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包含RNA结合域的蛋白质，其中大多数是较差的特征，基因组分析表明，转录后基因调控的广泛使用：在5'和3'的始终术语中，有很多序列的序列，并且有很多smortenty spection（utrantical systelly），并且是替代性的（utrs）。通常在与疾病相关的情况下，本地化，翻译的差异调节和转录本衰减的调节。理解人基因调控的一个关键方面是映射转录后调节网络，映射这些网络的重要步骤是获得对所有RNA结合蛋白的RNA结合活性的准确描述。我们已经开发了一种称为RNACOMPETE的方法，该方法使用单个结合反应测量RNA结合蛋白与成千上万的小RNA（27-35 nt长）的相对偏好是专门设计的，以涵盖一系列的主要序列和二级结构。除了快速和系统性外，rnacompete还会产生结合活性的描述，这些活性通常优于常规基序模型。在这里，我们建议使用rnacompete为所有已知和预测的人RNA结合蛋白获得完整的RNA结合活性指数。我们的具体目的是：（1）将当前基于阵列的RNACOMPETE方法应用于所有294个人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，以创建更复杂的池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进行更详细的分析，并最终促进RNA结合蛋白的复合物。 （3）创建AIM 1和2中的分析所产生的RNA结合曲线数据库。该目标的一个组成部分是探索用于RNA结合活动的模型，以便提供蜂窝RNA中潜在结合位点的最准确的预测。 （4）分析大RRM和KH域类的序列和结构识别的决定因素。解密（或反驳）这些普遍的RNA结合结构域的氨基酸序列特征与它们结合的RNA类型之间存在映射对于理解其功能至关重要，并且在确定如何在跨物种和不同蛋白质之间传递了结合偏好的知识。 公共卫生相关性：几乎所有人类基因都会产生RNA，许多基因都由与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索引。这项工作最终应确定控制正常健康和疾病的监管机制。