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Rapid detection of the rice false smut fungus Ustilaginoidea virens by lateral flow strip-based recombinase polymerase amplification assay
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作者 jiacheng xi Sanlian Wan +7 位作者 Yue Li Yuandi Xu Jing Yang Ting Zhang Jiajia Chen Zhengguang Zhang Danyu Shen Haifeng Zhang 《Journal of Integrative Agriculture》 SCIE CAS 2024年第11期3763-3773,共11页
Rice false smut,caused by Ustilaginoidea virens,is a devastating disease that greatly reduces rice yield and quality.However,controlling rice false smut disease is challenging due to the unique infection mode of U.vir... Rice false smut,caused by Ustilaginoidea virens,is a devastating disease that greatly reduces rice yield and quality.However,controlling rice false smut disease is challenging due to the unique infection mode of U.virens.Therefore,there is a need for early diagnosis and monitoring techniques to prevent the spread of this disease.Lateral flow strip-based recombinase polymerase amplification(LF-RPA)overcomes the limitations of current U.virens detection technologies,which are time-consuming,require delicate equipment,and have a high false-positive rate.In this study,we used a comparative genomics approach to identify Uv_3611,a specific gene of U.virens,as the target for the LF-RPA assay.The designed primers and probe efffectively detected the genomic DNA(gDNA)of U.virens and demonstrated no cross-reactivity with related pathogens.Under optimal conditions,the LF-RPA assay demonstrated a sensitivity of 10 pg of U.virens gDNA.Additionally,by incorporating a simplified PEG-NaOH method for plant DNA extraction,the LF-RPA assay enabled the detection of U.virens in rice spikelets within 30 min,without the need for specialized equipment.Furthermore,the LF-RPA assay successfully detected U.virens in naturally infected rice and seed samples in the field.Therefore,the LF-RPA assay is sensitive,efficient,and convenient,and could be developed as a kit for monitoring rice false smut disease in the field. 展开更多
关键词 rice false smut Ustilaginoidea virens isothermal amplification disease monitoring field diagnosis
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