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      Investigation of the transcriptomic response in Atlantic salmon ( Salmo salar) gill exposed to Paramoeba perurans during early onset of disease

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          Abstract

          Amoebic Gill Disease (AGD), caused by the protozoan extracellular parasite Paramoeba perurans ( P. perurans) is a disease affecting Atlantic salmon ( Salmo salar). This study investigated the gill transcriptomic profile of pre-clinical AGD using RNA-sequencing (RNA-seq) technology. RNA-seq libraries generated at 0, 4, 7, 14 and 16 days post infection (dpi) identified 19,251 differentially expressed genes (DEGs) of which 56.2% were up-regulated. DEGs mapped to 224 Gene Ontology (GO) terms including 140 biological processes (BP), 45 cellular components (CC), and 39 molecular functions (MF). A total of 27 reference pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and 15 Reactome gene sets were identified. The RNA-seq data was validated using real-time, quantitative PCR (qPCR). A host immune response though the activation of complement and the acute phase genes was evident at 7 dpi, with a concurrent immune suppression involving cytokine signalling, notably in interleukins, interferon regulatory factors and tumour necrosis factor-alpha ( tnf-α) genes. Down-regulated gene expression with involvement in receptor signalling pathways (NOD-like, Toll-like and RIG-1) were also identified. The results of this study support the theory that P. perurans can evade immune surveillance during the initial stages of gill colonisation through interference of signal transduction pathways.

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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
                anita.talbot@gmit.ie
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                19 October 2021
                19 October 2021
                2021
                : 11
                : 20682
                Affiliations
                [1 ]GRID grid.418104.8, ISNI 0000 0001 0414 8879, Galway Mayo Institute of Technology, ; Galway, Ireland
                [2 ]GRID grid.7886.1, ISNI 0000 0001 0768 2743, University College Dublin, ; Dublin 4, Ireland
                Article
                99996
                10.1038/s41598-021-99996-1
                8526816
                34667245
                116134d7-7040-4b38-9d0e-9ffd24e04c04
                © 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
                : 6 January 2021
                : 23 September 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001584, Department of Agriculture, Food and the Marine, Ireland;
                Award ID: Grant award No. 15 S 745
                Award ID: Grant award No. 15 S 745
                Award ID: Grant award No. 15 S 745
                Award ID: Grant award No. 15 S 745
                Award ID: Grant award No. 15 S 745
                Award ID: Grant award No. 15 S 745
                Award ID: Grant award No. 15 S 745
                Award ID: Grant award No. 15 S 745
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                molecular biology,transcriptomics,infection
                Uncategorized
                molecular biology, transcriptomics, infection

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