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A mitochondrial genome phylogeny of owlet moths (Lepidoptera: Noctuoidea), and examination of the utility of mitochondrial genomes for lepidopteran phylogenetics

机译:蛾的线粒体基因组系统发育(鳞翅目:夜蛾),以及检查线粒体基因组对鳞翅目系统发育的实用性

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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. (C) 2015 Elsevier Inc. All rights reserved.
机译:鳞翅目夜蛾夜蛾科的系统发育假说是基于12个物种(六个新测序的)的完整线粒体(mt)基因组推断的。最新分类的每个夜蛾科的单性类都得到了很好的支持。与以前使用核基因进行的分析相反,在家族水平上发现了新颖而牢固的关系。钩端螺旋体被恢复为(Nolidae +(Euteliidae + Noctuidae))的姐妹,而Notodontidae是所有这些类群的姐妹(不包括假定的最基础的谱系Oenosandridae)。为了提高使用mt基因组的系统发育分辨率,测试了多种分析方法:贝叶斯推断(BI)与最大似然(ML),排除与包含RNA基因(rRNA或tRNA)以及Gblocks处理。 mt基因组内的进化信号对分析变化的敏感性较低。推理方法的影响最大。包含tRNA肯定会增加拓扑结构的一致性,而包含rRNA则会导致一系列系统发育关系,具体取决于其他分析因素。这两种Gblocks参数设置对两种推断方法之间的节点支持有相反的影响。松弛参数(GBRA)在BI分析中得到较高的支持值,而严格参数(GBDH)在ML分析中得到较高的支持值。 (C)2015 Elsevier Inc.保留所有权利。

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