VirFree brings together participants from both academia and privatecompanies to collaborate through their expertise on the following objectives
Grapevine Roditis leaf discoloration-associated virus (GRLDaV) is an emerging grapevine pathogen included in the European and Mediterranean Plant Protection Organization (EPPO) alert list due to its ability to damage grapevine crops and cause production losses. This work aimed to develop a specific and reliable diagnostic tool that would contribute to preventing the spread of this pathogen. Therefore, a TaqMan real-time quantitative PCR was developed. The method was validated according to EPPO guidelines showing a high degree of analytical sensitivity, analytical specificity, selectivity, and repeatability and reproducibility.
The sensitivity of this method is much higher than the sensitivity reached by previously reported methods even when tested in crude extracts, which could allow rapid testing by avoiding nucleic acid extraction steps. The method was also able to detect GRLDaV isolates from all the geographic origins reported so far, despite their high degree of genetic diversity. In addition, this new technique has been successfully applied for the quantitative detection of GRLDaV in plant material and two mealybug species, Planococcus citri and Pseudococcus viburni. In conclusion, the methodology developed herein represents a significant contribution to the diagnosis and control of this emerging pathogen in grapevine.
The number of viruses identified in sweet cherry has been constantly increasing over the last few years, following the broad application of high throughput sequencing (HTS). Some of these were reported to cause leaf symptoms and yield reduction. In 2009-2013, surveys were performed on sweet cherry orchards located in Northern Greece for the presence of Betaflexiviridae viruses using generic and specific molecular assays (Foissac et al., 2005).
VirFree (H2020-MSCA-RISE-2016-Virus free fruit nurseries) © All Rights Reserved | This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 734736.