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      Transcriptomic Profiling of Equine and Viral Genes in Peripheral Blood Mononuclear Cells in Horses during Equine Herpesvirus 1 Infection

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          Abstract

          Equine herpesvirus 1 (EHV-1) affects horses worldwide and causes respiratory disease, abortions, and equine herpesvirus myeloencephalopathy (EHM). Following infection, a cell-associated viremia is established in the peripheral blood mononuclear cells (PBMCs). This viremia is essential for transport of EHV-1 to secondary infection sites where subsequent immunopathology results in diseases such as abortion or EHM. Because of the central role of PBMCs in EHV-1 pathogenesis, our goal was to establish a gene expression analysis of host and equine herpesvirus genes during EHV-1 viremia using RNA sequencing. When comparing transcriptomes of PBMCs during peak viremia to those prior to EHV-1 infection, we found 51 differentially expressed equine genes (48 upregulated and 3 downregulated). After gene ontology analysis, processes such as the interferon defense response, response to chemokines, the complement protein activation cascade, cell adhesion, and coagulation were overrepresented during viremia. Additionally, transcripts for EHV-1, EHV-2, and EHV-5 were identified in pre- and post-EHV-1-infection samples. Looking at micro RNAs (miRNAs), 278 known equine miRNAs and 855 potentially novel equine miRNAs were identified in addition to 57 and 41 potentially novel miRNAs that mapped to the EHV-2 and EHV-5 genomes, respectively. Of those, 1 EHV-5 and 4 equine miRNAs were differentially expressed in PBMCs during viremia. In conclusion, this work expands our current knowledge about the role of PBMCs during EHV-1 viremia and will inform the focus on future experiments to identify host and viral factors that contribute to clinical EHM.

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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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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              clusterProfiler: an R package for comparing biological themes among gene clusters.

              Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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                Author and article information

                Journal
                Pathogens
                Pathogens
                pathogens
                Pathogens
                MDPI
                2076-0817
                07 January 2021
                January 2021
                : 10
                : 1
                : 43
                Affiliations
                [1 ]Department of Pathobiology and Diagnostic Investigation, Michigan State University, East Lansing, MI 48824, USA; zarskili@ 123456msu.edu (L.M.Z.); windy77919@ 123456gmail.com (Y.L.)
                [2 ]Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, MI 48824, USA; weberp@ 123456msu.edu
                Author notes
                [* ]Correspondence: husseygi@ 123456msu.edu
                Author information
                https://orcid.org/0000-0003-1877-6926
                Article
                pathogens-10-00043
                10.3390/pathogens10010043
                7825769
                33430330
                3a348802-df01-447a-9500-6665a1aec2f8
                © 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 ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 December 2020
                : 05 January 2021
                Categories
                Article

                ehv-1,herpesvirus,horse,pbmc,transcriptomics,rna sequencing,microrna,gene expression

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