RoL: FELS: EAGER: Exploring the adaptive possibilities of 'redundancy' in a plant defense hormone signaling pathway

全球农业面临的挑战之一是，由于全球气温上升，农作物疾病爆发的频率增加。20世纪世纪的分子遗传学研究为农业带来了好处，它揭示了基因在作物生物学中的作用，指导植物育种者为农民生产更好的作物。在21世纪世纪，关于植物基因组DNA序列的信息要多得多，但这些丰富的信息仍然需要实验分析，以了解如何在植物育种中发挥适当的作用。该项目将开发新的方法来研究模式植物拟南芥的基因组，测量单个基因功能的微小差异如何对植物健康产生广泛影响。具体而言，该项目涉及植物对食草动物和微生物害虫的免疫反应的基因。植物免疫反应是由一小部分化学信使（称为植物激素）控制的，本项目研究的基因将这种化学信使转化为免疫反应。该项目的概念方法和实验室方法将为作物的未来研究奠定基础，为植物育种家开发抗病作物提供材料。该项目结合了系统和合成生物学的方法，以表征由看似冗余的信号成分组成的基因调控网络的功能。具体而言，茉莉酸（JA）受体系统的拟南芥将进行研究。基于微分方程的JA信号传导的数学模型将用于指导芽殖酵母中的最小合成系统的设计，所述最小合成系统能够根据一系列预定的传递函数将JA输入转化为转录输出。利用这些信息，基于CRISPR-Cas9的转录因子将被设计为针对植物中JA网络的特定子集。引导RNA靶基因将被选择来对系统的涌现特性进行特定的改变，正如我们的模型所告知的那样。所有这些工作首先依赖于能够生成实验数据来拟合相关相互作用强度的参数，为此，最近在Klavins实验室开发的SynAg方法将被调整和扩展。SynAg依赖于酵母表面展示和下一代测序，在一个实验中量化整个相互作用网络。通过开发JA信号模型，并测试这些模型对酵母中新基因电路构建的预测能力，或对植物中现有电路的扰动，该项目旨在阐明编码在明显冗余中的涌现特性。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

Among the challenges facing global agriculture is the increased frequency of crop disease outbreaks as a result of increasing global temperatures. Molecular-genetic studies of the 20th century yielded benefits for agriculture, by showing the roles that genes play in crop biology, guiding the hands of plant breeders to produce better crops for farmers. In the 21st century far more information is available about the DNA sequences of plant genomes, but this wealth of information still requires experimental analysis to understand how it can be used to proper effect in plant breeding. This project will develop new approaches to studying sets of genes from the model plant Arabidopsis thaliana, measuring the way that slight differences in individual gene functions can lead to broad effects on plant health. Specifically, this project addresses genes involved in the plant immune response to herbivores and microbial pests. Plant immune responses are directed by a small set of chemical messengers, known as plant hormones, and the genes studied in this project convert this chemical message into an immune response. Conceptual approaches and laboratory methods developed during this project may form the foundation for future work in crop plants, providing material for plant breeders to develop disease resistant crops.This project combines approaches from systems and synthetic biology to characterize functions of genetic regulatory networks composed of seemingly redundant signaling components. Specifically the Jasmonic acid (JA) receptor system of Arabidopsis thaliana will be studied. Mathematical models of JA signaling based on differential equations will be used to guide design of minimal synthetic systems in budding yeast able to convert JA inputs into transcriptional outputs according to a range of predetermined transfer functions. Using this information CRISPR-Cas9 based transcription factors will be designed to target particular subsets of the JA network in planta. Guide RNA target genes will be chosen to carry out specific changes to the emergent properties of the system, as informed by our models. All this work relies on first being able to generate experimental data to fit parameters for relevant interaction strengths, and to do this the SynAg method, recently developed in the Klavins lab, will be adapted and expanded. SynAg relies on yeast surface display and next generation sequencing to quantify entire interaction networks in a single experiment. By developing models of JA signaling and testing the predictive power of these models for the construction of new genetic circuits in yeast, or to perturb existing circuits in planta, this project aims to elucidate the emergent properties encoded in apparent redundancy.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.