14
views
0
recommends
+1 Recommend
1 collections
    0
    shares

      Publish your biodiversity research with us!

      Submit your article here.

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A metabarcode based (species) inventory of the northern Adriatic phytoplankton

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The northern Adriatic is characterised as the coldest and most productive marine area of the Mediterranean, which is due to high nutrient levels introduced by river discharges, the largest of which is the Italian Po River (at the same time also the largest freshwater input into the Mediterranean). The northern Adriatic is a very shallow marine ecosystem with ocean current patterns that result in long retention times of plankton in the area. The northern Adriatic phytoplankton biodiversity and abundance are well-studied, through many scientific and long-term monitoring reports. These datasets were based on phytoplankton morphological traits traditionally obtained with light microscopy. The most recent comprehensive eastern Adriatic phytoplankton checklist was published more than 20 years ago and is still valuable today. Since phytoplankton taxonomy and systematics are constantly being reviewed (partly also due to new molecular methods of species identification that complement classical methodologies), checklists need to be updated and complemented. Today, metabarcoding of molecular markers gains more and more importance in biodiversity research and monitoring. Here, we report the use of high throughput sequencing methods to re-examine taxonomic richness and provide updated knowledge of phytoplankton diversity in the eastern northern Adriatic to complement the standardised light microscopy method.

          New information

          This study aimed to report an up-to-date list of the phytoplankton taxonomic richness and phylogenetic relationships in the eastern northern Adriatic, based on sequence variability of barcoding genes resolved with advanced molecular tools, namely metabarcoding. Here, metabarcoding is used to complement standardised light microscopy to advance conventional monitoring and research of phytoplankton communities for the purpose of assessing biodiversity and the status of the marine environments. Monthly two-year net sampling targeted six phytoplankton groups including Bacillariophyceae (diatoms) and Chrysophyceae (golden algae) belonging to Ochrophyta , Dinophyceae (dinoflagellates), Cryptophyceae (cryptophytes), Haptophyta (mostly coccolithophorids) and Chlorophyta with Prasinophyceae (prasinophytes) and Chlorophyceae (protist green algae). Generated sequence data were taxonomically assigned and redistributed in two kingdoms, five classes, 32 orders, 49 families and 67 genera. The most diverse group were dinoflagellates, comprising of 34 found genera (48.3%), following by diatoms with 23 (35.4%) and coccolithophorids with three genera (4.0%). In terms of genetic diversity, results were a bit different: a great majority of sequences with one nucleotide tolerance (ASVs, Amplicon sequence variants) assigned to species or genus level were dinoflagellates (83.8%), 13.7% diatoms and 1.6% Chlorophyta , respectively. Although many taxa have not been detected that have been considered as common in this area, metabarcoding revealed five diatoms and 20 dinoflagellate genera that were not reported in previous checklists, along with a few species from other targeted groups that have been reported previously. We here describe the first comprehensive 18S metabarcode inventory for the northern Adriatic Sea.

          Related collections

          Most cited references57

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

            The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

              mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
                Bookmark

                Author and article information

                Contributors
                Journal
                Biodivers Data J
                Biodivers Data J
                1
                urn:lsid:arphahub.com:pub:F9B2E808-C883-5F47-B276-6D62129E4FF4
                urn:lsid:zoobank.org:pub:245B00E9-BFE5-4B4F-B76E-15C30BA74C02
                Biodiversity Data Journal
                Pensoft Publishers
                1314-2836
                1314-2828
                2023
                25 September 2023
                : 11
                : e106947
                Affiliations
                [1 ] Ruder Boskovic Institute, Centre for Marine Research, Rovinj-Rovigno, Croatia Ruder Boskovic Institute, Centre for Marine Research Rovinj-Rovigno Croatia
                Author notes
                Corresponding author: Ana Baričević ( ana.baricevic@ 123456cim.irb.hr ).

                Academic editor: Anne Thessen

                Author information
                https://orcid.org/0000-0002-7082-1977
                https://orcid.org/0000-0002-6253-4716
                Article
                106947 22051
                10.3897/BDJ.11.e106947
                10840511
                38318520
                c7787da7-9afb-4ca6-8b7c-f17c446ad17e
                Lana Grižančić, Ana Baričević, Mirta Smodlaka Tanković, Ivan Vlašiček, Mia Knjaz, Ivan Podolšak, Tjaša Kogovšek, Martin Andreas Pfannkuchen, Daniela Marić Pfannkuchen

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 29 May 2023
                : 29 August 2023
                Page count
                Figures: 4, Tables: 2, References: 56
                Categories
                Taxonomy & Inventories
                Plantae
                Chromista
                Ecology & Environmental sciences
                Biodiversity & Conservation
                Southern Europe and Mediterranean

                metabarcode,hts,18s,phytoplankton,northern adriatic,diatoms,dinoflagellates

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content525

                Cited by1

                Most referenced authors1,910