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.

Next-generation sequencing (NGS) allows ultra-deep sequencing of nucleic acids. The use of sequence-independent amplification of viral nucleic acids without utilization of target-specific primers provides advantages over traditional sequencing methods and allows detection of unsuspected variants and co-infecting agents. However, NGS is not widely used for small RNA viruses because of incorrectly perceived cost estimates and inefficient utilization of freely available bioinformatics tools. In this study, we have utilized NGS-based random sequencing of total RNA combined with barcode multiplexing of libraries to quickly, effectively and simultaneously characterize the genomic sequences of multiple avian paramyxoviruses. Thirty libraries were prepared from diagnostic samples amplified in allantoic fluids and their total RNAs were sequenced in a single flow cell on an Illumina MiSeq instrument. After digital normalization, data were assembled using the MIRA assembler within a customized workflow on the Galaxy platform. Twenty-eight avian paramyxovirus 1 (APMV-1), one APMV-13, four avian influenza and two infectious bronchitis virus complete or nearly complete genome sequences were obtained from the single run. The 29 avian paramyxovirus genomes displayed 99.6% mean coverage based on bases with Phred quality scores of 30 or more. The lower and upper quartiles of sample median depth per position for those 29 samples were 2984 and 6894, respectively, indicating coverage across samples sufficient for deep variant analysis. Sample processing and library preparation took approximately 25–30 h, the sequencing run took 39 h, and processing through the Galaxy workflow took approximately 2–3 h. The cost of all steps, excluding labor, was estimated to be 106 USD per sample. This work describes an efficient multiplexing NGS approach, a detailed analysis workflow, and customized tools for the characterization of the genomes of RNA viruses. The combination of multiplexing NGS technology with the Galaxy workflow platform resulted in a fast, user-friendly, and cost-efficient protocol for the simultaneous characterization of multiple full-length viral genomes. Twenty-nine full-length or near-full-length APMV genomes with a high median depth were successfully sequenced out of 30 samples. The applied de novo assembly approach also allowed identification of mixed viral populations in some of the samples.

Highly pathogenic A/H5N1 avian influenza (HPAI H5N1) viruses have seriously affected the Nigerian poultry industry since early 2006. Previous studies have identified multiple introductions of the virus into Nigeria and several reassortment events between cocirculating lineages. To determine the spatial, evolutionary, and population dynamics of the multiple H5N1 lineages cocirculating in Nigeria, we conducted a phylogenetic analysis of whole-genome sequences from 106 HPAI H5N1 viruses isolated between 2006 and 2008 and representing all 25 Nigerian states and the Federal Capital Territory (FCT) reporting outbreaks. We identified a major new subclade in Nigeria that is phylogenetically distinguishable from all previously identified sublineages, as well as two novel reassortment events. A detailed analysis of viral phylogeography identified two major source populations for the HPAI H5N1 virus in Nigeria, one in a major commercial poultry area (southwest region) and one in northern Nigeria, where contact between wild birds and backyard poultry is frequent. These findings suggested that migratory birds from Eastern Europe or Russia may serve an important role in the introduction of HPAI H5N1 viruses into Nigeria, although virus spread through the movement of poultry and poultry products cannot be excluded. Our study provides new insight into the genesis and evolution of H5N1 influenza viruses in Nigeria and has important implications for targeting surveillance efforts to rapidly identify the spread of the virus into and within Nigeria.