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Biases in bulk: DNA metabarcoding of marine communities and the methodology involved
In: Molecular Ecology. Blackwell: Oxford. ISSN 0962-1083; e-ISSN 1365-294X, meer
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Trefwoord |
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Author keywords |
Metabarcoding, marine monitoringtechnical biases |
Abstract |
With the growing anthropogenic pressure on marine ecosystems, the need for efficient monitoring of biodiversity grows stronger. DNA metabarcoding of bulk samples is increasingly being implemented in ecosystem assessments and is more cost‐efficient and less time‐consuming than monitoring based on morphology. However, before raw sequences are obtained from bulk samples, a profound number of methodological choices must be made. Here, we critically review the recent methods used for metabarcoding of marine bulk samples (including benthic, plankton and diet samples) and indicate how potential biases can be introduced throughout sampling, preprocessing, DNA extraction, marker and primer selection, PCR amplification and sequencing. From a total of 64 studies evaluated, our recommendations for best practices include to (a) consider DESS as a fixative instead of ethanol, (b) use the DNeasy PowerSoil kit for any samples containing traces of sediment, (c) not limit the marker selection to COI only, but preferably include multiple markers for higher taxonomic resolution, (d) avoid touchdown PCR profiles, (e) use a fixed annealing temperature for each primer pair when comparing across studies or institutes, (f) use a minimum of three PCR replicates, and (g) include both negative and positive controls. Although the implementation of DNA metabarcoding still faces several technical complexities, we foresee wide‐ranging advances in the near future, including improved bioinformatics for taxonomic assignment, sequencing of longer fragments and the use of whole‐genome information. Despite the bulk of biases involved in metabarcoding of bulk samples, if appropriate controls are included along the data generation process, it is clear that DNA metabarcoding provides a valuable tool in ecosystem assessments. |
Dataset |
- GEANS Data: Genetic tools for Ecosystem health Assessment in the North Sea region, meer
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