To recognize diverse threats, plants monitor extracellular molecular patterns and transduce intracellular immune signaling through receptor complexes at the plasma membrane. Pattern recognition occurs through a prototypical network of interacting proteins, comprising A) receptors that recognize inputs associated with a growing number of pest and pathogen classes (bacteria, fungi, oomycetes, caterpillars), B) co-receptor kinases that participate in binding and signaling, and C) cytoplasmic kinases that mediate first stages of immune output. While this framework has been elucidated in reference accessions of model organisms, network components are part of gene families with widespread variation, potentially tuning immunocompetence for specific contexts. Most dramatically, variation in receptor repertoires determines the range of ligands acting as immunogenic inputs for a given plant. Diversification of receptor kinase (RK) and related receptor-like protein (RLP) repertoires may tune responses even within a species. Comparative genomics at pangenome scale will reveal patterns and features of immune network variation.

中文翻译：

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跨植物免疫网络不断发展的细胞表面模式识别领域。

为了识别各种威胁，植物监测细胞外分子模式并通过质膜上的受体复合物转导细胞内免疫信号。模式识别通过相互作用蛋白的原型网络进行，包括：A）识别与越来越多的害虫和病原体类别（细菌，真菌，卵菌，毛毛虫）相关的输入的受体，B）参与结合和信号传导的共受体激酶和C）介导免疫输出第一阶段的胞质激酶。虽然已在模型生物的参考登录中阐明了该框架，但网络组件是具有广泛变异的基因家族的一部分，可能会针对特定情况调整免疫能力。最明显的是 受体组成的变化决定了作为给定植物的免疫原性输入的配体范围。受体激酶（RK）和相关受体样蛋白（RLP）谱的多样化甚至可以在一个物种内调节反应。泛基因组规模的比较基因组学将揭示免疫网络变异的模式和特征。