Abstract
DNA-based analyses have become powerful tools for characterizing the metazoan biodiversity of diverse marine ecosystems. Metabarcoding (i.e., large-scale taxonomic identification of complex samples via high-throughput sequencing of a DNA barcode region) frequently uses hypervariable regions of the nuclear eukaryotic 18S ribosomal RNA (rRNA) gene. However, species-level taxonomic identification is hampered by the conservative nature of the 18S gene in comparison to the mitochondrial cytochrome oxidase I (COI) barcode gene. Additionally, metabarcoding relies on reference DNA sequence databases for classification of millions of unknown sequence reads and molecular operational taxonomic units (OTUs); databases that are at present depauperate for marine zooplankton taxa. Here, we characterized the mesozooplankton community for the Chukchi Borderland (CBL) region, western Arctic Ocean, through metabarcoding analysis of the V4 and V9 hypervariable regions of 18S rRNA and a portion of COI. Characterization of zooplankton diversity for the epipelagic and upper mesopelagic layers (0–500 m) was based upon 17 metazoan taxonomic categories encompassing 24 orders in 14 classes. Taxonomic classification using the V4 and V9 markers was most reliable for orders, with copepods dominating OTU counts. To increase taxonomic resolution and allow detection of species, V4, V9, and COI OTUs were classified against DNA sequence databases for the Arctic Ocean for the subclass Copepoda. The geographic region-specific databases for 18S rRNA and COI resulted in the detection and identification of 6 genera and 49 species of copepods representing 23 families, a marked increase in the taxonomic classification of the 18S rRNA markers. The greatest copepod species diversity was captured with V4 (34 species) followed by COI (28 species) with the least copepod diversity detected by V9 (5 species). Our results demonstrate the power of using multiple gene markers, with DNA reference databases that are specific to the geographic region of interest, providing more accurate metabarcoding biodiversity measures for the copepod assemblages compared to universal metazoan sequence reference databases. Results from this study highlight the need for continued DNA barcode sequencing to increase species representation in the reference sequence databases that are crucial for accurate characterization of mesozooplankton communities.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abad D, Albaina A, Aguirre M, Estonba A (2017) 18S V9 metabarcoding correctly depicts plankton estuarine community drivers. Mar Ecol Prog Ser 584:31–43. https://doi.org/10.3354/meps12373
Altschul SF, Madden TL, Schäffer AA, Zhang J et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402. https://doi.org/10.1093/nar/25.17.3389
Amaral-Zettler LA, McCliment EA, Ducklow HW, Huse SM (2009) A method for studying protistan diversity using massively parallel sequencing of V9 hypervariable regions of small-subunit ribosomal RNA genes. PLoS One 4:e6372. https://doi.org/10.1371/journal.pone.0006372
Ashjian CJ, Campbell RG, Gelfman C et al (2017) Mesozooplankton abundance and distribution in association with hydrography on Hanna Shoal, NE Chukchi Sea, during August 2012 and 2013. Deep Res Part II Top Stud Oceanogr 144:21–36. https://doi.org/10.1016/j.dsr2.2017.08.012
Auel H, Hagen W (2002) Mesozooplankton community structure, abundance and biomass in the Central Arctic Ocean. Mar Biol 140:1013–1021. https://doi.org/10.1007/s00227-001-0775-4
Balzano S, Abs E, Leterme SC (2015) Protist diversity along a salinity gradient in a coastal lagoon. Aquat Microb Ecol 74:263–277. https://doi.org/10.3354/ame01740
