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Proteogenomics to characterize novel non-coding and extragenic translation

蛋白质基因组学表征新型非编码和外基因翻译

基本信息

批准号：
9247781
负责人：
Gabriel Kreiman
金额：
$ 54.66万
依托单位：
BOSTON CHILDREN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-01 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9247781
关键词：
Algorithmic Software Amino Acid Sequence Bioinformatics Biological Biological Models Biological Process Biology Brain Code Custom Data Data Set Databases Development Disease Eukaryota Event Gene Expression Genes Genetic Transcription Genome In Situ Hybridization Joints Junk DNA Kinetics Label Mammalian Cell Maps Mass Spectrum Analysis Measures Methods Modeling Mus Neuronal Plasticity Neurons Open Reading Frames Pattern Peptides Proteins Proteome Proteomics Pseudogenes RNA RNA Splicing Reading Frames Regulation Research Research Personnel Reverse Transcriptase Polymerase Chain Reaction Role Sampling Software Tools Stress Synaptic plasticity Testing Time Transcript Translating Translations Untranslated RNA Validation Western Blotting Work biological systems computer framework computer infrastructure cost experimental study genome-wide in vivo interest novel open source proteogenomics public health relevance synthetic peptide tool transcriptome transcriptome sequencing transcriptomics

项目摘要

DESCRIPTION (provided by applicant): During the last decade, a plethora of novel transcripts has been uncovered, many of which come from regions formerly considered to constitute "junk" DNA. The characterization of those RNA species during development and disease has led to a burgeoning field within the biology of gene expression. In this proposal, we take initial steps to define a similar path with the proteome. We develop the computational infrastructure and provide a proof-of-principle for the existence of novel peptides derived from regions of the genome that are traditionally considered to be non-coding. We use the new algorithms and tools to begin to identify and define novel peptides derived from presumed non-coding regions across different developmental conditions using the mouse brain as a model system. The framework will include software tools that will allow researchers to build custom-databases from RNA-seq experiments, making it possible to search for translation products without relying on annotation databases. We will carry out rigorous validation experiments and systematic characterization of the novel non-canonical translation events and probe function of select novel proteins. The proposed research has the potential to provide a paradigm-shift for proteomics as researchers will no longer be limited by annotated databases. Since both mass spectrometry and RNA-seq experiments are now practical and no longer cost-prohibitive for most labs, the proposed framework will be of general use and it will be important to understanding the relationship between the genome, transcriptome and the proteome across diseases and biological paradigms.

描述(申请人提供)：在过去的十年中，发现了过多的新的转录，其中许多来自以前被认为是“垃圾”DNA的地区。这些RNA物种在发育和疾病期间的特征已经导致了基因表达生物学中的一个新兴领域。在这个提案中，我们采取初步步骤来定义与蛋白质组相似的路径。我们开发了计算基础设施，并为从传统上被认为是非编码的基因组区域衍生的新肽的存在提供了原则证明。我们使用新的算法和工具，以小鼠大脑为模型系统，开始识别和定义来自不同发育条件的假定非编码区的新肽。该框架将包括软件工具，允许研究人员根据rna-seq实验建立定制数据库，从而可以在不依赖注释数据库的情况下搜索翻译产品。我们将对新的非规范翻译事件和精选新蛋白的探针功能进行严格的验证实验和系统的表征。这项拟议的研究有可能为蛋白质组学提供范式转换，因为研究人员将不再受到带注释的数据库的限制。由于质谱学和rna-seq实验现在都是实用的，对大多数实验室来说不再是成本高昂的，拟议的框架将得到普遍使用，对于理解跨疾病和生物范式的基因组、转录组和蛋白质组之间的关系将是重要的。