Molecular breeding approaches for sustainable rice blast management: Recent advances and challenges

Ragulakollu SravanthiArul LManonmani SwaminathanGopalakrishnan ChellappanRavichandran VRamalingam Jegadeesan^*

• Tamil Nadu Agricultural University, Coimbatore, India

Rice (Oryza sativa. L) is a staple crop globally, but blast disease caused by fungal pathogens Magnaporthe oryzae is one of the most devastating and results severe economic losses in rice production worldwide. Recent technological advancements have opened new possibilities for developing blast resistance. The dynamic and highly adaptable nature of M. oryzae allows it to overcome plant defense mechanisms rapidly, posing a major threat to global food security and agricultural sustainability. Traditional breeding approaches have been limited by their time-consuming nature and reliance on phenotypic selection. However, with the emergence of molecular breeding technologies, resistance breeding has experienced significant acceleration and precision. Tools such as marker-assisted selection (MAS), marker-assisted backcross breeding (MABB), and quantitative trait locus (QTL) mapping allow for the identification and introgression of resistance genes (R genes) more efficiently and accurately. Recent advances in genome engineering techniques, particularly CRISPR- Cas 9, have transformed the capability to manipulate resistance genes directly, enabling targeted editing and stacking of multiple genes (gene pyramiding) for durable resistance. Moreover, omics technologies—including genomics, transcriptomics, proteomics, and metabolomics—offer a comprehensive understanding of the molecular interactions between host and pathogen, facilitating the discovery of novel resistance mechanisms and regulatory pathways. The integration of allele mining with advanced biotechnological tools has further promoted the development of cisgenic and intragenic plants, where resistance genes from related cultivars or wild species are introduced without foreign DNA, thus addressing public concerns over transgenic crops. These strategies enhance resistance and help retain the desirable agronomic traits of elite rice varieties. Therefore, understanding host-pathogen interactions at the molecular and cellular levels remains essential. Emerging technologies such as nanotechnology show promise in developing targeted fungicide delivery systems and innovative diagnostic tools. Synthetic biology opens avenues for constructing synthetic resistance pathways or deploying plant biosensors. Additionally, machine learning and artificial intelligence (AI) algorithms are increasingly used to predict disease outbreaks, model gene interactions, and optimize breeding strategies based on large datasets. Thus, managing rice blast disease necessitates a holistic approach combining conventional breeding wisdom with modern molecular tools and emerging technologies and offers valuable insights for sustaining resilient breeding programs against this pathogen.