Elucidating Gene Networks Regulating Development in Tomato

首席研究员：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）植物从叶子捕获的光中获取大部分能量，而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，必须优化叶子形状以响应光质量的变化。为了了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异，并研究这两个遗传网络整合以确保最佳植物形态的机制。这些目标将通过表征番茄物种之间在光响应和叶子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。统计分析将用于重建调节叶片形态和光响应的相互作用基因网络（遗传网络）。该分析将允许识别发育和发育变异的中央调节器。增加对发展和环境背景下表型多样性基础的了解应该可以更好地操纵作物系统，从而提高农业生产力。最后，将制定一个项目，对加州大学戴维斯分校、加州州立大学萨克拉门托分校和洛斯里奥斯社区学院的未来研究人员和学生进行现代跨学科基因组生物学培训。该项目生成的所有数据、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 序列数据将存入 Genbank (http://www.ncbi.nlm.nih.gov/Genbank/)。所有微阵列数据将存放在基因表达综合数据库 (GEO) 中 (http://www.ncbi.nlm.nih.gov/geo/)。 此外，社区特定数据将通过 SOLGENES 网站 (http://www.sgn.cornell.edu/) 以及将要开发的项目特定网站提供。

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.