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      A group of ectomycorrhizal fungi restricts organic matter accumulation in boreal forest

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          Search and clustering orders of magnitude faster than BLAST.

          Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
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            Towards a unified paradigm for sequence-based identification of fungi.

            The nuclear ribosomal internal transcribed spacer (ITS) region is the formal fungal barcode and in most cases the marker of choice for the exploration of fungal diversity in environmental samples. Two problems are particularly acute in the pursuit of satisfactory taxonomic assignment of newly generated ITS sequences: (i) the lack of an inclusive, reliable public reference data set and (ii) the lack of means to refer to fungal species, for which no Latin name is available in a standardized stable way. Here, we report on progress in these regards through further development of the UNITE database (http://unite.ut.ee) for molecular identification of fungi. All fungal species represented by at least two ITS sequences in the international nucleotide sequence databases are now given a unique, stable name of the accession number type (e.g. Hymenoscyphus pseudoalbidus|GU586904|SH133781.05FU), and their taxonomic and ecological annotations were corrected as far as possible through a distributed, third-party annotation effort. We introduce the term 'species hypothesis' (SH) for the taxa discovered in clustering on different similarity thresholds (97-99%). An automatically or manually designated sequence is chosen to represent each such SH. These reference sequences are released (http://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and in the QIIME pipeline. The system and the data will be updated automatically as the number of public fungal ITS sequences grows. We invite everybody in the position to improve the annotation or metadata associated with their particular fungal lineages of expertise to do so through the new Web-based sequence management system in UNITE. © 2013 John Wiley & Sons Ltd.
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              piecewiseSEM: Piecewise structural equation modelling inr for ecology, evolution, and systematics

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                Author and article information

                Contributors
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                Journal
                Ecology Letters
                Ecol Lett
                Wiley
                1461-023X
                1461-0248
                July 2021
                May 02 2021
                July 2021
                : 24
                : 7
                : 1341-1351
                Affiliations
                [1 ]Department of Soil and Environment Swedish University of Agricultural Sciences Uppsala Sweden
                [2 ]Department of Forest Mycology and Plant Pathology Swedish University of Agricultural Sciences Uppsala Sweden
                Article
                10.1111/ele.13746
                33934481
                167f188a-6583-4df1-9af5-2c5da0eb3dbf
                © 2021

                http://creativecommons.org/licenses/by/4.0/

                http://doi.wiley.com/10.1002/tdm_license_1.1

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