Genomic Approaches to Identify Genes for Root System Architecture Traits

识别根系统结构特征基因的基因组方法

• 批准号: 0606873
• 负责人: Philip Benfey
• 金额: $ 74.99万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0606873&HistoricalAwards=false
• 关键词: Genomic; Approaches; Identify; Genes; Root

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.

PI: Philip N. Benfey（杜克大学）CoPI: John L. Harer（杜克大学）合作者：Herbert Edelsbrunner（杜克大学）该项目的长期目标是使用全基因组方法来确定负责根系结构特征的基因。在一个概念验证项目中，表型筛选公司开发的植物根系可视化和表征系统（PRVCS）已被用于获取水稻根系在不同时间点的图像。该系统将用于在最佳植物生长条件下对生长根系进行图像采集。一组具有广泛定量专业知识的科学家将开发用于根系结构比较分析的数学描述符。这些描述符将与目前可用的参数一起用于鉴定不同基因型水稻的根结构性状。对于选定的基因型，将确定养分有效性对这些根构型参数的影响。这个短期工具开发项目将为数量性状位点（QTL）分析奠定基础，这将对作物育种计划产生重大影响。为了利用现有基因组资源的力量来识别参与根功能的基因，需要新的工具来成像和分析根系结构。所提出的工具将会对利用植物基因组学资源进行农业改良做出深远的贡献。由于所提议的研究本质上是跨学科的，不同层次（本科、研究生、博士后）的培训将把定量方法与实验生物学的应用结合起来。将举行一次关于物理网络的专题讨论会和讲习班，以传播该项目的研究结果。