Digital Polymerase Chain Reaction as a Sensitive Diagnostic Tool: Detection and Quantification of Grapevine Fleck Virus in Grapevine

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Res. Plant Dis. 2026;32(1):87-92

Publication date (electronic) : 2026 March 31

doi : https://doi.org/10.5423/RPD.2026.32.1.87

Min-Jae Kim¹, Hyo-Jeong Lee^1,2, Rae-Dong Jeong^1,

¹Department of Applied Biology, Chonnam National University, Gwangju 61185, Korea

²Experiment & Analysis Division, Jungbu Regional Office, Animal and Plant Quarantine Agency, Incheon 22133, Korea

^*Corresponding author Tel: +82-62-530-2075 Fax: +82-62-530-2069 E-mail: jraed2@jnu.ac.kr

Received 2026 January 6; Revised 2026 January 21; Accepted 2026 January 23.

Abstract

Globally, grapevines (Vitis vinifera L.) are among the most economically important fruit crops cultivated for wine, table grapes, and raisins. Viral diseases seriously threaten the sustainability and productivity of grapevine cultivation. Among them, grapevine fleck virus (GFkV), a member of the Macula-virus genus, in the family Tymoviridae, is widely distributed and is associated with the “rugose wood complex,” a group of graft-transmissible diseases that affect the trunks of grapevines (Fuchs, 2020; Martelli, 2014).

GFkV is considered latent in V. vinifera, with no symptoms visible in most commercial cultivars. However, when grafted onto sensitive rootstocks such as those of hybrid Vitis rupestris and Vitis belandiei plants, it can cause serious symptoms such as stem pitting, grooving, and reduced vigor (Cieniewicz and Fuchs, 2025). These effects can result in significant economic losses due to plant grafting, as well as reduced nursery propagation. Because GFkV is graft-transmissible and causes symptomless infection in commercial scions, certification programs strictly require the use of GFkV-free planting materials.

Conventional methods such as enzyme-linked immunosorbent assays and reverse-transcription polymerase chain reaction (RT-PCR) have been used to detect GFkV; however, they often lack the sensitivity required for early-stage or low-titer infections (Sabanadzovic et al., 2000). Furthermore, although RT-quantitative PCR (RT-qPCR) has improved both the sensitivity of virus detection and throughput, it relies on reference genes or standard curves for quantification. This introduces variability, particularly when comparing results across laboratories or experiments (Gleerup et al., 2024).

To overcome these limitations, droplet digital PCR (ddPCR) has been developed as a third-generation nucleic-acid quantification technology; ddPCR partitions each reaction into thousands of droplets, allowing absolute quantification based on Poisson distribution statistics, without requiring standard curves. This technique has demonstrated superior sensitivity, accuracy, and robustness in detecting plant viruses, specifically in samples with low viral loads or high concentrations of PCR inhibitors (Gleerup et al., 2024).

This study developed and validated a RT-ddPCR assay for the detection and absolute quantification of GFkV in grapevine tissues. To evaluate its sensitivity, specificity, and potential as a diagnostic tool for GFkV detection in the context of virus-free certification, its performance was compared with that of RT-qPCR.

Leaf tissues were collected from grapevine (V. vinifera cv. Campbell Early) plants showing symptoms of GFkV infection. These samples were obtained from both field-grown vines and greenhouse-maintained stock plants at the National Institute of Horticultural and Herbal Science (Wanju, Korea). After collection, the leaf samples were immediately stored at −80°C until RNA extraction.

Using a Clear-S Total RNA extraction Kit (InVirusTech, Gwangju, Korea) according to the manufacturer's instructions, total RNA was extracted from 100 mg of grapevine leaf tissue. The RNA concentration and purity were assessed using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). RNA integrity was confirmed via agarose gel (1.5%) electrophoresis. To test the presence of GFkV in symptomatic grapevine leaves, RT-PCR was conducted using established diagnostic primers and procedures (Glasa et al., 2011). For RT-qPCR and RT-ddPCR, RNA extracted from GFkV-infected samples was used as the test template, while RNA from healthy grapevine samples was used as the control. Following RT-PCR amplification, a 520-bp partial coat protein (CP) gene from GFkV was inserted into a T&A cloning vector (Yeastern Biotech, New Taipei City, Taiwan) and sequenced. Based on a highly conserved CP gene sequence from 40 GenBank isolates identified using BioEdit (v7.0.5.3) (Supplementary Fig. 1), the GFkV-F5 (5ʹ-CCCTTCCAGTTCCTGTGGTA-3ʹ) and GFkV-R5 (5ʹ-GGCGACGGTGACGACTTC-3ʹ) primers, as well as a probe (6-FAM-ACTGAGTCCTCCTACACCTCCCTGT-BHQ-1), were designed using the Primer (v5.0) software (Premier Biosoft International, Palo Alto, CA, USA). The primers and probe were synthesized by Bionics (Daejeon, Korea) and then used in TaqMan RT-qPCR and RT-ddPCR assays. In vitro transcription of GFkV-CP was conducted using a method by Lee et al. (2021), the concentrations of the synthesized transcripts were measured using a BioDrop spectrophotometer (Biochrom, Ltd., Cambridge, UK), and the copy numbers were calculated using the following formula: concentration of transcripts (copies/μl) = concentration (μg/μl) / (fragment size [bp] × 182.5 × 10¹³) (Fronhoffs et al., 2002).

