Institute for Molecular Bioscience, and ARC Centre of Excellence in Bioinformatics, The University of Queensland, Brisbane, QLD 4072, Australia.
Sci Rep. 2016 Jul 1;6:28970. doi: 10.1038/srep28970.
Alignment-free (AF) approaches have recently been highlighted as alternatives to methods based on multiple sequence alignment in phylogenetic inference. However, the sensitivity of AF methods to genome-scale evolutionary scenarios is little known. Here, using simulated microbial genome data we systematically assess the sensitivity of nine AF methods to three important evolutionary scenarios: sequence divergence, lateral genetic transfer (LGT) and genome rearrangement. Among these, AF methods are most sensitive to the extent of sequence divergence, less sensitive to low and moderate frequencies of LGT, and most robust against genome rearrangement. We describe the application of AF methods to three well-studied empirical genome datasets, and introduce a new application of the jackknife to assess node support. Our results demonstrate that AF phylogenomics is computationally scalable to multi-genome data and can generate biologically meaningful phylogenies and insights into microbial evolution.
无比对(AF)方法最近作为系统发育推断中基于多重序列比对方法的替代方法而受到关注。然而,AF 方法对基因组规模进化情景的敏感性知之甚少。在这里,我们使用模拟的微生物基因组数据,系统地评估了九种 AF 方法对三种重要进化情景的敏感性:序列分歧、侧向基因转移(LGT)和基因组重排。在这些情景中,AF 方法对序列分歧的程度最为敏感,对低频率和中等频率的 LGT 不太敏感,对基因组重排最为稳健。我们描述了 AF 方法在三个研究充分的经验基因组数据集上的应用,并介绍了一种新的使用刀切法来评估节点支持的方法。我们的结果表明,AF 基因组系统发生学在计算上可扩展到多基因组数据,可以生成具有生物学意义的系统发生树,并深入了解微生物进化。