Blanco-Bercial L (2020) Metabarcoding analyses and seasonality of the zooplankton community at BATS. Front Mar Sci:7–173. https://doi.org/10.3389/fmars.2020.00173
Blanco-Bercial L, Cornils A, Copley N, Bucklin A (2014) DNA barcoding of marine copepods: assessment of analytical approaches to species identification. PloS Curr Tree Life:1–32. https://doi.org/10.1371/currents.tol.cdf8b74881f87e3b01d56b43791626d2
Bluhm BA, Gebruk AV, Gradinger R et al (2011) Arctic marine biodiversity: an update of species richness and examples of biodiversity change. Oceanography 24:232–248. https://doi.org/10.5670/oceanog.2011.65
Brown EA, Chain FJJ, Crease TJ et al (2015) Divergence thresholds and divergent biodiversity estimates: can metabarcoding reliably describe zooplankton communities? Ecol Evol 5:2234–2251. https://doi.org/10.1002/ece3.1485
Bucklin A, Hopcroft RR, Kosobokova KN et al (2010) DNA barcoding of Arctic Ocean holozooplankton for species identification and recognition. Deep Res Part II Top Stud Oceanogr 57:40–48. https://doi.org/10.1016/j.dsr2.2009.08.005
Bucklin A, Lindeque PK, Rodriguez-Ezpeleta N et al (2016) Metabarcoding of marine zooplankton: prospects, progress and pitfalls. J Plankton Res 38:393–400. https://doi.org/10.1093/plankt/fbw023
Bucklin A, Steinke D, Blanco-Bercial L (2011) DNA barcoding of marine metazoa. Annu Rev Mar Sci 3:471–508. https://doi.org/10.1146/annurev-marine-120308-080950
Bucklin A, Wiebe PH, Smolenack SB et al (2007) DNA barcodes for species identification of euphausiids (Euphausiacea, Crustacea). J Plankton Res 29:483–493. https://doi.org/10.1093/plankt/fbm031
Bucklin A, Yeh HD, Questel JM et al (2019) Time-series metabarcoding analysis of zooplankton diversity of the NW Atlantic continental shelf. Zool J Linnean Soc 76:1162–1176. https://doi.org/10.1093/zoolinnean/zly093
Callahan BJ, McMurdie PJ, Holmes SP (2017) Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J 11:2639–2643. https://doi.org/10.1038/ismej.2017.119
Carroll EL, Gallego R, Sewell MA et al (2019) Multi-locus DNA metabarcoding of zooplankton communities and scat reveal trophic interactions of a generalist predator. Sci Rep 9:1–14. https://doi.org/10.1038/s41598-018-36478-x
Carugati L, Corinaldesi C, Dell’Anno A, Danovaro R (2015) Metagenetic tools for the census of marine meiofaunal biodiversity: an overview. Mar Genomics 24:11–20. https://doi.org/10.1016/j.margen.2015.04.010
Chain FJJ, Brown EA, Macisaac HJ, Cristescu ME (2016) Metabarcoding reveals strong spatial structure and temporal turnover of zooplankton communities among marine and freshwater ports. Divers Distrib 22:493–504. https://doi.org/10.1111/ddi.12427
Chao A, Gotelli NJ, Hsieh TC, Sander EL, Ma KH, Colwell RK, Ellison AM (2014) Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies. Ecol Monogr 84:45–67. https://doi.org/10.1890/13-0133.1
Choquet M, Hatlebakk M, Dhanasiri AKS et al (2017) Genetics redraws pelagic biogeography of Calanus. Biol Lett 13:20170588. https://doi.org/10.1098/rsbl.2017.0588
Clarke LJ, Beard JM, Swadling KM, Deagle BE (2017) Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies. Ecol Evol 7:873–883. https://doi.org/10.1002/ece3.2667
Corell J, Rodríguez-Ezpeleta N (2014) Tuning of protocols and marker selection to evaluate the diversity of zooplankton using metabarcoding. Rev Investig Mar AZTI-Tecnalia 21:19–39
Cornils A, Wend-Heckmann B, Held C (2017) Global phylogeography of Oithona similis s.l. (Crustacea, Copepoda, Oithonidae) – a cosmopolitan plankton species or a complex of cryptic lineages? Mol Phylogenet Evol 107:473–485. https://doi.org/10.1016/j.ympev.2016.12.019
