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      metaPR 2 : A database of eukaryotic 18S rRNA metabarcodes with an emphasis on protists

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          Abstract

          In recent years, metabarcoding has become the method of choice for investigating the composition and assembly of microbial eukaryotic communities. The number of environmental data sets published has increased very rapidly. Although unprocessed sequence files are often publicly available, processed data, in particular clustered sequences, are rarely available in a usable format. Clustered sequences are reported as operational taxonomic units (OTUs) with different similarity levels or more recently as amplicon sequence variants (ASVs). This hampers comparative studies between different environments and data sets, for example examining the biogeographical patterns of specific groups/species, as well analysing the genetic microdiversity within these groups. Here, we present a newly‐assembled database of processed 18S rRNA metabarcodes that are annotated with the PR 2 reference sequence database. This database, called metaPR 2, contains 41 data sets corresponding to more than 4000 samples and 90,000 ASVs. The database, which is accessible through both a web‐based interface ( https://shiny.metapr2.org) and an R package, should prove very useful to all researchers working on protist diversity in a variety of systems.

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          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.
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            Cutadapt removes adapter sequences from high-throughput sequencing reads

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              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.
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                Author and article information

                Contributors
                vaulot@gmail.com
                lopesas.ufrj@gmail.com
                Journal
                Mol Ecol Resour
                Mol Ecol Resour
                10.1111/(ISSN)1755-0998
                MEN
                Molecular Ecology Resources
                John Wiley and Sons Inc. (Hoboken )
                1755-098X
                1755-0998
                13 July 2022
                November 2022
                : 22
                : 8 ( doiID: 10.1111/men.v22.8 )
                : 3188-3201
                Affiliations
                [ 1 ] UMR 7144, ECOMAP, CNRS Sorbonne Université, Station Biologique de Roscoff Roscoff France
                [ 2 ] Asian School of the Environment Nanyang Technological University Singapore
                [ 3 ] Department of Organismal Biology (Systematic Biology) Uppsala University Uppsala Sweden
                Author notes
                [*] [* ] Correspondence

                Daniel Vaulot, UMR 7144, ECOMAP, CNRS, Sorbonne Université, Station Biologique de Roscoff, 29680 Roscoff, France.

                Email: vaulot@ 123456gmail.com

                Adriana Lopes dos Santos, Asian School of the Environment, Nanyang Technological University, Singapore.

                Email: lopesas.ufrj@ 123456gmail.com

                Author information
                https://orcid.org/0000-0002-0717-5685
                https://orcid.org/0000-0003-2190-7261
                https://orcid.org/0000-0001-6053-6948
                https://orcid.org/0000-0002-2930-9226
                https://orcid.org/0000-0002-0736-4937
                Article
                MEN13674 MER-22-0044.R1
                10.1111/1755-0998.13674
                9796713
                35762265
                5ad9e984-6685-4931-8aee-92ae68d5ab4f
                © 2022 The Authors. Molecular Ecology Resources published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 May 2022
                : 07 February 2022
                : 20 June 2022
                Page count
                Figures: 9, Tables: 1, Pages: 14, Words: 7381
                Funding
                Funded by: Agence Nationale de la Recherche , doi 10.13039/501100001665;
                Award ID: ANR‐20‐CE02‐0025
                Funded by: Singapore Ministry of Education, Academic Research Fund Tier 1
                Award ID: RG26/19
                Funded by: Singapore Ministry of Education, Academic Research Fund Tier 1
                Award ID: RG91/21
                Categories
                Resource Article
                RESOURCE ARTICLES
                Computer Programs
                Custom metadata
                2.0
                November 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.3 mode:remove_FC converted:28.12.2022

                Ecology
                18s rrna,database,metabarcodes,pcr,protist,r,shiny
                Ecology
                18s rrna, database, metabarcodes, pcr, protist, r, shiny

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