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1. Comparative analysis of zooplankton diversities and compositions estimated from complement DNA and genomic DNA amplicons, metatranscriptomics, and morphological identifications

   https://doi.org/10.1093/icesjms/fsab084  

   Machida, Ryuji J ; Kurihara, Haruko ; Nakajima, Ryota ; Sakamaki, Takashi ; Lin, Ya-Ying ; Furusawa, Kazushi ( June 2021 , ICES Journal of Marine Science)

   Fields, David (Ed.)

   Abstract Community-based diversity analyses, such as metabarcoding, are increasingly popular in the field of metazoan zooplankton community ecology. However, some of the methodological uncertainties remain, such as the potential inflation of diversity estimates resulting from contamination by pseudogene sequences. Furthermore, primer affinity to specific taxonomic groups might skew community composition and structure during PCR. In this study, we estimated OTU (operational taxonomic unit) richness, Shannon’s H’, and the phylum-level community composition of samples from a coastal zooplankton community using four approaches: complement DNA (cDNA) and genomic DNA (gDNA) mitochondrial COI (Cytochrome oxidase subunit I) gene amplicon, metatranscriptome sequencing, and morphological identification. Results of mismatch distribution demonstrated that 90% is good threshold percentage to differentiate intra- and inter-species. Moderate level of correlations appeared upon comparing the species/OTU richness estimated from the different methods. Results strongly indicated that diversity inflation occurred in the samples amplified from gDNA because of mitochondrial pseudogene contamination (overall, gDNA produced two times more richness compared with cDNA amplicons). The unique community compositions observed in the PCR-based methods indicated that taxonomic amplification bias had occurred during the PCR. Therefore, it is recommended that PCR-free approaches be used whenever resolving community structure represents an essential aspect of the analysis.
2. New insights into biodiversity, biogeography, ecology, and evolution of marine zooplankton based on molecular approaches

   https://doi.org/10.1093/icesjms/fsab198  

   Bucklin, Ann ; Peijnenburg, Katja T. C. A. ; Kosobokova, Ksenia ; Machida, Ryuji J. ; Browman, ed., Howard ( October 2021 , ICES Journal of Marine Science)

   Marine zooplankton are key players in pelagic food webs, central links in ecosystem function, useful indicators of water masses, and rapid responders to environmental variation and climate change. Characterization of biodiversity of the marine zooplankton assemblage is complicated by many factors, including systematic complexity of the assemblage, with numerous rare and cryptic species, and high local-to-global ratios of species diversity. The papers in this themed article set document important advances in molecular protocols and procedures, integration with morphological taxonomic identifications, and quantitative analyses (abundance and biomass). The studies highlight several overarching conclusions and recommendations. A primary issue is the continuing need for morphological taxonomic experts, who can identify species and provide voucher specimens for reference sequence databases, which are essential for biodiversity analyses based on molecular approaches. The power of metabarcoding using multi-gene markers, including both DNA (Deoxyribonucleic Acid) and RNA (Ribonucleic Acid)templates, is demonstrated. An essential goal is the accurate identification of species across all taxonomic groups of marine zooplankton, with particular concern for detection of rare, cryptic, and invasive species. Applications of molecular approaches include analysis of trophic relationships by metabarcoding of gut contents, as well as investigation of the underlying ecological and evolutionary forces driving zooplanktonmore »diversity and structure.

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3. 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 COImore »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.« less
4. Vertical gradients in species richness and community composition across the twilight zone in the North Pacific Subtropical Gyre

   https://doi.org/10.1111/mec.14286  

   Sommer, Stephanie A. ; Van Woudenberg, Lauren ; Lenz, Petra H. ; Cepeda, Georgina ; Goetze, Erica ( September 2017 , Molecular Ecology)