Cowart DA, Pinheiro M, Mouchel O et al (2015) Metabarcoding is powerful yet still blind: a comparative analysis of morphological and molecular surveys of seagrass communities. PLoS One 10:e0117562. https://doi.org/10.1371/journal.pone.0117562
Cristescu ME (2014) From barcoding single individuals to metabarcoding biological communities: towards an integrative approach to the study of global biodiversity. Trends Ecol Evol 29:566–571. https://doi.org/10.1016/j.tree.2014.08.001
Daly KL (1997) Flux of particulate matter throught copepods in the Northeast Water Polynya. J Mar Syst 10:319–342
Darnis G, Barber DG, Fortier L (2008) Sea ice and the onshore-offshore gradient in pre-winter zooplankton assemblages in southeastern Beaufort Sea. J Mar Syst 74:994–1011. https://doi.org/10.1016/j.jmarsys.2007.09.003
Dawson MN, Jacobs DK (2001) Molecular evidence for cryptic species of Aurelia aurita (Cnidaria, Scyphozoa). Biol Bull 200:92–96. https://doi.org/10.2307/1543089
de Vargas C, Audic S, Henry N et al (2015) Eukaryotic plankton diversity in the sunlit ocean. Science 348:1261605. https://doi.org/10.1126/science.1261605
Djurhuus A, Pitz K, Sawaya NA et al (2018) Evaluation of marine zooplankton community structure through environmental DNA metabarcoding. Limnol Oceanogr Methods 16:209–221. https://doi.org/10.1002/lom3.10237
Edgar RC (2016) UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing. bioRxiv 081257. https://doi.org/10.1101/081257
Ershova EA, Hopcroft RR, Kosobokova KN (2015) Inter-annual variability of summer mesozooplankton communities of the western Chukchi Sea: 2004–2012. Polar Biol 38:1461–1481. https://doi.org/10.1007/s00300-015-1709-9
Ershova EA, Kosobokova KN (2019) Cross-shelf structure and distribution of mesozooplankton communities in the east-Siberian Sea and the adjacent Arctic Ocean. Polar Biol 42:1353–1367. https://doi.org/10.1007/s00300-019-02523-2
Folino-Rorem NC, Darling JA, D’Ausilio CA (2009) Genetic analysis reveals multiple cryptic invasive species of the hydrozoan genus Cordylophora. Biol Invasions 11:1869–1882. https://doi.org/10.1007/s10530-008-9365-4
Folmer O, Black M, Hoeh W et al (1994) DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotechnol 3:294–299. https://doi.org/10.1371/journal.pone.0013102
Goetze E (2003) Cryptic speciation on the high seas; global phylogenetics of the copepod family Eucalanidae. Proc Biol Sci 270:2321–2331. https://doi.org/10.1098/rspb.2003.2505
Goodall-Copestake WP (2017) One tunic but more than one barcode: evolutionary insights from dynamic mitochondrial DNA in Salpa thompsoni (Tunicata: Salpida). Biol J Linn Soc 120:637–648. https://doi.org/10.1111/bij.12915
Govindarajan AF, Boero F, Halanych KM (2006) Phylogenetic analysis with multiple markers indicates repeated loss of the adult medusa stage in Campanulariidae (Hydrozoa, Cnidaria). Mol Phylogenet Evol 38:820–834. https://doi.org/10.1016/j.ympev.2005.11.012
Hamby RK, Zimmer EA (1988) Ribosomal RNA sequences for inferring phylogeny within the grass family (Poaceae). Plant Syst Evol 160:29–37. https://doi.org/10.1007/BF00936707
Hillis DM, Dixon MT (1991) Ribosomal DNA: molecular evolution and phylogenetic inference. Q Rev Biol 66:411–453. https://doi.org/10.2307/2831326
Hirai J, Katakura S, Kasai H, Nagai S (2017) Cryptic zooplankton diversity reveaeled by a metagenetic approach to monitoring metazoan communities in the coastal waters of the Okhotsk Sea, Northeastern Hokkaido. Front Mar Sci 4:379. https://doi.org/10.3389/fmars.2017.00379
Hirai J, Kuriyama M, Ichikawa T et al (2015a) A metagenetic approach for revealing community structure of marine planktonic copepods. Mol Ecol Resour 15:68–80. https://doi.org/10.1111/1755-0998.12294
