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Metabarcoding reveals hidden species and improves identification of marine zooplankton communities in the North Sea
ICES Journal of Marine Science ( IF 3.3 ) Pub Date : 2021-02-28 , DOI: 10.1093/icesjms/fsaa256
Ilias Semmouri 1 , Karel A C De Schamphelaere 1 , Stijn Willemse 1 , Michiel B Vandegehuchte 2 , Colin R Janssen 1, 3 , Jana Asselman 1, 3
Affiliation  

Although easily collected in large numbers, the subsequent processing and identification of zooplankton have usually been a barrier to large-scale biodiversity assessments. Therefore, DNA barcoding has been increasingly used by non-taxonomists to identify specimens. Here, we studied the community composition of zooplankton in the Belgian part of the North Sea over the course of 1 year. We identified zooplankton using both a traditional approach based on morphological characteristics and by metabarcoding of a 650 bp fragment of the V4-V5 region of the 18S rRNA gene using nanopore sequencing. Using long rDNA sequences, we were able to identify several taxa at the species level, across a broad taxonomic scale. Using both methods, we compared community composition and obtained diversity metrics. Diversity indices were not significantly correlated. Metabarcoding allowed for comparisons of diversity and community composition, but not all groups were successfully sequenced. Additionally, some disparities existed between relative abundances of the most abundant taxa based on traditional counts and those based on sequence reads. Overall, we conclude that for zooplankton samples, metabarcoding is capable of detecting taxa with a higher resolution, regardless of developmental stage of the organism. Combination of molecular and morphological methods results in the highest detection and identification levels of zooplankton.

中文翻译:

元条形码揭示了隐藏的物种并改善了北海海洋浮游动物群落的识别

尽管很容易大量收集,但是浮游动物的后续加工和识别通常是大规模生物多样性评估的障碍。因此,非分类学家越来越多地使用DNA条形码来识别标本。在这里,我们研究了北海比利时部分地区历时1年的浮游动物的群落组成。我们使用传统的基于形态学特征的方法和通过纳米孔测序对18S rRNA基因V4-V5区的650 bp片段进行metabarcoding鉴定浮游动物。使用长的rDNA序列,我们能够在广泛的分类学规模上在物种水平上鉴定出几个分类单元。使用这两种方法,我们比较了社区组成并获得了多样性指标。多样性指数没有显着相关。元条形码可以比较多样性和群落组成,但并非所有组均已成功测序。此外,在基于传统计数的最丰富分类单元的相对丰度与基于序列读数的相对丰富度之间存在一些差异。总体而言,我们得出结论,对于浮游动物样本,无论生物体的发育阶段如何,元条形码都能以更高的分辨率检测分类单元。分子和形态学方法的结合导致浮游动物的最高检测和鉴定水平。总体而言,我们得出结论,对于浮游动物样本,无论生物体的发育阶段如何,元条形码都能以更高的分辨率检测分类单元。分子和形态学方法的结合导致浮游动物的最高检测和鉴定水平。总体而言,我们得出结论,对于浮游动物样本,无论生物体的发育阶段如何,元条形码都能以更高的分辨率检测分类单元。分子和形态学方法的结合导致浮游动物的最高检测和鉴定水平。
更新日期:2021-02-28
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