Discovery of Genes and Networks Regulating Tomato Fruit Morphology

PI: Esther van der Knaap（俄亥俄州立大学/OARDC）CoPIs: Brian McSpadden Gardener（俄亥俄州立大学/OARDC）， Carmen catal<e:1>（博伊斯汤普森研究所），Sofia Visa（伍斯特学院）Carri Gerber（俄亥俄州立大学/ATI）， Yuji Kamiya（理化研究所，日本横滨），Kazuki Saito（理化研究所和千叶大学，日本千叶），Simon Gray和John Ramsay（伍斯特学院）西红柿的遗传变异导致了不同的品种，产生圆形，扁平，细长，梨形，鱼雷形甚至各种大小的柿子椒形果实。这种形态的多样性为研究果实的形成及其长成不同形状提供了独特的机会。该项目的主要目标是：1)鉴定和表征控制番茄果实形状和大小的基因；2)发现控制果实形态发生的潜在分子网络。为此，将生成控制番茄形态的基因的转录物、代谢物和激素谱，同时将对新的形状和大小基因进行遗传定位和克隆。此外，番茄果实的形状将描述在数学术语，以帮助标准化和分类不同的水果类型。最后，建立番茄基因表达、激素和代谢物积累与形态之间的分子网络模型。从这个项目产生的更广泛的影响将是对控制植物果实形态发生过程的知识的显著增加。这些信息将为了解植物生长和发育的基本方面提供至关重要的见解。此外，这项研究的结果将为如何改善农产品的形状和大小提供线索，以使种植者、加工商和消费者受益。博士后研究人员和研究生之间在多学科项目上的互动将为生物信息学和统计建模与生物学，生化和分子实验室技能的整合提供极好的机会。这些活动将吸引主要研究机构、农业实验站、社区学院、文理学院和高中的研究人员和教师。本科研究人员将从事与水果形态分析相关的实验室和实地研究，生物信息学技能培训以及番茄分析仪软件应用程序的改进（http://www.oardc.ohio-state.edu/vanderknaap/tomato_analyzer.htm）。这些活动还将扩展到当地社区，让高中生参加将在俄亥俄州立大学举行的讲习班，并在他们的学校进行实验室实验。这些努力的最终目标是为研究和教育提供一种完全综合的方法，以提高对一般的基于植物科学的活动，特别是作物多样性的认识。数据将在SGN网站（http://sgn.cornell.edu/）和Plant MetGenMAP数据库（http://bioinfo.bti.cornell.edu/cgi-bin/MetGenMAP/home.cgi）以及GEO （www.ncbi.nlm.nih.gov/ GEO /）上公开提供。

PI: Esther van der Knaap (The Ohio State University/OARDC)CoPIs: Brian McSpadden Gardener (The Ohio State University/OARDC), Carmen Catalá (Boyce Thompson Institute), and Sofia Visa (The College of Wooster)Collaborators: Carri Gerber (The Ohio State University/ATI), Yuji Kamiya (RIKEN, Yokohama Japan), Kazuki Saito (RIKEN and Chiba University, Chiba Japan), Simon Gray and John Ramsay (The College of Wooster)Genetic variation within tomato resulted in distinct varieties that produce round, flat, elongated, pear, torpedo and even bell pepper-shaped fruit of various sizes. This morphological diversity offers unique opportunities to study the formation of fruits and their growth into different shapes. The main objectives of this project are i) to identify and characterize genes controlling tomato fruit shape and size, and ii) to discover the underlying molecular networks that control fruit morphogenesis. To do so, transcript, metabolite and hormone profiles will be generated for genes controlling tomato morphology while new shape and size genes will be genetically mapped and cloned. Furthermore, tomato fruit shapes will be described in mathematical terms to aid standardization and classification of the diverse fruit types. Lastly, models of the molecular networks present in tomato connecting gene expression, hormone and metabolite accumulation with morphology will be generated. The broader impacts resulting from this project will be a significant increase in the knowledge of the processes controlling fruit morphogenesis in plants. Such information will offer crucial insights into the fundamental aspects of plant growth and development. In addition, the outcomes of this research will provide clues of how shape and size of produce can be improved to benefit growers, processors and consumers.The interaction among post doctoral researchers and graduate students on the multidisciplinary project will provide excellent opportunities to integrate bioinformatics and statistical modeling with biological, biochemical and molecular laboratory skills. These activities will engage researchers and teachers at major research institutions, agricultural experiment stations, a community college, a liberal arts college and high schools. Undergraduate researchers will be engaged in laboratory and field studies related to fruit morphology analyses, training in bioinformatic skills as well as improvement of the Tomato Analyzer software application (http://www.oardc.ohio-state.edu/vanderknaap/tomato_analyzer.htm). These activities will also extend to the local community by the inclusion of high school students in workshops that will be held at Ohio State and laboratory experiments conducted at their schools. The ultimate goals of these efforts are to provide a fully integrated approach to research and education that will increase the appreciation of plant science-based activities in general and crop diversity in particular. Data will be publicly available at the SGN site (http://sgn.cornell.edu/) and the Plant MetGenMAP database (http://bioinfo.bti.cornell.edu/cgi-bin/MetGenMAP/home.cgi) as well as in GEO (www.ncbi.nlm.nih.gov/ geo/).