EAGER: Computed Tomography (CT) as a Novel Platform for Presenting Four-Dimensional (4D) 'omics' Expression Data: Tomato Fruit Development as Test Case

“组学”（新一代核酸测序、蛋白质组学等）方法在多细胞生物研究中的应用产生了大量难以直观理解的数据。该提案概述了一种策略，即创建一种新颖的、高分辨率的图形界面，以可扩展的格式显示“组学”数据，这将允许在四个维度（通过时间的三个维度）上轻松可视化和查询。在这个项目中，番茄果实发育将作为一个模型系统进行研究，以生成工具，将数据集投影到水果的数字化计算机断层扫描（CT）合成图像上，从而创建一个4D平台，在空间和时间上研究果实发育和代谢背后的调控和结构途径。该平台的一个重要用途是，它很容易适应任何复杂的多细胞生物（植物，动物等），其结构适合CT扫描。具体目标是：(1)在微米和/或亚微米分辨率水平上生成基于数字化CT的番茄果实发育和成熟图谱；(2)在相同的发育梯度上开发激光捕获番茄果皮中五种主要细胞/组织类型的微解剖RNA-Seq图谱；(3)创建生物信息学/分析管道，整合目标1和目标2的数据集。本项目将培养两名从事现代生物学和生物信息学研究的博士后研究员。如果成功，成像和RNA-Seq数据将与现有的蛋白质组学和代谢组学数据相结合，并作为番茄表达图谱公开提供，该图谱将通过Sol Genomics Network网站（http://solgenomics.net）访问。在康奈尔大学举行的植物基因组学和系统生物学年度研讨会上，将提供使用该项目开发的生物信息学工具的培训机会。

PI: Jocelyn K. Rose (Cornell University)CoPI: Zhangjun Fei (Cornell University)The application of 'omics' (next generation nucleic acid sequencing, proteomics etc.) approaches in the study of multicellular organisms have generated an enormous amount of data that is difficult to comprehend visually. This proposal outlines a strategy to create a novel, high resolution graphical interface to display 'omics' data in a scalable format that will allow easy visualization and interrogation in four dimensions (three dimensions through time). In this project tomato fruit development will be studied as a model system to generate tools to project data sets onto a digitized computed tomography (CT) composite image of the fruit and, thereby, create a 4D platform to spatially and temporally examine the regulatory and structural pathways underlying fruit development and metabolism. An important utility of this platform is that it is readily adaptable to any complex multicellular organisms (plants, animals etc.) whose structure is amenable to CT scans. The specific aims are to (1) generate a digitized CT based profile of tomato fruit development and ripening at the micron and/or submicron level of resolution, (2) develop laser capture microdissection RNA-Seq profiles of the five principal cell/tissue types in tomato fruit pericarp across the same developmental gradient and, (3) create a bioinformatics/analytical pipeline to integrate the data sets derived from aims 1 and 2.The project will train two postdoctoral research associates in modern biological and bioinformatics approaches. If successful, the imaging and RNA-Seq data will be combined with existing proteomic and metabolomic data and made publicly available as a Tomato Expression Atlas, which will be accessible through the Sol Genomics Network website (http://solgenomics.net). Opportunities for training in the use of the bioinformatics tools developed by the project will be made available at the annual Workshop in Plant Genomics and Systems Biology held at Cornell University.