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贝叶斯系统发育方法估计未知序列的年龄。

A Bayesian phylogenetic method to estimate unknown sequence ages.

机构信息

Department of Biology, The Pennsylvania State University, PA, USA.

出版信息

Mol Biol Evol. 2011 Feb;28(2):879-87. doi: 10.1093/molbev/msq262. Epub 2010 Oct 1.

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.

摘要

异时数据集包含在不同时间点采集的分子序列。如果采样序列的时间范围相对于突变率较大,则采样时间可以直接将进化率校准到日历时间。在这里,我们扩展了这个校准过程,提供了一种完整的概率方法,该方法利用异时数据集的时间信息来估计采样时间(叶龄),对于没有这些信息的测序样本。我们的方法类似于放松分子钟对系统发育树中特定谱系的约束。使用合成和经验数据集的组合,我们证明了该方法能够可靠和准确地估计叶龄。我们方法的潜在应用包括将不确定年龄或放射性碳无限年龄的样本纳入古 DNA 分析、评估特定序列或数据集的时间信号,以及探索某些有争议的序列年龄的可靠性。

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