NSF NPGI Postdoctoral Fellowship in Biology FY 2014

该行动资助了2014财年NSF国家植物基因组计划生物学博士后研究奖学金。该研究金支持研究员在东道实验室的研究和培训计划，研究员还提出了扩大生物学参与的计划。该奖学金的研究和培训计划的标题为R. J.科迪Markelz是“开发一个系统级的资源分配和分配模型，以预测多基因型和环境中的生长”。该奖学金的主办机构是加州大学戴维斯分校，赞助科学家是Julin Maloof和丹尼尔Kliebenstein博士。如果成功，该项目将通过将其与定量遗传学和代谢网络建模相结合，大大推进经典植物生长建模。训练目标包括统计遗传学、数学建模、代谢网络重建和系统生物学。更广泛的影响包括通过小型的、动手的QTL作图项目培训本科生和高中生。此外，还将为中学教师开发一个关于避荫的模块，以纳入植物iView推广计划。本单元将包括一个详细的课程计划，主要的生物学概念和国家教育标准，并在课堂上讲授课程的实用指南。研究将采取系统生物学方法来调查基因型之间的相互作用，对阴影的反应，以及对营养物质的反应。该项目将在芜菁的遗传作图群体中进行，该群体对遮荫和养分供应的反应是分离的。其目标是：（1）确定遮荫诱导的养分利用效率变化是否受遗传控制;（2）将组织水平的生理性状与潜在的代谢网络联系起来;（3）将数量性状基因座（QTL）和代谢网络整合到整个植物资源分配的数学模型中。然后，该模型将被用来预测基因型特定的生长和产量对遮荫和养分供应的反应。该模型将根据本科研究人员收集的数据集进行验证。整个工厂系统级数据集将通过一个关系数据库提供，该数据库将链接到一个开放访问的数据分析工作流程，利用iPlant Collaborative的免费云计算资源。

This action funds an NSF National Plant Genome Initiative Postdoctoral Research Fellowship in Biology for FY 2014. The fellowship supports a research and training plan in a host laboratory for the Fellow who also presents a plan to broaden participation in biology. The title of the research and training plan for this fellowship to R.J. Cody Markelz is "Develop a systems level model of resource allocation and partitioning in Brassica rapa to predict growth across multiple genotypes and environments". The host institution for the fellowship is the University of California, Davis and the sponsoring scientists are Drs. Julin Maloof and Daniel Kliebenstein.If successful, this project will significantly advance classical plant growth modeling by connecting it to quantitative genetics and metabolic network modeling. Training objectives include statistical genetics, mathematical modeling, metabolic network reconstruction, and systems biology. Broader impacts include training undergraduates and high school students through small, hands-on QTL mapping projects. Additionally, a module for middle school teachers about shade avoidance will be developed for inclusion in the Plants iView outreach program. This module will include a detailed lesson plan, the key biological concepts and national education standards addressed, and a practical guide for teaching the lessons in the classroom.The research will take a systems biology approach to investigate the interactions among genotype, response to shade, and response to nutrient availability. This project will be conducted in a genetic mapping population of Brassica rapa, which is segregating for the response to shade and nutrient availability. The objectives are to: (1) determine if shade-induced changes in nutrient use efficiency are genetically controlled; (2) link tissue-level physiological traits with the underlying metabolic networks; (3) integrate quantitative trait loci (QTL) and metabolic networks into a mathematical model of whole plant resource partitioning. The model will then be used to predict genotype-specific growth and yield responses to shade and nutrient availability. The model will be validated against datasets collected by undergraduate researchers. The whole-plant systems level dataset will be made available through a relational database that will be linked to an open-access data analysis workflow utilizing the free cloud computing resources at iPlant Collaborative.