AVF Proj. ID: 641
Year Funded: 2016
Category: Rootstocks - Genetics
Investigators: Dario Cantu

Deep Sequencing for Trunk Disease Diagnostics



The aim of this multi-year project is to develop rapid and cost-effective diagnostic methods based on Next Generation Sequencing (NGS) technologies for detection, identification and quantification of trunk pathogens in asymptomatic and symptomatic grape wood. In the 1st year of the project (2015 – 2016) we collected diseased wood material from commercial vineyards and characterized the associated fungal pathogen species using traditional methods, such as morphological and sequence-based identification of purified fungal colonies (see progress report for the 2015-2016 funding cycle). We used these samples to determine how effective ITS-sequencing, meta-genome sequencing and meta­transcriptome sequencing approaches are in identifying and quantifying pathogenic species directly in planta. Data simulations allowed us to determine what mapping algorithm was the most specific and sensitive in detecting trunk pathogens both qualitatively and quantitatively. All NGS methods we tested were in agreement with traditional diagnostic methods, but also allowed us to detect simultaneously multiple pathogen species with no need of hands-on sample culturing and colony purification. Additionally, unlike traditional diagnostics, which are strictly qualitative, NGS approaches allowed us to determine the relative abundances of the different infecting species. Among all methods tested, ITS-seq is still the most cost-effective until library preparation costs for RNA and DNA-seq do not decline significantly. For this reason, ITS-seq was chosen for further protocol optimization. Both sensitivity and specificity of the ITS-seq approach remain to be improved for diagnostics purposes. In the second year of the project (reported here), we (a) confirmed that NGS allows the detection with high specificity of actively infecting pathogens when vines are experimentally infected with individual pathogen strains; (b) established that NGS detection is quantitative and allows to differentiate between diseased and healthy vines; (c) developed a protocol for testing dormant cuttings and started testing cuttings provided by a commercial nursery. In the 2016-2017 funding cycle, we also developed a new DNA extraction protocol that reduced the time required for processing and the amounts of sample, reagents and waste.

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