Nucleic acid-based strategies to mitigate stripe rust disease of wheat for achieving global food security - A review

Wheat (Triticum aestivum), being a global staple crop, is critical in ensuring food security due to its significant nutritional value. However, it faces numerous challenges from both biotic and abiotic stresses, with fungal diseases being particularly detrimental to yield. Among these, wheat stripe rust, caused by the fungal pathogen Puccinia striiformis, poses a severe threat to wheat. Globally, 5.47 million tons of grains are lost due to the stripe rust pathogen, equivalent to a loss of USD 979 million annually; almost 88 % of the world's wheat production is susceptible to stripe rust. This review accentuates the global extensive distribution of stripe rust, detailing its causes and impact on crop productivity and mitigating approaches following traditional, genomic, and post-genomics. The mitigation approaches to wheat stripe rust have been mainly categorized into primitive (pre-genomic), modern (genomic), and next-generation (post-genomic) approaches. The primitive approaches include traditional breeding, phenotypic selection, and exotic germplasm to introduce resistance leads to early success in disease management. The advanced genomic era, with tools like QTL mapping, GWAS, marker-assisted selection, and high-throughput sequencing to deploy resistance genes, helps in precise mapping and developing high-throughput genotyping for large-scale screening and introgression of multiple resistant genes. The gene-editing approaches, including CRISPR/Cas9, RNAi, and epigenomics, now enable precise gene editing and regulation for durable resistance, together with multi-omics techniques, to identify resistant pathways and biomarkers with enhanced understanding of host-pathogen interactions and resistance mechanisms. Climate change events like shifts in rainfall patterns and rising temperatures expand the rust-prone area and pose more challenges in developing durable rust-resistant cultivars. Furthermore, the review explores using wheat's valuable genetic resources and integrating AI-based technologies to enhance stripe rust resistance by analyzing large datasets, including pathogen evolution and growth stages, allowing for timely interventions of the stripe rust epidemic. The role of multiomics approaches, particularly genomics and transcriptomics, in unraveling the genetic basis of stress tolerance is highlighted. A forward-looking framework is proposed, emphasizing the use of interdisciplinary methodologies, including big data, multi-omics, and AI-driven approaches, that hold immense promise to revolutionize wheat protection with the development of climate-resilient wheat genotypes and ensure real-time disease monitoring and precision-resistant strategies against the evolving rust pathogen.