TRTech-PGR: A PeptideAtlas for Arabidopsis thaliana and other plant species; harnessing world-wide proteomics data and mining for biological features

植物研究的一个主要限制是准确地识别和定量组织和生物体中的蛋白质。质谱学是一种允许科学家从组织或有机体中识别数千种蛋白质的技术。所有蛋白质的集合统称为“蛋白质组”。该项目将利用世界各地实验室公开可用的蛋白质质谱学研究，生成模式植物拟南芥菜(通常被称为泰尔水芹)中已识别蛋白质的图谱。这样的图谱将使研究人员能够解决关于这种植物蛋白质组的一些重要的生物学问题。一旦为拟南芥制作了第一份蛋白质图谱，研究人员还将为玉米、水稻或大豆等两种作物制作图谱。该项目还将在处理和管理质谱学数据以了解植物蛋白质组的技术方面对年轻科学家进行教育和培训。高质量注释基因组的可用性和基于公共可用质谱学(MS)的丰富的蛋白质组学数据使拟南芥成为绘制其蛋白质组图和改进基因组注释的理想植物。研究小组将把这些信息与其他系统数据结合起来，以解决一系列悬而未决的问题和假设。利用人类多肽图谱的基础设施，由ISB的合作者Pi Deutsch和同事，该项目将基于来自世界各地实验室的成百上千个现有的MS研究，通过ProteomeXchange(http://www.proteomexchange.org/)，)收集，并通过统一的处理管道重新分析，生成第一个拟南芥多肽图谱。所有匹配的MS衍生多肽数据将被投影到预测的初级蛋白质序列上，并链接到光谱、技术和生物元数据。这份多肽图谱及其元数据将用于解决几个生物学问题和假说，例如哪些信使核糖核酸异构体得到蛋白质组学证据的支持，以及是否有证据表明蛋白质内的相互作用或PTM之间的竞争。拟南芥多肽地图集将链接到TAIR(https://www.arabidopsis.org/)和其他网络资源)。完整的数据集将可供公众下载，从而进一步促进科学界的数据挖掘，并扩大该项目的影响。一旦为拟南芥发布了最初的几个构建，并在社区反馈/互动之后，PeptideAtlas的构建将扩展到其他具有社会和/或经济重要性的植物物种，这些植物具有广泛和全面的基于MS的蛋白质组学数据(例如玉米、番茄、水稻、大豆)。这一奖励反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

A major limitation of plant research is the accurate identification and quantification of proteins from tissues and organisms. Mass spectrometry is a technology that allows scientists to identify thousands of proteins from a tissue or organism. Together, the collective set of all proteins is called the "proteome". This project will generate an atlas of identified proteins in the model plant species Arabidopsis thaliana, commonly named "thale cress", using publicly available protein mass spectrometry studies from laboratories around the world. Such an atlas will then allow the researchers to address a number of important biological questions about this plant proteome. Once the first protein atlas has been generated for Arabidopsis, the researchers will also generate an atlas for two crop species, such as maize, rice, or soybean. This project will also educate and train young scientists in techniques for processing and managing mass spectrometry data for understanding the proteome of plants. The availability of a high quality annotated genome and a wealth of publicly available mass-spectrometry (MS) based proteomics data makes Arabidopsis thaliana an ideal plant for mapping its proteome and improving genome annotation. The research team will integrate this information with other systems data to address a range of outstanding questions and hypotheses. Taking advantage of the Human PeptideAtlas proteome infrastructure, by co-PI Deutsch and colleagues at ISB, this project will generate the first Arabidopsis PeptideAtlas based on hundreds of existing MS studies from laboratories around the world, collected through ProteomeXchange (http://www.proteomexchange.org/), and reanalyzed through a uniform processing pipeline. All matched MS-derived peptide data will be projected onto predicted primary protein sequences with links to spectral, technical and biological metadata. This PeptideAtlas and its metadata will serve to address several biological questions and hypotheses, such as which mRNA isoforms are supported by proteomics evidence and is there evidence for intra-protein cross-talk or competition between PTMs. The Arabidopsis PeptideAtlas will be linked to TAIR (https://www.arabidopsis.org/) and other web-based resources. Complete dataset will be publicly available for download, thus further facilitating data mining by the scientific community and amplifying the impact of this project. Once the first few builds are released for Arabidopsis, and following community feedback/interactions, PeptideAtlas building will be extended to other plant species of societal and/or economic importance for which extensive and comprehensive MS-based proteomics data are available (e.g. maize, tomato, rice, soybean).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.