Development of a Gene-Based Ecophysiology Model

首席研究员：James W. Jones, Kenneth J. Boote, Melanie J. Correll（佛罗里达大学），Arthur Berg, Rongling Wu（宾夕法尼亚州立大学），Juan Osorno（北达科他州立大学）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），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，利用分子水平的知识来模拟生化途径、细胞、器官和胚胎；自上而下的方法，利用生态生理-作物模拟模型，利用环境和生理知识来预测特定品种的表型。该项目的目的是产生一个基于基因的生态生理作物模型，能够使用植物的遗传组成来预测在一系列环境下的表型。这一目标将通过对菜豆（Phaseolus vulgaris）重组自交系（RI）家族的遗传分析来实现。这个家族是由父母之间的杂交产生的，具有不同的生理和形态特征，以及DNA序列。该家族包括200个品系，每个品系都包含亲本基因的独特组合，将使用最新的基因分型技术来确定。将在五种不同环境下测量水稻系的生长发育表型。这些品系的基因组成及其表型将通过功能作图进行分析，以识别、定位和量化控制在生长和发育过程中塑造表型的动态性状的基因的影响。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各种环境下的动态日常行为和最终产量。这个项目是按照美国国家科学基金会资助的iPlant合作项目的精神制定的，该项目旨在促进使用“计算思维”来解决生物学问题。该项目的预期结果是一个基于基因的模型，可以在植物生物学中广泛应用，包括遗传学，功能基因组学，生态学和植物育种。模型的模块化特性将使它能够与自底向上的建模方法相互连接。此外，该项目将通过为本科生和高中教师提供暑期实习机会，以及通过两个实践研讨会，为本科生、研究生和研究生提供教育和培训平台，这些研讨会将涉及作物建模和基因分型技术方面的培训。本项目产生的所有数据都可以通过项目网站（待定）和包括GenBank和Phaseolus Genomics Resource （http://phaseolus.genomics.purdue.edu/）在内的长期存储库访问。种质资源将通过佛罗里达大学、波多黎各大学和CIAT提供。软件、统计和分析工具可以通过项目网站访问，最终通过iPlant协作网站（http://www.iplantcollaborative.org/）访问。

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/).