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

植物根的大小和形状差异很大。目前尚不完全了解根结构的多样性如何影响作物产量或植物生物量，部分原因是根埋在地下且难以研究。这项研究采用定量方法来分析根架构的广泛多样性。对实验条件下生长的豆根进行成像，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，分析工具将识别根部形状的遗传元素，以响应环境和遗传变异。该研究将为豆类等作物的育种目标指出新的机会，并扩展到玉米。该研究还与一项将计算与植物研究相结合的教育计划相结合，从而满足了国家对受过计算训练的植物科学劳动力的关键需求。这些新颖的工具将公开提供并使用国家网络基础设施进行部署：此外，这些技术将被整合到两门课程中，从而在体验式学习环境中实现基础科学和计算生物学。植物中心和佐治亚信息学研究所设立了一个新的学生奖，以突出在计算和植物科学接口方面取得的进步。科学与教育的结合为将成果快速传播到育种计划中开辟了一条道路。经过数十年对植物根系的研究，根系结构如何以及为何以看似无穷无尽的形状变化仍然是一个谜。该研究引入了表型谱作为一种新的定量理论，将既定的可塑性概念扩展到了一个新的维度。一种基因型的表型谱由不同的根结构类型组成，假设每种根结构类型与跨环境的不同可塑性曲线相关。理论上，如果在每个个体根系内的所有位置进行所有基本几何测量，并且每个个体都由整个根描述符概括，则一种基因型群体的表型谱就会出现。具有相似特征的描述符对应于一种架构类型。因此，使用当前的表型分析工具无法观察到该谱，这些工具仅捕获每个性状根系统中的一个位置。量化表型谱需要开发前所未有的全根描述符和模拟技术，以捕获全根结构的 3D 空间组织的差异。在此过程中，提出了微分几何和成像方法的新组合以及新开发的统计分析。这些实验将通过将温室和田间的不同根系结构类型与已开发的描述符联系起来，让人们了解如何描述和评估温室和田地中不同根系结构类型的相互作用。教育目标是通过使用所开发工具的两门课程来增加计算科学和植物科学领域的研究人员数量。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，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.