Development of a Gene-Based Ecophysiology Model

基于基因的生态生理学模型的开发

• 批准号: 0923975
• 负责人: Carlos Vallejos
• 金额: $ 238.6万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-15 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0923975&HistoricalAwards=false
• 关键词: Development; Gene; Based; Ecophysiology; Model

PI: C. Eduardo Vallejos (University of Florida)CoPIs: James W. Jones, Kenneth J. Boote, and Melanie J. Correll (University of Florida), Arthur Berg and Rongling Wu (Pennsylvania State University), and Juan Osorno (North Dakota State University)Key Collaborators: William Farmerie and Fahong Yu (University of Florida), Steve Beebe and Idupulapati Rao [International Center for Tropical Agriculture (CIAT), Colombia], and James S. Beaver and Elvin Roman (University of Puerto Rico)Two systems biology approaches have been implemented to solve the genotype to phenotype problem: the bottom-up approach, which uses molecular level knowledge to simulate biochemical pathways, cells, organs, and embryos, and top-down approaches embodied by ecophysiology-crop simulation models which use environment and physiological knowledge to predict the phenotype of specific cultivars. The objective of this project is to generate a gene-based ecophysiology-crop model capable of using the genetic makeup of a plant to predict the phenotype under a range of environments. This goal will be accomplished via genetic analysis of a recombinant inbred (RI) family of Phaseolus vulgaris. This family was generated from a cross between parents with contrasting physiological and morphological characteristic, as well as DNA sequences. The family comprises 200 lines, each containing a unique combination of the parental versions of the genes, which will be determined using the latest genotyping technology. The growth and developmental phenotypes of the RI lines will be measured under five different environments. The genetic makeup of these lines along with their phenotypes will be analyzed by functional mapping to identify, locate, and quantify the effect of genes that control the dynamic traits that shape the phenotype throughout growth and development. Finally, genotypic and phenotypic data will be used to develop computer programs that can effectively predict the dynamic daily behavior and final yield of crops under a range of environments. This project is framed in the spirit of the NSF-funded iPlant Collaborative project which promotes the use of "computational thinking" to address biological questions. The expected outcome of this project is a gene-based model which can have a wide range of applications in plant biology including genetics, functional genomics, ecology, and plant breeding. The modular nature of the model will make it possible to interconnect with bottom-up modeling approaches. In addition, this project will provide a platform for the education and training of students at the undergraduate, graduate and post-graduate levels through summer internships for undergraduate students and high school teachers as well as through two hands-on workshops that will deal with training in both crop modeling and genotyping technologies. All data generated in this project can be accessed through project websites (to be determined) and through long-term repositories that include GenBank and the Phaseolus Genomics Resource (http://phaseolus.genomics.purdue.edu/). Germplasm will be made available through the University of Florida, the University of Puerto Rico and CIAT. Software and statistical and analytical tools can be accessed through the project websites and eventually through the iPlant Collaborative (http://www.iplantcollaborative.org/).

PI：C。Eduardo Vallejos（佛罗里达大学）CoPIs：James W. Jones、Kenneth J. Boote和Melanie J. Correll（佛罗里达大学）、亚瑟贝格和Rongling Wu（宾夕法尼亚州立大学）以及Juan Osorno（北达科他州州立大学）主要合作者：William Farmerie和Fahong Yu（佛罗里达大学）、Steve Beebe和Idupulapati Rao（哥伦比亚国际热带农业中心（CIAT））以及James S. Beaver和Elvin Roman（波多黎各大学）已经实施了两种系统生物学方法来解决基因型到表型的问题：自下而上的方法，其使用分子水平的知识来模拟生物化学途径、细胞、器官和胚胎，以及自上而下的方法，其通过生态生理学作物模拟模型体现，其使用环境和生理知识来预测特定品种的表型。该项目的目标是建立一个基于基因的生态生理学作物模型，该模型能够利用植物的遗传组成来预测一系列环境下的表型。这一目标将通过对菜豆的重组近交（RI）家族的遗传分析来实现。该家系是由具有不同生理和形态特征以及DNA序列的亲本杂交产生的。该家族由200个品系组成，每个品系都含有父母版本基因的独特组合，这将使用最新的基因分型技术来确定。RI系的生长和发育表型将在五种不同的环境下测量。这些品系的遗传组成沿着其表型将通过功能作图进行分析，以鉴定、定位和量化控制动态性状的基因的作用，所述动态性状在整个生长和发育过程中塑造表型。 最后，基因型和表型数据将用于开发计算机程序，可以有效地预测作物在一系列环境下的动态日常行为和最终产量。该项目是在NSF资助的iPlant协作项目的精神框架内，该项目促进使用“计算思维”来解决生物学问题。 该项目的预期成果是一个基于基因的模型，该模型可以在植物生物学中有广泛的应用，包括遗传学，功能基因组学，生态学和植物育种。该模型的模块化性质将使其能够与自下而上的建模方法互连。此外，该项目还将为本科生、研究生和研究生提供一个教育和培训平台，为本科生和高中教师提供暑期实习机会，并举办两个实践讲习班，培训作物建模和基因分型技术。 该项目产生的所有数据均可通过项目网站（待定）和包括基因库和菜豆基因组学资源（http：//phaseolus.genomics.purdue.edu/）在内的长期储存库获取。 种质将通过佛罗里达大学、波多黎各大学和美洲热带中心提供。 可通过项目网站并最终通过iPlant Collaborative（http：//www.iplantcollaborative.org/）获取软件以及统计和分析工具。