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      The identification of a transposon affecting the asexual reproduction of the wheat pathogen Zymoseptoria tritici


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          Zymoseptoria tritici, the causal agent of Septoria tritici blotch, is a fungal wheat pathogen that causes significant global yield losses. Within Z. tritici populations, quantitative differences in virulence among different isolates are commonly observed; however, the genetic components that underpin these differences remain elusive. In this study, intraspecific comparative transcriptomic analysis was used to identify candidate genes that contribute to differences in virulence on the wheat cultivar WW2449. This led to the identification of a multicopy gene that was not expressed in the high‐virulence isolate when compared to the medium‐ and low‐virulence isolates. Further investigation suggested this gene resides in a 7.9‐kb transposon. Subsequent long‐read sequencing of the isolates used in the transcriptomic analysis confirmed that this gene did reside in an active Class II transposon, which is composed of four genes named REP9‐1 to ‐4. Silencing and overexpression of REP9‐1 in two distinct genetic backgrounds demonstrated that its expression alone reduces the number of pycnidia produced by Z. tritici during infection. The REP9‐1 gene identified within a Class II transposon is the first discovery of a gene in a transposable element that influences the virulence of Z. tritici. This discovery adds further complexity to genetic loci that contribute to quantitative virulence in this important pathogen.


          The expression of the gene REP9‐1, which resides in an active Class II transposon, negatively regulates the rate of pycnidia appearance in planta of the wheat pathogen Zymoseptoria tritici.

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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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            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

              Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au

                Author and article information

                Mol Plant Pathol
                Mol Plant Pathol
                Molecular Plant Pathology
                John Wiley and Sons Inc. (Hoboken )
                05 May 2021
                July 2021
                : 22
                : 7 ( doiID: 10.1002/mpp.v22.7 )
                : 800-816
                [ 1 ] Division of Plant Sciences Research School of Biology The Australian National University Canberra ACT Australia
                [ 2 ] NSW Department of Primary Industries Wagga Wagga Agricultural Institute Wagga Wagga NSW Australia
                [ 3 ] School of Biosciences University of Birmingham Edgbaston Birmingham UK
                Author notes
                [*] [* ] Correspondence

                Megan C. McDonald and Peter S. Solomon, Division of Plant Sciences, Research School of Biology, The Australian National University, Canberra, ACT, Australia.

                Emails: m.c.mcdonald@ 123456bham.ac.uk (M. C. M); peter.solomon@ 123456anu.edu.au (P. S. S.)

                Author information
                © 2021 The Authors. Molecular Plant Pathology published by British Society for Plant Pathology and John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                : 15 March 2021
                : 22 May 2020
                : 16 March 2021
                Page count
                Figures: 7, Tables: 1, Pages: 17, Words: 12956
                Funded by: China Scholarship Council , open-funder-registry 10.13039/501100004543;
                Funded by: Grains Research and Development Corporation
                Funded by: Australian National University , open-funder-registry 10.13039/501100000995;
                Original Article
                Original Articles
                Custom metadata
                July 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:25.06.2021

                Plant science & Botany
                effector,quantitative virulence,transcriptomics,transposon,wheat,zymoseptoria tritici


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