A preliminary mitochondrial genome phylogeny of Orthoptera (Insecta) and approaches to maximizing phylogenetic signal found within mitochondrial genome data.
The phylogenetic utility of mitochondrial genomes (mtgenomes) is examined using the framework of a preliminary phylogeny of Orthoptera. This study presents five newly sequenced genomes from four orthopteran families. While all ensiferan and polyneopteran taxa retain the ancestral gene order, all caeliferan lineages including the newly sequenced caeliferan species contain a tRNA rearrangement from the insect ground plan tRNA(Lys)(K)-tRNA(Asp)(D) swapping to tRNA(Asp) (D)-tRNA(Lys) (K) confirming that this rearrangement is a possible molecular synapomorphy for this suborder. The phylogenetic signal in mtgenomes is rigorously examined under the analytical regimens of parsimony, maximum likelihood and Bayesian inference, along with how gene inclusion/exclusion, data recoding, gap coding, and different partitioning schemes influence the phylogenetic reconstruction. When all available data are analyzed simultaneously, the monophyly of Orthoptera and its two suborders, Caelifera and Ensifera, are consistently recovered in the context of our taxon sampling, regardless of the optimality criteria. When protein-coding genes are analyzed as a single partition, nearly identical topology to the combined analyses is recovered, suggesting that much of the signals of the mtgenome come from the protein-coding genes. Transfer and ribosomal RNAs perform poorly when analyzed individually, but contribute signal when analyzed in combination with the protein-coding genes. Inclusion of third codon position of the protein-coding genes does not negatively affect the phylogenetic reconstruction when all genes are analyzed together, whereas recoding of the protein-coding genes into amino acid sequences introduces artificial resolution. Over-partitioning in a Bayesian framework appears to have a negative effect in achieving convergence. Our findings suggest that the best phylogenetic inferences are made when all available nucleotide data from the mtgenome are analyzed simultaneously, and that the mtgenome data can resolve over a wide time scale from the Permian (approximately 260 MYA) to the Tertiary (approximately 50 MYA).
Fenn
J Daniel
JD
Department of Biology, Brigham Young University, Provo, UT 84602, USA. danfenn77@gmail.com
Song
Hojun
H
Cameron
Stephen L
SL
Whiting
Michael F
MF
D000818:Animals; D001499:Bayes Theorem; D004272:DNA, Mitochondrial / Q000235:genetics; D019143:Evolution, Molecular; D015321:Gene Rearrangement; D017344:Genes, Insect; D050259:Genes, Mitochondrial; D054629:Genome, Mitochondrial; D016013:Likelihood Functions; D008928:Mitochondria / Q000235:genetics; D009987:Orthoptera / Q000145:classification / Q000235:genetics*; D010802:Phylogeny; D012335:RNA, Ribosomal / Q000235:genetics; D012343:RNA, Transfer / Q000235:genetics; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA; D013045:Species Specificity
D004272:DNA, Mitochondrial; D012335:RNA, Ribosomal; D012343:RNA, Transfer