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ABSTRACT DNA metabarcoding of zooplankton biodiversity is used increasingly for monitoring global ocean ecosystems, requiring comparable data from different research laboratories and ocean regions. The MetaZooGene Intercalibration Experiment (MZG‐ICE) was designed to examine1 and analyse patterns of variation of DNA sequence data resulting from multi‐gene metabarcoding of 10 zooplankton samples carried out by 10 research groups affiliated with the Scientific Committee for Ocean Research (SCOR). Aliquots of DNA extracted from the 10 zooplankton samples were distributed to MZG‐ICE groups for metabarcoding of four gene regions: V1‐V2, V4 and V9 of nuclear 18S rRNA and mitochondrial COI. Molecular protocols and procedures were recommended; substitutions were allowed as necessary. Resulting data were uploaded to a common repository for centralised statistics and bioinformatics. Based on proportional sequence numbers for abundant phyla, overall patterns of variation were consistent across many—but not all—MZG‐ICE groups. V9 showed highest similarity, followed (in order) by V4, V1‐V2, and COI. Outlier data were hypothesised to result from the use of different PCR protocols and sequencing platforms, and possible contamination. MZG‐ICE results indicated that DNA metabarcoding data from different laboratories and research groups can provide reliable, accurate and valid descriptions of biodiversity of zooplankton throughout the ocean. Recommendations included: pre‐screening QA/QC of raw data, detailed records for laboratory protocols, reagents, and instrumentation, and centralised bioinformatics and multivariate statistics. In the absence of universal agreement on standardised protocols or best practices, intercalibration is the best way forward toward validation of DNA metabarcoding of zooplankton diversity for global ocean monitoring.
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Towards eradicating the nuisance of numts and noise in molecular biodiversity assessment
DNA metabarcoding is a popular methodology for biodiversity assessment and increasingly used for community level analysis of intraspecific genetic diversity. The evolutionary history of hundreds of specimens can be captured in a single collection vial. However, the method is not without pitfalls, which may inflate or misrepresent recovered diversity metrics. Nuclear pseudogene copies of mitochondrial DNA (numts) have been particularly difficult to control because they can evolve rapidly and appear deceptively similar to true mitochondrial sequences. While the problem of numts has long been recognized for traditional sequencing approaches, the issues they create are particularly evident in metabarcoding in which the identity of individual specimens is generally not known. In this issue ofMolecular Ecology Resources, Andújar et al. (2021) provide an easy to implement bioinformatic approach to reduce erroneous sequences due to numts and residual noise in metabarcoding data sets. The metaMATE software designates input sequences as authentic (mtDNA haplotypes) or nonauthentic (numts and erroneous sequences) by comparison to reference data and by analysing nucleotide substitution patterns. Filtering is applied over a range of abundance thresholds and the choice to proceed with a more rigid or less strict sequence removal strategy is at the researchers’ discretion. This is a valuable addition to a growing number of complementary tools for improving the reliability of modern biodiversity monitoring.
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- Award ID(s):
- 1927510
- PAR ID:
- 10449329
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Molecular Ecology Resources
- Volume:
- 21
- Issue:
- 6
- ISSN:
- 1755-098X
- Page Range / eLocation ID:
- p. 1755-1758
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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