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      High Fungal Diversity but Low Seasonal Dynamics and Ectomycorrhizal Abundance in a Mountain Beech Forest

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          Abstract

          Forests on steep slopes constitute a significant proportion of European mountain areas and are important as production and protection forests. This study describes the soil fungal community structure in a European beech-dominated mountain forest stands in the Northern Calcareous Alps and investigates how it is determined by season and soil properties. Samples were collected at high spatial resolution in an area of ca. 100 m × 700 m in May (spring) and August (summer). Illumina MiSeq high-throughput sequencing of the ITS2-region revealed distinct patterns for the soil fungal communities. In contrast to other studies from temperate European beech forest stands, Ascomycota dominated the highly diverse fungal community, while ectomycorrhizal fungi were of lower abundance. Russulaceae, which are often among the dominant ectomycorrhizal fungi associated with European beech, were absent from all samples. Potentially plant pathogenic fungi were more prevalent than previously reported. Only subtle seasonal differences were found between fungal communities in spring and summer. Especially, dominant saprotrophic taxa were largely unaffected by season, while slightly stronger effects were observed for ectomycorrhizal fungi. Soil characteristics like pH and organic carbon content, on the other hand, strongly shaped abundant taxa among the saprotrophic fungal community.

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          The online version contains supplementary material available at 10.1007/s00248-021-01736-5.

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          Most cited references71

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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              VSEARCH: a versatile open source tool for metagenomics

              Background VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.
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                Author and article information

                Contributors
                boris.rewald@boku.ac.at
                Journal
                Microb Ecol
                Microb Ecol
                Microbial Ecology
                Springer US (New York )
                0095-3628
                1432-184X
                23 March 2021
                23 March 2021
                2021
                : 82
                : 1
                : 243-256
                Affiliations
                [1 ]GRID grid.4332.6, ISNI 0000 0000 9799 7097, Bioresources Unit, Center for Health & Bioresources, , AIT Austrian Institute of Technology GmbH, ; Vienna, Austria
                [2 ]GRID grid.5173.0, ISNI 0000 0001 2298 5320, Forest Ecology, Dept. of Forest and Soil Sciences, , University of Natural Resources and Life Sciences (BOKU), ; Peter-Jordan-Strasse 82, 1190 Vienna, Austria
                [3 ]GRID grid.419754.a, ISNI 0000 0001 2259 5533, Forest Soils and Biogeochemistry, , Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), ; Birmensdorf, Switzerland
                [4 ]Symbiocyte, Vienna, Austria
                [5 ]GRID grid.100572.1, ISNI 0000 0004 0448 8410, Environment Agency Austria, ; Vienna, Austria
                Author information
                https://orcid.org/0000-0003-3010-6044
                https://orcid.org/0000-0003-4366-9188
                https://orcid.org/0000-0001-7974-3058
                http://orcid.org/0000-0001-8098-0616
                https://orcid.org/0000-0002-0790-3881
                https://orcid.org/0000-0001-9710-7688
                https://orcid.org/0000-0002-2496-6307
                https://orcid.org/0000-0003-0534-8391
                https://orcid.org/0000-0001-5607-5800
                Article
                1736
                10.1007/s00248-021-01736-5
                8282586
                33755773
                ac573e9d-d8b3-46b9-8d53-a80d516819c5
                © The Author(s) 2021

                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
                : 27 October 2020
                : 10 March 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001822, Österreichischen Akademie der Wissenschaften;
                Award ID: C-Alp I
                Award ID: C-Alp II
                Award Recipient :
                Categories
                Soil Microbiology
                Custom metadata
                © Springer Science+Business Media, LLC, part of Springer Nature 2021

                Microbiology & Virology
                ectomycorrhiza,mountainous beech forest,plant pathogenic fungi,saprotrophic fungi,soil fungal communities,spatial and seasonal diversity

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