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

TRTech-PGR：拟南芥和其他植物物种的肽图谱；

• 批准号: 1922871
• 负责人: Klaas van Wijk
• 金额: $ 141.51万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1922871&HistoricalAwards=false
• 关键词: TRTech; PGR; PeptideAtlas; Arabidopsis; thaliana; TRTech; PGR; PeptideAtlas; Arabidopsis; thaliana

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.

植物研究的主要局限性是对组织和生物体的蛋白质进行准确鉴定和定量。 质谱法是一项允许科学家从组织或生物体中鉴定出数千种蛋白质的技术。一起，所有蛋白质的集体集称为“蛋白质组”。该项目将使用来自世界各地实验室的公开蛋白质质谱研究研究，在模型植物拟南芥中生成鉴定蛋白质的地图集。然后，这样的地图集将使研究人员能够解决有关该植物蛋白质组的许多重要生物学问题。一旦为拟南芥生成了第一个蛋白质地图集，研究人员还将为两种农作物，例如玉米，大米或大豆生成一个地图集。该项目还将教育和培训年轻科学家的技术，以处理和管理质谱数据，以了解植物的蛋白质组。高质量注释的基因组的可用性以及基于公开的质谱法（MS）的蛋白质组学数据使拟南芥成为绘制其蛋白质组和改善基因组注释的理想植物。研究团队将将这些信息与其他系统数据集成在一起，以解决一系列杰出的问题和假设。 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.所有匹配的MS衍生肽数据都将投影到与光谱，技术和生物元数据的链接的预测主要蛋白质序列上。该肽座及其元数据将用于解决几种生物学问题和假设，例如，蛋白质组学证据支持mRNA同工型，并有证据表明蛋白质内交叉呼声或PTMS之间的竞争。 拟南芥peptideatlas将链接到Tair（https://www.arabidopsis.org/）和其他基于Web的资源。完整的数据集将公开下载，从而进一步促进了科学界的数据挖掘，并扩大了该项目的影响。一旦前几个版本发布给拟南芥，并且随着社区的反馈/互动，肽座建筑将扩展到其他社会和/或经济重要性的其他植物，基于MS的蛋白质组学数据可获得广泛而全面的蛋白质组学数据，例如玉米，番茄，番茄，稻米，大豆，大豆的基础奖，并反映了NSF的构建范围。更广泛的影响审查标准。