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      mRNA Inventory of Extracellular Vesicles from Ustilago maydis

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          Abstract

          Extracellular vesicles (EVs) can transfer diverse RNA cargo for intercellular communication. EV-associated RNAs have been found in diverse fungi and were proposed to be relevant for pathogenesis in animal hosts. In plant-pathogen interactions, small RNAs are exchanged in a cross-kingdom RNAi warfare and EVs were considered to be a delivery mechanism. To extend the search for EV-associated molecules involved in plant-pathogen communication, we have characterised the repertoire of EV-associated mRNAs secreted by the maize smut pathogen, Ustilago maydis. For this initial survey, we examined EV-enriched fractions from axenic filamentous cultures that mimic infectious hyphae. EV-associated RNAs were resistant to degradation by RNases and the presence of intact mRNAs was evident. The set of mRNAs enriched inside EVs relative to the fungal cells are functionally distinct from those that are depleted from EVs. mRNAs encoding metabolic enzymes are particularly enriched. Intriguingly, mRNAs of some known effectors and other proteins linked to virulence were also found in EVs. Furthermore, several mRNAs enriched in EVs are also upregulated during infection, suggesting that EV-associated mRNAs may participate in plant-pathogen interactions.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                J Fungi (Basel)
                J Fungi (Basel)
                jof
                Journal of Fungi
                MDPI
                2309-608X
                14 July 2021
                July 2021
                : 7
                : 7
                : 562
                Affiliations
                [1 ]Institute for Microbiology, Cluster of Excellence on Plant Sciences, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany; Seomun.Kwon@ 123456hhu.de (S.K.); Anton.Kraege@ 123456hhu.de (A.K.)
                [2 ]Bioinformatics and Systems Biology, Justus-Liebig-Universität, 35392 Giessen, Germany; oliver.rupp@ 123456computational.bio.uni-giessen.de (O.R.); Alexander.Goesmann@ 123456computational.bio.uni-giessen.de (A.G.)
                [3 ]Biocenter of the LMU Munich, Genetics Section, Grosshaderner Str. 2-4, 82152 Planegg-Martinsried, Germany; brachmann@ 123456lmu.de
                [4 ]Institute for Mathematical Modelling of Biological Systems, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany; Christopher.Blum@ 123456hhu.de
                Author notes
                [* ]Correspondence: feldbrue@ 123456hhu.de ; Tel.: +49-211-81-14720
                Author information
                https://orcid.org/0000-0002-0514-1465
                https://orcid.org/0000-0001-7980-8173
                https://orcid.org/0000-0002-7086-2568
                Article
                jof-07-00562
                10.3390/jof7070562
                8306574
                34356940
                3a563a75-af3e-48c0-965e-18bd49ec4788
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 08 June 2021
                : 07 July 2021
                Categories
                Article

                extracellular vesicles (evs),mrna,fungal pathogen,plant pathogen,ustilago maydis

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