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      Evaluating the effect of TLR4-overexpressing on the transcriptome profile in ovine peripheral blood mononuclear cells

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          Abstract

          Background

          Toll-like receptor 4 (TLR4) plays an important role in the elimination of Gram-negative bacteria infections and the initiation of antiinflammatory response. Using the technology of pronuclear microinjection, genetically modified (GM) sheep with TLR4 overexpression were generated. Previous studies have shown that these GM sheep exhibited a higher inflammatory response to Gram-negative bacteria infection than wild type (WT) sheep. In order to evaluate the gene expression of GM sheep and study the co-expressed and downstream genes for TLR4, peripheral blood mononuclear cells (PBMC) from TLR4-overexpressing (Tg) and wild type (WT) sheep were selected to discover the transcriptomic differences using RNA-Seq.

          Result

          An average of 18,754 and 19,530 known genes were identified in the Tg and WT libraries, respectively. A total of 338 known genes and 85 novel transcripts were found to be differentially expressed in the two libraries ( p < 0.01). A differentially expressed genes (DEGs) enrichment analysis showed that the GO terms of inflammatory response, cell recognition, etc. were significantly (FDR < 0.05) enriched. Furthermore, the above DEGs were significantly (FDR < 0.05) enriched in the sole KEGG pathway of the Phagosome. Real-time PCR showed the OLR1, TLR4 and CD14 genes to be differentially expressed in the two groups, which validated the DEGs data.

          Conclusions

          The RNA-Seq results revealed that the overexpressed TLR4 in our experiment strengthened the ovine innate immune response by increasing the phagocytosis in PBMC.

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          Most cited references 45

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          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.
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            Pfam: the protein families database

            Pfam, available via servers in the UK (http://pfam.sanger.ac.uk/) and the USA (http://pfam.janelia.org/), is a widely used database of protein families, containing 14 831 manually curated entries in the current release, version 27.0. Since the last update article 2 years ago, we have generated 1182 new families and maintained sequence coverage of the UniProt Knowledgebase (UniProtKB) at nearly 80%, despite a 50% increase in the size of the underlying sequence database. Since our 2012 article describing Pfam, we have also undertaken a comprehensive review of the features that are provided by Pfam over and above the basic family data. For each feature, we determined the relevance, computational burden, usage statistics and the functionality of the feature in a website context. As a consequence of this review, we have removed some features, enhanced others and developed new ones to meet the changing demands of computational biology. Here, we describe the changes to Pfam content. Notably, we now provide family alignments based on four different representative proteome sequence data sets and a new interactive DNA search interface. We also discuss the mapping between Pfam and known 3D structures.
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              featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

               Y. Liao,  G Smyth,  W Shi (2014)
              Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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                Author and article information

                Contributors
                guoxfnongda@163.com
                jlzhang1010@163.com
                yaoli19881015@126.com
                YangJing9599@163.com
                sheepteam@163.com
                dongchx16@163.com
                gshliu@cau.edu.cn
                lianzhx@cau.edu.cn
                zhangxs0221@126.com
                Journal
                J Biol Res (Thessalon)
                J Biol Res (Thessalon)
                Journal of Biological Research
                BioMed Central (London )
                1790-045X
                2241-5793
                29 July 2020
                29 July 2020
                December 2020
                : 27
                Affiliations
                [1 ]GRID grid.464465.1, ISNI 0000 0001 0103 2256, Tianjin Institute of Animal Husbandry and Veterinary Medicine, , Tianjin Academy of Agricultural Sciences, ; Tianjin, 300381 China
                [2 ]GRID grid.22935.3f, ISNI 0000 0004 0530 8290, College of Animal Science and Technology, , China Agricultural University, ; Beijing, 100193 China
                Article
                124
                10.1186/s40709-020-00124-3
                7392728
                © The Author(s) 2020

                Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                Funding
                Funded by: National Transgenic Creature Breeding Grand Project
                Award ID: No.2016zx08008-003
                Award Recipient :
                Funded by: Tianjin Science and Technology Plan Project
                Award ID: No.16ZXZYNC00050
                Award Recipient :
                Funded by: Beijing Science and Technology Planning Project (CN)
                Award ID: No.18ZXZYNC00180
                Award Recipient :
                Funded by: Tianjin Science and Technology Plan Project
                Award ID: No.19ZXZYSN00030
                Award Recipient :
                Funded by: The Youth Innovative Research and Experimental Project of Tianjin Academy of Agricultural Sciences
                Award ID: No. 201902
                Award ID: No. 201915
                Award ID: No. 2020013
                Award Recipient :
                Categories
                Research
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                © The Author(s) 2020

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