SNSB-Zoologische Staatssammlung, München, Germany.
Zoological Research Museum Alexander Koenig - Leibniz Institute for Animal Biodiversity, Bonn, Germany.
Mol Ecol Resour. 2019 Jul;19(4):900-928. doi: 10.1111/1755-0998.13022. Epub 2019 May 14.
This study summarizes results of a DNA barcoding campaign on German Diptera, involving analysis of 45,040 specimens. The resultant DNA barcode library includes records for 2,453 named species comprising a total of 5,200 barcode index numbers (BINs), including 2,700 COI haplotype clusters without species-level assignment, so called "dark taxa." Overall, 88 out of 117 families (75%) recorded from Germany were covered, representing more than 50% of the 9,544 known species of German Diptera. Until now, most of these families, especially the most diverse, have been taxonomically inaccessible. By contrast, within a few years this study provided an intermediate taxonomic system for half of the German Dipteran fauna, which will provide a useful foundation for subsequent detailed, integrative taxonomic studies. Using DNA extracts derived from bulk collections made by Malaise traps, we further demonstrate that species delineation using BINs and operational taxonomic units (OTUs) constitutes an effective method for biodiversity studies using DNA metabarcoding. As the reference libraries continue to grow, and gaps in the species catalogue are filled, BIN lists assembled by metabarcoding will provide greater taxonomic resolution. The present study has three main goals: (a) to provide a DNA barcode library for 5,200 BINs of Diptera; (b) to demonstrate, based on the example of bulk extractions from a Malaise trap experiment, that DNA barcode clusters, labelled with globally unique identifiers (such as OTUs and/or BINs), provide a pragmatic, accurate solution to the "taxonomic impediment"; and (c) to demonstrate that interim names based on BINs and OTUs obtained through metabarcoding provide an effective method for studies on species-rich groups that are usually neglected in biodiversity research projects because of their unresolved taxonomy.
本研究总结了德国双翅目昆虫 DNA 条形码研究计划的结果,共分析了 45,040 个标本。由此产生的 DNA 条形码文库包含了 2,453 个已命名物种的记录,共包含 5,200 个条形码索引编号(BIN),其中包括 2,700 个无种级分配的 COI 单倍型聚类,即所谓的“暗类群”。总体而言,德国记录的 117 科中的 88 科(75%)都有涉及,代表了德国已知 9,544 种双翅目昆虫的 50%以上。到目前为止,这些科中大多数,尤其是最多样化的科,在分类学上都难以触及。相比之下,在短短几年内,这项研究为德国双翅目动物区系的一半提供了一个中间分类系统,这将为随后的详细综合分类学研究提供有用的基础。通过使用由巴氏诱捕器采集的混合样本中提取的 DNA 进行研究,我们进一步证明,使用 BIN 和操作分类单元(OTU)进行物种划分是使用 DNA 代谢组学进行生物多样性研究的一种有效方法。随着参考文库的不断增长,以及物种名录中的空白不断填补,代谢组学组装的 BIN 列表将提供更高的分类分辨率。本研究有三个主要目标:(a)为双翅目 5,200 个 BIN 提供 DNA 条形码文库;(b)通过巴氏诱捕器实验的混合提取实例证明,标记有全球唯一标识符(如 OTU 和/或 BIN)的 DNA 条形码聚类为“分类障碍”提供了一种实用、准确的解决方案;(c)证明基于通过代谢组学获得的 BIN 和 OTU 的临时名称是一种有效的方法,可用于研究通常由于其分类学未解决而在生物多样性研究项目中被忽略的物种丰富类群。