HIGH THROUGHPUT SEQUENCING TESTING OF SMALL RNAS EMPOWERS THE SIMULTANEOUS DETECTION OF CITRUS VIRUSES AND VIROIDS
G. Licciardello (1), G. Scuderi (2), M. Russo (2), M.C. Bazzano (2), R. Ferraro (2), C. Oliveri (3), A.F. Catara (2)
(1) Council for Agricultural Research and Economics (CREA) Research Centre for Olive, Citrus and Tree fruit, Acireale, Italy;
(2) Agrobiotech soc. coop. Catania, Italy;
(3) Agronomic consultant of Novarancia project. E-mail: firstname.lastname@example.org
Citrus are affected by a relevant number of viruses and viroids routinely tested by bioindexing and molecular assays. Anyway, the selection of virus free mother trees candidate for the foundation block requires a process of shoot tip grafting and biological indexing in greenhouse and molecular assays.
A challenge which needs adequate professional and technical resources. Recent papers have shown the adoption of High Throughput Sequencing (HTS) technology is effective for the simultaneous detection and identification of viruses and viroids in Citrus and other crops, as pre-screening to conventional detection methods to solve ambiguous results. To explore the reliability of a potential HTS-based virus detection protocol in association of bioinformatic strategies, within the project Novarancia we developed a pilot testing of different field trees in parallel with molecular and biological methods. Three sweet orange trees and two alemow seedlings previously indexed by conventional methods were re-analyzed by HTS of small RNAs. High-quality reads, depleted of the Citrus sinensis genome, were aligned with reference genomes of 13 viruses and 6 viroids and analyzed by a bioinformatic pipeline. A genome coverage above 90% was assumed indicative of the presence of a specific genotype, and coverage > 50% of potential presence of variants not represented in the read mapping reference list. The results show the implementation of conventional certification scheme with HTS sequencing of small RNAs speeds up the time over all required and reduces the greenhouse footprint, labor, time, and cost needed for bioindexing.
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