Skip to main content

The genetic variability of grapevine Pinot gris virus (GPGV) in Australia


Grapevine Pinot gris virus (GPGV; genus Trichovirus in the family Betaflexiviridae) was detected in Australia in 2016, but its impact on the production of nursery material and fruit in Australia is still currently unknown. This study investigated the prevalence and genetic diversity of GPGV in Australia. GPGV was detected by reverse transcription-polymerase chain reaction (RT-PCR) in a range of rootstock, table and wine grape varieties from New South Wales, South Australia, and Victoria, with 473/2171 (21.8%) samples found to be infected. Genomes of 32 Australian GPGV isolates were sequenced and many of the isolates shared high nucleotide homology. Phylogenetic and haplotype analyses demonstrated that there were four distinct clades amongst the 32 Australian GPGV isolates and that there were likely to have been at least five separate introductions of the virus into Australia. Recombination and haplotype analysis indicate the emergence of new GPGV strains after introduction into Australia. When compared with 168 overseas GPGV isolates, the analyses suggest that the most likely origin of Australian GPGV isolates is from Europe. There was no correlation between specific GPGV genotypes and symptoms such as leaf mottling, leaf deformation, and shoot stunting, which were observed in some vineyards, and the virus was frequently found in symptomless grapevines.


Grapevine Pinot gris virus (GPGV) is a species in the genus Trichovirus, in the family Betaflexiviridae. The GPGV genome is a linear, positive-sense, single-stranded RNA of approximately 7259 nucleotides (nt), excluding the poly (A) tail at the 3′ end [1]. It has a typical Trichovirus genome with non-coding regions at the 5′ and 3′ ends and three overlapping open reading frames (ORFs): ORF 1 encodes 214 kiloDalton (kDa) virus replicase-associated proteins (1865 aa) including methyltransferase (44–333 aa), helicase (1040–1277 aa) and RNA-dependent RNA polymerase (RdRp) (1447–1797 aa); ORF2 encodes the 42 kDa cell-to-cell movement protein (MP) (367 aa); and ORF3 encodes a 22 kDa viral coat protein (CP) (195 aa) [1]. Previous studies indicate that GPGV is genetically diverse [2,3,4,5,6,7,8].

GPGV was first identified in plants of cv. Pinot gris in vineyards of northern Italy in 2012 [1] with characteristic grapevine leaf mottling and deformation disease (GLMD). Other symptoms associated with infection also include delayed budburst, shortened shoot internodes and increased berry acidity [1, 9, 10]. GLMD is caused by GPGV, and infection can lead to serious agronomic losses in sensitive grapevine varieties associated with reduced yield and low quality [11,12,13,14,15]. Since it was first described in Pinot gris, GPGV has been found in other grapevine varieties with GLMD and in varieties that are asymptomatic [1, 2, 6, 16]. Some studies suggest an association between GLMD and specific GPGV strains [1, 4, 6, 17], and one study showed that virus titer and small interfering RNA accumulation were affected by polymorphisms at the 3'end of the movement protein (MP) gene leading to differences in symptom severity [18]. Although significant progress has been made in the understanding of the interaction between GPGV and GLMD disease [15, 19,20,21], the effects of the GPGV infection on grapevines are still poorly understood, including the relationship between GPGV infection and disease symptoms. Interestingly asymptomatic GPGV infections have been reported in some sensitive varieties that are usually symptomatic, such as Pinot gris and Traminer [2, 22], which cast doubt about its association with GLMD.

It was predicted that GPGV originated from Asia, with China being the most probable source of emergence [5]. Thereafter, GPGV has gradually spread to several grape-producing regions of the world including Europe, USA, Canada, Middle East, and Asia [23]. GPGV colonizes the vascular tissues of grapevines [24] and its global spread is likely due to the movement of infected planting material. Transmission by Colomerus vitis, commonly known as grape leaf bud-blister mites, results in the spread of the virus within vineyards [6, 10, 25].

In 2016, GPGV was detected in Australia, New South Wales (NSW), and was subsequently found in Victoria (VIC) and South Australia (SA) [23, 26]. It is suspected that GPGV was introduced to Australia via infected propagation material sometime between 2003 when the movement of the virus into Europe was predicted, and 2014, when testing in Australian post-entry quarantine was introduced [1, 23]. In Australia, GPGV has been found in a broad range of wine grape, table grape and rootstock varieties, but the characteristic GLMD symptoms caused by GPGV infection have not been reported [1, 23]. There has been some recent conjecture that GPGV is associated with a restricted spring growth symptom in Australian table grapes, which includes delayed bud burst, shortened internodes, stunting and zig-zag shoots [23]. To better understand the potential risk of GPGV in Australian vineyards, molecular methods were used to determine the GPGV diversity in rootstock, table, and wine grape varieties, which showed a range of symptoms or were healthy.


Sampling of the grapevine samples

During 2017–2021, Agriculture Victoria’s Crop Health Services (CHS) plant diagnostic laboratory received a total of 2171 samples for GPGV testing from different grape-growing regions of Australia, including 1531 samples from South-eastern Australia in the states of VIC, NSW, and SA. The RNA of 191 GPGV positive CHS samples were selected and retained for further analysisand an additional 126 grapevine samples were collected from southeast Australia for this study (n = 317). Where possible, each of the 317 samples were checked for virus-like symptoms. The 317 grapevines included 70 table grapes, 126 wine grapes and 16 rootstocks. There were 105 grapevines for which the type was unknown.

RNA extraction and reverse transcription polymerase chain reaction (RT-PCR)

RNA was extracted from 0.3g tissue (fresh weight) of each grapevine sample using the RNeasy® Plant Mini Kit (Qiagen) and eluted in 30μl RNase-free water, as described by Constable et al. [27] and quantified using a spectrophotometer (Nanodrop, Thermo Fisher Scientific). Each RNA extract was stored at − 20 °C until use. An RT-PCR assay for the detection of NADH dehydrogenase ND2 subunit (ndhB gene, NAD) messenger ribonucleic acid (mRNA) by RT-PCR [28] was used to determine the presence and quality of the extracted RNA.

Each sample was screened using an endpoint RT-PCR assay [4] and a real-time RT-qPCR assay [29]. A GoTaq® 1-Step RT-PCR and RT-qPCR System (Promega) was used according to the manufacturer’s instructions except that the total reaction volume was 25 μl and contained 2 µl of RNA template. The 303bp endpoint RT-PCR amplicons were analyzed by electrophoresis in 2% agarose gels that were stained with SYBR® Safe DNA gel stain (Invitrogen) for visualization. The presence of amplicons corresponding to the size of the genome region of interest was observed on a GelDoc Go Gel Imaging System (Bio-Rad).

