Evolution and Domestication of Core Eudicot Defense Mechanisms against a Common Generalist Pathogen

植物防御变异研究通常集中在寄主或专门病原体中仅相互作用的单个大效应基因。然而，对大多数通用性病原体的抗性是定量的，不能用少数不同的基因类型的个体来研究。该项目将开始第一次直接调查核心植物谱系内和核心植物谱系之间的基因组多样性如何由广谱通用真菌的基因组多样性塑造，这种真菌可以感染大多数植物，如果不是所有植物的话。这将导致开发新的生物学和统计学方法，以处理不同系统发育谱系的基因组多样性，并提供目前仅适用于番茄灰霉病菌的独特的多植物物种数据集。所有数据和分析方案都将公之于众，在获得适当许可之前，应要求提供微生物分离株。在培训方面，该项目将为高中、本科生和研究生提供研究机会。这些学生将接受复杂性状的现代数量遗传学培训，为他们未来在工业或学术界的职业生涯做好准备。由于这是第一次尝试在两个相互作用的物种中进行数量遗传学研究，这将使它们在理论和计算应用方面处于该领域的前沿。本科生将在这个项目的框架内开发和设计他们自己的项目。这项研究的任何结果都可能包括至少一名本科生作为合著者，他在设计和解释实验方面发挥了不可或缺的作用。此外，首席调查员将参与教学，包括大学课堂环境和正在进行的外展工作，以教育社区成员有关植物新陈代谢、植物防御进化和数量基因组学。植物/病原菌的相互作用决定了植物的适合性/产量。大多数关于植物/病原体相互作用的研究都集中在只感染一个或几个类似人类流感的物种的病原体引起的流行病上。然而，这导致了对像灰霉病菌或普通感冒这样的地方性病原体的研究很少，这些病原体可以感染大多数寄主基因，但只会造成很低的经济损失。这些通才病原体在植物谱系中施加了进化压力，然而这种跨谱系压力很少被系统地解决。例如，目前还不知道是否存在一个共同的植物防御网络来抵御这些通用性病原体，这种网络可以在所有植物中发挥作用。为了测试这个问题，这个项目的目标是：1)利用高通量平台，利用100个病原菌的基因组测序分离物，测量六种独立驯化的植物(生菜、番茄、葡萄、大豆和甘蓝)的病斑发展；2)使用全基因组关联图谱数据集来识别病原体内允许其感染这些不同寄主的致病网络；3)使用一种新的共种共表达网络方法来识别和验证这些网络的植物基因靶标，以测试病原体靶标的防御机制在植物中是保守的还是变异的，以及这些防御机制是否受到人类诱导的驯化的影响；以及4)在这些植物/病原菌组合中进行转录组分析，以确定在eudicot谱系中保守或变异的转录反应。通过在每个植物物种中包括家养和野生基因类型，该项目将提供一个共同的参考框架，在其中研究驯化如何可能或可能不一致地影响植物的防御。从长远来看，这些信息将有助于更好地理解选择压力是如何推动优树谱系内的防御系统向通才病原体进化的。

Plant defense variation studies typically focus on single large effect genes within a host or specialist pathogen that interact only with each other. However, resistance to most generalist pathogens is quantitative and cannot be investigated using few genotypically distinct individuals. This project will begin one of the first direct surveys of how genomic diversity within and across core plant lineages may be shaped by genomic diversity in a broad spectrum generalist fungus that can infect most if not all plants. This will lead to the development of novel biological and statistical methods to handle genomic diversity across phylogenetic lineages and provide a unique multi-plant species dataset that is currently only feasible with Botrytis cincerea. All data and analysis protocols will be publicly available and microbial isolates will be available upon request pending the acquisition of the appropriate permits. With regard to training, the project will provide research opportunities for high school, undergraduate, and graduate students. These students will be trained in modern quantitative genetics of complex traits to prepare them for future careers in industry or academics. As this is the one of the first instances of attempting to do quantitative genetics in two interacting species, this will place them at the forefront of the field in both theory and computational applications. Undergraduates will develop and devise their own projects within the frame of this project. Any publication resulting from this research will likely include at least one undergraduate student as a co-author who was integral in designing and interpreting the experiments. In addition, the principal investigator will be involved in teaching, both in a university classroom setting and in ongoing outreach efforts to educate community members about plant metabolism, plant defense evolution, and quantitative genomics. Plant/pathogen interactions determine plants fitness/yield. Most research on plant/pathogen interactions focuses on epidemic diseases from pathogens that infect only one or a few species similar to the human flu. However, this has led to a paucity of research on pathogens that are endemic, like Botrytis cinerea or the common cold, which can infect most host genotypes but only cause a low level of economic loss. These generalist pathogens place evolutionary pressure across plant lineages, yet this cross-lineage pressure is rarely systematically addressed. For example, it is currently not known if there is a common plant defense network against these generalist pathogens that can function in all plants. To test this question, this project aims to: 1) measure lesion development with a high-throughput platform across six plant species that have independently undergone domestication (lettuce, tomato, grape, soy and Brassicas) with 100 genome sequenced isolates of the pathogen, Botrytis cinerea; 2) use the genome wide association mapping dataset to identify pathogenicity networks within the pathogen that allow it to infect these diverse hosts; 3) identify and validate plant gene targets of these networks using a new co-species co-expression network approach to test if the pathogen targets defense mechanisms that are conserved or variant across plants and if these defense mechanisms have been affected by human driven domestication; and 4) conduct transcriptome profiling across these plant/pathogen combinations to identify conserved or variant transcriptional responses across the eudicot lineages. By including domestic and wild genotypes in each plant species this project will provide a common reference frame in which to study how domestication may or may not consistently influence plant defenses. In the longer term, this information will provide for a better understanding of how selection pressures drive the evolution of defenses within eudicot lineages towards generalist pathogens.