RT-ddPCR was performed using a one-step RT-ddPCR Advanced Kit for probes (Bio-Rad, Hercules, CA, USA), on a QX200^TM ddPCR system. Each 20-μl reaction included 5-μl Supermix, 2-μl reverse transcriptase, 1-μl DTT, 1.8 μl of each primer (900 nM), a 0.5-μl probe (250 nM), 2-μl RNA, and 9 μl of DEPC-water. The reaction mixtures were loaded into DG8^TM cartridges with 70-μl droplet-generation oil, covered with gaskets, and processed in a droplet generator. The droplets were transferred to a 96-well plate, sealed, and amplified on a T100^TM Thermal Cycler. The thermal cycling regimen began at 50°C, which was maintained for 40 min (reverse transcription) and then increased to 95°C for 10 min, followed by 40 cycles at 94°C for 30 sec and 56°C for 60 sec and, finally, a step at 98°C for 10 min, which was maintained at 4°C. A temperature gradient (49-60°C) was applied to optimize droplet separation. After amplification, the droplets were analyzed using a QX200^TM Droplet Reader, and quantification was performed using the QuantaSoft^TM (v1.7.4) software (Bio-Rad Laboratories, Hercules, CA, USA), based on at least 15,000 droplets per reaction. The results included the poisson-based 95% confidence intervals for each well.

To optimize the annealing temperature for RT-ddPCR, a temperature gradient of 49-60°C was used. The clarity of the separation between positive and negative droplets increased as the annealing temperature decreased, with the most distinct separation occurring at 56°C. Contrastingly, higher temperatures, particularly those above 58°C, corresponded with a reduced signal resolution. Based on these results, a temperature of 56°C was selected as the optimal annealing temperature for subsequent RT-ddPCR assays (Fig. 1A). The specificity of the RT-ddPCR assay was further assessed using RNA samples infected with other grapevine viruses that are prominent in Korea, including grapevine leafroll-associated virus 3 (GLRaV-3) and the hop stunt viroid (HSVd), as well as a non-template control (NTC). Positive signals were observed only in the GFkV-infected sample, while no fluorescence signals above the threshold were detected in the GLRaV-3, HSVd, or NTC wells (Fig. 1B). These results confirm the high specificity of the assay, as no cross-reactivity to other grapevine viruses was observed. Each specificity test was independently repeated three times, and consistent results were obtained. In principle, specificity testing against a wider range of grapevine viruses would be desirable. However, due to the high prevalence of mixed infections in field samples, we could not secure suitable single-infection materials, and thus extensive cross-reactivity testing was not conducted.

Fig. 1.

Optimization of the annealing temperature and evaluation of specificity and cross-reactivity of RT-ddPCR assays for GFkV detection. (A) Annealing temperatures for primers and a probe were optimized within a range of 49°C to 60°C. (B) Fluorescence amplitude of GLRaV-3 and HSVd. GFkV, grapevine fleck virus; GLRaV-3, grapevine leafroll-associated virus 3; HSVd, hop stunt viroid; NTC, non-template control; RT-ddPCR, reverse-transcription droplet digital polymerase chain reaction.