Metagenomic high-throughput sequencing (HTS) library preparation and sequence reads analysis

Thirty-two GPGV-positive grapevines were randomly selected for metagenomic sequencing (Table 1). Five µl of each of the 32 grapevine RNA extracts were used for HTS. The HTS libraries for each sample were prepared using TruSeq® Stranded Total RNA Library Prep Plant with Ribo zero plant kit (Illumina), following the manufacturer’s instructions, and adapters (Perkin Elmer) were used. The size range and concentration of the libraries were determined using the 2200 TapeStation® system (Agilent Technologies) and Qubit® Fluorometer 2.0 (Invitrogen), respectively, and the resulting quantification values were used to pool the libraries. The resulting library was finally sequenced using the NovaSeq 6000 system (Illumina) with a paired read length of 2 × 150 bp.

Table 1 The metadata for each of the thirty-two grapevine Pinot gris virus-infected grapevines that were selected for high throughput sequencing (HTS) in this study including the year collected, grapevine type, variety, geographic origin, and symptoms observed

Bioinformatics analysis

All the raw data was quality filtered, adapters were trimmed, and the generated sequence read pairs were validated using Fastp (version 0.20.0) with default parameters. De novo assembly of the quality-checked paired sequence reads into contigs was carried out using the genome assembler SPAdes (version 3.13.0) [30]. The resulting de novo assembled contigs were searched [31] against the NCBI nucleotide database using the alignment search tool BLASTn for the presence of GPGV and other viruses in the grapevine samples. Reference mapping of the de novo assembled contigs for each sample was done using Bowtie2 (version using the most similar genome identified in the previous BLASTn search after which the mapped consensus sequence was viewed in Geneious (version 11.0) to determine the mapped reads coverage and average depth of the genomes generated for each sample.

RT-PCR confirmation of viruses detected by high-throughput sequencing (HTS)

The arrangement of the coding region (equivalent to nt positions 22 to 6812 of the reference isolate NC_015782) of the assembled genomes of two GPGV isolates (5.21 and LT6) that were generated by HTS was confirmed by Sanger sequencing of overlapping amplicons, to assure their quality. The overlapping amplicons were generated by RT-PCR with primer pairs that were designed in this study using Oligo Explorer (version 1.1.2; and three published primer pairs (Additional file 1: Table S1) [4, 6, 32]. PCR amplification and gel electrophoresis were done as described previously. The amplicons were purified using QIAquick® PCR & Gel Cleanup Kit (Qiagen) and sent to Macrogen (Seoul, Korea) for Sanger sequencing. Each amplicon was sequenced twice in the forward and reverse directions. The resulting sequences for each isolate were used in combination with the contigs assembled from the HTS data to generate consensus genome sequences for each isolate. Four GPGV isolates (5.5, 5.13, 5.24 and LT7) had genomes with low average coverage and depth and in some cases, gaps in the consensus, therefore Sanger sequencing of specific regions were used to complete and/or confirm the genome assembly.

Phylogenetic tree and sequence identity analyses

To establish a relationship between the manifestation of symptoms and specific strains of GPGV, phylogenetic analysis of a 460nt region of the GPGV genome encompassing the 3′ end of the movement protein and the 5′ end of the coat protein ORFs [2, 6] of 32 Australian isolates was compared to representative isolates previously described as associated with GLMD symptoms or with asymptomatic infections [6, 17]. Multiple alignments were performed using the MEGA X software [33] with default parameters. Phylogenetic trees were generated using the maximum likelihood (ML) method based on the Tamura-Nei model with 1000 bootstrap replicates.

The consensus genome sequences of the 32 Australian GPGV isolates generated in this study were aligned with 168 GPGV genome sequences available in GenBank (Additional file 1: Table S2) using MUSCLE alignment software [34], excluding the viral untranslated regions (UTRs). The genetic distances within the isolate groups were calculated and maximum-likelihood phylogenetic trees were constructed using Kimura’s two parameter model in MEGA X [33] with default parameters and 1000 bootstrap replicates. The sequence identity analysis was carried out using BioEdit Sequence Alignment Editor [35] and the Sequence Demarcation Tool (version 1.2) [36] on the aligned genome sequences. The sequence similarity percentages of the isolates were determined at the nucleotide level for GPGV by MUSCLE alignment implemented in the SDT software (version 1.2).

Based on current taxonomic demarcation criteria recommended by the International Committee on Taxonomy of Viruses (ICTV) for the Betaflexiviridae [37, 38], phylogenetic trees for the RdRp and CP region of GPGV were constructed and the sequence similarity percentage was determined at both the nucleotide and amino acid (aa) levels using the methods mentioned above.

Median-joining (MJ) network, population genetics, equilibrium model, neutrality test and fixation index analyses

Variants networks were created using the Median Joining (MJ) algorithm and visualized using the PopART software (, with default settings, for 51 aligned GPGV genome sequences including 32 Australian isolates and 19 overseas isolates that were used in the phylogenetic analysis and had highest nucleotide identity with the Australian isolates.

Further, the aligned genome sequences of the 32 GPGV isolates generated in this study along with 168 overseas GPGV isolates available in GenBank were also used to assess the genetic differentiation parameters such as number of variants (V), variants diversity (Vd), number of polymorphic (segregation) sites (S), the total number of mutations η (Eta), the average number of nucleotide differences (k) and average pairwise nucleotide diversity (π), the total number of synonymous sites (SS), the total number of non-synonymous sites (NS) and the ratio of non-synonymous nucleotide diversity to synonymous nucleotide diversity (\(\omega = dN{/}dS)\) using the DnaSP software (version 6.10.01) [39].

The Tajima’s D [40] statistical test of neutrality, included in the DnaSP software, was also used on the dataset with default sliding window parameters, to test the neutral selection hypothesis on the GPGV genomes between populations. This is to determine whether the viral populations are evolving under a non-random process (DT > 0: balancing selection, sudden population decline); mutation-drift equilibrium (DT = 0) or a recent selective sweep (DT < 0: population expansion after a recent bottleneck). The coefficient of FST (fixation index) is a measure of the average pairwise distances between pairs of individual variants in terms of allele frequencies and was calculated by performing 1000 sequence permutations in DnaSP to estimate the genetic differentiation between populations. The fixation index (FST) can range from 0 to 1, where 0 indicates no differentiation between populations and 1 indicates populations are completely isolated and there is no sharing of genetic material or gene flow [39, 41, 42].

Recombination analysis

The aligned genome sequences of virus isolates from this study and the sequences of corresponding GPGV isolates available in GenBank were checked for potential recombination events. When screening for recombination, likely parental isolates of potential recombinants and recombination breakpoints within the genome sequences of GPGV from this study were determined using the RDP program (version 4.9) [43] with default parameters [44]. A recombination event was considered to be genuine only if it was detected by four or more of the seven measures [RDP (R), GENECONV (G), BOOTSCAN (B), MAXCHI (M), CHIMAERA (C), SISCAN (S), and 3SEQ (Q)] with p values < 0.05, implemented in the software RDP4.9 [45,46,47]. Recombination signals were disregarded if they were flagged by RDP4.9 as potentially arising through evolutionary processes other than recombination.


