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中国蝗总科(直翅目:蝗亚目)部分物种的DNA条形码与物种界限界定

DNA barcoding and species boundary delimitation of selected species of Chinese Acridoidea (Orthoptera: Caelifera).

作者信息

Huang Jianhua, Zhang Aibing, Mao Shaoli, Huang Yuan

机构信息

College of Life Sciences, Shaanxi Normal University, Xi'an, People's Republic of China ; College of Life Sciences, Guangxi Normal University, Guilin, People's Republic of China.

College of Life Sciences, Capital Normal University, Beijing, People's Republic of China.

出版信息

PLoS One. 2013 Dec 20;8(12):e82400. doi: 10.1371/journal.pone.0082400. eCollection 2013.

Abstract

We tested the performance of DNA barcoding in Acridoidea and attempted to solve species boundary delimitation problems in selected groups using COI barcodes. Three analysis methods were applied to reconstruct the phylogeny. K2P distances were used to assess the overlap range between intraspecific variation and interspecific divergence. "Best match (BM)", "best close match (BCM)", "all species barcodes (ASB)" and "back-propagation neural networks (BP-based method)" were utilized to test the success rate of species identification. Phylogenetic species concept and network analysis were employed to delimitate the species boundary in eight selected species groups. The results demonstrated that the COI barcode region performed better in phylogenetic reconstruction at genus and species levels than at higher-levels, but showed a little improvement in resolving the higher-level relationships when the third base data or both first and third base data were excluded. Most overlaps and incorrect identifications may be due to imperfect taxonomy, indicating the critical role of taxonomic revision in DNA barcoding study. Species boundary delimitation confirmed the presence of oversplitting in six species groups and suggested that each group should be treated as a single species.

摘要

我们测试了DNA条形码在蝗总科中的性能,并尝试使用细胞色素氧化酶亚基I(COI)条形码解决选定类群中的物种界限划分问题。应用了三种分析方法来重建系统发育。采用Kimura双参数(K2P)距离来评估种内变异和种间差异的重叠范围。利用“最佳匹配(BM)”、“最佳近匹配(BCM)”、“所有物种条形码(ASB)”和“反向传播神经网络(基于BP的方法)”来测试物种鉴定的成功率。采用系统发育物种概念和网络分析来划定八个选定物种组的物种界限。结果表明,COI条形码区域在属和种水平的系统发育重建中表现优于更高分类水平,但在排除第三位碱基数据或同时排除第一位和第三位碱基数据时,在解决更高分类水平关系方面略有改进。大多数重叠和错误鉴定可能是由于分类学不完善所致,这表明分类学修订在DNA条形码研究中的关键作用。物种界限划分证实了六个物种组中存在过度细分的情况,并建议将每个组视为一个单一物种。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8418/3869712/bae5fdc94105/pone.0082400.g001.jpg

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