Our laboratory studies how viral pathogens evolve, hijact hosts, and interact with host plants and their transmitting insect vectors under fluctuating environmental conditions. By integrating multi-omics, systems biology, molecular biology, and functional genomics (RNAi/CRISPR), population genomics, and computational biology, we aim to transition plant pathology from retrospective analysis to predictive and preventative disease intervention.
Core focus areas:
Tracking how viral populations evolve, spread, and adapt in changing field conditions
Mapping global virus-host interactomes to identify core drivers of infection and transmission
Harnessing translational technologies, such as CRISPR and RNAi, to interfere virus transmission and build durable crop resistance
Shifting field conditions continuously alter viral population structures, accelerating the emergence of virulent strains and changing pathogen persistence across agricultural landscapes. Our research examines the genetic adaptation of viral pathogens under these dynamic pressures. By capturing high-resolution evolutionary snapshot data and evaluating viral fitness across varied contexts, we generate the critical parameters needed to build predictive models, forecast disease emergence, and guide proactive intervention strategies.
To cause disease and spread across agricultural landscapes, plant viruses must overcome physiological barriers and systematically manipulate host machinery. Using multi-omics and systems biology approaches, we construct complete interaction networks across plant-virus-vector pathosystems. We aim to identify critical viral interaction nodes that drive infection, laying the groundwork for targeted molecular intervention.
Aphids pose dual threats to crop productivity: direct yield loss from heavy phloem sap feeding and systemic damage as primary vectors of plant viruses. Our research explores the molecular and physiological mechanisms driving plant-aphid dynamics. Current ongoing, collaborative projects focus on:
Tissue-specific host translatome responses to aphid feeding
Diurnal rhythms in aphid feeding behavior and gene expression as a potential mechanism to enhance aphid performance