5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Differential expression of long non-coding RNAs under Peste des petits ruminants virus (PPRV) infection in goats

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          ABSTRACT

          Peste des petits ruminants (PPR) characterized by fever, sore mouth, conjunctivitis, gastroenteritis, and pneumonia, is an acute, highly contagious viral disease of sheep and goats. The role of long non-coding RNAs (lncRNAs) in PPRV infection has not been explored to date. In this study, the transcriptome profiles of virulent Peste des petits ruminants virus (PPRV) infected goat tissues – lung and spleen were analyzed to identify the role of lncRNAs in PPRV infection. A total of 13,928 lncRNA transcripts were identified, out of which 170 were known lncRNAs. Intergenic lncRNAs (7625) formed the major chunk of the novel lncRNA transcripts. Differential expression analysis revealed that 15 lncRNAs (11 downregulated and 4 upregulated) in the PPRV infected spleen samples and 16 lncRNAs (13 downregulated and 3 upregulated) in PPRV infected lung samples were differentially expressed as compared to control. The differentially expressed lncRNAs (DElncRNAs) possibly regulate various immunological processes related to natural killer cell activation, antigen processing and presentation, and B cell activity, by regulating the expression of mRNAs through the cis- or trans-regulatory mechanism. Functional enrichment analysis of differentially expressed mRNAs (DEmRNAs) revealed enrichment of immune pathways and biological processes in concordance with the pathways in which correlated lncRNA-neighboring genes were enriched. The results suggest that a coordinated immune response is raised in both lung and spleen tissues of the goat through mRNA-lncRNA crosstalk.

          Related collections

          Most cited references68

          • Record: found
          • Abstract: found
          • Article: not found

          STAR: ultrafast universal RNA-seq aligner.

          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/.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Cytoscape: a software environment for integrated models of biomolecular interaction networks.

              Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
                Bookmark

                Author and article information

                Journal
                Virulence
                Virulence
                Virulence
                Taylor & Francis
                2150-5594
                2150-5608
                6 February 2022
                2022
                6 February 2022
                : 13
                : 1
                : 310-322
                Affiliations
                [a ]Division of Veterinary Biotechnology, ICAR-IVRI; , Bareilly, India
                [b ]Department of Biological Sciences, SHUATS; , Allahabad, India
                [c ]Genomics and Bioinformatics, National Institute of Animal Biotechnology; , Hyderabad, India
                [d ]Division of Animal Genetics and Breeding, ICAR-IVRI; , Bareilly, India
                [e ]Division of Biological Products, ICAR-IVRI; , Bareilly, India
                [f ]Division of Virology, ICAR-IVRI; , Nainital, India
                Author notes
                CONTACT Bishnu Prasad Mishra bpmishra_1@ 123456hotmail.com Division of Veterinary Biotechnology, ICAR-IVRI, Bareilly, India
                Ravi Kumar Gandham gandham71@ 123456gmail.com Genomics and Bioinformatics National Institute of Animal Biotechnology; , India
                [#]

                Equal contributors

                Author information
                https://orcid.org/0000-0002-9505-8648
                Article
                2026564
                10.1080/21505594.2022.2026564
                8824212
                35129076
                dee9372f-8a13-44a7-9c41-b87772c73639
                © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Figures: 7, Tables: 3, References: 68, Pages: 13
                Categories
                Research Article
                Research Paper

                Infectious disease & Microbiology
                lncrna,goat,immune response,ppr,rna-seq,pprv
                Infectious disease & Microbiology
                lncrna, goat, immune response, ppr, rna-seq, pprv

                Comments

                Comment on this article