Metabarcoding of marine zooplankton in South Africa

Singh, Sohana P.; Groeneveld, JC; Huggett, Jenny A.; Naidoo, Dhesigen; Cedras, Riaan; Willows‐Munro, Sandi

doi:10.2989/1814232x.2021.1919759

Cited by 12 publications

(23 citation statements)

References 67 publications

(72 reference statements)

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“…Various solutions have been proposed, including using multiple COI sub-regions, with specially-designed primers for target groups (Leray et al, 2013;Corell and Rodrıǵuez-Ezpeleta, 2014;Elbrecht and Leese, 2017;Elbrecht et al, 2019) and integrative multi-region sequence analysis and bioinformatics (Antich et al, 2021;Creedy et al, 2021). Most importantly, classification and identification of species based on COI metabarcodes requires a taxonomicallycomplete and geographically-appropriate reference sequence database (Leray and Knowlton, 2017;Singh et al, 2021). Continued effort is needed to allow and ensure progress toward inclusion of COI barcode sequences for all zooplankton species, including sibling and cryptic species, recorded from regions throughout the global ocean (Bucklin et al, 2021b).…”

Section: S3mentioning

confidence: 99%

“…The potential of COI metabarcoding has been examined from many perspectives, including accuracy of species-level resolution of biodiversity (Brown et al, 2015;Leray and Knowlton, 2017;Schroeder et al, 2021), availability of reference sequence databases resulting from DNA barcoding efforts (Andújar et al, 2018;Porter and Hajibabaei, 2018;Bucklin et al, 2021b;Singh et al, 2021), and prospects for quantitative analysis related to species abundance and/or biomass (Lamb et al, 2018;Matthews et al, 2021). Challenges and disadvantages of COI as a metabarcode include lack of universal primers and missing groups due to primer-mismatch (Deagle et al, 2014;Clarke et al, 2017;Hajibabaei et al, 2019).…”

Section: Introduction Metabarcoding Of Zooplankton Diversitymentioning

confidence: 99%

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COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

et al. 2022

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Marine zooplankton are rapid-responders and useful indicators of environmental variability and climate change impacts on pelagic ecosystems on time scales ranging from seasons to years to decades. The systematic complexity and taxonomic diversity of the zooplankton assemblage has presented significant challenges for routine morphological (microscopic) identification of species in samples collected during ecosystem monitoring and fisheries management surveys. Metabarcoding using the mitochondrial Cytochrome Oxidase I (COI) gene region has shown promise for detecting and identifying species of some – but not all – taxonomic groups in samples of marine zooplankton. This study examined species diversity of zooplankton on the Northwest Atlantic Continental Shelf using 27 samples collected in 2002-2012 from the Gulf of Maine, Georges Bank, and Mid-Atlantic Bight during Ecosystem Monitoring (EcoMon) Surveys by the NOAA NMFS Northeast Fisheries Science Center. COI metabarcodes were identified using the MetaZooGene Barcode Atlas and Database (https://metazoogene.org/MZGdb) specific to the North Atlantic Ocean. A total of 181 species across 23 taxonomic groups were detected, including a number of sibling and cryptic species that were not discriminated by morphological taxonomic analysis of EcoMon samples. In all, 67 species of 15 taxonomic groups had ≥ 50 COI sequences; 23 species had >1,000 COI sequences. Comparative analysis of molecular and morphological data showed significant correlations between COI sequence numbers and microscopic counts for 5 of 6 taxonomic groups and for 5 of 7 species with >1,000 COI sequences for which both types of data were available. Multivariate statistical analysis showed clustering of samples within each region based on both COI sequence numbers and EcoMon counts, although differences among the three regions were not statistically significant. The results demonstrate the power and potential of COI metabarcoding for identification of species of metazoan zooplankton in the context of ecosystem monitoring.