RT-PCR results

GPGV was detected in 473/2171 (21.8%) of the samples tested, including 23/133 samples from NSW, 26/706 samples from SA and 424/1176 samples from VIC. GPGV was not detected in 23 samples from Tasmania or 133 samples from Western Australia. The samples from VIC and NSW were analyzed by region (Fig. 1) and the highest proportion of positive samples (415/840; 49.4%) was observed in the Sunraysia horticultural district which encompasses northwestern VIC (350 samples) and southwestern NSW (70 samples).

Fig. 1
figure 1

The number of samples submitted to Crop Health Services Plant Diagnostic Laboratory from various grape growing regions in South Australia (SA), New South Wales (NSW) and Victoria (VIC) that tested positive or negative for grapevine Pinot gris virus (GPGV). The Sunraysia horticultural district encompasses growers located in northwest VIC and southwest NSW. Other NSW isolates in the image includes samples from various regions in that state. Image generated by tracing Google Maps (Scale = 20 km)

Using retained RNA of the CHS samples and samples collected specifically for this study (n = 317), GPGV was detected in 113/317 samples, including 37/70 table grape, 59/126 wine grape, 2/16 rootstock and 15/105 unknown varieties based on the presence of the expected 303bp amplified PCR product [4] as well as Ct values ranging from 16.24 to 35.24 (data not shown) [29]. The presence of GPGV was confirmed in 81/191 reanalyzed CHS RNA extracts. Most of the GPGV-positive samples (101) were from the Sunraysia region in VIC and surrounding areas, with the remaining samples from the Sunraysia region in NSW (9) and vineyards in SA (3).

Symptoms were not recorded for 14 GPGV-positive grapevines, which were submitted through the CHS plant diagnostic laboratory for virus testing. Of the remaining 99 GPGV-positive grapevines, 6 had GLMD-like symptoms, 31 grapevines had a range of symptoms including restricted spring growth, millerandage and zigzag shoots and 62 were asymptomatic (Fig. 2).

Fig. 2
figure 2

Symptoms were observed in different table and wine grape varieties. Leaf mottling and deformation symptoms were observed in (a) Nero d’Avola; (b) Fiano; (c) Vermintino; (d) Malbec and zig-zag shoots observed in (e) Crimson seedless

Metagenomic high-throughput sequencing (HTS) and bioinformatics analysis

The total raw reads generated by metagenomic HTS from 32 grapevine samples ranged from 81,949 to 30,198,881 reads/sample and these numbers were reduced to 81,714 to 29,489,728 reads/sample after quality trimming. De novo assembly of reads from each sample using SPAdes resulted in 3329–178,375 contigs from which 10 to 2674 contigs matched with known viral sequences. Of those virus-related contigs, 1–12 contigs matched most closely to GPGV across the 32 samples which were confirmed to be GPGV after a BLASTn [31] search of the GenBank database. The genome size of the various GPGV contigs in the different samples ranged from 6574 to 7449 nt with the average size of contigs per GPGV genome ranging from 1534 to 7426 nt (Additional file 1: Table S3). The most complete genome sequences for the GPGV strains found in each grapevine sample were used for downstream analysis.

Sanger sequencing of overlapping amplicons generated by RT-PCR confirmed the genome sequence of the two Australian exemplar isolates 5.21 and LT6 and completed the assembly of the GPGV genome for isolates 5.5, 5.13, 5.24 and LT7, which had gaps and low coverage across the assembled genomes. The consensus genome sequences (excluding UTRs) generated in this study for 32 Australian GPGV isolates are available on GenBank (Accession number: OQ198990-OQ199021).

Phylogenetic and sequence identity analysis

The phylogenetic relationships between the 32 GPGV isolates from Australia and representative overseas isolates found on symptomatic and asymptomatic grapevines in previous studies were assessed using a 460nt genomic region encompassing the 3′ end of the MP and 5′ end of the CP ORFs [2, 6]. Five Australian GPGV isolates, including one isolate associated with GLMD-like symptoms (9.9), two isolates from grapevines with other symptoms including restricted spring growth, millerandage and zigzag shoots (9.1, 9.13), and two isolates that were from asymptomatic grapevines (LT6, LT7) were in clade C (high occurrence of symptoms), that included isolates from other countries that were associated with GLMD. The remaining 27 Australian isolates, which included three isolates (9.10, 9.5, 9.14) from grapevines with GLMD-like symptoms, 12 isolates from grapevines with other symptoms and 11 isolates from asymptomatic grapevines, were in clade A that included isolates from other countries that were detected in asymptomatic grapevines (Fig. 3).

Fig. 3
figure 3

Maximum likelihood phylogenetic tree with 1000 bootstrap replicates of the 3′ end of movement protein and 5′ end of coat protein genes of the genome for 32 Australian grapevine Pinot gris virus (GPGV) isolates and 68 isolates from previous studies that were associated with grapevine leaf mottling and deformation disease (GLMD) or with asymptomatic infections in various grapevine varieties. Clade A (asymptomatic grapevines) and clades B and C (GLMD-affected grapevines) are based on the clades described previously [2, 6]. Bootstrap values (> 70%) are reported at the nodes

Isolates of all four clades were found in the Sunraysia grape-growing region of VIC (Mildura and surrounding towns, Robinvale) and NSW (Euston) (Figs. 4a, 5). Only clade I and clade III isolates were found in SA, from the Barossa Valley (Angaston) and Adelaide Hills (AH), respectively. The SA clade I isolates, which shared 99.3% nt identity with each other, were from the same Barossa Valley grower, and the SA clade III isolates, which shared 98.8% nt identity with each other, were from the same Adelaide Hills grower.

Fig. 4
figure 4

Maximum likelihood tree inferred from thirty-two genome sequences of grapevine Pinot gris virus (GPGV) which were de novo assembled from high throughput sequencing (HTS) datasets (a) only Australian isolates; b full tree with 32 Australian and 168 overseas isolates published on GenBank; c collapsed tree to highlight the global relationships of Australian isolates to isolates from other regions. The number at each node indicates bootstrap percentages based on 1000 replicates. The scale bar corresponds to the number of substitutions per site. The percentage identity to each other for each clade is on the right

Fig. 5
figure 5

Location of sample collection sites of GPGV isolates in different vine-growing regions of Australia. Image generated by tracing Google Maps (Scale = 20 km). Mildura refers to the Victorian area of the Sunraysia horticultural region surrounding the city of Mildura and which extends 60km from Yelta in the northwest and Colignan in the southeast

The nucleotide percentage identity between the Australian GPGV isolates ranged from 96.6 to 99.8% for the RdRp gene and 93.1 to 100% for the CP gene (Additional file 1: Fig. S1). The overall percentage amino acid identity between the Australian GPGV isolates ranged from 97.7 to 100% for the RdRp protein and 93.9 to 100% for the CP gene (Additional file 1: Fig. S2).

