A Rapid and Field-Compatible Detection Platform for the AvrPi9 Gene in Magnaporthe oryzae Using Integrated DNA Extraction, RPA and CRISPR–Cas12a
Atcharapohn Jai-uean, Pattavipha Songkumarn, Tanee Sreewongchai, Nonglak Parinthawong, Jyh Jian Chen and Chatchawan Jantasuriyarat** Author for corresponding; e-mail address: fscicwj@ku.ac.th
ORCID ID: https://orcid.org/0000-0002-7278-9704
Volume: Vol.53 No.5 (September 2026)
Research Article
DOI: https://doi.org/10.12982/CMJS.2026.089
Received: 4 May 2026, Revised: 29 July 2026, Accepted: 10 August 2026, Published: -
Citation: Jai-uean A., Songkumarn P., Sreewongchai T., Parinthawong N., Chen J.J. and Jantasuriyarat C., A rapid and field-compatible detection platform for the AvrPi9 gene in Magnaporthe oryzae using integrated DNA extraction, RPA and CRISPR–Cas12a. Chiang Mai Journal of Science, 2026; 53(5): e2026089. DOI 10.12982/CMJS.2026.089.
Graphical Abstract
Abstract
Rice blast, caused by Magnaporthe oryzae, remains one of the most destructive diseases of rice worldwide. Although molecular diagnostics enable rapid pathogen detection, tools for monitoring avirulence genes that directly inform resistance deployment remain limited. Here, we developed a field-compatible molecular detection platform for the avirulence gene AvrPi9 by integrating rapid crude DNA extraction with recombinase polymerase amplification (RPA) and CRISPR–Cas12a-based detection. The rapid extraction method enabled direct analysis of fungal mycelia and infected rice tissues without conventional DNA purification. Following RPA amplification, AvrPi9 was detected by Cas12a-mediated collateral cleavage and visualized by endpoint fluorescence using a portable blue LED illuminator. The assay specifically detected AvrPi9-positive isolates, with no fluorescence observed in AvrPi9-negative or control samples, and achieved a detection limit of 0.8 ng/µL genomic DNA following RPA amplification. The complete workflow was completed within 40–45 min using only simple heating devices and a portable blue LED illuminator. Validation using experimentally infected and naturally infected field-collected rice leaves confirmed that crude extracts were fully compatible with downstream RPA and CRISPR–Cas12a detection. This platform provides a practical approach for rapid AvrPi9 monitoring to support decentralized disease surveillance, informed resistance gene deployment, and future molecular surveillance of avirulence gene dynamics in M. oryzae populations.