A new method for inferring timetrees from temporally sampled molecular sequences
A new method for inferring timetrees from temporally sampled molecular sequences
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DOI：
10.1371/journal.pcbi.1007046
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发表时间：
2020-01-01
影响因子：
4.3
通讯作者：
Kumar, Sudhir
中科院分区：
文献类型：
--
作者：
Miura, Sayaka;Tamura, Koichiro;Kumar, Sudhir
病原体时间树是按时间缩放的病原体。它们揭示了病原体在种群中传播的时间历史，正如菌株进化史中所捕获的那样。这些时间树是通过使用在不同时间采样的致病菌株的分子序列来推断的。也就是说，时间采样序列能够推断序列发散时间。在这里，我们提出了一种新的方法（RelTime与过时的提示[RTDT]），估计病原体时间树的基础上的相对速率框架的RelTime方法，是代数的性质和不同的所有其他当前的方法。RTDT不需要贝叶斯方法所要求的许多先验知识，并且它具有轻计算要求。在对大量计算机模拟数据集的分析中，我们发现RTDT时间估计的准确性及其置信区间（CI）的覆盖概率非常出色。在经验数据集的分析中，RTDT产生的数据与文献中报道的数据相似。在与贝叶斯和非贝叶斯方法（LSD，TreeTime和Treedater）的比较基准测试中，我们发现没有一种方法在每种情况下都表现最好。因此，我们提供了一个简短的指南，供用户选择最合适的方法在实证数据分析。RTDT通过图形用户界面和最新版本的跨平台MEGA X软件中的高通量设置实现，可从http://www.megasoftware.net.Author免费获得摘要病原体时间树跟踪种群，宿主和爆发中菌株的起源和进化历史。这些分子生物学的提示通常包含采样时间信息，因为序列通常在疾病爆发和传播期间的不同时间获得。本文提出了一种新的方法，用于推求具有尖点日期的多源系统的发散时间和置信区间。新的带有日期提示的相对时间（RTDT）方法在计算机模拟数据集的分析中表现出出色的性能，与其他快速的非贝叶斯方法相比，在几种进化场景中产生了类似或更好的结果。这种新方法可在跨平台MEGA软件包（10.1版及更高版本）中使用，该软件包提供图形用户界面，并允许通过脚本和高吞吐量分析中的命令行使用（www.megasoftware.net）。
Pathogen timetrees are phylogenies scaled to time. They reveal the temporal history of a pathogen spread through the populations as captured in the evolutionary history of strains. These timetrees are inferred by using molecular sequences of pathogenic strains sampled at different times. That is, temporally sampled sequences enable the inference of sequence divergence times. Here, we present a new approach (RelTime with Dated Tips [RTDT]) to estimating pathogen timetrees based on a relative rate framework underlying the RelTime approach that is algebraic in nature and distinct from all other current methods. RTDT does not require many of the priors demanded by Bayesian approaches, and it has light computing requirements. In analyses of an extensive collection of computer-simulated datasets, we found the accuracy of RTDT time estimates and the coverage probabilities of their confidence intervals (CIs) to be excellent. In analyses of empirical datasets, RTDT produced dates that were similar to those reported in the literature. In comparative benchmarking with Bayesian and non-Bayesian methods (LSD, TreeTime, and treedater), we found that no method performed the best in every scenario. So, we provide a brief guideline for users to select the most appropriate method in empirical data analysis. RTDT is implemented for use via a graphical user interface and in high-throughput settings in the newest release of cross-platform MEGA X software, freely available from http://www.megasoftware.net.Author summary Pathogen timetrees trace the origins and evolutionary histories of strains in populations, hosts, and outbreaks. The tips of these molecular phylogenies often contain sampling time information because the sequences were generally obtained at different times during the disease outbreaks and propagation. We have developed a new method for inferring divergence times and confidence intervals for phylogenies with tip dates. The new Relative Times with Dated Tips (RTDT) methods showed excellent performance in the analysis of computer-simulated datasets, producing similar or better results in several evolutionary scenarios as compared to other fast, non-Bayesian methods. The new method is available in the cross-platform MEGA software package (version 10.1 and higher) that provides a graphical user interface and allows usage via a command line in scripting and high throughput analysis (www.megasoftware.net).