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1. Recommendations for interpreting zooplankton metabarcoding and integrating molecular methods with morphological analyses

   https://doi.org/10.1093/icesjms/fsab107  

   Matthews, Stephanie A ; Goetze, Erica ; Ohman, Mark D ( June 2021 , ICES Journal of Marine Science)

   Hauser, Lorenz (Ed.)

   Abstract Metabarcoding of zooplankton communities is becoming more common, but molecular results must be interpreted carefully and validated with morphology-based analyses, where possible. To evaluate our metabarcoding approach within the California Current Ecosystem, we tested whether physical subsampling and PCR replication affects observed community composition; whether community composition resolved by metabarcoding is comparable to morphological analyses by digital imaging; and whether pH neutralization of ethanol with ammonium hydroxide affects molecular diversity. We found that (1) PCR replication was important to accurately resolve alpha diversity and that physical subsampling can decrease sensitivity to rare taxa; (2) there were significant correlations between relative read abundance and proportions of carbon biomass for most taxonomic groups analyzed, but such relationships showed better agreement for the more dominant taxonomic groups; and (3) ammonium hydroxide in ethanol had no effect on molecular diversity. Together, these results indicate that with appropriate replication, paired metabarcoding and morphological analyses can characterize zooplankton community structure and biomass, and that metabarcoding methods are to some extent indicative of relative community composition when absolute measures of abundance or biomass are not available. 

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

   https://doi.org/10.3389/fmars.2022.867893  

   Bucklin, Ann ; Batta-Lona, Paola G. ; Questel, Jennifer M. ; Wiebe, Peter H. ; Richardson, David E. ; Copley, Nancy J. ; O’Brien, Todd D. ( April 2022 , Frontiers in Marine Science)

   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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3. Metabarcoding Appalachian leaf litter arthropods

   Caterino, M.S. ; Recuero, E. ; Etzler, F.E. ( November 2022 , Entomological Society of America)
4. Minimizing polymerase biases in metabarcoding

   https://doi.org/10.1111/1755-0998.12895  

   Nichols, Ruth V. ; Vollmers, Christopher ; Newsom, Lee A. ; Wang, Yue ; Heintzman, Peter D. ; Leighton, McKenna ; Green, Richard E. ; Shapiro, Beth ( September 2018 , Molecular Ecology Resources)
5. Population Genomics of Marine Zooplankton

   https://doi.org/10.1007/13836_2017_9  

   Bucklin, A ; DiVito, K ; Smolina, I ; Choquet, M ; Questel, JM ; Hoarau, G ; O’Neill, RJ ( January 2018 , Population Genomics)

   The exceptionally large population size and cosmopolitan biogeographic distribution that distinguish many – but not all – marine zooplankton species generate similarly exceptional patterns of population genetic and genomic diversity and structure. The phylogenetic diversity of zooplankton has slowed the application of population genomic approaches, due to lack of genomic resources for closelyrelated species and diversity of genomic architecture, including highly-replicated genomes of many crustaceans. Use of numerous genomic markers, especially single nucleotide polymorphisms (SNPs), is transforming our ability to analyze population genetics and connectivity of marine zooplankton, and providing new understanding and different answers than earlier analyses, which typically used mitochondrial DNA and microsatellite markers. Population genomic approaches have confirmed that, despite high dispersal potential, many zooplankton species exhibit genetic structuring among geographic populations, especially at large ocean-basin scales, and have revealed patterns and pathways of population connectivity that do not always track ocean circulation. Genomic and transcriptomic resources are critically needed to allow further examination of micro-evolution and local adaptation, including identification of genes that show evidence of selection. These new tools will also enable further examination of the significance of small-scale genetic heterogeneity of marine zooplankton, to discriminate genetic “noise” in large and patchy populations from local adaptation to environmental conditions and change. 

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