A Bayesian phylogenetic method to estimate unknown sequence ages

Abstract

Heterochronous data sets comprise molecular sequences sampled at different points in time. If the temporal range of the sampled sequences is large relative to the rate of mutation, the sampling times can directly calibrate evolutionary rates to calendar time. Here, we extend this calibration process to provide a full probabilistic method that utilizes temporal information in heterochronous data sets to estimate sampling times (leaf-ages) for sequenced for which this information unavailable. Our method is similar to relaxing the constraints of the molecular clock on specific lineages within a phylogenetic tree. Using a combination of synthetic and empirical data sets, we demonstrate that the method estimates leaf-ages reliably and accurately. Potential applications of our approach include incorporating samples of uncertain or radiocarbon-infinite age into ancient DNA analyses, evaluating the temporal signal in a particular sequence or data set, and exploring the reliability of sequence ages that are somehow contentious.

FIG. 1.

Relative bias in posterior mean leaf-age estimates from 960 leave-one-out analyses of synthetic data sets with varying true leaf-ages. For true ages sufficiently distinct from zero, the posterior mean estimator is unbiased.

FIG. 2.

Empirical distributions of rMSE when estimating leaf-dates under flexible coalescent models based on a multiple change-point (MCP) process and GMRF.

FIG. 3.

Examples of two different leave-one-out analyses for which the true age was not recovered within the 95% HPDs of the leaf-age estimates. In (A), the analysis identifies two similarly likely leaf-ages, whereas in B the analysis identifies a single, precise estimate that does not coincide with the radiocarbon date of the specimen from which the sequence was isolated. By evaluating the trace files from each leaf-age estimate, it is possible to identify potentially erroneous sequences and to devise an appropriate strategy to authenticate these sequences.