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Vol. 52, 2013
The phylogeny of the Orthoptera (Insecta) as deduced from
mitogenomic gene sequences
Hong-Li
Zhang1,2, Yuan Huang2, Li-Liang Lin2,
Xiao-Yang Wang2 and Zhe-Min Zheng2*
1College
of Life Science, Shanxi Datong University, Datong 037009, China
2Institute of Zoology, Shaanxi Normal University,
Xi'an 710062, China
Abstract
Background: The phylogeny of the
Orthoptera was analyzed based on 6 datasets from 47 orthopteran
mitochondrial genomes (mitogenomes). The phylogenetic signals in the
mitogenomes were rigorously examined under analytical regimens of
maximum likelihood (ML) and Bayesian inference (BI), along with how
gene types and different partitioning schemes influenced the
phylogenetic reconstruction within the Orthoptera. The monophyly of the
Orthoptera and its two suborders (Caelifera and Ensifera) was
consistently recovered in the analyses based on most of the datasets we
selected, regardless of the optimality criteria.
Results: When the seven NADH dehydrogenase
subunits were concatenated into a single alignment (NADH) and were
analyzed; a near-identical topology to the traditional morphological
analysis was recovered, especially for BI_NADH. In both the
concatenated cytochrome oxidase (COX) subunits and COX + cytochrome b
(Cyt b) datasets, the small extent of sequence divergence seemed to be
helpful for resolving relationships among major Orthoptera lineages
(between suborders or among superfamilies). The conserved and variable
domains of ribosomal (r)RNAs performed poorly when respectively
analyzed but provided signals at some taxonomic levels.
Conclusions: Our findings suggest
that the best phylogenetic inferences can be made when moderately
divergent nucleotide data from mitogenomes are analyzed, and that the
NADH dataset was suited for studying orthopteran phylogenetic
relationships at different taxonomic levels, which may have been due to
the larger amount of DNA sequence data and the larger number of
phylogenetically informative sites.
Key words: Orthoptera; Acrididae; Phylogeny;
Protein-coding genes; Ribosomal RNA.
*Correspondence: E-mail: zhengzhemin@163.com
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