Reed R D, Sperling F A
Department of Environmental Science, Policy, and Management, University of California, Berkeley, USA.
Mol Biol Evol. 1999 Feb;16(2):286-97. doi: 10.1093/oxfordjournals.molbev.a026110.
In this study, we explored how the concept of the process partition may be applied to phylogenetic analysis. Sequence data were gathered from 23 species and subspecies of the swallowtail butterfly genus Papilio, as well as from two outgroup species from the genera Eurytides and Pachliopta. Sequence data consisted of 1,010 bp of the nuclear protein-coding gene elongation factor-1 alpha (EF-1 alpha) as well as the entire sequences (a total of 2,211 bp) of the mitochondrial protein-coding genes cytochrome oxidase I and cytochrome oxidase II (COI and COII). In order to examine the interaction between the nuclear and mitochondrial partitions in a combined analysis, we used a method of visualizing branch support as a function of partition weight ratios. We demonstrated how this method may be used to diagnose error at different levels of a tree in a combined maximum-parsimony analysis. Further, we assessed patterns of evolution within and between subsets of the data by implementing a multipartition maximum-likelihood model to estimate evolutionary parameters for various putative process partitions. COI third positions have an estimated average substitution rate more than 15 times that of EF-1 alpha, while COII third positions have an estimated average substitution rate more than 22 times that of EF-1 alpha. Ultimately, we found that although the mitochondrial and nuclear data were not significantly incongruent, homoplasy in the fast-evolving mitochondrial data confounded the resolution of basal relationships in the combined unweighted parsimony analysis despite the fact that there was relatively strong support for the relationships in the nuclear data. We conclude that there may be shortcomings to the methods of "total evidence" and "conditional combination" because they may fail to detect or accommodate the type of confounding bias we found in our data.
在本研究中，我们探讨了过程划分的概念如何应用于系统发育分析。我们收集了凤蝶属23个物种和亚种的序列数据，以及Eurytides属和红珠凤蝶属两个外群物种的序列数据。序列数据包括核蛋白编码基因延伸因子-1α（EF-1α）的1010个碱基对，以及线粒体蛋白编码基因细胞色素氧化酶I和细胞色素氧化酶II（COI和COII）的完整序列（共2211个碱基对）。为了在联合分析中检验核分区与线粒体分区之间的相互作用，我们使用了一种将分支支持度可视化为分区权重比函数的方法。我们展示了该方法如何用于在联合最大简约分析中诊断树不同层次的错误。此外，我们通过实施多分区最大似然模型来估计各种假定过程分区的进化参数，从而评估数据子集内部和之间的进化模式。COI的第三密码子位置估计平均替换率是EF-1α的15倍以上，而COII的第三密码子位置估计平均替换率是EF-1α的22倍以上。最终，我们发现尽管线粒体和核数据没有明显不一致，但快速进化的线粒体数据中的同塑性混淆了联合非加权简约分析中基部关系的分辨率，尽管核数据中的关系有相对较强的支持。我们得出结论，“总证据”和“条件组合 ”方法可能存在缺点，因为它们可能无法检测或适应我们在数据中发现的那种混淆偏差。