   Although metazoan animals in the mesopelagic zone play critical roles in deep pelagic food webs and in the attenuation of carbon in midwaters, the diversity of these assemblages is not fully known. A metabarcoding survey of mesozooplankton diversity across the epipelagic, mesopelagic and upper bathypelagic zones (0–1500 m) in the North Pacific Subtropical Gyre revealed far higher estimates of species richness than expected given prior morphology‐based studies in the region (4,024OTUs, 10‐fold increase), despite conservative bioinformatic processing. Operational taxonomic unit (OTU) richness of the full assemblage peaked at lower epipelagic–upper mesopelagic depths (100–300 m), with slight shoaling of maximal richness at night due to diel vertical migration, in contrast to expectations of a deep mesopelagic diversity maximum as reported for several plankton groups in early systematic and zoogeographic studies. Four distinct depth‐stratified species assemblages were identified, with faunal transitions occurring at 100 m, 300 m and 500 m. Highest diversity occurred in the smallest zooplankton size fractions (0.2–0.5 mm), which had significantly lower %OTUs classified due to poor representation in reference databases, suggesting a deep reservoir of poorly understood diversity in the smallest metazoan animals. A diverse meroplankton assemblage also was detected (350OTUs), including larvae of both shallow and deep livingmore »benthic species. Our results provide some of the first insights into the hidden diversity present in zooplankton assemblages in midwaters, and a molecular reappraisal of vertical gradients in species richness, depth distributions and community composition for the full zooplankton assemblage across the epipelagic, mesopelagic and upper bathypelagic zones.

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5. The precautionary principle and dietary DNA metabarcoding: commonly used abundance thresholds change ecological interpretation

   https://doi.org/10.5061/dryad.kwh70rz4s  

   Littleford-Colquhoun, Bethan ; Freeman, Patrick ; Sackett, Violet ; Tulloss, Camille ; McGarvey, Lauren ; Geremia, Chris ; Kartzinel, Tyler ( January 2021 )

   Abstract

   Dietary DNA metabarcoding enables researchers to identify and characterize trophic interactions with a high degree of taxonomic precision. It is also sensitive to sources of bias and contamination in the field and lab. One of the earliest and most common strategies for dealing with such sensitivities has been to filter resulting sequence data to remove low-abundance sequences before conducting ecological analyses based on the presence or absence of food taxa. Although this step is now often perceived to be both necessary and sufficient for cleaning up datasets, evidence to support this perception is lacking and more attention needs to be paid to the related risk of introducing other undesirable errors. Using computer simulations, we demonstrate that common strategies to remove low-abundance sequences can erroneously eliminate true dietary sequences in ways that impact downstream dietary inferences. Using real data from well-studied wildlife populations in Yellowstone National Park, we further show how these strategies can markedly alter the composition of individual dietary profiles in ways that scale-up to obscure ecological interpretations about dietary generalism, specialism, and niche partitioning. Although the practice of removing low-abundance sequences may continue to be a useful strategy to address a subset of research questions that focus on a subset of relatively abundant food resources, its continued widespread use risks generating misleading perceptions about the structure of trophic networks. Researchers working with dietary DNA metabarcoding data—or similar data such as environmental DNA, microbiomes, or pathobiomes—should be aware of potential drawbacks and consider alternative bioinformatic, experimental, and statistical solutions.
   

   Methods

   We used fecal DNA metabarcoding to characterize the diets of bison and bighorn sheep in winter and summer. Our analyses are based on 35 samples (median per species per season = 10) analyzed using the P6 loop of the chloroplast trnL(UAA) intron together with publicly available plant reference data (Illumina sequence read data are available at NCBI (BioProject: PRJNA780500)). Obicut was used to trim reads with a minimum quality threshold of 30, and primers were removed from forward and reverse reads using cutadapt. All further sequence identifications were performed using obitools; forward and reverse sequences were aligned using the illuminapairedend command using a minimum alignment score of 40, and only joined sequences retained. We used the obiuniq command to group identical sequences and tally them within samples, enabling us to quantify the relative read abundance (RRA) of each sequence. Sequences that occurred ≤2 times overall or that were ≤8 bp were discarded. Sequences were considered to be likely PCR artifacts if they were highly similar to another sequence (1 bp difference) and had a much lower abundance (0.05%) in the majority of samples in which they occurred; we discarded these sequences using the obiclean command. Overall, we characterized 357 plant sequences and a subset of 355 sequences were retained in the dataset after rarefying samples to equal sequencing depth. We then applied relative read abundance thresholds from 0% to 5% to the fecal samples. We compared differences in the inferred dietary richness within and between species based on individual samples, based on average richness across samples, and based on the total richness of each population after accounting for differences in sample size.
   

   Other

   The readme file contains an explanation of each of the variables in the dataset. Information on the methodology can be found in the associated manuscript referenced above. 
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