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      Divergent Viruses Discovered in Swine Alter the Understanding of Evolutionary History and Genetic Diversity of the Respirovirus Genus and Related Porcine Parainfluenza Viruses

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          ABSTRACT

          Paramyxoviridae is a rapidly growing family of viruses, whose potential for cross-species transmission makes it difficult to predict the harm of newly emerging viruses to humans and animals. To better understand their diversity, evolutionary history, and co-evolution with their hosts, we analyzed a collection of porcine parainfluenza virus (PPIV) genomes to reconstruct the species classification basis and evolutionary history of the Respirovirus genus. We sequenced 17 complete genomes of porcine respirovirus 1 (also known as porcine parainfluenza virus 1; PPIV-1), thereby nearly tripling the number of currently available PPIV-1 genomes. We found that PPIV-1 was widely prevalent in China with two divergent lineages, PPIV-1a and PPIV-1b. We further provided evidence that a new species, porcine parainfluenza virus 2 (PPIV-2), had recently emerged in China. Our results pointed to a need for revising the current species demarcation criteria of the Respirovirus genus. In addition, we used PPIV-1 as an example to explore recombination and diversity of the Respirovirus genus. Interestingly, we only detected heterosubtypic recombination events between PPIV-1a and PPIV-1b with no intrasubtypic recombination events. The recombination hotspots highlighted a diverse geography-dependent genome structure of paramyxovirus infecting swine in China. Furthermore, we found no evidence of co-evolution between respirovirus and its host, indicating frequent cross-species transmission. In summary, our analyses showed that swine can be infected with a broad range of respiroviruses and recombination may serve as an important evolutionary mechanism for the Respirovirus genus’ greater diversity in genome structure than previously anticipated.

          IMPORTANCE Livestock have emerged as critically underrecognized sources of paramyxovirus diversity, including pigs serving as the source of Nipah virus (NiV) and swine parainfluenza virus type 3, and goats and bovines harboring highly divergent viral lineages. Here, we identified a new species of Respirovirus genus named PPIV-2 in swine and proposed to revise the species demarcation criteria of the Respirovirus genus. We found heterosubtypic recombination events and high genetic diversity in PPIV-1. Further, we showed that genetic recombination may have occurred in the Respirovirus genus which may be associated with host range expansion. The continued expansion of Respirovirus genus diversity in livestock with relatively high human contact rates requires enhanced surveillance and ongoing evaluation of emerging cross-species transmission threats.

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          Most cited references98

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            MEGA11: Molecular Evolutionary Genetics Analysis Version 11

            The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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              Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

              Abstract Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                Microbiol Spectr
                Microbiol Spectr
                spectrum
                Microbiology Spectrum
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2165-0497
                1 June 2022
                May-Jun 2022
                1 June 2022
                : 10
                : 3
                : e00242-22
                Affiliations
                [a ] Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, China
                [b ] Key Laboratory of Animal Virology of Ministry of Agriculture, Zhejiang Universitygrid.13402.34, , Hangzhou, China
                [c ] College of Natural, Applied, and Health Sciences, Kentucky State Universitygrid.258527.f, , Frankfort, Kentucky, USA
                [d ] Department of Microbiology, Immunology and Transplantation, Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Leuven, Belgium
                [e ] Department of Mathematics, School of Science & Engineering, Tulane University, New Orleans, Louisiana, USA
                [f ] College of Veterinary Medicine, Yunnan Agricultural Universitygrid.410696.c, , Kunming, China
                Changchun Veterinary Research Institute
                Author notes

                Jin Zhao and Jiumeng Sun contributed equally to this article. Author order was determined by the corresponding author after negotiation.

                Guy Baele, Xiang Ji, and Shuo Su are senior authors.

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0003-4995-3251
                https://orcid.org/0000-0003-0187-1185
                Article
                00242-22 spectrum.00242-22
                10.1128/spectrum.00242-22
                9241844
                35647875
                96bacfa2-2428-4341-b6cc-4b6775d31f77
                Copyright © 2022 Zhao et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 23 January 2022
                : 26 April 2022
                Page count
                supplementary-material: 1, Figures: 5, Tables: 0, Equations: 0, References: 98, Pages: 14, Words: 9624
                Funding
                Funded by: National Natural Science Foundation of China (NSFC), FundRef https://doi.org/10.13039/501100001809;
                Award ID: 339194534
                Award Recipient :
                Categories
                Research Article
                evolution, Evolution
                Custom metadata
                May/June 2022

                divergent viruses discovered,genetic diversity,porcine parainfluenza virus 2

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