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Mol Biol Evol. 1999 Feb;16(2):286-97.

Interaction of process partitions in phylogenetic analysis: an example from the swallowtail butterfly genus Papilio.

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1
Department of Environmental Science, Policy, and Management, University of California, Berkeley, USA. reed@u.arizona.edu

Abstract

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.

[Indexed for MEDLINE]

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