Characterization of Rice Blast (Magnaporthe oryzae) Isolates through Whole-Genome Sequencing to Monitor Geographic Distribution and Optimize Gene Deployment for Breeding

  • Cereal: Rice
  • Stressor: Rice Blast Disease
  • Principal Investigator: Jonathan Richards, Louisiana State University

Jonathan Richards, PIWorking to improve rice resistance against rapidly evolving rice blast disease, this effort focuses on characterizing pathogen populations and identifying resistance genes that remain effective against current strains. Rice blast, caused by Magnaporthe oryzae, is a major constraint to rice production globally and can result in significant yield loss, particularly in regions like Bangladesh where disease pressure is high. Because pathogen populations shift over time and across environments, resistance genes that are effective in one context may quickly become ineffective, creating a need for continuous monitoring and updated genetic information.

Whole-genome sequencing and population genetic analyses will be used to characterize the diversity and structure of M. oryzae populations collected from Bangladesh and the United States. These data will be used to identify informative genetic markers and effector gene profiles that define distinct pathogen groups, enabling classification of isolates based on both genetic similarity and predicted virulence. A targeted genotyping panel will then be developed and validated to provide a rapid, cost-effective method for identifying pathogen groups without requiring full genome sequencing. To ensure accessibility, a user-friendly analysis pipeline will be created to allow researchers to process and interpret genotyping data without specialized bioinformatics expertise.

This genotyping framework will support the implementation of a sustained pathogen monitoring system across regions and growing seasons, generating data on pathogen population dynamics and the prevalence of specific blast groups. Resulting datasets, validated markers, and characterized pathogen groups will be made publicly available as resources to support breeding programs. In parallel, the project strengthens capacity in bioinformatics, data analysis, and disease monitoring, enabling continued application of these tools to support blast resistance gene discovery and deployment.