CAREER: The phenotypic spectrum: Quantifying new patterns of architecture variation in crop roots

植物的根在大小和形状上有很大的不同。根构型的多样性对作物产量或植物生物量的贡献还不完全清楚，部分原因是根埋在地下，难以研究。本研究采用定量的方法来分析根构型的广泛多样性。在实验条件下生长的豆根将被成像，所得数据将用于创建新的数学和计算工具，以辨别根变异的原因。结合基因组信息，分析工具将确定根形状的遗传因素，以应对环境和遗传变异。这项研究将为豆类等作物的育种目标提供新的机会，并扩展到玉米。该研究还结合了一个教育计划，将计算与植物研究相结合，从而解决了国家对经过计算培训的植物科学劳动力的关键需求。这些新工具将公开提供，并利用国家网络基础设施加以部署：此外，这些技术将被纳入两门课程，使基础科学和计算生物学能够在体验式学习环境中进行。一个新的学生奖是通过植物中心和格鲁吉亚信息学研究所实施，以突出在计算和植物科学接口工作所取得的进展。科学和教育的结合为育种计划的快速传播提供了一条途径。经过几十年对植物根系的研究，它仍然是一个谜如何以及为什么根结构出现在看似无穷无尽的形状变化。该研究引入了表型谱作为一种新的定量理论，将塑性的既定概念扩展到一个新的维度。一个基因型的表型谱由不同的根构型类型，其中每一个被假设为与不同的可塑性曲线在不同的环境。从理论上讲，表型谱出现一个基因型的人口，如果所有的基本几何测量在所有位置在每个单独的根系内，每个人是由一个完整的根描述符总结。具有相似特征的描述符对应于一种体系结构类型。因此，光谱是不可观察到的与当前的表型分析工具，捕获每个性状的根系中只有一个位置。量化的表型谱需要前所未有的全根描述符和模拟技术的发展，以捕捉整个根结构的三维空间组织的差异。在这样做，微分几何和成像方法，以及一个新开发的统计分析的新组合提出。实验将提供一个了解如何描述和评估不同的根构型类型的相互作用，在温室和外地连接两者与发达的描述符。教育目标是通过使用开发的工具的两门课程来增加计算科学和植物科学接口的研究人员数量。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估而被认为值得支持。

Plant roots are remarkably diverse in size and shape. It is not fully understood how the diversity in root architecture contributes to crop yields or plant biomass in part because roots are buried underground and difficult to study. This research takes a quantitative approach to analyze the wide diversity of root architectures. Bean roots grown under experimental conditions will be imaged and the resulting data will be used to create new mathematical and computational tools to discern causes of root variability. Combined with genomic information, the analytical tools will identify genetic elements underlying root shapes in response to environmental and genetic variation. The research will point to new opportunities for breeding targets in crops such as bean and extended to maize. The research also couples with an education program that integrates computation with plant research, thus addressing the critical national need for a computationally trained plant science workforce. The novel tools will be publicly available and deployed using national cyberinfrastructure: further the technologies will be integrated into two courses that enable basic science and computational biology within an experiential learning environment. A new student award is implemented through the Plant Center and the Georgia Informatics Institute to highlight advances attained by working at the computational and plant science interface. Together, the integration of science and education sets forth a path for fast dissemination of results into breeding programs. After decades of research on plant roots it is still a mystery how and why root architecture arises in seemingly endless variations of shapes. The research introduces the phenotypic spectrum as a new quantitative theory that extends the established concept of plasticity by a new dimension. The phenotypic spectrum of one genotype consists of distinct root architecture types, each of which is hypothesized to be associated with a different plasticity curve across environments. Theoretically, the phenotypic spectrum emerges for a population of one genotype if all elementary geometric measurements at all locations within each individual root system are taken and each individual is summarized by a whole root descriptor. Descriptors with similar characteristics correspond to one architecture type. Hence, the spectrum is not observable with current phenotyping tools that capture only one location in a root system per trait. Quantifying the phenotypic spectrum demands the development of unprecedented whole root descriptors and simulation techniques to capture the differences in the 3D spatial organization of the whole root architecture. In doing so, a new combination of differential geometry and imaging approaches as well as a newly developed statistical analysis is proposed. The experiments will provide an understanding of how to describe and evaluate the interplay of different root architecture types in the greenhouse and the field by linking both with the developed descriptors. The educational goal is to increase the number of researchers at the interface of computational and plant sciences through two courses using the developed tools.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.