Detection of recombination events in bacterial genomes from large population samples
Detection of recombination events in bacterial genomes from large population samples
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DOI：
10.1093/nar/gkr928
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发表时间：
2012-01-01
影响因子：
14.9
通讯作者：
Corander, Jukka
中科院分区：
文献类型：
--
作者：
Marttinen, Pekka;Hanage, William P.;Corander, Jukka
重要的人类病原体群体的分析目前正在向全球范围内收集的越来越多的样本的全基因组测序过渡。由于细菌中的重组通常是通过使抗性元件和毒力性状从一个进化谱系快速转移到另一个进化谱系来塑造其进化的重要因素，因此获得可以检测重组事件的工具是非常有益的。存在多种先进的统计方法用于此类目的;然而，它们通常限于仅少数样品或来自总基因组的相对较短区域的数据。通过利用贝叶斯建模技术的最新进展的力量，我们在这里介绍了一种方法，用于检测同源重组事件的细菌种群样本的全基因组序列数据在大规模上。我们的统计方法可以有效地处理数百个全基因组测序的群体样本，并确定重组序列的不同来源，从而在全基因组水平上更深入地了解细菌克隆的多样性。一个数据集的241个全基因组序列从一个重要的流行性谱系肺炎链球菌与多个模拟数据集一起使用，以证明我们的方法的潜力。
Analysis of important human pathogen populations is currently under transition toward whole-genome sequencing of growing numbers of samples collected on a global scale. Since recombination in bacteria is often an important factor shaping their evolution by enabling resistance elements and virulence traits to rapidly transfer from one evolutionary lineage to another, it is highly beneficial to have access to tools that can detect recombination events. Multiple advanced statistical methods exist for such purposes; however, they are typically limited either to only a few samples or to data from relatively short regions of a total genome. By harnessing the power of recent advances in Bayesian modeling techniques, we introduce here a method for detecting homologous recombination events from whole-genome sequence data for bacterial population samples on a large scale. Our statistical approach can efficiently handle hundreds of whole genome sequenced population samples and identify separate origins of the recombinant sequence, offering an enhanced insight into the diversification of bacterial clones at the level of the whole genome. A data set of 241 whole genome sequences from an important pandemic lineage of Streptococcus pneumoniae is used together with multiple simulated data sets to demonstrate the potential of our approach.