This project focused on identification and characterization of unknown viruses responsible for the stone fruit tree diseases along with investigating other known viruses in mixed infections of Prunus crops using high throughput sequencing (HTS)-based approaches to generate a depth understanding of plant virus populations which consist of a few genetic variants and many infrequent variants.
In order to virome scanning, four cultivated Prunus species (P. avium, P. domestica, P. persica, and P. cerasus), from Biological Resource Centers of wide geographical origins were collected. In parallel, some uncultivated Prunus sp will be also analyzed, as well as wild populations of P. armeniaca (4 populations), P. brigantina, and P. cerasifera collected from their diversification centers. Beside double-stranded RNAs high-throughput sequencing of samples, a data mining will be performed with publicly available RNASeq data (SRA), in order to identify potentially novel viruses. The validation of HTS-based approaches for viral diagnostic in Prunus will include the comparison of various HTS technologies (dsRNA HTS, depleted RNASeq, …) for some well-characterized samples, as well as the comparison of their performance with classical detection tests used so far. The data mining analysis will allow sequence comparisons for known viruses, with implications for diagnostics, with the aim of better understanding that how the efficiency of published primers can be affected by mutations in order to redesign new more general primers.
four main objectives:
(1) Description of the virome of Prunus crops (peach, apricot, plum, almond, sour and sweet cherries)
(2) Molecular and biological characterization of two or three newly identified Prunus-infecting viruses
(3) Development of specific detection assays targeting the novel viruses
(4) Validation of HTS-based approaches for viral diagnostics in Prunus through a comparison of their performance with those of existing biological, serological, or molecular detection assays.