Modeling virus progression with increased accuracy by incorporating gene silencing – supporting data

Crop loss due to viral infection is a significant issue around the world with increasing significance as climate change alters viral vector host range. Enhanced crop protection strategies are essential to mitigating food shortages. In order to design targeted interventions, fundamental knowledge of the viral infection time-course is needed. A key component of disease progression is the dynamics of plant gene-silencing and virus anti-gene-silencing that occur as a plant’s immune system responds to virus replication noting that the virus must recruit plant functions to complete its life cycle. Herein, a deterministic model that accounts for gene-silencing is developed. The model predicts the overall timecourse of a begomovirus (specifically, the tomato mottle virus) infection within a plant cell. It identifies that levels of coat protein expression are a limiting factor to viral load which is corroborated by co-transient expression of coat protein in conjunction with a luciferase reporter virus.