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Updated: Jun 4, 2026

Screening and Identification of RNA Silencing Suppressors from Secreted Effectors of Plant Pathogens
Published on: February 3, 2020
Spray-induced gene silencing for plant disease control: mechanistic basis and deployment-oriented design
Mohamed Mannaa1,2, Eui-Joon Kil3, Inmyoung Park4
1Department of Microbiology, Pusan National University, Busan, Republic of Korea.
None:
Spray-induced gene silencing (SIGS) is a transgene-free, biodegradable RNA-based approach for crop protection in which exogenously applied double-stranded RNA (dsRNA) is taken up and processed by plants or susceptible pathogens to drive the sequence-specific silencing of essential or virulence-associated genes. This review synthesizes advancements in transitioning SIGS from proof-of-concept to field-relevant deployment. Here, we frame SIGS as a two-compartment process: (i) dsRNA deposition on foliage, access to cuticular/apoplastic microenvironments, processing into small interfering RNAs (siRNAs), amplification, and systemic movement within plants; and (ii) pathogen acquisition of dsRNA/siRNAs at infection interfaces, followed by RNA interference (RNAi) execution, with outcomes strongly conditioned by pathogen RNA-uptake competence and, in some systems, cross-kingdom RNA trafficking. Because performance is often constrained by exposure rather than sequence potency, we evaluated the key determinants of delivery and persistence and compared carrier strategies that extend stability and bioavailability, including layered double hydroxide clays, vesicle-inspired lipid systems, polymer complexes, and carbon-based nanomaterials. We then consolidated the mechanism-informed design rules for target selection, within-transcript positioning, and dsRNA architecture, along with specificity, non-target risk, and durability/escape management. Finally, we defined the current scope boundaries, including the limited applicability to bacterial phytopathogens lacking canonical eukaryotic RNAi. We outline deployment-oriented priorities for achieving reliable SIGS performance under realistic agricultural conditions.
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