Metabarcoding reveals hidden species and improves identification of marine zooplankton communities in the North Sea

Abstract

Abstract 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.