The genomes (excluding UTRs) of 32 Australian and 168 overseas GPGV isolates shared 69–100% nucleotide identity with each other. Phylogenetic analysis of the genomes demonstrated that Australian GPGV isolates in Australian clades I and II (defined in Fig. 4a) formed a distinct cluster that was most closely related to a cluster of isolates from Italy, and which also contained the two GPGV isolates from Australian clade III (Fig. 4b, c). Australian clades I and II share 97.8–99.8% nucleotide identity, the Australian clade III and Italian isolates share 97.7–100% nucleotide identity, and the larger cluster of the three Australian clades and the Italian isolates shared 97.2–100% nucleotide identity. Australian clade III isolates which includes isolates 8.33 and 9.14, and which were detected in asymptomatic Lambrusco and Malbec with GLMD-like symptoms respectively, were most closely related (98.5–99.6% nucleotide identity) to isolates fvg-Is6 (MH087440) and fvg-Is1 (MH087439), which were isolated from asymptomatic grapevines.

Australian clade IV GPGV isolates fell into a second distinct cluster of isolates that were primarily from Europe and also included one isolate from China (Fig. 4b, c). These isolates shared 96.7–99.7% nucleotide identity with each other. Australian grapevine isolates 9.1 (asymptomatic Ralli seedless table grape) and 9.9 (Malbec with GLMD-like symptoms) from the Sunraysia region (Mildura), were most closely related to isolate fvg-Is7 from Italy (MH087441), which was isolated from a symptomatic grapevine. Isolates LT6 and LT7, from asymptomatic Grüner Veltliner were most closely related (97.8–99.7% nt identity) to two Cabernet sauvignon isolates from Italy (BK011097, BK011099), one Cabernet sauvignon isolate from China (BK011073) of unknown disease status, and one isolate from a symptomatic grapevine cv. Pinot noir in France (KY706085).

Median-joining (MJ) network, population genetics, equilibrium model, neutrality test and fixation index analysis

MJ networks of 32 GPGV isolates from Australia and 19 overseas isolates, which clustered with Australian isolates in the Australian clades I-IV of the phylogenetic tree (Fig. 4c), showed four distinct variant clusters (Fig. 6). The formation of these clusters is supported by the phylogenetic analysis in which four clades were formed that contained the same Australian and overseas isolates (Fig. 4c) as the related median-joining network clusters (Fig. 6). Each MJ network cluster contained hypothetical intermediate variants (represented by black dots) that were often directly linked to only one or a few of the known variants that were analyzed.

Fig. 6
figure 6

Median-joining network showing grapevine Pinot gris virus (GPGV) variants dividing the isolates into four distinct clusters including 32 GPGV isolates from Australia and 19 overseas isolates. The sizes of the circles are proportional to the number of times each variant was observed. Unlabelled black dots (median vectors) are hypothetical intermediate variants connecting the variant groups. Numbers in the bracket infer the number of mutations separating the variants

Genetic diversity parameters and selective pressure were analyzed for the 32 Australian and 168 overseas GPGV isolates (Table 2). The sequences were grouped and analyzed based on clusters formed in the phylogenetic analysis (Fig. 4c). All four populations share a high level of variant diversity (Vd) which is either 1 or closer to one, indicating high levels of diversity for each cluster. Low nucleotide diversity (π) was observed and ranged between 0.008 and 0.022 within the four MJ network clusters indicating GPGV population expansions (Table 2). The population of GPGV isolates in the four clusters had a ratio of < 1 for nonsynonymous nucleotide diversity to synonymous nucleotide diversity (ω) indicating that they have been under a purifying selection (Table 2). The neutrality test (Tajima’s Dt) produced negative values for each cluster and are indicative of low population differentiation and infer population growth (Table 2). The fixation index (FST) test statistic, which was used to estimate the degree of genetic divergence between the MJ network clusters, ranged between 0.44 and 0.52 for each pair of clusters that were compared, suggesting infrequent gene flow and high genetic differentiation (Table 3).

Table 2 Summary of genetic variation and neutrality test analysis of grapevine Pinot gris virus (GPGV) genomes for different populations formed by four phylogenetic clusters which include 32 Australian and 19 overseas GPGV isolates from France, Italy, and China
Table 3 Measurements of population’s differentiation (fixation index, FST) of genome sequences of the four clusters formed phylogenetically with the 32 Australian grapevine Pinot gris virus (GPGV) and 19 representative overseas isolates from France, Italy, and China

Recombination analysis

The analysis of 168 global isolates did not identify any international isolates as major or minor parents of 32 Australian GPGV isolates. However, four statistically significant (p < 0.05) recombinants were were predicted by the analysis (Table 4): recombinant 1—9.13 (clade I) with major parent 9.9 (clade IV) with 97.0% similarity and minor parent 5.13 (clade I) with 98.6% similarity; recombinant 2—9.14 (clade III) with major parent 8.33 with 99.1% similarity and minor parent 9.1 (clade IV) with 96.9% similarity; recombinant 3—9.1 (clade IV) with major parent 9.9 (clade IV) and minor parent 8.47 (clade I); recombinant 4—5.13 (clade I) with major parent 2.1 (clade I) with 99.0% similarity (refer to Fig. 4a). Recombination affected the RdRp gene in three outcomes (isolates 9.1, 9.13, 9.14) and the MP gene in one outcome (isolate 5.13) (Fig. 7, Table 4). All recombinants and parents were located in the Sunraysia region of VIC (Mildura), within approximately a 25km radius.

Table 4 The number of predicted recombinants and recombination events identified using the RDP4.9 package within the genome sequences of grapevine Pinot gris virus (GPGV) isolates
Fig. 7
figure 7

The location of the recombination events on the genome of four Australian grapevine Pinot gris virus (GPGV) isolates as detected by recombination-detection algorithms (RDP4 program)


This study provides a snapshot of the prevalence of GPGV in wine, table grape and rootstock varieties in Australia between the years 2017 and 2021. GPGV was detected in grapevines with GLMD-like symptoms as well as in grapevines with other symptoms such as delayed budburst, increased berry acidity, stunted shoots, poor yield, restricted spring growth, zig-zag shoots and millerandage. The virus was also detected in asymptomatic grapevines. GPGV was only found in southeastern Australia, in NSW, SA and VIC and had the highest prevalence in the Sunraysia horticultural region, where table grapes and wine grapes are grown and where some germplasm collections and grapevine nurseries are located.

