A mitochondrial genome phylogeny of owlet moths (Lepidoptera: Noctuoidea), and examination of the utility of mitochondrial genomes for lepidopteran phylogenetics
| Autor: | David C. Lees, Xiushuai Yang, Dayong Xue, Stephen L. Cameron, Hongxiang Han |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
0106 biological sciences
Nuclear gene Lineage (evolution) Genome Insect Moths DNA Mitochondrial 010603 evolutionary biology 01 natural sciences Erebidae Genome Noctuoidea 03 medical and health sciences RNA Transfer Phylogenetics Euteliidae Gene Order Genetics Animals Molecular Biology Phylogeny Ecology Evolution Behavior and Systematics 030304 developmental biology Likelihood Functions 0303 health sciences biology Phylogenetic tree Bayes Theorem Sequence Analysis DNA biology.organism_classification Lepidoptera RNA Ribosomal Genome Mitochondrial |
| Zdroj: | Molecular Phylogenetics and Evolution. 85:230-237 |
| ISSN: | 1055-7903 |
| DOI: | 10.1016/j.ympev.2015.02.005 |
| Popis: | A phylogenetic hypothesis for the lepidopteran superfamily Noctuoidea was inferred based on the complete mitochondrial (mt) genomes of 12 species (six newly sequenced). The monophyly of each noctuoid family in the latest classification was well supported. Novel and robust relationships were recovered at the family level, in contrast to previous analyses using nuclear genes. Erebidae was recovered as sister to (Nolidae+(Euteliidae+Noctuidae)), while Notodontidae was sister to all these taxa (the putatively basalmost lineage Oenosandridae was not included). In order to improve phylogenetic resolution using mt genomes, various analytical approaches were tested: Bayesian inference (BI) vs. maximum likelihood (ML), excluding vs. including RNA genes (rRNA or tRNA), and Gblocks treatment. The evolutionary signal within mt genomes had low sensitivity to analytical changes. Inference methods had the most significant influence. Inclusion of tRNAs positively increased the congruence of topologies, while inclusion of rRNAs resulted in a range of phylogenetic relationships varying depending on other analytical factors. The two Gblocks parameter settings had opposite effects on nodal support between the two inference methods. The relaxed parameter (GBRA) resulted in higher support values in BI analyses, while the strict parameter (GBDH) resulted in higher support values in ML analyses. |
| Databáze: | OpenAIRE |
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