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Grapevine leafroll-associated virus 3 (GLRaV-3) is the most widely prevalent and economically important of the complex of RNA viruses associated with grapevine leafroll disease (GLD). Phylogenetic studies have grouped GLRaV-3 isolates into nine different monophyletic groups and four supergroups, making GLRaV-3 a genetically highly diverse virus species. In addition, new divergent variants have been discovered recently around the world. Accurate identification of the virus is an essential component in the management and control of GLRaV-3; however, the diversity of GLRaV-3, coupled with the limited sequence information, have complicated the development of a reliable detection assay. In this study, GLRaV-3 sequence data available in GenBank and those generated at Foundation Plant Services, University of California-Davis, was used to develop a new RT-qPCR assay with the capacity to detect all known GLRaV-3 variants. The new assay, referred to as FPST, was challenged against samples that included plants infected with different GLRaV-3 variants and originating from 46 countries. The FPST assay detected all known GLRaV-3 variants, including the highly divergent variants, by amplifying a small highly conserved region in the 3’ untranslated terminal region (UTR) of the virus genome. The reliability of the new RT-qPCR assay was confirmed by an enzyme linked immunosorbent assay (ELISA) that can detect all known GLRaV-3 variants characterized to date. Additionally, three new GLRaV-3 divergent variants, represented by four isolates, were identified using a hierarchical testing process involving the FPST assay, GLRaV-3 variant-specific assays and high-throughput sequencing analysis. These variants were distantly related to groups I, II, III, V, VI, VII and IX, but much similar to GLRaV-3 variants with no assigned group; thus, they may represent new clades. Finally, based on the phylogenetic analysis, a new GLRaV-3 subclade is proposed and named as group X.

Characterization of grapevine leafroll-associated virus 3 genetic variants and application towards RT-qPCR assay design