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，农作物病害暴发的频率增加。20世纪的分子遗传学研究为农业带来了好处，因为它展示了基因在作物生物学中扮演的角色，指导植物育种者为农民生产更好的作物。在21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，以了解它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集，测量单个基因功能的微小差异可能会对植物健康产生广泛影响的方式。具体地说，这个项目涉及植物对食草动物和微生物害虫的免疫反应所涉及的基因。植物的免疫反应是由一小部分化学信使引导的，这种化学信使被称为植物激素，该项目研究的基因将这种化学信息转化为免疫反应。在这个项目中开发的概念方法和实验室方法可能形成未来作物植物工作的基础，为植物育种者培育抗病作物提供材料。该项目结合了系统和合成生物学的方法来表征由看似多余的信号组件组成的遗传调控网络的功能。具体地说，将研究拟南芥的茉莉酸(JA)受体系统。基于微分方程式的JA信号的数学模型将被用于指导芽期酵母中最小合成系统的设计，该系统能够根据预定的传递函数范围将JA输入转换为转录输出。利用这一信息，基于CRISPR-Cas9的转录因子将被设计成针对PLANTA中JA网络的特定子集。根据我们的模型，将选择引导RNA目标基因来对系统的紧急特性进行特定的改变。所有这些工作都依赖于首先能够产生实验数据来拟合相关相互作用强度的参数，为了做到这一点，最近在克拉文斯实验室开发的SynAg方法将被适应和扩展。SynAg依靠酵母表面显示和下一代测序在一次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的预测能力，用于在酵母中构建新的遗传电路，或扰乱植物中的现有电路，该项目旨在阐明以明显冗余编码的紧急性质。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.