates from time-structured data sets: root-to-tip regression, least-squares dating, and Bayesian inference. Our results show that these methods produce reliable estimates when the substitution rate is high, rate variation is low, and samples of similar ages are not phylogenetically clustered. The interaction of these factors is particularly important for Bayesian estimation of evolutionary rates. We also inferred rates for time-structured mitogenomic data sets from six vertebrate species. Root-to-tip regression estimated a different rate from least-squares dating and Bayesian inference for mitogenomes from the horse, which has high levels of among-lineage rate variation. We recommend using multiple methods of inference and testing data for temporal signal, among-lineage rate variation, and phylo-temporal clustering.