Hirai J, Tachibana A, Tsuda A (2020) Large-scale metabarcoding analysis of epipelagic and mesopelagic copepods in the Pacific. PLoS One 15:e0233189. https://doi.org/10.1371/journal.pone.0233189
Hirai J, Yasuike M, Fujiwara A et al (2015b) Effects of plankton net characteristics on metagenetic community analysis of metazoan zooplankton in a coastal marine ecosystem. J Exp Mar Biol Ecol 469:36–43. https://doi.org/10.1016/j.jembe.2015.04.011
Hopcroft RR, Clarke C, Nelson RJ, Raskoff KA (2005) Zooplankton communities of the Arctic’s Canada Basin: the contribution by smaller taxa. Polar Biol 28:198–206. https://doi.org/10.1007/s00300-004-0680-7
Hopcroft RR, Kosobokova KN, Pinchuk AI (2010) Zooplankton community patterns in the Chukchi Sea during summer 2004. Deep Sea Res Part II Top Stud Oceanogr 57:27–39. https://doi.org/10.1016/j.dsr2.2009.08.003
Hsieh TC, Ma KH, Chao A (2016) iNEXT: an R package for interpolation and extrapolation of species diversity (Hill numbers). Methods Ecol Evol 7:1451–1456. https://doi.org/10.1111/2041-210X.1213
Hulsen T, de Vlieg J, Alkema W (2008) BioVenn – a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams. Genomics 9:488
Hunt B, Strugnell J, Bednarsek N et al (2010) Poles apart: the “bipolar” pteropod species limacina helicina is genetically distinct between the Arctic and Antarctic Oceans. PLoS One 5:e9835. https://doi.org/10.1371/journal.pone.0009835
Kelly RP, Shelton AO, Gallego R (2019) Understanding PCR processes to draw meaningful conclusions from environmental DNA studies. Sci Rep 9:12133. https://doi.org/10.1038/s41598-01904846-x
Kircher M, Sawyer S, Meyer M (2012) Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res 40:e3. https://doi.org/10.1093/nar/gkr771
Klode R (2018) pheatmap: pretty Heatmaps. https://cran.r-project.org/web/packages/pheatmap/index.html. Accessed 1 Nov 2019
Knowlton N (2000) Molecular genetic analyses of species boundaries in the sea. Hydrobiologia 420:73–90
Kosobokova K, Hirche HJ (2000) Zooplankton distribution across the Lomonosov Ridge, Arctic Ocean: species inventory, biomass and vertical structure. Deep Res Part I 47:2029–2060. https://doi.org/10.1016/S0967-0637(00)00015-7
Kosobokova KN, Hopcroft RR (2010) Diversity and vertical distribution of mesozooplankton in the Arctic’s Canada Basin. Deep Res Part II Top Stud Oceanogr 57:96–110. https://doi.org/10.1016/j.dsr2.2009.08.009
Kosobokova KN, Hopcroft RR, Hirche HJ (2011) Patterns of zooplankton diversity through the depths of the Arctic’s central basins. Mar Biodivers 41:29–50. https://doi.org/10.1007/s12526-010-0057-9
Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35:1547–1549. https://doi.org/10.1093/molbev/msy096
Leray M, Yang JY, Meyer CP et al (2013) A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front Zool 10:34. https://doi.org/10.1186/1742-9994-10-34
Lindeque PK, Parry HE, Harmer RA et al (2013) Next generation sequencing reveals the hidden diversity of zooplankton assemblages. PLoS One 8:e81327. https://doi.org/10.1371/journal.pone.0081327
Lindsay D, Grossmann MM, Nishikawa J et al (2015) DNA barcoding of pelagic cnidarians: current status and future prospects. Bull Plankt Soc Jpn 62:39–43. https://doi.org/10.24763/bpsj.62.1_39
Longhurst AR, Glen Harrison W (1989) The biological pump: profiles of plankton production and consumption in the upper ocean. Prog Oceanogr 22:47–123. https://doi.org/10.1016/0079-6611(89)90010-4
López-Escardó D, Paps J, De Vargas C et al (2018) Metabarcoding analysis on European coastal samples reveals new molecular metazoan diversity. Sci Rep. https://doi.org/10.1038/s41598-018-27509-8
