Laboratoire des Interactions Plantes-Microorganismes, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, CNRS, Université de Toulouse, 31326 Castanet-Tolosan, France.
KWS SAAT SE & Co, 37574 Einbeck, Germany.
Proc Natl Acad Sci U S A. 2020 Jul 28;117(30):18099-18109. doi: 10.1073/pnas.2000078117. Epub 2020 Jul 15.
Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in in response to the bacterial pathogen To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of , a gene underlying a QTL conferring quantitative and broad-spectrum resistance to -dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in Protein-protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.
定量疾病抗性 (QDR) 是自然种群和作物中主要的抗性形式。令人惊讶的是,关于这种植物免疫形式的信号机制的生物分子网络的信息非常有限。这种信息的缺乏可能是由于其复杂和定量的性质。在这里,我们使用了一种整合的方法,包括基因组学、网络重建和突变分析,来识别和验证控制 QDR 的分子网络,以响应细菌病原体 。为了应对这一挑战,我们首先进行了一项转录组分析,重点关注感染的早期阶段,并使用转基因系对 进行表达调控,该基因是一个 QTL 的基础,赋予对 的定量和广谱抗性。依赖基因表达被证明涉及多种细胞活动(信号转导、运输和代谢过程),主要与已经在 中表征的效应子触发免疫 (ETI) 和病原体相关分子模式 (PAMP) 触发免疫 (PTI) 反应不同。然后,蛋白质-蛋白质相互作用网络重建揭示了一个高度互联和分布式的 RKS1 依赖性网络,组织在五个基因模块中。最后,属于网络不同功能模块的 41 个基因的 knockout 突变体表明,76%的基因和所有基因模块都部分参与了 RKS1 介导的抗性。然而,这些功能模块对遗传突变表现出不同的稳健性,表明在 QDR 网络的分散结构中,一些模块比其他模块更具弹性。总之,我们的工作揭示了 QDR 的复杂性,并提供了对 QDR 免疫网络的全面理解。