There is no doubt that infected planting material is responsible for the introduction of GPGV into Australia, and it has been reported that once testing was introduced at the Australian border, 10% of imported grapevines had GPGV [23]. The close relationship of many Australian isolates to Italian isolates, demonstrated by the phylogenetic analysis, supports the hypothesis that the introduction of GPGV into Australia has a European origin. This is further supported by the MJ variant network analysis, in which European isolates and one Chinese isolate occur with Australian isolates in cluster IV and Italian and Australian isolates occur together in cluster III. It is likely that GPGV was introduced into Australia from Europe after it was introduced into Italy, which is estimated to have occurred in 2003, and before the time testing commenced at the Australian border in 2014 [23, 26].

The Australian and overseas GPGV isolates in clades I and II are closely related suggesting that GPGV isolates from both clades may have emerged from one introduction into Australia (Fig. 4b). However, the MJ network indicates that they are distinct clusters emerging from different hypothetical intermediate variants and therefore it is more likely that phylogenetic clades I and II are associated with separate introductions (Fig. 6). Thus, the presence of four distinct Australian phylogenetic clades and four MJ network clusters suggests at least four different introductions of GPGV into the country. The presence of GPGV isolates from Sunraysia in all four clades and MJ network clusters suggests multiple introductions of the virus into this region. Isolates LT6 and LT7 from SA, which are closely related to Sunraysia GPGV isolates found in Malbec (9.9) and Ralli Seedless (9.1), were derived from Gruner veltliner planting material that was imported independently from Europe and was not distributed to or in contact with material from Sunraysia at the time this study was conducted. This indicates a minimum of five introductions of GPGV into Australia. However, it is possible that these four closely related isolates have a common European origin.

RNA viruses are known to have high mutation rates which lead to the production of deleterious mutations that can destabilize the virus population [48, 49]. Thus, when RNA viruses with a large population size reach a bottleneck, a purifying selection helps in eliminating these mutants and improves the survival of the population [48, 49]. The neutrality test parameter DT is known to test the distribution of nucleotide polymorphisms in the genome [40]. The negative numbers of DT suggest a recent introduction of this virus in Australia and infer a recent expansion of Australian GPGV populations through new mutations. Virus populations were shown to survive bottleneck selections, which were indicated by negative neutrality test values, and could be caused by a transmission during grafting or transmission by the vector bud-blister mites. The presence of hypothetical intermediate variants in the MJ network clusters is an indicator of diversity within the clusters. Further sampling and sequencing of GPGV isolates is required to determine how the known variants are linked to a specific variant introduced into Australia or if multiple introductions of closely related variants has occurred.

The FST values of 0.44–0.52 between the four clusters suggest that the clusters are linked. This is likely due to the high relatedness of the Italian isolates that are linked to the five introductions of GPGV into Australia. There is some association between Australian isolates in cluster IV and an isolate from China (BK011073) and therefore an introduction from this region cannot be ruled out. However, Australia has imported most grapevine material from Europe or the Americas and an introduction from Europe seems more likely. It is also possible that the Chinese isolate, which was detected in the variety Cabernet sauvignon, is also a result of the importation of infected grapevine material from Europe into China.

Recombination events have been previously reported in GPGV [4, 5, 19] and this study also predicted recombination amongst the Australian isolates within the RdRp and MP regions. No international isolates were identified as parents which suggests that the evolution of these GPGV isolates occurred after their introduction into Australia (Table 4). Based on the phylogenetic, variant and recombination analysis, it is hypothesized that isolate 9.9 (major parent 1) could be an early introduction of GPGV into Australia which led to the generation of a recombinant 9.1 (recombinant 1) by combining with a second introduction of GPGV, 8.47 (minor parent 1). A second recombination event led to the formation of 9.14 (recombinant 2) which was formed by a recombination event between isolate 8.33 (major parent 2) and the recombinant isolate 9.1 (minor parent 2, Fig. 8). The prediction of Australian recombinants with Australian parent GPGV strains provides further evidence for the emergence of new variants since the initial introduction into Australia and could indicate that GPGV has been present here for a long time although the year of introduction could not be established.

Fig. 8
figure 8

Hypothetical introductions of grapevine Pinot gris virus (GPGV) in Australia including the major and minor parents of predicted GPGV recombinants based on phylogenetic, median-joining (MJ) network and recombination analyses

The results of this study demonstrate that GPGV spread and divergence has occurred in Australia. Infected planting material is likely to have contributed to some spread within and between Australian table and wine grape growing regions. However, GPGV is also transmitted by the grape leaf bud-blister mites which has led to greater GPGV transmission efficiency [50]. The mite is dispersed through wind, transported through the movement of infested leaf materials, on clothing and equipment, and may be dispersed in cuttings [51]. The evidence for mite transmission lies in the diversity of Vitis species and varieties that are infected by GPGV, and which are represented in each phylogenetic clade and MJ network cluster. The close relatedness of the GPGV variants found in rootstocks, table grapes and wine grapes for example, isolate CK1 (rootstock), 8.28 (table grape) and 8.29 (wine grape) in phylogenetic clade II, which have > 99% nt identity, supports the hypothesis of localized transmission. A high abundance of blister mites has been observed in the Sunraysia horticultural district of VIC and NSW (data not shown) and would account for some of the spread and high prevalence of GPGV in this region. The lower prevalence of GPGV in other grape-growing regions in Australia might be associated with a lower abundance of the mite vector and possibly fewer introductions of the virus in planting material. There is evidence for the spread of GPGV between regions. For example, GPGV isolates in two wine grapes vines (unknown variety) in Angaston, SA, and an isolate in a table grape var. Ralli seedless from Sunraysia, VIC share > 99% nucleotide identity. The two regions are > 300km apart and this spread could be solely due to the movement of a viruliferous vector, but transmission between regions could also be due to the movement of infected planting material.

GLMD symptoms relating to GPGV infection are known to become visible during the beginning of the grapevine growing season, in spring, but fade later in the season towards veraison, when berries ripen [2]. It has been reported that there are mild and severe strains of GPGV that affect the severity of symptom expression [15]. Expression of GLMD symptoms in GPGV-affected vines collected as part of this study was variable with both symptomatic and asymptomatic vines of the same grape cultivar testing positive for the virus. There appeared to be no trend observed between cultivar, time of sampling (seasonality) or growing region and the expression of GLMD symptoms. These results were supported by the phylogenetic analyses conducted in this study. No association could be made between the presence of specific Australian GPGV strains and the presence of any symptom type in Australian grapevines when the same region was compared phylogenetically. These findings are in contrast to previous studies suggesting that two distinct genetic GPGV lineages represent asymptomatic and symptomatic grapevines [2, 6]. We observed strains of GPGV normally associated with asymptomatic infections overseas in grapevines with GLMD-like symptoms in Australia, and we have seen GPGV strains that would normally be associated with symptomatic vines in Italy in asymptomatic Australian grapevines. A similar lack of association between GPGV variants and disease has also been reported by others [52,53,54].

