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      Analysis of Evolutionary Processes of Species Jump in Waterfowl Parvovirus

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          Abstract

          Waterfowl parvoviruses are classified into goose parvovirus (GPV) and Muscovy duck parvovirus (MDPV) according to their antigenic features and host preferences. A novel duck parvovirus (NDPV), identified as a new variant of GPV, is currently infecting ducks, thus causing considerable economic loss. This study analyzed the molecular evolution and population dynamics of the emerging parvovirus capsid gene to investigate the evolutionary processes concerning the host shift of NDPV. Two important amino acids changes (Asn-489 and Asn-650) were identified in NDPV, which may be responsible for host shift of NDPV. Phylogenetic analysis indicated that the currently circulating NDPV originated from the GPV lineage. The Bayesian Markov chain Monte Carlo tree indicated that the NDPV diverged from GPV approximately 20 years ago. Evolutionary rate analyses demonstrated that GPV evolved with 7.674 × 10 -4 substitutions/site/year, and the data for MDPV was 5.237 × 10 -4 substitutions/site/year, whereas the substitution rate in NDPV branch was 2.25 × 10 -3 substitutions/site/year. Meanwhile, viral population dynamics analysis revealed that the GPV major clade, including NDPV, grew exponentially at a rate of 1.717 year -1. Selection pressure analysis showed that most sites are subject to strong purifying selection and no positively selected sites were found in NDPV. The unique immune-epitopes in waterfowl parvovirus were also estimated, which may be helpful for the prediction of antibody binding sites against NDPV in ducks.

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          Most cited references42

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          Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology.

          Datamonkey is a popular web-based suite of phylogenetic analysis tools for use in evolutionary biology. Since the original release in 2005, we have expanded the analysis options to include recently developed algorithmic methods for recombination detection, evolutionary fingerprinting of genes, codon model selection, co-evolution between sites, identification of sites, which rapidly escape host-immune pressure and HIV-1 subtype assignment. The traditional selection tools have also been augmented to include recent developments in the field. Here, we summarize the analyses options currently available on Datamonkey, and provide guidelines for their use in evolutionary biology. Availability and documentation: http://www.datamonkey.org.
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            There is an increasing interest in detecting genes, or genomic regions, that have been targeted by natural selection. The interest stems from a basic desire to learn more about evolutionary processes in humans and other organisms, and from the realization that inferences regarding selection may provide important functional information. This review provides a nonmathematical description of the issues involved in detecting selection from DNA sequences and SNP data and is intended for readers who are not familiar with population genetic theory. Particular attention is placed on issues relating to the analysis of large-scale genomic data sets.
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              A semi-empirical method for prediction of antigenic determinants on protein antigens.

              Analysis of data from experimentally determined antigenic sites on proteins has revealed that the hydrophobic residues Cys, Leu and Val, if they occur on the surface of a protein, are more likely to be a part of antigenic sites. A semi-empirical method which makes use of physicochemical properties of amino acid residues and their frequencies of occurrence in experimentally known segmental epitopes was developed to predict antigenic determinants on proteins. Application of this method to a large number of proteins has shown that our method can predict antigenic determinants with about 75% accuracy which is better than most of the known methods. This method is based on a single parameter and thus very simple to use.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                14 March 2017
                2017
                : 8
                : 421
                Affiliations
                [1] 1College of Veterinary Medicine, Nanjing Agricultural University Nanjing, China
                [2] 2Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University Nanjing, China
                [3] 3Waterfowl Healthy Breeding Engineering Research Center, Guangdong Higher Education Institutes Guangzhou, China
                Author notes

                Edited by: Akio Adachi, University of Tokushima, Japan

                Reviewed by: Marta Canuti, Memorial University of Newfoundland, Canada; Dongbo Sun, Heilongjiang Bayi Agricultural University, China

                *Correspondence: Liping Yan, yanliping@ 123456njau.edu.cn

                This article was submitted to Virology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2017.00421
                5349109
                539de1fe-bd09-42ff-9d21-188492a90ba6
                Copyright © 2017 Fan, Sun, Shen, Xu, Huang, Zhou, Song and Yan.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 January 2017
                : 28 February 2017
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 62, Pages: 9, Words: 0
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                species jump,waterfowl parvovirus,phylogeny,epidemiology,evolution,bayesian inference

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