Yang Jialiang, Grünewald Stefan, Xu Yifei, Wan Xiu-Feng
Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.
BMC Syst Biol. 2014 Feb 20;8:21. doi: 10.1186/1752-0509-8-21.
Phylogenetic networks are employed to visualize evolutionary relationships among a group of nucleotide sequences, genes or species when reticulate events like hybridization, recombination, reassortant and horizontal gene transfer are believed to be involved. In comparison to traditional distance-based methods, quartet-based methods consider more information in the reconstruction process and thus have the potential to be more accurate.
We introduce QuartetSuite, which includes a set of new quartet-based methods, namely QuartetS, QuartetA, and QuartetM, to reconstruct phylogenetic networks from nucleotide sequences. We tested their performances and compared them with other popular methods on two simulated nucleotide sequence data sets: one generated from a tree topology and the other from a complicated evolutionary history containing three reticulate events. We further validated these methods to two real data sets: a bacterial data set consisting of seven concatenated genes of 36 bacterial species and an influenza data set related to recently emerging H7N9 low pathogenic avian influenza viruses in China.
QuartetS, QuartetA, and QuartetM have the potential to accurately reconstruct evolutionary scenarios from simple branching trees to complicated networks containing many reticulate events. These methods could provide insights into the understanding of complicated biological evolutionary processes such as bacterial taxonomy and reassortant of influenza viruses.
当认为涉及杂交、重组、重配和水平基因转移等网状事件时,系统发育网络用于可视化一组核苷酸序列、基因或物种之间的进化关系。与传统的基于距离的方法相比,基于四重奏的方法在重建过程中考虑了更多信息,因此有可能更准确。
我们引入了四重奏套件(QuartetSuite),其中包括一组新的基于四重奏的方法,即四重奏S(QuartetS)、四重奏A(QuartetA)和四重奏M(QuartetM),用于从核苷酸序列重建系统发育网络。我们在两个模拟核苷酸序列数据集上测试了它们的性能,并将它们与其他流行方法进行了比较:一个是从树形拓扑结构生成的,另一个是从包含三个网状事件的复杂进化历史生成的。我们进一步在两个真实数据集上验证了这些方法:一个是由36种细菌的七个串联基因组成的细菌数据集,另一个是与中国最近出现的H7N9低致病性禽流感病毒相关的流感数据集。
四重奏S、四重奏A和四重奏M有潜力从简单的分支树到包含许多网状事件的复杂网络准确重建进化场景。这些方法可以为理解复杂的生物进化过程提供见解,如细菌分类学和流感病毒的重配。