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ITSoneDB: a comprehensive collection of eukaryotic ribosomal RNA Internal Transcribed Spacer 1 (ITS1) sequences

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      Abstract

      A holistic understanding of environmental communities is the new challenge of metagenomics. Accordingly, the amplicon-based or metabarcoding approach, largely applied to investigate bacterial microbiomes, is moving to the eukaryotic world too. Indeed, the analysis of metabarcoding data may provide a comprehensive assessment of both bacterial and eukaryotic composition in a variety of environments, including human body. In this respect, whereas hypervariable regions of the 16S rRNA are the de facto standard barcode for bacteria, the Internal Transcribed Spacer 1 (ITS1) of ribosomal RNA gene cluster has shown a high potential in discriminating eukaryotes at deep taxonomic levels. As metabarcoding data analysis rely on the availability of a well-curated barcode reference resource, a comprehensive collection of ITS1 sequences supplied with robust taxonomies, is highly needed. To address this issue, we created ITSoneDB (available at http://itsonedb.cloud.ba.infn.it/) which in its current version hosts 985 240 ITS1 sequences spanning over 134 000 eukaryotic species. Each ITS1 is mapped on the NCBI reference taxonomy with its start and end positions precisely annotated. ITSoneDB has been developed in agreement to the FAIR guidelines by enabling the users to query and download its content through a simple web-interface and access relevant metadata by cross-linking to European Nucleotide Archive.

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      QIIME allows analysis of high-throughput community sequencing data.

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        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.
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          UCHIME improves sensitivity and speed of chimera detection

          Motivation: Chimeric DNA sequences often form during polymerase chain reaction amplification, especially when sequencing single regions (e.g. 16S rRNA or fungal Internal Transcribed Spacer) to assess diversity or compare populations. Undetected chimeras may be misinterpreted as novel species, causing inflated estimates of diversity and spurious inferences of differences between populations. Detection and removal of chimeras is therefore of critical importance in such experiments. Results: We describe UCHIME, a new program that detects chimeric sequences with two or more segments. UCHIME either uses a database of chimera-free sequences or detects chimeras de novo by exploiting abundance data. UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences. In testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus. UCHIME is >100× faster than Perseus and >1000× faster than ChimeraSlayer. Contact: robert@drive5.com Availability: Source, binaries and data: http://drive5.com/uchime. Supplementary information: Supplementary data are available at Bioinformatics online.
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            Author and article information

            Affiliations
            Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, Consiglio Nazionale delle Ricerche, Bari 70126, Italy
            Institute of Biomedical Technologies, Consiglio Nazionale delle Ricerche, Bari 70126, Italy
            Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari ‘A. Moro’, Bari 70126, Italy
            Author notes
            To whom correspondence should be addressed. Tel: +39 080 544 3588; Fax: +39 080 544 3317; Email: graziano.pesole@ 123456uniba.it

            These authors contributed equally to the paper as first authors.

            Journal
            Nucleic Acids Res
            Nucleic Acids Res
            nar
            Nucleic Acids Research
            Oxford University Press
            0305-1048
            1362-4962
            04 January 2018
            25 September 2017
            25 September 2017
            : 46
            : Database issue , Database issue
            : D127-D132
            29036529
            5753230
            10.1093/nar/gkx855
            gkx855
            © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

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            Pages: 6
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            Database Issue

            Genetics

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