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在黑暗中进行条码编制?对动物 DNA 条码数据库充分性的批判性观察,以及对更广泛整合分类学知识的呼吁。

Barcoding in the dark? A critical view of the sufficiency of zoological DNA barcoding databases and a plea for broader integration of taxonomic knowledge.

机构信息

Museum of Comparative Zoology, Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, USA.

出版信息

Mol Phylogenet Evol. 2013 Oct;69(1):39-45. doi: 10.1016/j.ympev.2013.05.012. Epub 2013 May 28.

Abstract

The functionality of standard zoological DNA barcoding practice (the identification of unknown specimens by comparison of COI sequences) is contingent on working barcode databases with sufficient taxonomic coverage. It has already been established that the main barcoding repositories, NCBI and BOLD, are devoid of data for many animal groups but the specific taxonomic coverage of the repositories across animal biodiversity remains unexplored. Here, I shed light on this mystery by contrasting the number of unique taxon labels in the two databases with the number of currently recognized species for each animal phylum. The numbers reveal an overall paucity of COI sequence data in the repositories (15.13% total coverage across the recognized biodiversity on Earth, and 20.76% average taxonomic coverage for each phylum) and, more importantly, bear witness to the idleness towards numerous phyla, rendering current barcoding efforts either ineffective or inaccurate. The importance of further integrating taxonomic expertise into barcoding practice is briefly discussed and some guidelines, previously mentioned in the barcoding literature, are suggested anew. Finally, the asserted values concerning the taxonomic coverage in barcoding databases for Animalia are contrasted with those of Plantae and Fungi.

摘要

标准动物 DNA 条码实践(通过比较 COI 序列鉴定未知标本)的功能取决于使用具有足够分类学覆盖范围的条码数据库。已经确定,主要的条码存储库 NCBI 和 BOLD 缺乏许多动物群的数据,但这些存储库在动物生物多样性方面的具体分类学覆盖范围仍未得到探索。在这里,我通过将两个数据库中的独特分类标签数量与每个动物门目前公认的物种数量进行对比,揭示了这个谜团。这些数字揭示了存储库中 COI 序列数据的总体匮乏(地球上已识别生物多样性的总覆盖率为 15.13%,每个门的平均分类学覆盖率为 20.76%),更重要的是,这些数字证明了对许多门的忽视,使得当前的条码工作要么无效,要么不准确。本文简要讨论了进一步将分类学专业知识纳入条码实践的重要性,并重新提出了条码文献中提到的一些准则。最后,对比了动物界条码数据库中分类学覆盖范围的主张值与植物界和真菌界的主张值。

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