A bayesian analysis of metazoan mitochondrial genome arrangements

• Published in: Molecular biology and evolution Vol. 22; no. 3; pp. 486 - 495
• Main Authors: Larget, Bret, Simon, Donald L, Kadane, Joseph B, Sweet, Deborah
• Format: Journal Article
• Language: English
• Published: United States 01-03-2005
• Subjects: Animals; Bayes Theorem; DNA, Mitochondrial - genetics; Evolution, Molecular; Humans; Models, Genetic; Molecular Sequence Data; Phylogeny; Sequence Analysis, DNA - methods
• ISSN: 0737-4038; 1537-1719
• DOI: 10.1093/molbev/msi032

Genome arrangements are a potentially powerful source of information to infer evolutionary relationships among distantly related taxa. Mitochondrial genome arrangements may be especially informative about metazoan evolutionary relationships because (1) nearly all animals have the same set of definitively homologous mitochondrial genes, (2) mitochondrial genome rearrangement events are rare relative to changes in sequences, and (3) the number of possible mitochondrial genome arrangements is huge, making convergent evolution of genome arrangements appear highly unlikely. In previous studies, phylogenetic evidence in genome arrangement data is nearly always used in a qualitative fashion-the support in favor of clades with similar or identical genome arrangements is considered to be quite strong, but is not quantified. The purpose of this article is to quantify the uncertainty among the relationships of metazoan phyla on the basis of mitochondrial genome arrangements while incorporating prior knowledge of the monophyly of various groups from other sources. The work we present here differs from our previous work in the statistics literature in that (1) we incorporate prior information on classifications of metazoans at the phylum level, (2) we describe several advances in our computational approach, and (3) we analyze a much larger data set (87 taxa) that consists of each unique, complete mitochondrial genome arrangement with a full complement of 37 genes that were present in the NCBI (National Center for Biotechnology Information) database at a recent date. In addition, we analyze a subset of 28 of these 87 taxa for which the non-tRNA mitochondrial genomes are unique where the assumption of our inversion-only model of rearrangement is more plausible. We present summaries of Bayesian posterior distributions of tree topology on the basis of these two data sets.