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Section: S3mentioning

confidence: 99%

Section: Introduction Metabarcoding Of Zooplankton Diversitymentioning

confidence: 99%

COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

et al. 2022

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“…Similarly, we found a significant reduction in false results in both the mock and coastal zooplankton analyses when using primer cocktails. The false-positive readings were attributed to low taxonomic coverage within reference databases (see Singh et al 2021) combined with the relatively high level of stringency (95% match threshold) applied in our annotation pipeline (Valsecchi et al 2020).…”

Section: Discussionmentioning

confidence: 99%

“…The false‐positive readings were attributed to low taxonomic coverage within reference databases (see Singh et al. 2021) combined with the relatively high level of stringency (95% match threshold) applied in our annotation pipeline (Valsecchi et al. 2020).…”

Section: Discussionmentioning

confidence: 99%

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Experimental validation of taxon‐specific mini‐barcode primers for metabarcoding of zooplankton

Govender

Singh

Groeneveld

et al. 2021

Ecological Applications

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Metabarcoding to determine the species composition and diversity of marine zooplankton communities is a fast‐developing field in which the standardization of methods is yet to be fully achieved. The selection of genetic markers and primer choice are particularly important because they substantially influence species detection rates and accuracy. Validation is therefore an important step in the design of metabarcoding protocols. We developed taxon‐specific mini‐barcode primers for the cytochrome c oxidase subunit I (COI) gene region and used an experimental approach to test species detection rates and primer accuracy of the newly designed primers for prawns, shrimps and crabs and published primers for marine lobsters and fish. Artificially assembled mock communities (with known species ratios) and unsorted coastal tow‐net zooplankton samples were sequenced and the detected species were compared with those seeded in mock communities to test detection rates. Taxon‐specific primers increased detection rates of target taxa compared with a universal primer set. Primer cocktails (multiple primer sets) significantly increased species detection rates compared with single primer pairs and could detect up to 100% of underrepresented target taxa in mock communities. Taxon‐specific primers recovered fewer false‐positive or false‐negative results than the universal primer. The methods used to design taxon‐specific mini‐barcodes and the experimental mock community validation protocols shown here can easily be applied to studies on other groups and will allow for a level of standardization among studies undertaken in different ecosystems or geographic locations.

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Extending deep-sea benthic biodiversity inventories with environmental DNA metabarcoding

Oosthuizen

Seymour²,

Atkinson

et al. 2023

Mar Biol

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Inventories of biodiversity are crucial for helping support conservation and management efforts, yet the deep-sea, which is the largest biome on earth remains vastly understudied. Recent advances in molecular detection methods offer alternative techniques for studying inaccessible ecosystems, including those at depth. In this study we utilized environmental DNA metabarcoding, a first for studying deep-sea benthic environments in southern Africa, to assess biological diversity and to test the effects of depth and historical trawling activities on deep-sea communities. Utilising 29 sediment samples (thus focussing on predominantly meiofaunal and epifaunal biodiversity) and targeting a 313 bp region of the mtDNA cytochrome oxidase I gene, we recovered 444 OTUs across a wide array of species and genera. Even though many OTUs could only be assigned to higher taxonomic levels, results showed that biodiversity differed significantly across depth, suggesting that even at relatively small spatial scales (~ 6 km, across a depth gradient of 355 m to 515 m), eDNA derived biodiversity detected variation linked to the depth gradient. Comparison of the OTU database with known species inventories from the sampled area revealed little overlap, highlighting the need for expanding barcoding efforts of deep-sea species to aid future eDNA survey efforts. Overall our results suggest that within a South African context, increased barcoding efforts, in combination with eDNA metabarcoding and physical sampling could capture a greater proportion of benthic deep-sea biodiversity. This provides additional opportunities to underpin conservation and management decision-making in the region, such as evaluating potential sites for future protection.

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Metabarcoding of marine zooplankton in South Africa

Cited by 12 publications

References 67 publications

COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

Experimental validation of taxon‐specific mini‐barcode primers for metabarcoding of zooplankton

Extending deep-sea benthic biodiversity inventories with environmental DNA metabarcoding

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