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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；

基本信息

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

项目摘要

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.

植物研究的一个主要限制是准确识别和定量组织和生物体中的蛋白质。质谱是一种技术，使科学家能够从组织或生物体中识别数千种蛋白质。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提供的蛋白质质谱研究，生成模式植物物种拟南芥（通常称为“塔勒水芹”）中已鉴定蛋白质的图谱。这样的图谱将使研究人员能够解决一些关于这种植物蛋白质组的重要生物学问题。一旦为拟南芥生成了第一个蛋白质图谱，研究人员还将为两种作物物种生成一个图谱，如玉米，水稻或大豆。该项目还将教育和培训青年科学家掌握处理和管理质谱数据的技术，以了解植物蛋白质组。高质量的注释基因组和丰富的公开可用的质谱（MS）为基础的蛋白质组学数据的可用性，使拟南芥蛋白质组作图和改进基因组注释的理想植物。研究团队将把这些信息与其他系统数据整合起来，以解决一系列悬而未决的问题和假设。利用人类PeptideAtlas蛋白质组基础设施，由co-PI多伊奇和ISB的同事，该项目将基于来自世界各地实验室的数百个现有MS研究产生第一个拟南芥PeptideAtlas，通过ProteomeXchange（http：//www.proteomexchange.org/）收集，并通过统一的处理管道重新分析。所有匹配的MS衍生肽数据将被投影到预测的一级蛋白质序列上，并与光谱、技术和生物学元数据相关联。该PeptideAtlas及其元数据将用于解决几个生物学问题和假设，例如蛋白质组学证据支持哪些mRNA亚型，以及是否存在蛋白质内串扰或PTM之间竞争的证据。拟南芥肽图谱将链接到TAIR（https：//www.arabidopsis.org/）和其他基于网络的资源。完整的数据集将公开下载，从而进一步促进科学界的数据挖掘，扩大该项目的影响。一旦拟南芥的前几个构建版本发布，并遵循社区反馈/互动，PeptideAtlas构建将扩展到具有社会和/或经济重要性的其他植物物种，这些植物物种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）该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的评估被认为值得支持。影响审查标准。