Elucidating Gene Networks Regulating Development in Tomato

PI：Nelima 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)植物从叶片获取大部分能量，而叶片形状直接影响光捕获和光合作用固碳的效率。因此，叶片形状必须根据光质的变化进行优化。为了了解控制这些基本过程的过程，必须整合调控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品种之间在光响应和叶片复杂性上的差异来实现。将使用基因组技术对这些差异进行表征，以找出DNA序列和基因表达的差异。统计分析将被用来重建调节叶片形态和光反应的相互作用的基因网络(遗传网络)。这一分析将有助于确定发育和发育变异的中央调控因素。增加对发展和环境背景下表型多样性基础的了解，应该能够更好地操纵作物系统，以提高农业生产力。最后，将开发一个项目，以培训来自加州大学戴维斯分校、加州州立大学萨克拉门托分校和洛杉矶社区学院的未来研究人员和学生，了解现代跨学科基因组生物学。该项目产生的所有数据、基因芯片数据、BIN图谱、QTL分析和网络将在数据通过质量控制后立即向公众开放。所有SolexA序列数据将保存在基因库(http://www.ncbi.nlm.nih.gov/Genbank/).所有微阵列数据将存放在基因表达总览数据库(http://www.ncbi.nlm.nih.gov/geo/).)中此外，社区具体数据将通过SOLGENES网站(http://www.sgn.cornell.edu/))和将开发的具体项目网站提供。

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.