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

派：Jocelyn K.Rose(康奈尔大学)Copi：张军飞(康奈尔大学)‘组学’(下一代核酸测序，蛋白质组学等)的应用研究多细胞生物体的方法产生了大量的数据，这些数据很难用视觉来理解。这项提案概述了一项战略，即创建一种新颖的、高分辨率的图形界面，以可伸缩的格式显示“组学”数据，这将允许在四个维度(随时间变化的三个维度)中轻松地可视化和询问。在这个项目中，番茄果实发育将被作为一个模型系统进行研究，以生成工具来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平台来在空间和时间上研究水果发育和代谢的调控和结构路径。这个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体(植物、动物等)。它的结构可以接受CT扫描。该项目的具体目标是(1)在微米和/或亚微米的分辨率水平上生成基于CT的番茄果实发育和成熟的数字化轮廓；(2)开发同一发育梯度上番茄果皮中五种主要细胞/组织类型的激光捕获显微切割RNA-Seq图谱；(3)创建一个生物信息学/分析管道来整合来自目标1和2的数据集。该项目将在现代生物和生物信息学方法方面培训两名博士后研究人员。如果成功，成像和核糖核酸序列数据将与现有的蛋白质组和代谢组数据相结合，并作为番茄表达图集公开提供，该图集将通过SOL基因组网络网站(http://solgenomics.net).)访问将在康奈尔大学举行的植物基因组学和系统生物学年度讲习班上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.