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      Putative Novel Avian Paramyxovirus (AMPV) and Reidentification of APMV-2 and APMV-6 to the Species Level Based on Wild Bird Surveillance (United States, 2016–2018)

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          Abstract

          Most species of APMVs are understudied and/or underreported, and many species were incidentally identified from asymptomatic wild birds; however, the disease significance of APMVs in wild birds is not fully determined. The rapid rise in high-throughput sequencing coupled with avian influenza surveillance programs have identified 12 different APMV species in the last decade and have challenged the resolution of classical serological methods to identify new viral species.

          ABSTRACT

          Avian paramyxoviruses (APMVs) (subfamily Avulavirinae ) have been isolated from over 200 species of wild and domestic birds around the world. The International Committee on Taxonomy of Viruses (ICTV) currently defines 22 different APMV species, with Avian orthoavulavirus 1 (whose viruses are designated APMV-1) being the most frequently studied due to its economic burden to the poultry industry. Less is known about other APMV species, including limited knowledge on the genetic diversity in wild birds, and there is a paucity of public whole-genome sequences for APMV-2 to -22. The goal of this study was to use MinION sequencing to genetically characterize APMVs isolated from wild bird swab samples collected during 2016 to 2018 in the United States. Multiplexed MinION libraries were prepared using a random strand-switching approach using 37 egg-cultured, influenza-negative, hemagglutination-positive samples. Forty-one APMVs were detected, with 37 APMVs having complete polymerase coding sequences allowing for species identification using ICTV’s current Paramyxoviridae phylogenetic methodology. APMV-1, -4, -6, and -8 viruses were classified, one putative novel species ( Avian orthoavulavirus 23 ) was identified from viruses isolated in this study, two putative new APMV species ( Avian metaavulavirus 24 and 27 ) were identified from viruses isolated in this study and from retrospective GenBank sequences, and two putative new APMV species ( Avian metaavulavirus 25 and 26 ) were identified solely from retrospective GenBank sequences. Furthermore, coinfections of APMVs were identified in four samples. The potential limitations of the branch length being the only species identification criterion and the potential benefit of a group pairwise distance analysis are discussed.

          IMPORTANCE Most species of APMVs are understudied and/or underreported, and many species were incidentally identified from asymptomatic wild birds; however, the disease significance of APMVs in wild birds is not fully determined. The rapid rise in high-throughput sequencing coupled with avian influenza surveillance programs have identified 12 different APMV species in the last decade and have challenged the resolution of classical serological methods to identify new viral species. Currently, ICTV’s only criterion for Paramyxoviridae species classification is the requirement of a branch length of >0.03 using a phylogenetic tree constructed from polymerase (L) amino acid sequences. The results from this study identify one new APMV species, propose four additional new APMV species, and highlight that the criterion may have insufficient resolution for APMV species demarcation and that refinement or expansion of this criterion may need to be established for Paramyxoviridae species identification.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

            The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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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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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Applied and Environmental Microbiology
                Appl Environ Microbiol
                American Society for Microbiology
                0099-2240
                1098-5336
                June 14 2022
                June 14 2022
                : 88
                : 11
                Affiliations
                [1 ]Department of Pathology, College of Veterinary Medicine, University of Georgia, Athens, Georgia, USA
                [2 ]Department of Population Health, Southeastern Cooperative Wildlife Disease Study, University of Georgia, Athens, Georgia, USA
                [3 ]Department of Virology, Texas A&M University, College Station, Texas, USA
                [4 ]Department of Pathology, University of Agriculture Faisalabad, Faisalabad, Pakistan
                Article
                10.1128/aem.00466-22
                35612300
                c068e61b-8201-4ea6-af49-c01d9fad2e0e
                © 2022

                https://doi.org/10.1128/ASMCopyrightv2

                https://journals.asm.org/non-commercial-tdm-license

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