The correlation between symptoms associated with Australian GPGV isolates is further complicated by the presence of other viruses in some of the grapevines that were examined, which could also contribute to the presence of the disease (Additional file 1: Table S3). Similar results have been noted in other studies that reported the inability to link specific symptoms to the presence of GPGV given the mixed viral infection in grapevines [4, 55, 56].

GLMD-like symptoms, restricted spring growth, zig-zag shoots and millerandage, which were observed in some GPGV-infected grapevines in this study, can be caused by a range of abiotic and biotic factors such as other pathogens, environmental conditions, temperature, nutrient deficiency, soil type and presence of mites. It is possible these factors have contributed to the expression of these symptoms in some Australian grapevines that are infected with GPGV only or in combination with other viruses [2, 22, 57,58,59]. Variable GLMD expression has also been linked to boron deficiency [24]. Although the availability of boron was not measured in the Australian vineyards where GPGV-infected samples were collected for this study, soils in the Sunraysia region may be alkaline and with low organic matter which can affect boron content and availability and therefore may explain the variable association between GPGV presence and GLMD-like symptoms that were observed [60,61,62,63,64].


In this study, a combination of the documented history of importation of some infected grapevine varieties into Australia, together with data obtained from surveillance and phylogenetic, MJ network, sequence identity and recombination analyses contributes to an improved understanding of GPGV introduction and spread in Australia. It indicated a minimum of five introductions of GPGV followed by the emergence of new variants. A high level of GPGV distribution in south-eastern Australian vineyards, particularly in Sunraysia, that was observed is likely linked to transmission by a bud-blister mite and distribution of infected planting material as has been observed in Italy [2, 5, 22]. Therefore in Australia, to minimize risk to production when establishing new vineyards, the use of planting material in which GPGV has not been detected is recommended and effective management of the bud mite vectors is required. The absence of a clear correlation between the distinct GPGV strains and the manifestation of symptoms in grapevines makes it necessary to conduct further research aimed at studying the biology of GPGV and its interaction with rootstocks, wine and table grape varieties grown in Australia.

Availability of data and materials

The genomic data generated and/or analyzed during the current study are available in the open access database GenBank in National Center for Biotechnology Information repository (Accession numbers: OQ198990—OQ199021).


  1. Giampetruzzi A, Roumi V, Roberto R, Malossini U, Yoshikawa N, La Notte P, et al. A new grapevine virus discovered by deep sequencing of virus-and viroid-derived small RNAs in Cv Pinot gris. Virus Res. 2012;163(1):262–8.

    Article  CAS  PubMed  Google Scholar 

  2. Bertazzon N, Forte V, Filippin L, Causin R, Maixner M, Angelini E. Association between genetic variability and titre of Grapevine Pinot gris virus with disease symptoms. Plant Pathol. 2017;66(6):949–59.

    Article  Google Scholar 

  3. Eichmeier A, Peňázová E, Muljukina N. Survey of Grapevine Pinot gris virus in certified grapevine stocks in Ukraine. Eur Found Plant Pathol. 2018;152(2):555–60.

    Article  Google Scholar 

  4. Glasa M, Predajňa L, Komínek P, Nagyová A, Candresse T, Olmos A. Molecular characterization of divergent grapevine Pinot gris virus isolates and their detection in Slovak and Czech grapevines. Adv Virol. 2014;159(8):2103–7.

    Article  CAS  Google Scholar 

  5. Hily J-M, Poulicard N, Candresse T, Vigne E, Beuve M, Renault L, et al. Datamining, genetic diversity analyses, and phylogeographic reconstructions redefine the worldwide evolutionary history of Grapevine Pinot gris virus and Grapevine berry inner necrosis virus. Phytobiomes J. 2020;4(2):165–77.

    Article  Google Scholar 

  6. Saldarelli P, Giampetruzzi A, Morelli M, Malossini U, Pirolo C, Bianchedi P, et al. Genetic variability of Grapevine Pinot gris virus and its association with grapevine leaf mottling and deformation. Phytopathology. 2015;105(4):555–63.

    Article  CAS  PubMed  Google Scholar 

  7. Eichmeier A, Penazova E, Nebish A. First report of grapevine pinot gris virus on grapevines in Armenia. Plant Dis. 2020;104(3):1000.

    Article  Google Scholar 

  8. Eichmeier A, Peňázová E, Čechová J, Berraf-Tebbal A. Survey and diversity of grapevine pinot gris virus in algeria and comprehensive high-throughput small rna sequencing analysis of two isolates from vitis vinifera cv. Sabel revealing high viral diversity. Genes. 2020;11(9):1110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Pleško IM, Marn MV, Seljak G, Žežlina I. First report of Grapevine Pinot gris virus infecting grapevine in Slovenia. Plant Dis. 2014;98(7):1014.

    Article  PubMed  Google Scholar 

  10. Saldarelli P, Beber R, Covelli L, Bianchedi P, Credi R, Giampetruzzi A, et al. Studies on a new grapevine disease in Trentino vineyards. J Plant Pathol. 2013;95(S4):60.

    Google Scholar 

  11. Bertazzon N, Forte V, Filippin L, Angelini E, editors. Studies on Grapevine Pinot gris virus (GPGV) presence and its association with an emergent disease of grapevine. Proceedings of the 18th Congress of ICVG; 2015.

  12. Malossini U, Bianchedi P, Beber R, Credi R, Saldarelli P, Gualandri V, editors. Spread of GPGV-associated disease in two vineyards in Trentino (Italy). ICVG18: 18th Conference of the International Council for the Study of Virus and Virus-like Diseases of the Grapevine; 2015.

  13. Malossini U, Bianchedi P, Roman T, Varner M, Gualandri V, Nicolini G, editors. An updating about the performances of Pinot Gris and Traminer vines affected by the GPGV trichovirus-related grapevine disease. 37th World Congress of Vine and Wine, 12th General Assembly of the OIV" Southern Vitiviniculture, a Confluence of Knowledge and Nature"; 2014.

  14. Malossini U, Bianchedi P, Villegas TR, Varner M, Gualandri V, Nicolini G. Aggiornamento sulle performance di viti Pinot grigio e Traminer affette dalla fitopatologia correlata al Trichovirus GPGV.

  15. Tarquini G, Zaina G, Ermacora P, De Amicis F, Franco-Orozco B, Loi N, et al. Agroinoculation of Grapevine Pinot Gris Virus in tobacco and grapevine provides insights on viral pathogenesis. PLoS ONE. 2019;14(3):e0214010.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Eichmeier A, Komínková M, Komínek P, Baránek M. Comprehensive virus detection using next generation sequencing in grapevine vascular tissues of plants obtained from the wine regions of Bohemia and Moravia (Czech Republic). PLoS ONE. 2016;11(12):e0167966.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Bertazzon N, Filippin L, Forte V, Angelini E. Grapevine Pinot gris virus seems to have recently been introduced to vineyards in Veneto, Italy. Arch Virol. 2016;161(3):711–4.

