Generating and Managing Large Scale Proteogenomic Data for ENCODE Cell Lines

生成和管理 ENCODE 细胞系的大规模蛋白质组数据

• 批准号: 7855660
• 负责人: XIAN CHEN
• 金额: $ 80万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-26 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7855660
• 关键词: Affect; Alternative Splicing; Biochemical; Biological; Biological Assay; Biological Process; California; Cell Line; Code; Communities; Computer software; DNA; DNA Sequence; Data; Data Coordinating Center; Data Element; Data Set; Databases; Elements; Exons; Faculty; Functional RNA; Genes; Genetic Transcription; Genome; Goals; Grant; Health; Histocompatibility Testing; Human; Human Cell Line; Human Genome; Immunology; Indium; Instruction; Knowledge; Language; Life; Management Information Systems; Maps; Mass Spectrum Analysis; Methods; Modeling; Molecular and Cellular Biology; National Human Genome Research Institute; Nature; Open Reading Frames; Peptides; Phase; Pilot Projects; Policies; Process; Protein Splicing; Proteins; Proteome; Proteomics; Publishing; RNA; RNA Splicing; Research Personnel; Site; Structure; Technology; Transcript; Translating; Universities; Variant; Work; base; experience; genome sequencing; improved; insight; public health relevance; repository; scale up; software development

DESCRIPTION (provided by applicant): The first human genome sequence was published in 2001, yet as of now, eight years later, major questions remain, such as how many genes are encoded by the genome, and of those genes, how many functional products are encoded due to phenomena like alternative splicing. The Encyclopedia of DNA Elements (ENCODE) project has been coordinated by National Human Genome Research Institute (NHGRI) to answer these questions by comprehensively classifying functional elements on the human genome. The pilot phase of the project studied 1% of the genome in detail, revealing extensive transcription well beyond that predicted by classical gene models. The biological function of a significant portion of the discovered transcripts is unclear. The ENCODE project is now scaling up to examine the whole human genome. It is likely that results will echo the pilot project, revealing extensive transcription, a significant fraction of which has unexplained function. Proteomic technologies can be applied, in a process called proteogenomic mapping, to determine which of the myriad transcripts encode proteins. This approach has been used to reveal new genes, new alternative splice variants, new start sites, and upstream open reading frames (ORFs). While substantive progress has been made in developing proteogenomic mapping technologies, a significant hurdle in using proteogenomics to assist with the ENCODE project is the lack of proteomic data sets that are coordinated with the ENCODE transcription mapping efforts. Here we propose to generate large-scale proteomic data sets directly from the same tier I ENCODE cell lines studied by the transcription efforts, coordinating the results with the transcription mapping efforts to determine which of the pervasive transcripts are translated. Our specific aims are to: 1) produce large scale proteomic data sets on ENCODE cell lines using the most advanced mass spectrometry methods, 2) use our database technologies to store, manage, and make accessible to the community all results of the project, and 3) use our software pipeline to map the results to the latest human genome drafts, producing a UCSC (University of California Santa Cruz) genome browser track with the results. We believe the result will be a significant advancement in knowledge about our genomes and the functional products they encode. PUBLIC HEALTH RELEVANCE: The human genome is the blueprint for human life and human health, but we do not yet understand its language - the language of genes. The ENCODE project is deciphering that language systematically, and the goal of this proposal is to accelerate that effort by revealing which parts of the blueprint contain instructions to build proteins.

描述（由申请人提供）：第一个人类基因组序列于2001年发表，但截至目前，八年后，主要问题仍然存在，例如基因组编码多少基因，以及这些基因中，由于选择性剪接等现象，编码了多少功能产物。DNA元件百科全书（ENCODE）项目由国家人类基因组研究所（NHGRI）协调，通过对人类基因组上的功能元件进行全面分类来回答这些问题。该项目的试验阶段详细研究了1%的基因组，揭示了广泛的转录，远远超出了经典基因模型的预测。所发现的转录本中有很大一部分的生物学功能尚不清楚。ENCODE项目目前正在扩大规模，以检查整个人类基因组。结果很可能会呼应试点项目，揭示广泛的转录，其中很大一部分具有无法解释的功能。蛋白质组学技术可以应用于蛋白质基因组作图过程，以确定无数转录本中的哪一种编码蛋白质。这种方法已被用来揭示新的基因，新的选择性剪接变异体，新的起始位点，和上游开放阅读框架（ORF）。虽然在开发蛋白质基因组作图技术方面取得了实质性进展，但利用蛋白质基因组学协助ENCODE项目的一个重大障碍是缺乏与ENCODE转录作图工作相协调的蛋白质组数据集。在这里，我们建议直接从转录工作研究的同一层I ENCODE细胞系生成大规模蛋白质组数据集，将结果与转录映射工作协调，以确定哪些普遍的转录本被翻译。我们的具体目标是：1）使用最先进的质谱方法在ENCODE细胞系上产生大规模蛋白质组数据集，2）使用我们的数据库技术存储、管理并向社区提供项目的所有结果，以及3）使用我们的软件管道将结果映射到最新的人类基因组草图，产生具有结果的UCSC（加州大学圣克鲁斯）基因组浏览器跟踪。我们相信，这一结果将是对我们的基因组及其编码的功能产品的知识的重大进步。 公共卫生相关性：人类基因组是人类生命和人类健康的蓝图，但我们还不理解它的语言--基因的语言。ENCODE项目正在系统地破译这种语言，该提案的目标是通过揭示蓝图的哪些部分包含构建蛋白质的指令来加速这一努力。