32
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Comparative environmental RNA and DNA metabarcoding analysis of river algae and arthropods for ecological surveys and water quality assessment

      research-article

      Read this article at

          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

          Environmental DNA (eDNA) metabarcoding is widely used for species analysis, while the use of environmental RNA (eRNA) metabarcoding is more limited. We conducted comparative eDNA/eRNA metabarcoding of the algae and arthropods (aquatic insects) in water samples from Naka River, Japan, to evaluate their potential for biological monitoring and water quality assessment. Both methods detected various algae and arthropod species; however, their compositions were remarkably different from those in traditional field surveys (TFSs), indicating low sensitivity. For algae, the species composition derived from eDNA and eRNA metabarcoding was equivalent. While TFSs focus on attached algae, metabarcoding analysis theoretically detects both planktonic and attached algae. A recently expanded genomic database for aquatic insects significantly contributed to the sensitivity and positive predictivity for arthropods. While the sensitivity of eRNA was lower than that of eDNA, the positive predictivity of eRNA was higher. The eRNA of terrestrial arthropods indicated extremely high or low read numbers when compared with eDNA, suggesting that eRNA could be an effective indicator of false positives. Arthropod and algae eDNA/eRNA metabarcoding analysis enabled water quality estimates from TFSs. The eRNA of algae and arthropods could thus be used to evaluate biodiversity and water quality and provide insights from ecological surveys.

          Related collections

          Most cited references57

          • Record: found
          • Abstract: found
          • Article: not found

          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
            • Record: found
            • Abstract: not found
            • Article: not found

            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

              • Record: found
              • Abstract: found
              • Article: not found

              DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates.

              M Beier (1966)
              We describe "universal" DNA primers for polymerase chain reaction (PCR) amplification of a 710-bp fragment of the mitochondrial cytochrome c oxidase subunit I gene (COI) from 11 invertebrate phyla: Echinodermata, Mollusca, Annelida, Pogonophora, Arthropoda, Nemertinea, Echiura, Sipuncula, Platyhelminthes, Tardigrada, and Coelenterata, as well as the putative phylum Vestimentifera. Preliminary comparisons revealed that these COI primers generate informative sequences for phylogenetic analyses at the species and higher taxonomic levels.

                Author and article information

                Contributors
                miyata.kaede@kao.com
                honda.hiroshi@kao.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 November 2022
                18 November 2022
                2022
                : 12
                : 19828
                Affiliations
                [1 ]GRID grid.419719.3, ISNI 0000 0001 0816 944X, R&D Safety Science Research, , Kao Corporation, ; 2606 Akabane, Ichikai-Machi, Haga-Gun, Tochigi, 321-3497 Japan
                [2 ]Bioindicator Co., Ltd., 18 Iwato-Cho, Shinjuku-Ku, Tokyo, 162-0832 Japan
                Article
                23888
                10.1038/s41598-022-23888-1
                9674700
                36400924
                8b80009a-44b5-4be1-91f5-52e121373d4a
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 28 April 2022
                : 7 November 2022
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                ecosystem ecology
                Uncategorized
                ecosystem ecology

                Comments

                Comment on this article

                Related Documents Log