Inferring Ancestral Recombination Graphs from Bacterial Genomic Data.
Inferring Ancestral Recombination Graphs from Bacterial Genomic Data.
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DOI：
10.1534/genetics.116.193425
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发表时间：
2017-02
期刊：
影响因子：
3.3
通讯作者：
French NP
中科院分区：
文献类型：
--
作者：
Vaughan TG;Welch D;Drummond AJ;Biggs PJ;George T;French NP
同源重组是细菌进化的一个重要特征，但它混淆了传统的系统发育方法。虽然已经开发了一些特定于细菌进化的方法，但这些方法都不允许联合推断细菌重组图和相关参数。在这篇文章中，我们提出了一种新的方法来解决这个缺点。我们的方法使用了一种新的马尔可夫链蒙特卡罗算法进行系统发育推断ClonalOrigin模型下。我们证明了我们的方法的实用性，将其应用到核糖体多位点序列分型数据从致病性和非致病性大肠杆菌血清型O157和O26菌株在新西兰农村收集测序。该方法作为开源BEAST 2包Bacter实现，可通过项目网页http://tgvaughan.github.io/bacter获得。
Homologous recombination is a central feature of bacterial evolution, yet it confounds traditional phylogenetic methods. While a number of methods specific to bacterial evolution have been developed, none of these permit joint inference of a bacterial recombination graph and associated parameters. In this article, we present a new method which addresses this shortcoming. Our method uses a novel Markov chain Monte Carlo algorithm to perform phylogenetic inference under the ClonalOrigin model. We demonstrate the utility of our method by applying it to ribosomal multilocus sequence typing data sequenced from pathogenic and nonpathogenic Escherichia coli serotype O157 and O26 isolates collected in rural New Zealand. The method is implemented as an open source BEAST 2 package, Bacter, which is available via the project web page at http://tgvaughan.github.io/bacter.