Virus infections in plants are a major threat to crop production and sustainable agriculture, which results in significant yield losses globally. The past decade has seen the development and deployment of sophisticated high-throughput omics technologies including genomics, transcriptomics, proteomics, and metabolomics, in order to try to understand the mechanisms underlying plant-virus interactions and implement strategies to ameliorate crop losses. In this review, we discuss the current state-of-the-art applications of such key omics techniques, their challenges, future, and combinatorial use (e.g., single cell and spatial omics coupled with super-resolution high-throughput imaging methods and artificial intelligence-based predictive models) to obtain new mechanistic insights into plant-virus interactions, which could be exploited for more effective plant disease management and monitoring.