Identifying currents in the gene pool for bacterial populations using an integrative approach.
Identifying currents in the gene pool for bacterial populations using an integrative approach.
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DOI：
10.1371/journal.pcbi.1000455
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发表时间：
2009-08
影响因子：
4.3
通讯作者：
Corander J
中科院分区：
文献类型：
--
作者：
Tang J;Hanage WP;Fraser C;Corander J
由于对种群样本进行了大规模测序，最近对细菌种群的进化有了更好的了解。很明显，需要来自多个基因的DNA序列，以及目标人群的广泛样本覆盖率，以获得其遗传结构和与菌株相关的祖先模式的相对公正的观点。然而，传统的进化推理的统计方法，如系统发育分析，在这样一个广泛的抽样情况下，特别是当相当数量的重组预计已经发生的几个困难。为了满足大规模分析细菌种群结构的需要，我们在这里介绍了几种用于检测和表示种群间重组的统计工具。此外，我们引入了一个基于模型的描述人口的形状在序列空间中，在其分子变异性和亲和力对其他人群。广泛的真实的数据，从属奈瑟氏菌被用来证明这些人口的遗传工具相结合的系统发育分析的方法的潜力。这里介绍的统计工具可在BAPS 5.2软件中免费获得，该软件可从http://web.abo.fi/fak/mnf/mate/jc/software/baps.html下载。细菌种群生物学的研究是复杂的，因为尽管细菌在很大程度上是无性的，但它们也可以通过同源重组交换遗传物质。与真核生物不同，细菌中的重组不是一个强制性的过程。此外，重组机制受到许多生物和生态因素的影响，这些因素甚至在同一物种的不同种群中也会有所不同。虽然在许多细菌物种中发现了越来越多的同源重组证据，但确定重组频率并了解其对细菌种群进化的影响仍然是一项具有挑战性的工作。在这篇文章中，我们提供了一个动态的图片重组内和密切相关的细菌物种之间。通过几个贝叶斯统计模型的整合，我们的方法突出了重组的定量估计的重要性。我们对一个具有挑战性的多位点序列分型（MLST）数据库的分析表明，使用传统系统发育方法、探索性MLST工具和贝叶斯群体遗传模型的组合分析可以共同产生有趣的生物学见解，而这些见解是任何单独的方法都无法轻易达到的。
The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relatively unbiased view of its genetic structure and the patterns of ancestry connected to the strains. However, the traditional statistical methods for evolutionary inference, such as phylogenetic analysis, are associated with several difficulties under such an extensive sampling scenario, in particular when a considerable amount of recombination is anticipated to have taken place. To meet the needs of large-scale analyses of population structure for bacteria, we introduce here several statistical tools for the detection and representation of recombination between populations. Also, we introduce a model-based description of the shape of a population in sequence space, in terms of its molecular variability and affinity towards other populations. Extensive real data from the genus Neisseria are utilized to demonstrate the potential of an approach where these population genetic tools are combined with an phylogenetic analysis. The statistical tools introduced here are freely available in BAPS 5.2 software, which can be downloaded from http://web.abo.fi/fak/mnf/mate/jc/software/baps.html. The study of bacterial population biology is complicated by the fact that, although bacteria are largely asexual, they can also exchange genetic materials through homologous recombination. Unlike eukaryotes, recombination in bacteria is not an obligatory process. Furthermore, the recombination mechanisms are subject to many biological and ecological factors that can vary even within different populations of the same species. Although increasing evidence for homologous recombination has been found in many bacterial species, determining the frequency of recombination and understanding the influence that it exerts upon the evolution of bacterial populations remains a challenging work. In this article, we provide a dynamic picture of recombination within and between closely related bacteria species. Through an integration of several Bayesian statistical models, our method highlights the importance of a quantitative estimation of recombination. Our analyses of a challenging multi-locus sequence typing (MLST) database demonstrate that combined analyses using both traditional phylogenetic methods, explorative MLST tools and Bayesian population genetic models can together yield interesting biological insights that cannot easily be reached by any of the approaches alone.
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影响因子：
3
作者：
Chan CX;Beiko RG;Ragan MA
通讯作者：
Ragan MA
影响因子：
2.2
作者：
Corander, Jukka;Gyllenberg, Mats;Koski, Timo
通讯作者：
Koski, Timo
影响因子：
3.3
作者：
Didelot, Xavier;Falush, Daniel
通讯作者：
Falush, Daniel
影响因子：
10.7
作者：
Bryant, D;Moulton, V
通讯作者：
Moulton, V
影响因子：
3.2
作者：
Feil, EJ;Li, BC;Spratt, BG
通讯作者：
Spratt, BG