Mayer LA, Armstrong AA, Calder BR, Gardner JV (2010) Seafloor mapping in the Arctic: support for a potential US extended continental shelf. Int Hydrogr Rev 3:14–23
McLaughlin F, Shimada K, Carmack E et al (2005) The hydrography of the southern Canada Basin, 2002. Polar Biol 28:182–189. https://doi.org/10.1007/s00300-004-0701-6
Miyamoto H, Machida RJ, Nishida S (2010) Genetic diversity and cryptic speciation of the deep sea chaetognath Caecosagitta macrocephala (Fowler, 1904). Deep Res Part II Top Stud Oceanogr 57:2211–2219. https://doi.org/10.1016/j.dsr2.2010.09.023
Nigro LM, Angel MV, Blachowiak-Samolyk K et al (2016) Identification, discrimination, and discovery of species of marine planktonic ostracods using DNA barcodes. PLoS One 11:e0146327. https://doi.org/10.1371/journal.pone.0146327
Oksanen J, Blanchet FG, Friendly M, et al. (2018) Vegan: community ecology package. R package version 2.5–3. http://cran.rproject.org/package=vegan. Accessed 1 Nov 2019
Perovich DK (2011) The changing Arctic sea ice cover. Oceanography 24:162–173. https://doi.org/10.5670/oceanog.2011.68
Quast C, Pruesse E, Yilmaz P et al (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:590–596. https://doi.org/10.1093/nar/gks1219
Questel JM, Clarke C, Hopcroft RR (2013) Seasonal and interannual variation in the planktonic communities of the northeastern Chukchi Sea during the summer and early fall. Cont Shelf Res 67:23–41. https://doi.org/10.1016/j.csr.2012.11.003
Richardson AJ (2008) In hot water: zooplankton and climate change. ICES J Mar Sci 65:279–295. https://doi.org/10.1093/icesjms/fsn028
Rognes T, Flouri T, Nichols B, Quince C, Mahé F (2016) VSEARCH: a versatile open source tool for metagenomics. PeerJ 4:e2584. https://doi.org/10.7717/peerj.2584
Rutzen I, Hopcroft RR (2018) Abundance, biomass and community structure of epipelagic zooplankton in the Canada Basin. J Plankton Res 40:486–499. https://doi.org/10.1093/plankt/fby028
Santoferrara LF (2019) Current pracrice in plankton metabarcoding: optimization and error management. J Plankton Res 41:571–582. https://doi.org/10.1093/plankt/fbz041
Schloss PD, Westcott SL, Ryabin T et al (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541. https://doi.org/10.1128/AEM.01541-09
Schroeder A, Stanković D, Pallavicini A, Gionechetti F et al (2020) DNA metabarcoding and morphological analysis – assessment of zooplankton biodiversity in transitional waters. Mar Environ Res 160:104946. https://doi.org/10.1016/j.marenvres.2020.104946
Sirenko BS, Clarke C, Hopcroft RR, et al. (2019) The Arctic Register of Marine Species (ARMS) compiled by the Arctic Ocean Diversity (ArcOD). http://www.marinespecies.org/arms. Accessed 28 Nov 2019
Smoot CA, Hopcroft RR (2017a) Depth-stratified community structure of Beaufort Sea slope zooplankton and its relations to water masses. J Plankton Res 39:79–91. https://doi.org/10.1093/plankt/fbw087
Smoot CA, Hopcroft RR (2017b) Cross-shelf gradients of epipelagic zooplankton communities of the Beaufort Sea and the influence of localized hydrographic features. J Plankton Res 39:65–78. https://doi.org/10.1093/plankt/fbw080
Sommer SA, Van Woudenberg L, Lenz PH et al (2017) Vertical gradients in species richness and community composition across the twilight zone in the North Pacific Subtropical Gyre. Mol Ecol 26:6136–6156. https://doi.org/10.1111/mec.14286
Stefanni S, Stanko D, Borme D et al (2018) Multi-marker metabarcoding approach to study mesozooplankton at basin scale. Sci Rep 8:12085. https://doi.org/10.1038/s41598-018-30157-7
