Peter A. Durr, Bénédicte Lambrecht, Mikael Berg, Muhammad Munir, Claude P. Muller, Siba K. Samal, Claudio L. Afonso, Emmanuel Albina, Dilmara Reischak, Mia Kim Torchetti, Hualei Liu, David L. Suarez, Chantal J. Snoeck, Nicola S Lewis, Mahmoud Sabra, Gabriela V. Goujgoulova, Diego G. Diel, Kiril M. Dimitrov, Kang-Seuk Choi, Joseph T. Hicks, Zhiliang Wang, Renata Servan de Almeida, Steven Van Borm, Isabella Monne, Frank Y. K. Wong, Patricia Gil, Celia Abolnik, Patti J. Miller, Sam McCullough, Christian Grund, Ilya Chvala, Alice Fusaro, Tony M. Joannis, Helena Lage Ferreira, Ian H. Brown, Haijin Liu, Justin Bahl, S. N. Kolosov, Ismaila Shittu, François-Xavier Briand, USDA-ARS : Agricultural Research Service, University of Pretoria [South Africa], Animal, Santé, Territoires, Risques et Ecosystèmes (UMR ASTRE), Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of Georgia [USA], Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences (SLU), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Animal and Plant Health Agency [Addlestone, UK] (APHA), Ministry of Agriculture, Food and Rural Affairs, Partenaires INRAE, Federal State Budgetary Institution Federal Centre for Animal Health, South Dakota State University (SDSTATE), Australian Animal Health Laboratory (AAHL), CSIRO Health and Biosecurity [Australia], Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Universidade de São Paulo (USP), Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe), National Diagnostic Science and Research Veterinary Medical Institute, Friedrich-Loeffler-Institut (FLI), National Veterinary Research Institute, United States Department of Agriculture - Animal and Plant Health Inspection Service, Sciensano [Bruxelles], Réseau International des Instituts Pasteur (RIIP), University of London, Northwest A&F University, China Animal Health and Epidemiology Center, Luxembourg Institute of Health (LIH), Lancaster University, Ministério da Agricultura, Pecuária e Abastecimento [Brasil] (MAPA), Governo do Brasil, South Valley University, University of Maryland [College Park], University of Maryland System, U.S. Department of Agriculture, ARS CRIS Project [6612-32000-072-00D], and BBSRCBiotechnology and Biological Sciences Research Council (BBSRC) [BB/R012695/1, BB/M008681/1]
Several Avian paramyxoviruses 1 (synonymous with Newcastle disease virus or NDV, used hereafter) classification systems have been proposed for strain identification and differentiation. These systems pioneered classification efforts; however, they were based on different approaches and lacked objective criteria for the differentiation of isolates. These differences have created discrepancies among systems, rendering discussions and comparisons across studies difficult. Although a system that used objective classification criteria was proposed by Diel and co-workers in 2012, the ample worldwide circulation and constant evolution of NDV, and utilization of only some of the criteria, led to identical naming and/or incorrect assigning of new sub/genotypes. To address these issues, an international consortium of experts was convened to undertake in-depth analyses of NDV genetic diversity. This consortium generated curated, up-to-date, complete fusion gene class I and class II datasets of all known NDV for public use, performed comprehensive phylogenetic neighbor-Joining, maximum-likelihood, Bayesian and nucleotide distance analyses, and compared these inference methods. An updated NDV classification and nomenclature system that incorporates phylogenetic topology, genetic distances, branch support, and epidemiological independence was developed. This new consensus system maintains two NDV classes and existing genotypes, identifies three new class II genotypes, and reduces the number of sub-genotypes. In order to track the ancestry of viruses, a dichotomous naming system for designating sub-genotypes was introduced. In addition, a pilot dataset and sub-trees rooting guidelines for rapid preliminary genotype identification of new isolates are provided. Guidelines for sequence dataset curation and phylogenetic inference, and a detailed comparison between the updated and previous systems are included. To increase the speed of phylogenetic inference and ensure consistency between laboratories, detailed guidelines for the use of a supercomputer are also provided. The proposed unified classification system will facilitate future studies of NDV evolution and epidemiology, and comparison of results obtained across the world., Highlights • An international consortium phylogenetically studied the diversity of NDV. • Consensus objective NDV classification and nomenclature system was developed. • Optimal phylogenetic inference method with guidelines is recommended. • Curated, up-to-date, complete fusion gene datasets for public use were created. • Three new NDV genotypes were identified.