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.

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Five Grapevine leafroll-associated virus 3 (GLRaV-3) epidemics were analyzed utilizing a standardized approach to robustly characterize the temporal and spatial parameters. Published data included in the analysis are from Spain, New Zealand, and Napa Valley, CA together with new data from a historic vineyard in Napa Valley, CA. Linear regression analyses of logit-transformed incidence data indicated a maximum average increase of 11% per year in disease incidence, with considerable variation among locations. Spatial analyses, including distribution fitting, examination of the effective sample size, and evaluation of the parameters of the binary power law fitted to variance data for disease incidence, indicated a high degree of consistency among the data sets. In all cases, except at very low disease incidence, a high degree of spatial aggregation was noted, with evidence that the degree of aggregation varied as a function of mean disease incidence. The polyetic dynamics of disease follow a logistic-like pattern over multiple seasons, consistent with limitation by inoculum availability (infected vines) at low incidence and limitation by disease-free vines at high incidence.