Data from: Identification of North Sea molluscs with DNA barcoding

Sequence-based specimen identification, known as DNA barcoding, is a common method complementing traditional morphology-based taxonomic assignments. The fundamental resource in DNA barcoding is the availability of a taxonomically reliable sequence database to use as a reference for sequence comparisons. Here, we provide a reference library including 579 sequences of the mitochondrial cytochrome c oxidase subunit I for 113 North Sea mollusc species. We tested the efficacy of this library by simulating a sequence-based specimen identification scenario using Best Match, Best Close Match (BCM) and All Species Barcode (ASB) criteria with three different threshold values. Each identification result was compared with our prior morphology-based taxonomic assignments. Our simulation resulted in 87.7% congruent identifications (93.8% when excluding singletons). The highest number of congruent identifications was obtained with BCM and ASB and a 0.05 threshold. We also compared identifications with genetic clustering (Barcode Index Numbers, BINs) computed by the Barcode of Life Datasystem (BOLD). About 68% of our morphological identifications were congruent with BINs created by BOLD. Forty-nine sequences were clustered in 16 discordant BINs, and these were divided in two classes: sequences from different species clustered in a single BIN and conspecific sequences divided in more BINs. Whereas former incongruences were probably caused by BOLD entries in need of a taxonomic update, the latter incongruences regarded taxa requiring further investigations. These include species with amphi-Atlantic distribution, whose genetic structure should be evaluated over their entire range to produce a reliable sequence-based identification system.

基于序列的标本鉴定技术，即DNA条形码（DNA barcoding），是一类常用于补充传统基于形态学的分类鉴定工作的通用方法。DNA条形码技术的核心基础资源，是一套可供序列比对分析使用的、具备分类学可靠性的序列参考数据库。本研究构建了一套参考文库，涵盖113种北海软体动物的579条线粒体细胞色素c氧化酶亚基I（mitochondrial cytochrome c oxidase subunit I）序列。我们通过模拟基于序列的标本鉴定场景，对该文库的鉴定效能进行了验证：分别采用最佳匹配（Best Match）、最近匹配（Best Close Match, BCM）以及全物种条形码（All Species Barcode, ASB）三种判定准则，并设置了三种不同的阈值参数。将每一组鉴定结果与本研究前期获得的基于形态学的分类鉴定结果进行比对。模拟分析结果显示，整体一致鉴定率为87.7%；若排除仅包含单条序列的物种样本，则一致率可达93.8%。采用BCM与ASB准则并设置0.05的阈值时，可获得最多的一致鉴定结果。此外，我们还将鉴定结果与生命条形码数据系统（Barcode of Life Datasystem, BOLD）计算得到的遗传聚类结果——条形码索引编号（Barcode Index Numbers, BINs）——进行了比对。约68%的形态学鉴定结果与BOLD生成的BINs相一致。共有49条序列被聚类至16个不一致的BINs中，这类不一致可分为两类：一类是来自不同物种的序列被聚类至同一个BIN内，另一类是同一物种种群的序列被拆分至多个不同的BIN中。前者的不一致现象大概率源于BOLD数据库中的条目亟需进行分类学更新，而后者则涉及需要开展进一步研究的类群。这些类群包含泛大西洋分布的物种，其遗传结构需要在整个分布范围内进行系统性评估，方可构建出可靠的基于序列的标本鉴定系统。