Abstract
Bois noir (BN) is the most widespread European grapevine yellows disease caused by ‘Candidatus Phytoplasma solani’. Although our knowledge of the mechanisms of interactions of this pathogenic bacteria with host is largely unknown, the plant-pathogen system of BN is commonly used as a model system for studying grapevine yellows diseases. We applied here a conceptual model of general plant pathology – a disease triangle for describing interactions among the host plant, the pathogen and the environment. We generated a proof-of-concept statistical model for disease triangle using original experimental data and different statistical and data mining approaches for a selected system of ‘Ca. P. solani’ infection of cv. ‘Chardonnay’ grapevine plants. We monitored individual plants from a single vineyard over a period of six years. Phytoplasma content, the expression of 21 selected grapevine genes and environmental conditions were recorded and related to disease severity. Our model predicts that in described conditions BN is a function of the expression of grapevine gene VvDMR6, summer rainfall and abundance of ‘Ca. P. solani’. The greatest impact among elements of the disease triangle is attributed to the pathogen, and is independent of the pathogen titer. We showed that this first de facto representation of the disease triangle is useful for showing disease dynamics over several years and could be applied to other plant-pathogen systems. The overall results of this study will contribute to understanding of ‘Ca. P. solani’ biology and its interactions with grapevine host.
Highlights
Research on phytoplasma-incited plant diseases has received increasing attention in recent years (Strauss2009)
Disease triangle model and keep it as simple as possible by not overfitting, different types of experimental data were generated: pathogen abundance estimated from collected samples, relative expression of several host plant genes that have been shown to be associated with development of grapevine yellows symptoms, symptom evaluation, and environmental factors collected from the nearby weather station
The computed model of disease triangle was validated by data acquired in a year that was excluded from the statistical analysis
Summary
Research on phytoplasma-incited plant diseases has received increasing attention in recent years (Strauss2009). In order to find the most suitable candidate to represent the host element in the disease triangle, we checked the difference in gene expression due to the sanitary status of the plants using Wilcoxon test with Bonferroni correction in each growing season.
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