ArticlePloS one2024
Assigning the unassigned: A signature-based classification of rDNA metabarcodes reveals new deep-sea diversity.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Sanctuary for vulnerable Arctic species at the Borealis Mud Volcano.Nature communications · 2025Article
- Sediment eDNA metabarcoding reveals the endemism in benthic foraminifera from Arctic methane cold seepages.ISME communications · 2025Article
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Authors and funding
5 authors.
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Abstract
Environmental DNA metabarcoding reveals a vast genetic diversity of marine eukaryotes. Yet, most of the metabarcoding data remain unassigned due to the paucity of reference databases. This is particularly true for the deep-sea meiofauna and eukaryotic microbiota, whose hidden diversity is largely unexplored. Here, we tackle this issue by using unique DNA signatures to classify unknown metabarcodes assigned to deep-sea foraminifera. We analyzed metabarcoding data obtained from 311 deep-sea sediment samples collected in the Clarion-Clipperton Fracture Zone, an area of potential polymetallic nodule exploitation in the Eastern Pacific Ocean. Using the signatures designed in the 37F hypervariable region of the 18S rRNA gene, we were able to classify 802 unassigned metabarcodes into 61 novel lineages, which have been placed in 27 phylogenetic clades. The comparison of new lineages with other foraminiferal datasets shows that most novel lineages are widely distributed in the deep sea. Five lineages are also present in the shallow-water datasets; however, phylogenetic analysis of these lineages separates deep-sea and shallow-water metabarcodes except in one case. While the signature-based classification does not solve the problem of gaps in reference databases, this taxonomy-free approach provides insight into the distribution and ecology of deep-sea species represented by unassigned metabarcodes, which could be useful in future applications of metabarcoding for environmental monitoring.
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