Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana Champaign, Urbana, IL, USA.
Veterinary Diagnostic Laboratory and Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois, Urbana, IL, USA.
Infect Genet Evol. 2021 Aug;92:104866. doi: 10.1016/j.meegid.2021.104866. Epub 2021 Apr 17.
Atypical porcine pestivirus (APPV) is an emerging virus discovered in 2014 and it can cause congenital tremors in pigs. Molecular epidemiology serves as an essential tool in monitoring and controlling the disease. Virus epidemiology mainly relies on genome sequencing and phylogenetic characterization. Previous molecular epidemiology studies have been using different genes/regions for phylogeny, namely whole genome, Npro, and E2 coding sequences. However, with increasing number of APPV sequences available in GenBank, no systemic studies have been performed for detailed classification of APPV strains around the globe. The goal of this study is to propose a classification strategy or taxonomy of APPV strains at genotype, subgenotype, and isolate levels. A total of 76 whole genomes and 16 partial polyprotein coding sequences were analyzed for genetic variability and suitability of all individual genes for viral phylogenies. Our results revealed that, among all the viral genes, NS5a coding sequences were proved to be the most suitable alternative for tracing APPV strains supported by its capability of reproducing the same phylogenetic and evolutionary information as the whole viral genome did. Also, a reliable cutoff to accurately classify APPV at different levels is established. We propose a genotyping scheme with three well-defined genotypes (1-3) and 7 subgenotypes for genotype 1 (1.1-1.7). For whole genome analysis, a threshold value of 84%-91% pairwise identity allows separation of all APPV subgenotypes, whereas 80% identity clearly segregate the three major APPV genotypes. For NS5a gene analysis, 82%-91% identity allows subgenotype separation and 76% identity segregate APPV genotypes. Additionally, genetic distance of whole genome exhibits ≤8% in isolate level, 9%-14% in subgenotype level, and 17%-22% in genotype level, while for NS5a encoding sequences the genetic distance displays ≤9% in isolate level, 9.9%-19.1% in subgenotype level, and 21.6%-29.7% in genotype level. These allow a clear segregation among APPV genotypes, subgenotypes, and isolates. Therefore, the proposed strategy in this study provides a solid and improved basis for molecular phylogenetics to understand APPV genetic diversity, trace the origins and control the spread of new disease outbreaks.
非典型猪瘟病毒（APPV）是一种新兴病毒，于 2014 年发现，可引起猪先天性震颤。分子流行病学是监测和控制该病的重要工具。病毒流行病学主要依赖于基因组测序和系统发育特征分析。先前的分子流行病学研究使用不同的基因/区域进行系统发育分析，即全基因组、Npro 和 E2 编码序列。然而，随着 GenBank 中 APPV 序列数量的增加，尚未对全球 APPV 毒株进行详细分类的系统研究。本研究的目的是提出一种 APPV 毒株在基因型、亚基因型和分离株水平的分类策略或分类法。对 76 个全基因组和 16 个部分多蛋白编码序列进行了遗传变异性分析，并评估了所有单个基因用于病毒系统发育的适用性。研究结果表明，在所研究的病毒基因中，NS5a 编码序列被证明是替代 APPV 株系追踪的最适选择，因为其能够复制全病毒基因组所具有的相同的系统发育和进化信息。此外，还建立了一个可靠的截断值，以准确地在不同水平上对 APPV 进行分类。我们提出了一种基因型方案，包括三个明确界定的基因型（1-3）和基因型 1 的 7 个亚基因型（1.1-1.7）。对于全基因组分析，84%-91%的成对同一性阈值可分离所有 APPV 亚基因型，而 80%的同一性可清楚地区分三个主要的 APPV 基因型。对于 NS5a 基因分析，82%-91%的同一性可分离亚基因型，76%的同一性可区分 APPV 基因型。此外，全基因组的遗传距离在分离株水平上≤8%，在亚基因型水平上为 9%-14%，在基因型水平上为 17%-22%；而对于 NS5a 编码序列，遗传距离在分离株水平上≤9%，在亚基因型水平上为 9.9%-19.1%，在基因型水平上为 21.6%-29.7%。这使得 APPV 基因型、亚基因型和分离株之间能够清晰地区分。因此，本研究提出的策略为分子系统发生学提供了坚实而改进的基础，以了解 APPV 的遗传多样性，追踪新疾病爆发的起源和控制其传播。