Steinberg DK, Van Mooy BAS, Buesseler KO et al (2008) Bacterial vs. zooplankton control of sinking particle flux in the ocean’s twilight zone. Limnol Oceanogr 53:1327–1338
Stoeck T, Bass D, Nebel M et al (2010) Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol Ecol 19:21–31. https://doi.org/10.1111/j.1365-294X.2009.04480.x
Sun C, Zhao Y, Li H et al (2015) Unreliable quantitation of species abundance based on high-throughput sequencing data of zooplankton communities. Aquat Biol 24:9–15. https://doi.org/10.3354/ab00629
Tanabe AS, Nagai S, Hida K et al (2016) Comparative study of the validity of three regions of the 18S-rRNA gene for massively parallel sequencing-based monitoring of the planktonic eukaryote community. Mol Ecol Resour 16:402–414. https://doi.org/10.1111/1755-0998.12459
Tempestini A, Fortier L, Pinchuk A, Dufresne F (2017) Molecular phylogeny of the genus Themisto (Guérin, 1925) (Amphipoda: Hyperiidae) in the Northern Hemisphere. J Crustac Biol:1–11. https://doi.org/10.1093/jcbiol/rux076
Ueda H, Bucklin AC (2006) Acartia (Odontacartia) ohtsukai, a new brackish-water calanoid copepod from Ariake Bay, Japan, with a redescription of the closely related A. pacifica from the Seto Inland Sea. Hydrobiologia 560:77–91. https://doi.org/10.1007/s10750-005-9513-0
Walkusz W, Williams WJ, Kwasniewski S (2013) Vertical distribution of mesozooplankton in the coastal Canadian Beaufort Sea in summer. J Mar Syst 127:26–35. https://doi.org/10.1016/j.jmarsys.2012.01.001
Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267. https://doi.org/10.1128/AEM.00062-07
Wickham H (2016) ggplot2: elegant graphics for data analysis, Second edn. Springer International Publishing. https://doi.org/10.1007/978-3-319-24277-4
Wiebe PH, Bucklin A, Madin L et al (2010) Deep-sea sampling on CMarZ cruises in the Atlantic Ocean – an introduction. Deep Res Part II Top Stud Oceanogr 57:2157–2166. https://doi.org/10.1016/j.dsr2.2010.09.018
Witt JDS, Threloff DL, Hebert PDN (2006) DNA barcoding reveals extraordinary cryptic diversity in an amphipod genus: implications for desert spring conservation. Mol Ecol 15:3073–3082. https://doi.org/10.1111/j.1365-294X.2006.02999.x
Woodgate RA, Aagaard K, Swift JH et al (2007) Atlantic water circulation over the Mendeleev Ridge and Chukchi Borderland from thermohaline intrusions and water mass properties. J Geophys Res Ocean 112:1–20. https://doi.org/10.1029/2005JC003416
Wu S, Xiong J, Yu YY (2015) Taxonomic resolutions based on 18S rRNA genes: a case study of subclass Copepoda. PLoS One 12:e0131498. https://doi.org/10.1371/journal.pone.0131498
Xu Z, Zhang G, Sun S (2018) Inter-annual variation of the summer zooplankton community in the Chukchi Sea: spatial heterogeneity during a decade of rapid ice decline. Polar Biol 41:1827–1843. https://doi.org/10.1007/s00300-018-2324-3
Yang J, Zhang X, Zhang W et al (2017) Indigenous species barcode database improves the identification of zooplankton. PLoS One 12:e0185697. https://doi.org/10.1371/journal.pone.0185697October
Yebra L, Bonnet D, Harris RP et al (2011) Barriers in the pelagic: population structuring of Calanus helgolandicus and C. euxinus in European waters. Mar Ecol Prog Ser 428:135–149. https://doi.org/10.3354/meps09056
Zhang GK, Chain FJJ, Abbott CL, Cristescu ME (2018) Metabarcoding using multiplexed markers increases species detection in complex zooplankton communities. Evol Appl:1–14. https://doi.org/10.1111/eva.12694
Acknowledgments
