Location: Southern Horticultural Research Unit
Project Number: 6062-21000-011-004-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 26, 2022
End Date: Sep 30, 2024
Objective:
1) Measure the population of Xylella fastidiosa in stem internode of 638 accessions of muscadine and bunch grapes using the double antibody sandwich enzyme-linked immunosorbent assay (ELISA) and a set of primers targeting the rRNA genes.
2) Examine the correlation between the pathogen population and disease symptoms.
Approach:
Leaves samples will be collected from 638 individuals from four mapping populations. Five petioles will be collected from leaves with pierce’s disease (PD) symptoms from each genotype. Tissue will be grinded into fine powder using liquid nitrogen and 100 mg will be used to isolate DNA. A set of primers targeting the rRNA genes will be used to detect and quantify X. fastidiosa following the protocol described by Deyett et al 2019. Standard curve will be generated using DNA from pure culture of X. fastidiosa strain NOB1. Four biological replicates of each genotype will be tested, and mean will be standardized by the amount of DNA input and used to calculate the correlation between the Xf quantity and PD rating. Mean disease rating will be estimated using 0-5 scale where 0= no disease; 1= 1-2 leaves displaying PD symptoms with leaf scorching; 2=3-4 leaves displaying PD symptoms; 3= less than 50% of the leaves displaying PD symptoms; 4= more than 50% of the leaves displaying PD symptoms; 5= dead plant. To investigate the relationships among trait variables and the factors underlying trait variation, PCA and multivariate analysis will be performed for fruit-related traits. This includes physical parameters and chemical parameters. Statistical analyses will be performed using SAS software. Significant differences between means will be estimated using analysis of variance (ANOVA, General linear model) followed by Tukey’s multiple comparison test. The relationship between measured traits will be calculated using the Pearson coefficient of correlation using SAS.