    Article  CAS  PubMed  Google Scholar 

  18. Tarquini G, Ermacora P, Firrao G. Polymorphisms at the 3’end of the movement protein (MP) gene of grapevine Pinot gris virus (GPGV) affect virus titre and small interfering RNA accumulation in GLMD disease. Virus Res. 2021;302:198482.

    Article  CAS  PubMed  Google Scholar 

  19. Tarquini G, De Amicis F, Martini M, Ermacora P, Loi N, Musetti R, et al. Analysis of new grapevine Pinot gris virus (GPGV) isolates from Northeast Italy provides clues to track the evolution of a newly emerging clade. Adv Virol. 2019;164(6):1655–60.

    Article  CAS  Google Scholar 

  20. Tarquini G, Ermacora P, Bianchi G, De Amicis F, Pagliari L, Martini M, et al. Localization and subcellular association of Grapevine Pinot Gris Virus in grapevine leaf tissues. Int J Anim Fungal Plant Cell Biol. 2018;255(3):923–35.

    Article  CAS  Google Scholar 

  21. Tarquini G, Pagliari L, Ermacora P, Musetti R, Firrao G. Trigger and suppression of antiviral defenses by grapevine Pinot gris virus (GPGV): novel insights into virus-host interaction. Mol Plant Microbe Interact. 2021;34(9):1010–23.

    Article  CAS  PubMed  Google Scholar 

  22. Bertazzon N, Forte V, Angelini E. Fast transmission of grapevine ‘Pinot gris’ virus (GPGV) in vineyard. Vitis. 2020;59(1):29–34.

    Article  CAS  Google Scholar 

  23. Constable F, Tassie E, McLoughlin S. A comprehensive review of Grapevine Pinot gris virus (GPGV). 2019.

  24. Buoso S, Pagliari L, Musetti R, Fornasier F, Martini M, Loschi A, et al. With or without you: Altered plant response to boron-deficiency in hydroponically grown grapevines infected by Grapevine Pinot gris virus suggests a relation between grapevine leaf mottling and deformation symptom occurrence and boron plant availability. Front Plant Sci. 2020;11:226.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Malagnini V, De Lillo E, Saldarelli P, Beber R, Duso C, Raiola A, et al., editors. Preliminary data on the transmission of grapevine pinot Gris virus by Colomerus vitis. Proceedings of the 18th congress of ICVG; 2015: Turkey Ankara.

  26. Wu Q, Habili N. The recent importation of Grapevine Pinot gris virus into Australia. Virus Genes. 2017;53(6):935–8.

    Article  CAS  PubMed  Google Scholar 

  27. Constable F, Joyce P, Rodoni B. A survey of key Australian pome fruit growing districts for exotic and endemic pathogens. Austral Plant Pathol. 2007;36(2):165–72.

    Article  Google Scholar 

  28. Thompson JR, Wetzel S, Klerks M, Vašková D, Schoen C, Špak J, et al. Multiplex RT-PCR detection of four aphid-borne strawberry viruses in Fragaria spp. in combination with a plant mRNA specific internal control. J Virol Methods. 2003;111(2):85–93.

    Article  CAS  PubMed  Google Scholar 

  29. Bianchi G, De Amicis F, De Sabbata L, Di Bernardo N, Governatori G, Nonino F, et al. Occurrence of grapevine pinot gris virus in Friuli Venezia Giulia (Italy): field monitoring and virus quantification by real-time RT-PCR. EPPO Bull. 2015;45(1):22–32.

    Article  Google Scholar 

  30. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–10.

    Article  CAS  PubMed  Google Scholar 

  32. Morelli M, Catarino AdM, Susca L, Saldarelli P, Gualandri V, Martelli G. First report of grapevine pinot gris virus from table grapes in Southern Italy. J Plant Pathol. 2014.

    Article  Google Scholar 

  33. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol. 2018;35(6):1547.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Hall TA. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows. Nucleic Acids Symp Ser. 1999;41(41):95–8.

    CAS  Google Scholar 

  36. Muhire BM, Varsani A, Martin DP. SDT: a virus classification tool based on pairwise sequence alignment and identity calculation. PLoS ONE. 2014;9(9):e108277.

    Article  PubMed  PubMed Central  Google Scholar 

  37. King AM, Lefkowitz E, Adams MJ, Carstens EB. Virus taxonomy: ninth report of the International Committee on Taxonomy of Viruses: Elsevier; 2011.

  38. Silva JMF, Melo FL, Elena SF, Candresse T, Sabanadzovic S, Tzanetakis IE, et al. Virus classification based on in-depth sequence analyses and development of demarcation criteria using the Betaflexiviridae as a case study. J Gener Virol. 2022;103(11):001806.

    Article  CAS  Google Scholar 

  39. Rozas J, Sánchez-DelBarrio JC, Messeguer X, Rozas R. DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics. 2003;19(18):2496–7.

    Article  CAS  PubMed  Google Scholar 

  40. Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123(3):585–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Hudson RR, Slatkin M, Maddison WP. Estimation of levels of gene flow from DNA sequence data. Genetics. 1992;132(2):583–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Tsompana M, Abad J, Purugganan M, Moyer J. The molecular population genetics of the Tomato spotted wilt virus (TSWV) genome. Mol Ecol. 2005;14(1):53–66.

    Article  CAS  PubMed  Google Scholar 

  43. Martin DP, Murrell B, Golden M, Khoosal A, Muhire B. RDP4: Detection and analysis of recombination patterns in virus genomes. Virus Evol. 2015.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Kinoti WM, Nancarrow N, Dann A, Rodoni BC, Constable FE. Updating the quarantine status of prunus infecting viruses in Australia. Viruses. 2020;12(2):246.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kehoe MA, Coutts BA, Buirchell BJ, Jones RA. Split personality of a Potyvirus: to specialize or not to specialize? PLoS ONE. 2014;9(8):e105770.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Wylie S, Jones R. Role of recombination in the evolution of host specialization within Bean yellow mosaic virus. Phytopathology. 2009;99(5):512–8.

    Article  CAS  PubMed  Google Scholar 

  47. Ohshima K, Yamaguchi Y, Hirota R, Hamamoto T, Tomimura K, Tan Z, et al. Molecular evolution of Turnip mosaic virus: evidence of host adaptation, genetic recombination and geographical spread. J Gen Virol. 2002;83(6):1511–21.

    Article  CAS  PubMed  Google Scholar 

  48. Elena S, Agudelo-Romero P, Carrasco P, Codoner F, Martin S, Torres-Barceló C, et al. Experimental evolution of plant RNA viruses. Heredity. 2008;100(5):478–83.