We gratefully thank Leocadio Blanco-Bercial (Bermuda Institute of Ocean Science) for use of his database customized from SILVA Release 132 and guidance with the Mothur pipeline. Bioinformatics were carried out using resources of the computational Biological Core, Institute of System Genomics, University of Connecticut (https://bioinformatics.uconn.edu/). We thank Bo Reese and staff at the UConn Center for Genomic Innovation (CGI) and Kendra Mass at the UConn center for Microbial Analysis, Resources, and Services (MARS) for their guidance with molecular protocols, sequencing, and bioinformatics. Many thanks to the officers and crew of the USCGC Healy and members of the scientific team, particularly Katrin Iken, Heidi Mendoza-Islas, Atsushi Yamaguchi, and Dhugal Lindsay. We would also like to thank Captain S. Schwarze, his crew of the RV Polarstern, and the chief scientist Ursula Schauer for their support during the ARK-XXVI/3 “TransArc” Polarstern cruise (PS78), 2011. We thank two peer reviewers for their comments that have helped improve the manuscript.
Funding
This work was supported by the NOAA Office of Exploration and Research under the Chukchi Borderlands: Exploration of Pelagic Life in a Complex Polar Environment project NA15OAR0110209. The work on Polarstern 2011 Arctic cruise collections that provided expertly identified specimens was performed in the framework of the state assignment of IO RAS (theme No. 0149-2019-0008) and supported by the Russian Foundation for Basic Research grants No 18-05-60158 and 19-04-00955.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
All applicable international, national, and/or institutional guidelines for the care and use of animals were followed by the authors.
Sampling and field studies
All necessary permits for sampling and observational field studies have been obtained by the authors from the competent authorities and are mentioned in the acknowledgments, if applicable.
Data availability
The V4 and V9 nuclear 18 rRNA and mitochondrial COI metabarcoding data generated and analyzed during this study have been deposited in the NCBI GenBank Short Read Archive (https://www.ncbi.nlm.nih.gov/sra/). Raw sequence reads in FASTQ format from the NOAA Hidden Ocean 2016: Chukchi Borderland expedition can be accessed using SRA BioProject ID PRJNA593255. Eukaryotic 18S rRNA sequences were deposited in GenBank under the accession numbers MG660871-MG661071 and MN784560-MN784617. Metazoan mitochondrial COI sequences were assigned GenBank accession numbers MN831487-MN831677. Sequences for 18S and COI used to complete species representation in the ArCop databases were mined from the NCBI GenBank public repository. Bioinformatic scripts, taxonomic mapping, and corresponding FASTA sequence files formatted for Mothur for each DNA marker are available at https://github.com/JQuestel/Chukchi_Borderland_Zooplankton_Metabarcoding.
Author contributions
J.Q. conducted laboratory methods for metabarcoding, bioinformatics, created the ArCop databases, analyzed data, and wrote the manuscript. C.S., J.Q., K.K., and R.H. identified specimens used in the ArCop database. C.S., J.Q., and R.H. collected zooplankton samples used for metabarcoding analysis. H.D. sequenced 18S and COI for the ArCop databases. R.H. and A.B. acquired funding and designed the research. A.B. provided molecular ecology expertise. All authors contributed to writing the manuscript.
Additional information
Communicated by H. Stuckas
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Questel, J.M., Hopcroft, R.R., DeHart, H.M. et al. Metabarcoding of zooplankton diversity within the Chukchi Borderland, Arctic Ocean: improved resolution from multi-gene markers and region-specific DNA databases. Mar. Biodivers. 51, 4 (2021). https://doi.org/10.1007/s12526-020-01136-x
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12526-020-01136-x