COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf
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 significa...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Marine Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2022.867893/full |
| _version_ | 1818278309749850112 |
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| author | Ann Bucklin Paola G. Batta-Lona Jennifer M. Questel Peter H. Wiebe David E. Richardson Nancy J. Copley Todd D. O’Brien |
| author_facet | Ann Bucklin Paola G. Batta-Lona Jennifer M. Questel Peter H. Wiebe David E. Richardson Nancy J. Copley Todd D. O’Brien |
| author_sort | Ann Bucklin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-12T23:15:24Z |
| format | Article |
| id | doaj.art-b5de68f793bf483fa47cff66fc36fc03 |
| institution | Directory Open Access Journal |
| issn | 2296-7745 |
| language | English |
| last_indexed | 2024-12-12T23:15:24Z |
| publishDate | 2022-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj.art-b5de68f793bf483fa47cff66fc36fc032022-12-22T00:08:28ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452022-04-01910.3389/fmars.2022.867893867893COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental ShelfAnn Bucklin0Paola G. Batta-Lona1Jennifer M. Questel2Peter H. Wiebe3David E. Richardson4Nancy J. Copley5Todd D. O’Brien6Department of Marine Sciences, University of Connecticut, Groton, CT, United StatesDepartment of Marine Sciences, University of Connecticut, Groton, CT, United StatesCollege of Fisheries and Ocean Sciences, University of Alaska, Fairbanks, AK, United StatesDepartment of Biology, Woods Hole Oceanographic Institution, Woods Hole, MA, United StatesNational Oceanic and Atmospheric Association (NOAA) Northeast Fisheries Science Center, Narragansett, RI, United StatesDepartment of Biology, Woods Hole Oceanographic Institution, Woods Hole, MA, United StatesNational Oceanic and Atmospheric Association (NOAA) Fisheries, Office of Science and Technology Science Center, Silver Spring, MD, United StatesMarine 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.https://www.frontiersin.org/articles/10.3389/fmars.2022.867893/fullzooplanktonmetabarcodingcytochrome oxidase Ispecies diversityecosystem monitoringNorthwest Atlantic continental shelf |
| spellingShingle | Ann Bucklin Paola G. Batta-Lona Jennifer M. Questel Peter H. Wiebe David E. Richardson Nancy J. Copley Todd D. O’Brien COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf Frontiers in Marine Science zooplankton metabarcoding cytochrome oxidase I species diversity ecosystem monitoring Northwest Atlantic continental shelf |
| title | COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf |
| title_full | COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf |
| title_fullStr | COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf |
| title_full_unstemmed | COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf |
| title_short | COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf |
| title_sort | coi metabarcoding of zooplankton species diversity for time series monitoring of the nw atlantic continental shelf |
| topic | zooplankton metabarcoding cytochrome oxidase I species diversity ecosystem monitoring Northwest Atlantic continental shelf |
| url | https://www.frontiersin.org/articles/10.3389/fmars.2022.867893/full |
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