Changing the Game: Using Integrative Genomics to Probe Virulence Mechanisms of the Stem Rust Pathogen Puccinia graminis f. sp. tritici.
Changing the Game: Using Integrative Genomics to Probe Virulence Mechanisms of the Stem Rust Pathogen Puccinia graminis f. sp. tritici.
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改变游戏：使用综合基因组学探测茎病原体Puccinia graminis f的毒力机制。 sp。 Tritici。
DOI：
10.3389/fpls.2016.00205
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发表时间：
2016
影响因子：
5.6
通讯作者：
Dodds PN
中科院分区：
文献类型：
--
作者：
Figueroa M;Upadhyaya NM;Sperschneider J;Park RF;Szabo LJ;Steffenson B;Ellis JG;Dodds PN
小麦秆锈病是近年来由禾柄锈菌（Puccinia graminis f.）对粮食安全构成威胁。这些担忧促使全球为控制这种疾病做出了广泛的努力。大量的研究和育种计划的目标是在品种中鉴定和引入新的抗茎锈病（Sr）基因，以防止病害的遗传保护。这种抗性基因通常编码识别病原体特定成分的免疫受体蛋白，称为无毒（Avr）蛋白。部署具有单个Sr基因的栽培品种的一个显著缺点是，它们通常被病原体的进化克服，以通过Avr基因的改变来逃避识别。因此，实现持久锈病控制的一个关键因素是通过常规育种或转基因方法组合部署多种有效的Sr基因，以最大限度地降低抗性崩溃的风险。在这种情况下，病原体毒力的进化将需要多个Avr基因的变化，以绕过识别。然而，选择最佳的Sr基因组合部署是一个挑战，需要详细了解病原体Avr基因与它们相互作用和Pgt的毒力表型存在于自然界中。从Pgt中鉴定特定的Avr基因将提供筛选工具，以加强病原体毒力监测，评估病原体群体的杂合性和突变倾向，并确认携带多种有效抗性基因的作物品种中单个Sr基因的功能。为了实现这一目标，在组装Pgt的高质量参考基因组序列以及包含具有不同毒力谱的多个田间分离株之间的变异的泛基因组方面已经取得了很大进展。反过来，这允许预测Pgt效应基因候选人的基础上已知的功能Avr基因在其他植物病原体，包括相关的亚麻锈病真菌。吸器中基因表达的上调和多样化选择的证据是鉴定候选Avr基因的两个有用参数。最近，我们还应用机器学习方法来不可知地预测候选效应器。在这里，我们回顾了茎锈病病原体组学的进展和方法，目前正在进行的识别小麦Sr基因识别的Avr基因。
The recent resurgence of wheat stem rust caused by new virulent races of Puccinia graminis f. sp. tritici (Pgt) poses a threat to food security. These concerns have catalyzed an extensive global effort toward controlling this disease. Substantial research and breeding programs target the identification and introduction of new stem rust resistance (Sr) genes in cultivars for genetic protection against the disease. Such resistance genes typically encode immune receptor proteins that recognize specific components of the pathogen, known as avirulence (Avr) proteins. A significant drawback to deploying cultivars with single Sr genes is that they are often overcome by evolution of the pathogen to escape recognition through alterations in Avr genes. Thus, a key element in achieving durable rust control is the deployment of multiple effective Sr genes in combination, either through conventional breeding or transgenic approaches, to minimize the risk of resistance breakdown. In this situation, evolution of pathogen virulence would require changes in multiple Avr genes in order to bypass recognition. However, choosing the optimal Sr gene combinations to deploy is a challenge that requires detailed knowledge of the pathogen Avr genes with which they interact and the virulence phenotypes of Pgt existing in nature. Identifying specific Avr genes from Pgt will provide screening tools to enhance pathogen virulence monitoring, assess heterozygosity and propensity for mutation in pathogen populations, and confirm individual Sr gene functions in crop varieties carrying multiple effective resistance genes. Toward this goal, much progress has been made in assembling a high quality reference genome sequence for Pgt, as well as a Pan-genome encompassing variation between multiple field isolates with diverse virulence spectra. In turn this has allowed prediction of Pgt effector gene candidates based on known features of Avr genes in other plant pathogens, including the related flax rust fungus. Upregulation of gene expression in haustoria and evidence for diversifying selection are two useful parameters to identify candidate Avr genes. Recently, we have also applied machine learning approaches to agnostically predict candidate effectors. Here, we review progress in stem rust pathogenomics and approaches currently underway to identify Avr genes recognized by wheat Sr genes.