Mitochondrial genome data alone are not enough to unambiguously resolve the relationships of Entognatha, Insecta and Crustacea sensu lato (Arthropoda)

Abstract

An analysis of the relationships of the major arthropod groups was undertaken using mitochondrial genome data to examine the hypotheses that Hexapoda is polyphyletic and that Collembola is more closely related to branchiopod crustaceans than insects. We sought to examine the sensitivity of this relationship to outgroup choice, data treatment, gene choice and optimality criteria used in the phylogenetic analysis of mitochondrial genome data. Additionally we sequenced the mitochondrial genome of an archaeognathan, Nesomachilis australica, to improve taxon selection in the apterygote insects, a group poorly represented in previous mitochondrial phylogenies. The sister group of the Collembola was rarely resolved in our analyses with a significant level of support. The use of different outgroups (myriapods, nematodes, or annelids + mollusks) resulted in many different placements of Collembola. The way in which the dataset was coded for analysis (DNA, DNA with the exclusion of third codon position and as amino acids) also had marked affects on tree topology. We found that nodal support was spread evenly throughout the 13 mitochondrial genes and the exclusion of genes resulted in significantly less resolution in the inferred trees. Optimality criteria had a much lesser effect on topology than the preceding factors; parsimony and Bayesian trees for a given data set and treatment were quite similar. We therefore conclude that the relationships of the extant arthropod groups as inferred by mitochondrial genomes are highly vulnerable to outgroup choice, data treatment and gene choice, and no consistent alternative hypothesis of Collembola's relationships is supported. Pending the resolution of these identified problems with the application of mitogenomic data to basal arthropod relationships, it is difficult to justify the rejection of hexapod monophyly, which is well supported on morphological grounds.Ó The Willi Hennig Society 2004.Mitochondrial (mt) genomes are seeing wider use as phylogenetic markers in studies aiming to resolve the relationships of distantly related groups (Saccone et al., 1999). Many of these studies have, however, produced results which are difficult to reconcile with trees produced using other markers. For example, in mammal phylogeny, mitochondrial analyses suggest (monotremes + marsupials) + eutherians (Janke et al., 1996(Janke et al., , 1997(Janke et al., , 2002, whereas most nuclear and morphological ⁄ physiological studies support (marsupials + eutherians) + monotremes (Lee et al., 1999;Lou et al., 2002). These studies have highlighted the need for sophisticated analysis of the different groups of signals found within the mitochondrial genome (e.g., protein coding versus ribosomal genes, first and second versus third codon position and DNA versus amino acid sequence data) and the effect these differing data sets ⁄ treatments may

Phylogenetic information of freshwater copepod (Diaptomus sicilis) with special reference to 18S rRNA

“…Even rapidly-evolving mitochondrial genes often show support for deep notes. Cameron et al (2004) reported that 18S rRNA had the best phylogenetic signal ratio using Neighbour-joining tree. Mitochondrial Cytochrome Oxidase I (mtCOI) gene proved to be useful to resolve evolutionary relationships among closely related species for a wide range of taxa, especially for calanoid copepods and euphausiids (Bucklin 2011).…”

The phylogeny of the Orthoptera (Insecta) as deduced from mitogenomic gene sequences

“…The phylogenetic performance of different genes is related to their particular rates of evolution. The three protein-coding genes, atp6, atp8, and nad4L, are the fastest evolving genes, while COX subunits and Cyt b show much-slower overall rates of evolution (Russo et al 1996;Zardoya and Meyer 1996; Cameron et al 2004). Cox1 is the most conserved gene in terms of amino acid evolution.…”

“…Different optimality criteria and dataset compilation techniques have been applied to find the best method of analyzing complex mitogenomic data (Stewart and Beckenbach 2009, Cameron et al 2004, Castro and Dowton 2005, Kim et al 2005. In this paper, we compared the effect of partitioning according to different protein-coding genes (NADH, COX, COX + Cyt b, and ATP) and different regions in rRNA (rRNA(C) (small subunit ribosomal RNA (rrnS) (III) + large subunit ribosomal RNA (rrnL) (III + IV + V)) and rRNA(V) (rrnS (I + II) + rrnL (I + II + VI))).…”

The first mitochondrial genome for the wasp superfamily Platygastroidea: the egg parasitoidTrissolcus basalis

“…Dataset alignment strategies may also affect the recovered topology (Cameron et al 2004;Cameron et al 2009). Comparison of the topologies recovered from the datasets aligned by Clustal and Muscle (both with third codon positions excluded) indicated that the topology produced from the Muscle alignment was more congruent with expected relationships than the Clustal alignment.…”