Elucidating Gene Networks Regulating Development in Tomato

阐明调控番茄发育的基因网络

• 批准号: 0820854
• 负责人: Neelima Sinha
• 金额: $ 446.38万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-12-01 至 2014-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0820854&HistoricalAwards=false
• 关键词: Elucidating; Gene; Networks; Regulating; Development

PI: Neelima R. Sinha (University of California, Davis)CoPI: Julin Maloof (University of California, Davis)CoPI: Jie Peng (University of California, Davis)Plants acquire the bulk of their energy from light capture by leaves, and leaf shape has direct consequences on the efficiency of light capture and photosynthetic carbon fixation. As a result, leaf shape must be optimized in response to variation in light quality. To understand the processes controlling these fundamental processes, genetic networks regulating both environmental response and morphological form must be integrated. This project uses a genomics approach to understand natural variation in leaf morphology and light response, and to investigate the mechanism by which these two genetic networks are integrated to ensure optimal plant form. These goals will be accomplished by characterizing the differences between tomato species varying in both light response and leaf complexity. Characterization of these differences will be made using genomic technologies to find differences in DNA sequence and gene expression. Statistical analyses will be used to reconstruct the web of interacting genes (genetic networks) that regulate leaf morphology and light responses. This analysis will allow identification of central regulators of development and developmental variation. Increased knowledge of the basis of phenotypic diversity in the developmental and environmental context should allow better manipulation of crop systems for improved agricultural productivity. Finally, a program will be developed to train future researchers and students from under-represented groups from UC Davis, Cal State University Sacramento, and Los Rios Community College in modern cross-disciplinary genomic biology.All data, gene chip data, BIN maps, QTL analysis and networks generated by this project will be made available to the public as soon as the data has passed quality control. All Solexa sequence data will be deposited in Genbank (http://www.ncbi.nlm.nih.gov/Genbank/). All microarray data will be deposited in the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). In addition, community specific data will be made available via the SOLGENES website (http://www.sgn.cornell.edu/) and a project-specific web site that will be developed.

PI：Neelima R. Sinha（加州大学戴维斯分校）CoPI：Julin Maloof（加州大学戴维斯分校）CoPI：Jie Peng（加州大学戴维斯分校）植物从叶子的光捕获中获得大部分能量，叶子的形状对光捕获和光合作用固碳的效率有直接影响。因此，必须优化叶片形状以响应光质量的变化。为了理解控制这些基本过程的过程，必须整合调节环境反应和形态形式的遗传网络。该项目使用基因组学方法来了解叶片形态和光响应的自然变化，并研究这两个遗传网络整合的机制，以确保最佳的植物形态。这些目标将通过表征番茄物种在光响应和叶复杂性方面的差异来实现。这些差异的表征将使用基因组技术来发现DNA序列和基因表达的差异。统计分析将被用来重建网络的相互作用的基因（遗传网络），调节叶形态和光响应。该分析将允许鉴定发育和发育变异的中央调节器。在发展和环境背景下增加对表型多样性基础的了解，应能更好地操纵作物系统，以提高农业生产力。最后，将开发一个计划，以培养未来的研究人员和学生从加州大学戴维斯分校，加州州立大学萨克拉门托，和洛斯里奥斯社区学院的代表性不足的群体在现代跨学科的基因组生物学。所有的数据，基因芯片数据，BIN地图，QTL分析和网络产生的这个项目将提供给公众，一旦数据通过质量控制。所有Solexa序列数据将保存在Genbank（http：//www.ncbi.nlm.nih.gov/Genbank/）中。所有微阵列数据将保存在Gene Expression Omnibus（GEO）数据库（http：//www.ncbi.nlm.nih.gov/geo/）中。 此外，将通过SOLGENES网站（http：//www.sgn.cornell.edu/）和将开发的项目专用网站提供社区专用数据。