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      Microbial community composition in the rhizosphere of Larix decidua under different light regimes with additional focus on methane cycling microorganisms

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      Scientific Reports
      Nature Publishing Group UK
      Microbial ecology, Soil microbiology, Archaea, Bacteria, Fungi, Microbiome, Symbiosis, Ecology

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          Abstract

          Microbial community and diversity in the rhizosphere is strongly influenced by biotic and/or abiotic factors, like root exudates, nutrient availability, edaphon and climate. Here we report on the microbial diversity within the rhizosphere of Larix decidua, a dominant tree species in the Alps, as compared with the microbiome within the surrounding soil. We describe how increased light intensity influenced the rhizobiome and put emphasize on methane cycling microorganisms. Microbial taxa were classified into 26 bacterial, 4 archaeal and 6 fungal phyla revealing significant differences between bulk and rhizosphere soils. The dominant prokaryotic phyla were Proteobacteria, Acidobacteria, Actinobacteria (both, rhizosphere and bulk soil) and Bacteroidetes (rhizosphere soil only) and dominant fungal phyla in both fractions included Ascomycota and Basidiomycota. The rhizosphere community was indicated by Suillus sp., plant growth-promoting bacteria and Candidatus Saccharibacteria. Predicted genes in membrane transport and carbohydrate metabolism were significantly more abundant in rhizosphere soils while genes connected with energy metabolisms and cell motility increased in bulk soils. Dominant methanotrophic microorganisms were Upland Soil Cluster (USC) α methanotrophs, Methylogaea spp. and Methylosinus spp., while most methanogens belonged to Methanomassiliicoccales. The overall abundance of methanotrophs distinctly increased in the rhizosphere but to a very different species-specific extent. The increased light intensity only led to minor changes in the rhizobiome, nevertheless a couple of indicator species (e.g. Pseudomonas sp.) for intensified light conditions were established.

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

            We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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
                Nadine.Praeg@uibk.ac.at
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 December 2020
                18 December 2020
                2020
                : 10
                : 22324
                Affiliations
                GRID grid.5771.4, ISNI 0000 0001 2151 8122, Department of Microbiology, , Universität Innsbruck, ; Technikerstrasse 25d, 6020 Innsbruck, Austria
                Article
                79143
                10.1038/s41598-020-79143-y
                7749151
                33339837
                c623bac0-4f50-4e7b-8d6a-5ddda263e7dd
                © The Author(s) 2020

                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
                : 24 January 2020
                : 1 December 2020
                Categories
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                Custom metadata
                © The Author(s) 2020

                Uncategorized
                microbial ecology,soil microbiology,archaea,bacteria,fungi,microbiome,symbiosis,ecology
                Uncategorized
                microbial ecology, soil microbiology, archaea, bacteria, fungi, microbiome, symbiosis, ecology

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