Significant taxon sampling gaps in DNA databases limit the operational use of marine macrofauna metabarcoding
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ORIGINAL PAPER
Significant taxon sampling gaps in DNA databases limit the operational use of marine macrofauna metabarcoding Jon Thomassen Hestetun 1 & Einar Bye-Ingebrigtsen 1 Per-Otto Johansen 1 & Thomas G. Dahlgren 1,3,5
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R. Henrik Nilsson 2,3
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Adrian G. Glover 4
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Received: 17 September 2018 / Revised: 22 June 2020 / Accepted: 6 July 2020 # The Author(s) 2020
Abstract Significant effort is spent on monitoring of benthic ecosystems through government funding or indirectly as a cost of business, and metabarcoding of environmental DNA samples has been suggested as a possible complement or alternative to current morphological methods to assess biodiversity. In metabarcoding, a public sequence database is typically used to match barcodes to species identity, but these databases are naturally incomplete. The North Sea oil and gas industry conducts large-scale environmental monitoring programs in one of the most heavily sampled marine areas worldwide and could therefore be considered a “best-case scenario” for macrofaunal metabarcoding. As a test case, we investigated the database coverage of two common metabarcoding markers, mitochondrial COI and the ribosomal rRNA 18S gene, for a complete list of 1802 macrofauna taxa reported from the North Sea monitoring region IV. For COI, species level barcode coverage was 50.4% in GenBank and 42.4% for public sequences in BOLD. For 18S, species level coverage was 36.4% in GenBank and 27.1% in SILVA. To see whether rare species were underrepresented, we investigated the most commonly reported species as a separate dataset but found only minor coverage increases. We conclude that compared to global figures, barcode coverage is high for this area, but that a significant effort remains to fill barcode databases to levels that would make metabarcoding operational as a taxonomic tool, including for the most common macrofaunal taxa. Keywords Barcodes . Biomonitoring . North Sea . Benthic . COI . 18S
Introduction Communicated by K. Kocot Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12526-020-01093-5) contains supplementary material, which is available to authorized users. * Thomas G. Dahlgren [email protected] 1
NORCE Norwegian Research Centre, Nygårdsgaten 112, 5008 Bergen, Norway
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Department of Biological and Environmental Sciences, University of Gothenburg, PO Box 463, 405 30 Göteborg, Sweden
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Gothenburg Global Biodiversity Centre, PO Box 461, SE-405 30 Göteborg, Sweden
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Life Sciences Department, Natural History Museum, Cromwell Rd, London SW7 5BD, UK
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Department of Marine Sciences, University of Gothenburg, PO Box 463, 405 30 Göteborg, Sweden
Advances in molecular biology and computer technology have redefined the way most areas of natural sciences are carried out, but assessment of biodiversity has yet to take full advantage of these technology leaps (e.g., Taberlet et al. 2012; Bourlat et al. 2013). In particular, the practice of using estimates of biodiversity change to understand the extent of anthrop
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