Genomic Approaches to Identify Genes for Root System Architecture Traits

PI：Philip N.本杰明（杜克大学）CoPI：约翰L。Harer（杜克大学）合作者：赫伯特Edelsbrunner（杜克大学）该项目的长期目标是使用全基因组方法来识别负责根系结构性状的基因。在一个概念验证项目中，由Phenotype Screening Corporation开发的植物根系可视化和表征系统（PRINTS）已被用于获取不同时间点的水稻根系图像。该系统将实现图像采集生长的根系加上最佳的植物生长条件。一个具有广泛定量专业知识的科学家团队将开发用于根系结构比较分析的数学描述符。这些描述符将沿着与目前可用的参数，以确定不同基因型的水稻根构型性状。养分有效性对这些根构型参数的影响将被确定为选定的基因型。这个短期工具开发项目将为数量性状基因座（QTL）分析奠定基础，这对作物育种计划有很大的影响。 为了利用现有的基因组资源的力量，以确定参与根功能的基因，需要新的工具来成像和分析根系结构。 即将开发的拟议工具可以为利用植物基因组资源进行农业改良做出深远的贡献。由于拟议研究的性质本质上是跨学科的，因此各级（本科生，研究生，博士后）的培训将把定量方法与实验生物学的应用相结合。将举办一次关于有形网络的专题讨论会和讲习班，以传播该项目的研究结果。

PI: Philip N. Benfey (Duke University)CoPI: John L. Harer (Duke University)Collaborator: Herbert Edelsbrunner (Duke University)The long-term goal of this project is to use genome-wide approaches to identify the genes responsible for root system architecture traits. In a proof-of-concept project, the Plant Root Visualization and Characterization System (PRVCS) developed by Phenotype Screening Corporation, has been used to acquire images of rice roots at different time points. This system will be implemented for image acquisition of growing roots coupled with optimal plant growth conditions. A team of scientists with broad quantitative expertise will develop mathematical descriptors for comparative analysis of root system architecture. These descriptors will be used along with currently available parameters to identify root architecture traits that differ among genotypes of rice. The effect of nutrient availability on these root architecture parameters will be determined for selected genotypes. This short-term tool development project will lay the groundwork for quantitative trait locus (QTL) analysis that should have high impact on crop breeding programs. To leverage the power of the available genomic resources to identify genes involved in root function requires new tools to image and analyze root system architecture. The proposed tools that will be developed could make far-reaching contributions to the utilization of the resources of plant genomics toward agricultural improvement. Because the nature of the proposed research is inherently interdisciplinary, training at various levels (undergraduate, graduate, post-doctoral) will integrate quantitative approaches with applications to experimental biology. A symposium and workshop on physical networks will be held to disseminate the findings of the project.