Proteogenomics to characterize novel non-coding and extragenic translation

 描述（由申请人提供）：在过去的十年中，已经发现了大量的新转录本，其中许多来自以前被认为构成“垃圾”DNA的区域。在发育和疾病过程中对这些RNA种类的表征导致了基因表达生物学中的一个新兴领域。在这个提议中，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理证明。我们使用新的算法和工具，开始，以小鼠大脑为模型系统，在不同的发育条件下，识别和定义来自假定的非编码区的新肽。该框架将包括软件工具，允许研究人员从RNA-seq实验中构建定制数据库，从而可以在不依赖注释数据库的情况下搜索翻译产品。我们将进行严格的验证实验和新的非经典翻译事件和选择新蛋白质的探针功能的系统表征。拟议的研究有可能为蛋白质组学提供范式转变，因为研究人员将不再受注释数据库的限制。由于质谱和RNA-seq实验现在都是实用的，并且对于大多数实验室来说不再是成本高昂的，因此所提出的框架将具有普遍用途，并且对于理解疾病和生物学范式中基因组，转录组和蛋白质组之间的关系非常重要。

 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.