Аңдатпа
Emerging and re-emerging plant diseases are becoming more frequent and severe due to climate change, agricultural intensification, crop genetic uniformity, and the expanding global movement of planting materials. These drivers have altered host-pathogen-environment interactions, facilitating pathogen range expansion, host shifts, and erosion of resistance, thereby increasing the risk of epidemics and pandemics in major crops. In this context, genetic and genomic approaches have become central to modern plant pathology, providing high-resolution tools to investigate disease emergence, spread, and adaptation. This review summarizes recent advances in genomic surveillance, high-throughput sequencing-based diagnostics, pathogen pangenomes, and data-driven prediction as interconnected components of an integrated framework for studying emerging and re-emerging plant diseases. Genome-scale analyses have improved outbreak reconstruction and population-level inference, while unbiased sequencing and metagenomic approaches have expanded diagnostic capacity to include complex, latent, and previously undetected infections. Pangenomic studies further demonstrate that virulence evolution is frequently driven by gene content variation, structural rearrangements, and demographic processes, challenging reference-centric models of pathogen adaptation. Predictive and risk assessment approaches increasingly integrate genomic information with environmental, epidemiological, and pathway data to support proactive surveillance and management. Taken together, the evidence indicates that plant disease emergence results from interacting evolutionary, ecological, and anthropogenic processes. Genetic and genomic tools, when embedded within coordinated surveillance systems and supported by standardized data practices, provide a robust foundation for early warning, improved outbreak interpretation, and risk-informed plant health management under accelerating global change.