Determining the sequence and structure specificities of RNA-binding proteins

确定 RNA 结合蛋白的序列和结构特异性

• 批准号: 7852462
• 负责人: Timothy Hughes
• 金额: $ 29.86万
• 依托单位: UNIVERSITY OF TORONTO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-26 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7852462
• 关键词: 3' Untranslated Regions; Affinity; Alternative Splicing; Amino Acid Sequence; Binding; Binding Sites; Complex; Consensus; Data; Databases; Development; Disease; Gene Expression Regulation; Genes; Genomics; Health; Human; Human Genome; In Vitro; Individual; KH Domain; Knowledge; Literature; Maps; Measures; Methodology; Methods; Modeling; Output; Post-Transcriptional RNA Processing; Prevalence; Protein Analysis; Protein Binding; Proteins; RNA; RNA Binding; RNA Recognition Motif; RNA-Binding Proteins; RNA-Protein Interaction; Reaction; Regulation; Relative (related person); Small RNA; Specificity; Structure; Transcript; Translations; Work; base; design; in vivo; indexing; next generation; preference; public health relevance

DESCRIPTION (provided by applicant): The human genome encodes hundreds of proteins that contain RNA-binding domains, most of which are poorly-characterized, and genomic analyses indicate widespread use of post- transcriptional gene regulation: there is high sequence conservation in 5' and 3' untranslated regions (UTRs), alternative splicing is prevalent, and there are many individual examples of subcellular transcript localization, differential regulation of translation, and regulation of transcript decay, often in a disease-relevant context. A key aspect of understanding human gene regulation will be to map post-transcriptional regulatory networks, and an essential step in mapping these networks is to obtain an accurate description of the RNA-binding activity of all of the RNA-binding proteins. We have developed a method called RNAcompete which measures, using a single binding reaction, the relative preference of an RNA-binding protein to hundreds of thousands of small RNAs (27-35 nt long) specially designed to encompass a broad range of primary sequences and secondary structures. In addition to being rapid and systematic, RNAcompete produces descriptions of binding activity that are generally superior to conventional motif models. Here, we propose to use RNAcompete to obtain a complete index of RNA-binding activities for all known and predicted human RNA-binding proteins. Our Specific Aims are: (1) Application of the current array-based RNAcompete method to all 294 human RNA- binding proteins and all of their 470 individual RNA-binding domains. (2) Further development of the RNAcompete methodology to create more complex pools and use next-generation sequencing as an output, to facilitate more detailed analysis of proteins that have multiple RNA-binding domains, and, eventually, complexes of RNA-binding proteins. (3) Creation of a database of RNA-binding profiles, both compiled from the literature and produced by our analyses in Aims 1 and 2. A component of this aim will be to explore models for RNA-binding activities, in order to provide the most accurate predictions of potential binding sites in cellular RNAs. (4) Analysis of the determinants of sequence and structure recognition for the large RRM and KH domain classes. Deciphering (or refuting) the existence of a mapping between amino- acid sequence features of these prevalent RNA-binding domains and the types of RNAs they bind will be important for understanding their function, and also in determining how knowledge of the binding preferences can be transferred across species and among different proteins. PUBLIC HEALTH RELEVANCE: Virtually all human genes produce RNA, and many genes are controlled by proteins that bind to the RNA. We propose to use a new method we have developed in order to obtain a complete index of RNA-protein interactions. This work should ultimately identify regulatory mechanisms that control both normal health and disease.

描述（由申请人提供）：人类基因组编码数百种含有 RNA 结合结构域的蛋白质，其中大多数特征尚不清楚，基因组分析表明转录后基因调控的广泛使用：5' 端存在高度序列保守性和 3' 非翻译区 (UTR)，选择性剪接很普遍，并且有许多亚细胞转录本定位、翻译的差异调节和转录本衰减调节的个体例子，通常在疾病相关的背景下。了解人类基因调控的一个关键方面是绘制转录后调控网络图谱，而绘制这些网络图谱的一个重要步骤是获得所有 RNA 结合蛋白的 RNA 结合活性的准确描述。我们开发了一种称为 RNAcompete 的方法，该方法使用单一结合反应来测量 RNA 结合蛋白对数十万个小 RNA（27-35 nt 长）的相对偏好，这些小 RNA 专门设计用于涵盖广泛的一级序列和二级结构。除了快速和系统之外，RNAcompete 生成的结合活性描述通常优于传统基序模型。在这里，我们建议使用 RNAcompete 来获得所有已知和预测的人类 RNA 结合蛋白的 RNA 结合活性的完整指数。我们的具体目标是： (1) 将当前基于阵列的 RNAcompete 方法应用于所有 294 个人类 RNA 结合蛋白及其所有 470 个单独的 RNA 结合域。 (2) 进一步开发 RNAcompete 方法，以创建更复杂的库并使用下一代测序作为输出，以促进对具有多个 RNA 结合结构域的蛋白质以及最终的 RNA 结合蛋白复合物进行更详细的分析。 (3) 创建 RNA 结合谱数据库，该数据库均根据文献汇编并通过我们在目标 1 和 2 中的分析产生。该目标的一个组成部分将是探索 RNA 结合活性的模型，以便提供对细胞 RNA 中潜在结合位点的最准确预测。 (4)分析大RRM和KH域类的序列和结构识别的决定因素。破译（或驳斥）这些普遍的RNA结合域的氨基酸序列特征和它们结合的RNA类型之间是否存在映射对于理解它们的功能以及确定如何了解结合偏好非常重要。跨物种和不同蛋白质之间转移。 公共健康相关性：几乎所有人类基因都会产生 RNA，并且许多基因受与 RNA 结合的蛋白质控制。我们建议使用我们开发的新方法来获得 RNA-蛋白质相互作用的完整指数。这项工作最终应确定控制正常健康和疾病的调节机制。