Nonstationary Evolution and Compositional Heterogeneity in Beetle Mitochondrial Phylogenomics
Nonstationary Evolution and Compositional Heterogeneity in Beetle Mitochondrial Phylogenomics
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DOI：
10.1093/sysbio/syp037
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发表时间：
2009-08-01
影响因子：
6.5
通讯作者：
Whiting, Michael F.
中科院分区：
文献类型：
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作者：
Sheffield, Nathan C.;Song, Hojun;Whiting, Michael F.
许多已发表的系统发育基于假设类群之间核苷酸组成相同的方法。然而，研究表明，这种假设往往不准确，特别是在不同的谱系中。非平稳序列进化，当不同谱系中的类群以不同方式进化时，可能会导致不相等的核苷酸组成。这可能会导致推理方法失败和系统发育不准确。系统发生理论的最新进展提出了非平稳序列进化的新模型；这些模型通常优于同等的固定模型。已经开发了多种实现此类模型的新系统发育软件，但采用新方法的研究仍然很少。我们发现鞘翅目昆虫（甲虫）线粒体基因组内核苷酸组成的趋同。我们发现物种之间和基因组中基因之间的碱基含量存在差异。对于这个数据集，我们应用了广泛的系统发育方法，包括一些传统的平稳进化模型和所有更新的非平稳模型。我们比较了应用于同一数据集的 8 种推理方法。尽管更常用的方法普遍无法恢复已建立的进化枝，但我们发现一些较新的软件包更适合这种性质的数据。软件包 p4、PHASE 和 nhPhyML 能够克服我们数据集中的系统偏差，但 parsimony、MrBayes、NJ、LogDet 和 PhyloBayes 却不能。
Many published phylogenies are based on methods that assume equal nucleotide composition among taxa. Studies have shown, however, that this assumption is often not accurate, particularly in divergent lineages. Nonstationary sequence evolution, when taxa in different lineages evolve in different ways, can lead to unequal nucleotide composition. This can cause inference methods to fail and phylogenies to be inaccurate. Recent advancements in phylogenetic theory have proposed new models of nonstationary sequence evolution; these models often outperform equivalent stationary models. A variety of new phylogenetic software implementing such models has been developed, but the studies employing the new methodology are still few. We discovered convergence of nucleotide composition within mitochondrial genomes of the insect order Coleoptera (beetles). We found variation in base content both among species and among genes in the genome. To this data set, we have applied a broad range of phylogenetic methods, including some traditional stationary models of evolution and all the more recent nonstationary models. We compare 8 inference methods applied to the same data set. Although the more commonly used methods universally fail to recover established clades, we find that some of the newer software packages are more appropriate for data of this nature. The software packages p4, PHASE, and nhPhyML were able to overcome the systematic bias in our data set, but parsimony, MrBayes, NJ, LogDet, and PhyloBayes were not.