To compare the sensitivity of RT-ddPCR and RT-qPCR, 10-fold serial dilutions of in-vitro-transcribed GFkV-CP RNA (ranging from 3.28 × 10⁸ to 3.28 × 10² copies/μl) were analyzed. RT-qPCR was performed using an EzAmp^TM HS One-step RT-qPCR Master Mix (ELPIS-Biotech, Daejeon, Korea), based on a method by Lee et al. (2021). Copy numbers were calculated using the following formula: concentration of transcripts (copies/μl) = concentration (μg/μl) / (fragment size [bp] × 182.5 × 10¹³). The RT-ddPCR assay reliably quantified RNA down to 0.73 ± 0.05 copies/μl (coefficient of variation, 7.87%), whereas RT-qPCR failed to detect this concentration (Table 1). These results indicate that RT-ddPCR was at least 10-fold more sensitive than RT-qPCR, with an estimated detection limit at least 10-fold lower than that of RT-qPCR. All assays were conducted in triplicates within a single run and repeated over three independent runs for reproducibility. Subsequently, to assess the quantitative performance of each method, standard curves were generated using 10-fold serial dilutions of GFkV RNA transcripts. Both RT-qPCR and RT-ddPCR exhibited high linearity within the dynamic detection range. The coefficients of determination (R²) were 0.9998 and 0.9935 for RT-qPCR and RT-ddPCR, respectively, indicating a strong correlation between the input transcript concentrations and the measured values (Fig. 2). These results confirm that both methods were highly reliable for quantitative detection, as their coefficients approached 1.

Table 1.

Sensitivities of the RT-qPCR and RT-ddPCR assays for GFkV

Fig. 2.

Linear regression analysis of a comparison between RT-qPCR and RT-ddPCR. A 10-fold serial dilution of GFkV-CP transcripts was employed to assess the correlation coefficients between (A) RT-qPCR and (B) RT-ddPCR. The quantitative linearity correlation coefficients (R²) for RT-qPCR and RT-ddPCR were 0.9998 and 0.9935, respectively. RT-qPCR, reverse-transcription quantitative polymerase chain reaction; RT-ddPCR, reverse-transcription droplet digital polymerase chain reaction; GFkV-CP, grapevine fleck virus-coat protein.

To further compare the detection performances of RT-ddPCR and RT-qPCR, 66 grapevine field samples collected from various regions were tested for the presence of GFkV. GFkV was detectable in 84.8% (56/66) of the samples via RT-ddPCR, whereas RT-qPCR detected GFkV in only 53% (35/66) of the samples. Specifically, GFkV was detected in multiple samples exclusively via RT-ddPCR, with concentrations ranging from 2.5 (H3-5) to 20 (H1-2 and H1-3) copies (Table 2). These findings indicate that RT-ddPCR surpassed RT-qPCR in detecting GFkV in the grapevine field samples, offering greater sensitivity for identifying low-titer infections.

Table 2.

Detection of GFkV in field samples by RT-qPCR and RT-ddPCR

GFkV is a widespread pathogen that seriously threatens grapevine health and productivity. Although its infection is often latent in V. vinifera cultivars, it can considerably damage rootstock and hybrid varieties, leading to reduced vine vigor, delayed fruit ripening, and yield losses in susceptible genotypes (Sabanadzovic et al., 2000). In mixed infections, GFkV may also contribute to synergistic effects that lead to declines in the abundance of grapevines. Because mixed infections can mask GFkV by lowering its apparent titer and increasing assay background, a highly sensitive method is particularly important for reliable detection and accurate quantification under these conditions. Given the increasing demand for virus-free grapevine stocks, as well as the potential for latent spread through propagation materials, early and accurate detection of GFkV is crucial for certifying vine health and sustaining commercial grape production.

ddPCR has become a powerful tool for nucleic-acid quantification, offering several advantages over conventional PCR and qPCR methods. Unlike RT-qPCR, dPCR enables absolute quantification without requiring standard curves, by partitioning reaction mixtures into thousands of nanoliter-scale droplets. This allows for enhanced sensitivity, precision, and reproducibility (Lei et al., 2021). In addition, dPCR has been successfully applied to detect plant viruses and viroids in various fruit trees (Kim et al., 2022).

In this study, an RT-ddPCR assay was developed and validated for the detection and absolute quantification of GFkV in grapevine leaf tissues. The optimized assay exhibited high specificity for GFkV, with no cross-reactivity observed with other grapevine viruses. Owing to the frequent occurrence of mixed infections in grapevines, obtaining samples containing single infections of individual viruses was challenging, which restricted our ability to evaluate cross-reactivity against a broader range of grapevine viruses. RT-ddPCR could reliably detect as few as 0.73 copies/μl and was approximately 10 times more sensitive than RT-qPCR. When applied to field-collected grapevine samples, RT-ddPCR detected GFkV in 84.8% (56/66) of samples, whereas RT-qPCR detected the virus in only 53.0% (35/66) of samples. Several samples with low viral loads were identified exclusively via RT-ddPCR. These findings highlight the superior sensitivity and diagnostic potential of RT-ddPCR for detecting GFkV in grapevines. This technology not only enhances early detection and virus indexing efforts in vineyards and nurseries but also contributes to more accurate epidemiological studies and certification programs aimed at ensuring the sanitary quality of planting materials.

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