Data from initial evaluation of DNA metabarcoding for processing continuous plankton recorder samples

Data stored in a Dryad package (doi:10.5061/dryad.c75sj) associated with the publication: Genetic monitoring of open ocean biodiversity: an evaluation of DNA metabarcoding for processing continuous plankton recorder samples Authors: Bruce Deagle , Laurence Clarke , John Kitchener, Andrea Polanowski,...

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Bibliographic Details
Other Authors: DEAGLE, BRUCE (hasPrincipalInvestigator), DEAGLE, BRUCE (processor), Australian Antarctic Data Centre (publisher)
Format: Dataset
Language:unknown
Published: Australian Antarctic Data Centre
Subjects:
Online Access:https://researchdata.ands.org.au/initial-evaluation-dna-recorder-samples/992335
https://doi.org/10.5061/dryad.c75sj
https://data.aad.gov.au/metadata/records/AAS_4313_Genetic_CPR
http://nla.gov.au/nla.party-617536
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Summary:Data stored in a Dryad package (doi:10.5061/dryad.c75sj) associated with the publication: Genetic monitoring of open ocean biodiversity: an evaluation of DNA metabarcoding for processing continuous plankton recorder samples Authors: Bruce Deagle , Laurence Clarke , John Kitchener, Andrea Polanowski, Andrew Davidson. Molecular Ecology Resources. The Continuous Plankton Recorder (CPR) has been used to characterise zooplankton biodiversity along transects covering hundreds of thousands of kilometres in the Southern Ocean CPR survey. Plankton collected by the CPR is currently identified using is classical taxonomy (i.e. using a microscope and morphological features). We investigated the potential to use DNA metabarcoding (species identification from DNA mixtures using high-throughput DNA sequencing) as a tool for rapid collection of taxonomic data from CPR samples. In our study, zooplankton were collected on CPR silks along two transects between Tasmania and Macquarie Island. Plankton were identified using standard microscopic methods and by sequencing a mitochondrial COI marker. Data provided in the Dryad Data entry include the DNA sequences (Illumina MiSeq) recovered, the morphological identifications and the R-code used to analyse these data. The results from our study show that a DNA-based approach increased the number of metazoan species identified and provided high resolution taxonomy of groups problematic in conventional surveys (e.g. larval echinoderms and hydrozoans). Metabarcoding also generally produced more detections than microscopy, but this sensitivity may make cross-contamination during sampling a problem. In some samples, the prevalence of DNA from larger plankton (such as krill) masked the presence of smaller species. Overall, the genetic data represents a substantial shift in perspective, making direct integration into current long-term time-series challenging. We discuss a number of hurdles that exist for progressing this powerful DNA metabarcoding approach from the current snapshot studies to the requirements of a long-term monitoring program.