NSF NPGI Postdoctoral Fellowship in Biology FY 2014

这一行动为NSF国家植物基因组计划2014财年生物学博士后研究奖学金提供了资金。该奖学金支持在东道主实验室为该研究员制定的研究和培训计划，该研究员还提出了扩大生物学参与度的计划。R.J.Cody Markelz的这项研究和培训计划的标题是“在油菜上开发一个系统级的资源分配和分配模型，以预测跨多种基因型和环境的生长”。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博士和Daniel Kliebenstein博士。如果该项目成功，该项目将通过将其与数量遗传学和代谢网络建模联系起来，极大地推动经典植物生长模型的发展。培训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遮荫避免的模块，以包括在Plants iView推广计划中。这一单元将包括详细的课程计划，所涉及的关键生物学概念和国家教育标准，以及课堂教学的实践指南。研究将采用系统生物学的方法来调查基因、对遮荫的反应和对养分供应的反应之间的相互作用。这个项目将在白菜的遗传图谱群体中进行，该群体是为了对遮荫和养分供应的反应而分离的。其目的是：(1)确定遮荫引起的养分利用效率的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特定基因型的生长和产量对遮荫和养分供应的反应。该模型将根据本科生研究人员收集的数据集进行验证。整个工厂系统级的数据集将通过一个关系数据库提供，该数据库将利用iFactory Collaborative的免费云计算资源链接到开放访问的数据分析工作流程。

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.