    Article  CAS  PubMed  Google Scholar 

  49. García-Arenal F, Fraile A, Malpica JM. Variability and genetic structure of plant virus populations. Annu Rev Phytopathol. 2001;39:157.

    Article  PubMed  Google Scholar 

  50. Malagnini V, de Lillo E, Saldarelli P, Beber R, Duso C, Raiola A, et al. Transmission of grapevine Pinot gris virus by Colomerus vitis (Acari: Eriophyidae) to grapevine. Adv Virol. 2016;161(9):2595–9.

    Article  CAS  Google Scholar 

  51. Michalska K, Skoracka A, Navia D, Amrine JW. Behavioural studies on eriophyoid mites: an overview. Exp Appl Acarol. 2010;51(1):31–59.

    Article  PubMed  Google Scholar 

  52. Marra M, Giampetruzzi A, Abou Kubaa R, de Lillo E, Saldarelli P. Grapevine pinot gris virus variants in vines with chlorotic mottling and leaf deformation. J Plant Pathol. 2020;102(2):531.

    Article  Google Scholar 

  53. Shvets D, Vinogradova S. Occurrence and genetic characterization of grapevine pinot gris virus in Russia. Plants. 2022;11(8):1061.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Vu M, Vemulapati BM, McFadden-Smith W, Fall ML, Úrbez-Torres JR, Moreau DL, et al. Phylogenetic and evolutionary studies of grapevine pinot gris virus isolates from Canada. Viruses. 2023;15(3):735.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Vončina D, Al Rwahnih M, Rowhani A, Gouran M, Almeida RP. Viral diversity in autochthonous croatian grapevine cultivars. Plant Dis. 2017;101(7):1230–5.

    Article  PubMed  Google Scholar 

  56. Porotikova E, Terehova U, Volodin V, Yurchenko E, Vinogradova S. Distribution and genetic diversity of grapevine viruses in Russia. Plants. 2021;10(6):1080.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Angelini E, Bazzo I, Bertazzon N, Filippin L, Forte V. A New Disease In Italian Vineyards. Wines & Vines, September. 2015;

  58. Constable F, Tassie L, McLoughlin S. Pests and diseases: GPGV knowledge boost. Austr NZ Grapegrower Winemak. 2019.

    Article  Google Scholar 

  59. Morán F, Olmos A, Lotos L, Predajňa L, Katis N, Glasa M, et al. A novel specific duplex real-time RT-PCR method for absolute quantitation of grapevine pinot gris virus in plant material and single mites. PLoS ONE. 2018;13(5):e0197237.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Berger K, Truog E. Boron availability in relation to soil reaction and organic matter content. Soil Sci Soc Am J. 1946;10(c):113–6.

    Article  CAS  Google Scholar 

  61. Constable F, Connellan J, Nicholas P, Rodoni B. The reliability of woody indexing for detection of grapevine virus-associated diseases in three different climatic conditions in A ustralia. Aust J Grape Wine Res. 2013;19(1):74–80.

    Article  Google Scholar 

  62. Kiss T, Kocanová M, Vavřiník A, Tekielska D, Pečenka J, Hakalová E, et al. Incidence of GLMD-like symptoms on grapevines naturally infected by grapevine Pinot gris virus, boron content and gene expression analysis of boron metabolism genes. Agronomy. 2021;11(6):1020.

    Article  CAS  Google Scholar 

  63. Mikhail EH, Martin JJ. Soils of the Nangiloc-Colignan Irrigation Area: Department of Agriculture and Rural Affairs; 1986.

  64. Penman F, Hubble GD, Taylor JK, Hooper PD. A soil survey of the Mildura Irrigation Settlement, Victoria: T. Rider, government printer; 1940.

Download references


We thank the growers and Crop Health Services (CHS) for supplying samples and colleagues, including Dr. Ian Dry and Libby Tassie (Tassie Viticulture Consulting), who assisted in sending samples for the present study. Thanks to Chris Bottcher (Agriculture Victoria Research) and Ruvinda N Aluthgama Kankanamalage (Agriculture Victoria Research) for technical assistance, especially at the early stages of the project analysis.


This research was funded by La Trobe University for financial support through their provision of the La Trobe Full Fee Research Scholarship (LTUFFRS) and La Trobe University Graduate Research Scholarship (LTUGRS) and PhD research scholarship by Wine Australia. Wine Australia supports a competitive wine sector by investing in research, development, and extension (RD&A), growing domestic and international markets, and protecting the reputation of Australian Wine. We would like to acknowledge Agriculture Victoria Research (AVR) for use of facilities that enabled the study to be undertaken.

Author information

Authors and Affiliations



All authors have read and agreed to the published version of the manuscript. Conceptualization, KPK and FC; methodology, KPK, DL and FC; formal analysis, KPK; investigation, KPK; resources, KPK, DL and FC; data curation, KPK, DL and FC; writing—original draft preparation, KPK; writing—review and editing, KPK AR, B.R and FC; visualization, KPK; supervision, FC, AR and BR; project administration, FC.; funding acquisition, FC and BR.

Corresponding author

Correspondence to Kamalpreet Kaur.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1

. Figure S1. Percentage identity for thirty-two genome sequences of grapevine Pinot gris virus (GPGV) which were de novo assembled from high throughput sequencing (HTS) datasets. Figure S2. Maximum likelihood tree with 1000 bootstrap replicates inferred from amino acid sequences of the protein-encoding Open reading frames (ORFs) of the thirty-two genome sequences of grapevine Pinot gris virus (GPGV) datasets. The scale bar corresponds to the number of substitutions per site. (a) RNA-dependent RNA polymerase protein (RdRp, ORF1) (b) Coat protein (CP, ORF3). The scale bar corresponds to the number of substitutions per site. Bootstrap values (> 70%) are reported at the nodes. Table S1: The primer pairs and their annealing temperatures used in endpoint RT-PCR and Sanger Sequencing to confirm the genome sequences of Australian grapevine Pinot gris virus (GPGV) isolates that were generated by high throughput sequencing (HTS). Table S2: The GenBank accession numbers for 168 GPGV genome sequences available on NCBI and their respective country of origin. Table S3: The sample identity, RT-PCR results, number of raw reads generated from metagenomic high-throughput sequencing (HTS), number of reads after quality trimming, number of contigs generated by SPAdes, number of viral contigs, number of grapevine Pinot gris virus (GPGV) contigs, GPGV contig size, percentage similarity to reference genome NC_015782, depth and mapped reads calculated using Geneious in each grapevine sample sequenced.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kaur, K., Rinaldo, A., Lovelock, D. et al. The genetic variability of grapevine Pinot gris virus (GPGV) in Australia. Virol J 20, 211 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: