Identification of citrus immune regulators involved in defence against Huanglongbing using a new functional screening system.

Abstract

Huanglongbing (HLB) is the most devastating citrus disease in the world. Almost all commercial citrus varieties are susceptible to the causal bacterium, Candidatus Liberibacter asiaticus (CLas), which is transmitted by the Asian citrus psyllid (ACP). Currently, there are no effective management strategies to control HLB. HLB-tolerant traits have been reported in some citrus relatives and citrus hybrids, which offer a direct pathway for discovering natural defence regulators to combat HLB. Through comparative analysis of small RNA profiles and target gene expression between an HLB-tolerant citrus hybrid (Poncirus trifoliata × Citrus reticulata) and a susceptible citrus variety, we identified a panel of candidate defence regulators for HLB-tolerance. These regulators display similar expression patterns in another HLB-tolerant citrus relative, with a distinct genetic and geographic background, the Sydney hybrid (Microcitrus virgata). Because the functional validation of candidate regulators in tree crops is always challenging, we developed a novel rapid functional screening method, using a C. Liberibacter solanacearum (CLso)/potato psyllid/Nicotiana benthamiana interaction system to mimic the natural transmission and infection circuit of the HLB complex. When combined with efficient virus-induced gene silencing in N. benthamiana, this innovative and cost-effective screening method allows for rapid identification and functional characterization of regulators involved in plant immune responses against HLB, such as the positive regulator BRCA1-Associated Protein, and the negative regulator Vascular Associated Death Protein.

Plant phenotyping relevance

植物免疫応答を評価する新規かつ迅速な機能スクリーニング法の開発が研究の中心であり、HLB関連の植物状態・防御応答を表現型として評価している。

Code and data availability

The supplied blocks describe sRNA profiling, qRT-PCR, and a Nb/psyllid/CLso VIGS screening system, but contain no public phenotype dataset, image/sensor inputs, author analysis code, or trained model with an explicit deposit URL. Only in-text references to supplementary tables (Tables S1–S9) appear, without any public,

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