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      dRNA-Seq Reveals Genomewide TSSs and Noncoding RNAs of Plant Beneficial Rhizobacterium Bacillus amyloliquefaciens FZB42

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          Abstract

          Bacillus amyloliquefaciens subsp. plantarum FZB42 is a representative of Gram-positive plant-growth-promoting rhizobacteria (PGPR) that inhabit plant root environments. In order to better understand the molecular mechanisms of bacteria-plant symbiosis, we have systematically analyzed the primary transcriptome of strain FZB42 grown under rhizosphere-mimicking conditions using differential RNA sequencing (dRNA-seq). Our analysis revealed 4,877 transcription start sites for protein-coding genes, identified genes differentially expressed under different growth conditions, and corrected many previously mis-annotated genes. We also identified a large number of riboswitches and cis-encoded antisense RNAs, as well as trans-encoded small noncoding RNAs that may play important roles in the gene regulation of Bacillus. Overall, our analyses provided a landscape of Bacillus primary transcriptome and improved the knowledge of rhizobacteria-host interactions.

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          Most cited references67

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          Pathview: an R/Bioconductor package for pathway-based data integration and visualization

          Summary: Pathview is a novel tool set for pathway-based data integration and visualization. It maps and renders user data on relevant pathway graphs. Users only need to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps and integrates user data onto the pathway and renders pathway graphs with the mapped data. Although built as a stand-alone program, Pathview may seamlessly integrate with pathway and functional analysis tools for large-scale and fully automated analysis pipelines. Availability: The package is freely available under the GPLv3 license through Bioconductor and R-Forge. It is available at http://bioconductor.org/packages/release/bioc/html/pathview.html and at http://Pathview.r-forge.r-project.org/. Contact: luo_weijun@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online.
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            Rfam: an RNA family database.

            Rfam is a collection of multiple sequence alignments and covariance models representing non-coding RNA families. Rfam is available on the web in the UK at http://www.sanger.ac.uk/Software/Rfam/ and in the US at http://rfam.wustl.edu/. These websites allow the user to search a query sequence against a library of covariance models, and view multiple sequence alignments and family annotation. The database can also be downloaded in flatfile form and searched locally using the INFERNAL package (http://infernal.wustl.edu/). The first release of Rfam (1.0) contains 25 families, which annotate over 50 000 non-coding RNA genes in the taxonomic divisions of the EMBL nucleotide database.
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              Regulatory RNAs in bacteria.

              Bacteria possess numerous and diverse means of gene regulation using RNA molecules, including mRNA leaders that affect expression in cis, small RNAs that bind to proteins or base pair with target RNAs, and CRISPR RNAs that inhibit the uptake of foreign DNA. Although examples of RNA regulators have been known for decades in bacteria, we are only now coming to a full appreciation of their importance and prevalence. Here, we review the known mechanisms and roles of regulatory RNAs, highlight emerging themes, and discuss remaining questions.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                5 November 2015
                2015
                : 10
                : 11
                : e0142002
                Affiliations
                [1 ]Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, 210037 Nanjing, China
                [2 ]RNA Biology Group, Institute for Molecular Infection Biology, University of Würzburg, 97080 Würzburg, Germany
                [3 ]Fachgebiet Phytomedizin, Albrecht Daniel Thaer Institut für Agrar- und Gartenbauwissenschaften, Lebenswissenschaftliche Fakultät, Humboldt Universität zu Berlin, 14195 Berlin, Germany
                Max-Planck-Institute for Terrestrial Microbiology, GERMANY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: BF. Performed the experiments: BF. Analyzed the data: BF LL YC KF. Contributed reagents/materials/analysis tools: RB JV XW. Wrote the paper: BF LL YC RB JV.

                Article
                PONE-D-15-30729
                10.1371/journal.pone.0142002
                4634765
                26540162
                d43852fe-b672-43d4-abc7-733b5c764ceb
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 13 July 2015
                : 15 October 2015
                Page count
                Figures: 5, Tables: 0, Pages: 24
                Funding
                The financial support by the National Natural Science Foundation of China (No. 31100081) and Scientific Research Foundation of Nanjing Forestry University for Introduction of High Level Talents (YJ2012-03) is gratefully acknowledged, as well as the financial support given by the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions. This study was further supported by the Natural Science Foundation of Jiangsu Province (No. BK20151514).
                Categories
                Research Article
                Custom metadata
                All detailed TSS information is available from the NCBI Gene Expression Omnibus (GEO) with accession number GSE66681.

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