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      RNA Sequencing (RNA-Seq) Based Transcriptome Analysis in Immune Response of Holstein Cattle to Killed Vaccine against Bovine Viral Diarrhea Virus Type I

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          Abstract

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          Due to the undeniable detrimental impact of bovine viral diarrhea virus (BVDV) on cattle worldwide, various preventive approaches are carried out to control the spread of this disease. Among the established preventive approaches, vaccination remains the most widely used cost-effective method of control. Hence, a deeper study into the host immune response to vaccines will further refine the efficacy of these vaccines; the identification of differentially expressed genes (DEGs) related to immune response might bring a long-lasting solution. Thus far, studies showing the genes related to the immune response of cattle to vaccines are still limited. Therefore, this study identified DEGs in animals with high and low sample to positive (S/P) ratio based on the BVDV antibody level, using RNA sequencing (RNA-seq) transcriptome analysis, and functional enrichment analysis in gene ontology (GO) annotations and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Results revealed that several upregulated and downregulated genes were significantly annotated to antigen processing and presentation (MHC class I), immune response, and interferon-gamma production, indicating the immune response of the animals related to possible shaping of their adaptive immunity against the BVDV type I. Moreover, significant enrichment to various KEGG pathways related to the development of adaptive immunity was observed.

          Abstract

          Immune response of 107 vaccinated Holstein cattle was initially obtained prior to the ELISA test. Five cattle with high and low bovine viral diarrhea virus (BVDV) type I antibody were identified as the final experimental animals. Blood samples from these animals were then utilized to determine significant differentially expressed genes (DEGs) using the RNA-seq transcriptome analysis and enrichment analysis. Our analysis identified 261 DEGs in cattle identified as experimental animals. Functional enrichment analysis in gene ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed the DEGs potentially induced by the inactivated BVDV type I vaccine, and might be responsible for the host immune responses. Our findings suggested that inactivated vaccine induced upregulation of genes involved in different GO annotations, including antigen processing and presentation of peptide antigen (via MHC class I), immune response, and positive regulation of interferon-gamma production. The observed downregulation of other genes involved in immune response might be due to inhibition of toll-like receptors (TLRs) by the upregulation of the Bcl-3 gene. Meanwhile, the result of KEGG pathways revealed that the majority of DEGs were upregulated and enriched to different pathways, including cytokine-cytokine receptor interaction, platelet activation, extracellular matrix (ECM) receptor interaction, hematopoietic cell lineage, and ATP-binding cassette (ABC) transporters. These significant pathways supported our initial findings and are known to play a vital role in shaping adaptive immunity against BVDV type 1. In addition, type 1 diabetes mellitus pathways tended to be significantly enriched. Thus, further studies are needed to investigate the prevalence of type 1 diabetes mellitus in cattle vaccinated with inactivated and live BVDV vaccine.

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          Computational methods for transcriptome annotation and quantification using RNA-seq.

          High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications.
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            RNA-Seq methods for transcriptome analysis

            Deep sequencing has been revolutionizing biology and medicine in recent years, providing single base-level precision for our understanding of nucleic acid sequences in high throughput fashion. Sequencing of RNA, or RNA-Seq, is now a common method to analyze gene expression and to uncover novel RNA species. Aspects of RNA biogenesis and metabolism can be interrogated with specialized methods for cDNA library preparation. In this study, we review current RNA-Seq methods for general analysis of gene expression and several specific applications, including isoform and gene fusion detection, digital gene expression profiling, targeted sequencing and single-cell analysis. In addition, we discuss approaches to examine aspects of RNA in the cell, technical challenges of existing RNA-Seq methods, and future directions.
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              Transcriptome analysis using next-generation sequencing.

              Up to date research in biology, biotechnology, and medicine requires fast genome and transcriptome analysis technologies for the investigation of cellular state, physiology, and activity. Here, microarray technology and next generation sequencing of transcripts (RNA-Seq) are state of the art. Since microarray technology is limited towards the amount of RNA, the quantification of transcript levels and the sequence information, RNA-Seq provides nearly unlimited possibilities in modern bioanalysis. This chapter presents a detailed description of next-generation sequencing (NGS), describes the impact of this technology on transcriptome analysis and explains its possibilities to explore the modern RNA world. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Animals (Basel)
                Animals (Basel)
                animals
                Animals : an Open Access Journal from MDPI
                MDPI
                2076-2615
                21 February 2020
                February 2020
                : 10
                : 2
                : 344
                Affiliations
                [1 ]Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju 55365, Korea; irvinelopez@ 123456korea.kr
                [2 ]Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Korea; santiagokier2015@ 123456gmail.com (K.G.S.); a3832737@ 123456naver.com (D.L.)
                [3 ]Department of Animal Science, College of Agriculture, Central Luzon State University, Science City of Muńoz 3120, Philippines
                [4 ]Dairy Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Korea; justusha@ 123456korea.kr
                Author notes
                [* ]Correspondence: sks@ 123456sunchon.ac.kr
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-3288-5849
                Article
                animals-10-00344
                10.3390/ani10020344
                7070844
                32098229
                9a842d95-ebc4-4279-b319-2a7e736d188e
                © 2020 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
                : 07 February 2020
                : 18 February 2020
                Categories
                Article

                bovine viral diarrhea virus,rna-seq,transcriptome analysis,holstein cattle

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