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      Dual Host and Pathogen RNA-Seq Analysis Unravels Chicken Genes Potentially Involved in Resistance to Highly Pathogenic Avian Influenza Virus Infection

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          Abstract

          Highly pathogenic avian influenza viruses (HPAIVs) cause severe systemic disease and high mortality rates in chickens, leading to a huge economic impact in the poultry sector. However, some chickens are resistant to the disease. This study aimed at evaluating the mechanisms behind HPAIV disease resistance. Chickens of different breeds were challenged with H7N1 HPAIV or clade 2.3.4.4b H5N8 HPAIV, euthanized at 3 days post-inoculation (dpi), and classified as resistant or susceptible depending on the following criteria: chickens that presented i) clinical signs, ii) histopathological lesions, and iii) presence of HPAIV antigen in tissues were classified as susceptible, while chickens lacking all these criteria were classified as resistant. Once classified, we performed RNA-Seq from lung and spleen samples in order to compare the transcriptomic signatures between resistant and susceptible chickens. We identified minor transcriptomic changes in resistant chickens in contrast with huge alterations observed in susceptible chickens. Interestingly, six differentially expressed genes were downregulated in resistant birds and upregulated in susceptible birds. Some of these genes belong to the NF-kappa B and/or mitogen-activated protein kinase signaling pathways. Among these six genes, the serine protease-encoding gene PLAU was of particular interest, being the most significantly downregulated gene in resistant chickens. Expression levels of this protease were further validated by RT-qPCR in a larger number of experimentally infected chickens. Furthermore, HPAIV quasi-species populations were constructed using 3 dpi oral swabs. No substantial changes were found in the viral segments that interact with the innate immune response and with the host cell receptors, reinforcing the role of the immune system of the host in the clinical outcome. Altogether, our results suggest that an early inactivation of important host genes could prevent an exaggerated immune response and/or viral replication, conferring resistance to HPAIV in chickens.

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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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              Fast and accurate short read alignment with Burrows–Wheeler transform

              Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                22 December 2021
                2021
                : 12
                : 800188
                Affiliations
                [1] 1Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona (UAB) , Bellaterra, Spain
                [2] 2Departament de Sanitat i Anatomia Animals, Universitat Autònoma de Barcelona, Campus de la Universitat Autònoma de Barcelona (UAB) , Bellaterra, Spain
                Author notes

                Edited by: Aurelio Cafaro, National Institute of Health (ISS), Italy

                Reviewed by: Katharine Edens Magor, University of Alberta, Canada; Lee Campbell, University of Alberta, Canada, in important truncation collaboration with reviewer KEM; Jacqueline Smith, University of Edinburgh, United Kingdom

                *Correspondence: Albert Perlas, albert.perlas@ 123456irta.cat

                This article was submitted to Viral Immunology, a section of the journal Frontiers in Immunology

                †These authors have contributed equally to this work and share last authorship

                Article
                10.3389/fimmu.2021.800188
                8727699
                35003125
                c909c6a5-3947-4c9a-bc96-02c37160abae
                Copyright © 2021 Perlas, Argilaguet, Bertran, Sánchez-González, Nofrarías, Valle, Ramis, Cortey and Majó

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 October 2021
                : 06 December 2021
                Page count
                Figures: 7, Tables: 0, Equations: 0, References: 95, Pages: 16, Words: 7240
                Funding
                Funded by: Instituto Nacional de Investigaciones Agropecuarias , doi 10.13039/501100010975;
                Award ID: RTA2015-00088-C03-03
                Funded by: Ministerio de Economía, Industria y Competitividad, Gobierno de España , doi 10.13039/501100010198;
                Award ID: RYC 2014 17154
                Categories
                Immunology
                Original Research

                Immunology
                chicken,avian influenza,innate immune response,genetic resistance,rna-seq,plau
                Immunology
                chicken, avian influenza, innate immune response, genetic resistance, rna-seq, plau

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