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      Molecular epidemiological study of feline coronavirus strains in Japan using RT-PCR targeting nsp14 gene

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          Abstract

          Background

          Feline infectious peritonitis is a fatal disease of cats caused by infection with feline coronavirus (FCoV). For detecting or genotyping of FCoV, some RT-PCR plus nested PCR techniques have been reported previously. However, referring to the whole genome sequences (WGSs) registered at NCBI, there are no detection methods that can tolerate the genetic diversity among FCoV population. In addition, the quasispecies nature of FCoV, which consists of heterogeneous variants, has been also demonstrated; thus, a universal method for heteropopulations of FCoV variants in clinical specimens is desirable.

          Results

          To develop an RT-PCR method for detection and genotyping of FCoV, we performed comparative genome analysis using WGSs of 32 FCoV, 7 CCoV and 5 TGEV strains obtained from NCBI. As the PCR target, we focused on the nsp14 coding region, which is highly conserved and phylogenetically informative, and developed a PCR method targeting nsp14 partial sequences. Among 103 ascites, 45 pleural effusion and 214 blood specimens from clinically ill cats, we could detect FCoV in 55 (53.4%), 14 (31.1%) and 19 (8.9%) specimens using the present method. Direct sequencing of PCR products and phylogenetic analysis allowed discrimination between type I- and II-FCoV serotypes. Our nsp14 amino acid sequence typing (nsp14 aa ST) showed that the FCoV clone with sequence type (ST) 42, which was the most predominant genotype of WGS strains, was prevalent in domestic cats in Japan.

          Conclusions

          Our nsp14 PCR scheme will contribute to virus detection, epidemiology and ecology of FCoV strains.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12917-015-0372-2) contains supplementary material, which is available to authorized users.

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          Most cited references34

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          GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.

          J Besemer (2001)
          Improving the accuracy of prediction of gene starts is one of a few remaining open problems in computer prediction of prokaryotic genes. Its difficulty is caused by the absence of relatively strong sequence patterns identifying true translation initiation sites. In the current paper we show that the accuracy of gene start prediction can be improved by combining models of protein-coding and non-coding regions and models of regulatory sites near gene start within an iterative Hidden Markov model based algorithm. The new gene prediction method, called GeneMarkS, utilizes a non-supervised training procedure and can be used for a newly sequenced prokaryotic genome with no prior knowledge of any protein or rRNA genes. The GeneMarkS implementation uses an improved version of the gene finding program GeneMark.hmm, heuristic Markov models of coding and non-coding regions and the Gibbs sampling multiple alignment program. GeneMarkS predicted precisely 83.2% of the translation starts of GenBank annotated Bacillus subtilis genes and 94.4% of translation starts in an experimentally validated set of Escherichia coli genes. We have also observed that GeneMarkS detects prokaryotic genes, in terms of identifying open reading frames containing real genes, with an accuracy matching the level of the best currently used gene detection methods. Accurate translation start prediction, in addition to the refinement of protein sequence N-terminal data, provides the benefit of precise positioning of the sequence region situated upstream to a gene start. Therefore, sequence motifs related to transcription and translation regulatory sites can be revealed and analyzed with higher precision. These motifs were shown to possess a significant variability, the functional and evolutionary connections of which are discussed.
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            Middle East Respiratory Syndrome Coronavirus (MERS-CoV): Announcement of the Coronavirus Study Group

            Journal of Virology, 87(14), 7790-7792
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              Coronavirus Genomics and Bioinformatics Analysis

              The drastic increase in the number of coronaviruses discovered and coronavirus genomes being sequenced have given us an unprecedented opportunity to perform genomics and bioinformatics analysis on this family of viruses. Coronaviruses possess the largest genomes (26.4 to 31.7 kb) among all known RNA viruses, with G + C contents varying from 32% to 43%. Variable numbers of small ORFs are present between the various conserved genes (ORF1ab, spike, envelope, membrane and nucleocapsid) and downstream to nucleocapsid gene in different coronavirus lineages. Phylogenetically, three genera, Alphacoronavirus, Betacoronavirus and Gammacoronavirus, with Betacoronavirus consisting of subgroups A, B, C and D, exist. A fourth genus, Deltacoronavirus, which includes bulbul coronavirus HKU11, thrush coronavirus HKU12 and munia coronavirus HKU13, is emerging. Molecular clock analysis using various gene loci revealed that the time of most recent common ancestor of human/civet SARS related coronavirus to be 1999–2002, with estimated substitution rate of 4×10−4 to 2×10−2 substitutions per site per year. Recombination in coronaviruses was most notable between different strains of murine hepatitis virus (MHV), between different strains of infectious bronchitis virus, between MHV and bovine coronavirus, between feline coronavirus (FCoV) type I and canine coronavirus generating FCoV type II, and between the three genotypes of human coronavirus HKU1 (HCoV-HKU1). Codon usage bias in coronaviruses were observed, with HCoV-HKU1 showing the most extreme bias, and cytosine deamination and selection of CpG suppressed clones are the two major independent biological forces that shape such codon usage bias in coronaviruses.
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                Author and article information

                Contributors
                ytanaka@nvlu.ac.jp
                hiteiha@juntendo.ac.jp
                oyradustam@gmail.com
                uematsu@canine-lab.jp
                yamaguchi@canine-lab.jp
                Journal
                BMC Vet Res
                BMC Vet. Res
                BMC Veterinary Research
                BioMed Central (London )
                1746-6148
                11 March 2015
                11 March 2015
                2015
                : 11
                : 57
                Affiliations
                [ ]Department of Veterinary Hygiene, Veterinary School, Nippon Veterinary & Life Science University, 1-7-1 Kyounan, Musashino, Tokyo 180-8602 Japan
                [ ]Canine Lab., Inc., Nokodai-Tamakoganei Venture Port 302, 2-24-16, Koganei, Tokyo 184-0012 Japan
                Article
                372
                10.1186/s12917-015-0372-2
                4359392
                25889235
                4223ebf9-accf-4545-85c1-3a455c8cc3e8
                © Tanaka et al.; licensee BioMed Central. 2015

                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 credited. 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.

                History
                : 21 June 2014
                : 24 February 2015
                Categories
                Methodology Article
                Custom metadata
                © The Author(s) 2015

                Veterinary medicine
                feline coronavirus,epidemiology,phylogenetic study
                Veterinary medicine
                feline coronavirus, epidemiology, phylogenetic study

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