New methods for inferring population dynamics from microbial sequences.
New methods for inferring population dynamics from microbial sequences.
复制标题
从微生物序列推断种群动态的新方法。
DOI：
10.1016/j.meegid.2006.03.004
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
Crandall,KeithA
中科院分区：
文献类型：
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作者：
Pérez-Losada,Marcos;Porter,MeganL;Tazi,Loubna;Crandall,KeithA
高通量测序成本的降低、自动化程度的提高以及序列数据对进化分析的适应性使得 DNA 数据（或相应的氨基酸序列）成为研究微生物群体遗传学和系统发育学的首选分子标记。与此同时，由于计算能力不断增强，人们正在开发新的、更准确（有时更快）的基于序列的分析方法并将其应用于这些新数据。在这里，我们回顾了一些常用的、最近改进的和新开发的使用核苷酸和氨基酸序列数据推断种群动态和进化关系的方法，包括：比对、模型选择、分叉和网络系统发育方法，以及估计人口历史、种群结构和种群参数（重组、遗传多样性、生长和自然选择）的方法。由于有关这些主题的大量文献已发表，因此本综述的范围无法全面。相反，对于讨论的所有方法，我们介绍了我们认为对微生物序列分析特别有用的方法，并在可能的情况下，包括对最近和更具包容性的评论的参考。
The reduced cost of high throughput sequencing, increasing automation, and the amenability of sequence data for evolutionary analysis are making DNA data (or the corresponding amino acid sequences) the molecular marker of choice for studying microbial population genetics and phylogenetics. Concomitantly, due to the ever-increasing computational power, new, more accurate (and sometimes faster), sequence-based analytical approaches are being developed and applied to these new data. Here we review some commonly used, recently improved, and newly developed methodologies for inferring population dynamics and evolutionary relationships using nucleotide and amino acid sequence data, including: alignment, model selection, bifurcating and network phylogenetic approaches, and methods for estimating demographic history, population structure, and population parameters (recombination, genetic diversity, growth, and natural selection). Because of the extensive literature published on these topics this review cannot be comprehensive in its scope. Instead, for all the methods discussed we introduce the approaches we think are particularly useful for analyses of microbial sequences and where possible, include references to recent and more inclusive reviews.