Abstract

Phylogenetic methods can use the sampling times of molecular sequence data to calibrate the molecular clock, enabling the estimation of evolutionary rates and timescales for rapidly evolving pathogens and data sets containing ancient DNA samples. A key aspect of such calibrations is whether a sufficient amount of molecular evolution has occurred over the sampling time window, that is, whether the data can be treated as having come from a measurably evolving population. Here, we investigate the performance of a fully Bayesian evaluation of temporal signal (BETS) in sequence data. The method involves comparing the fit to the data of two models: a model in which the data are accompanied by the actual (heterochronous) sampling times, and a model in which the samples are constrained to be contemporaneous (isochronous). We conducted simulations under a wide range of conditions to demonstrate that BETS accurately classifies data sets according to whether they contain temporal signal or not, even when there is substantial among-lineage rate variation. We explore the behavior of this classification in analyses of five empirical data sets: modern samples of A/H1N1 influenza virus, the bacterium Bordetella pertussis, coronaviruses from mammalian hosts, ancient DNA from Hepatitis B virus, and mitochondrial genomes of dog species. Our results indicate that BETS is an effective alternative to other tests of temporal signal. In particular, this method has the key advantage of allowing a coherent assessment of the entire model, including the molecular clock and tree prior which are essential aspects of Bayesian phylodynamic analyses.

中文翻译：

---

在可衡量的不断发展的人口中对时间信号的贝叶斯评估。

摘要

系统发育方法可以使用分子序列数据的采样时间来校准分子时钟，从而能够估算出快速进化的病原体和包含古代DNA样本的数据集的进化速率和时标。此类校准的一个关键方面是在采样时间窗口内是否发生了足够数量的分子进化，也就是说，是否可以将数据视为来自可衡量的进化种群。在这里，我们调查序列数据中的时间信号（BETS）的完全贝叶斯评估的性能。该方法包括将拟合度与两个模型的数据进行比较：一个模型，其中数据伴随有实际（异时）采样时间；一个模型中，样本被约束为同时（等时）。我们在广泛的条件下进行了仿真，以证明即使在谱系间差异很大的情况下，BETS仍会根据它们是否包含时间信号来准确地对数据集进行分类。我们通过分析以下五个经验数据集来探索这种分类的行为：A / H1N1流感病毒，百日咳博德特氏菌，来自哺乳动物宿主的冠状病毒，来自乙型肝炎病毒的古老DNA以及犬种的线粒体基因组。我们的结果表明，BETS是其他时间信号测试的有效替代方法。尤其是，此方法的主要优点是可以对整个模型进行连贯的评估，包括先验的分子钟和树，这是贝叶斯系统动力学分析的重要方面。