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Defining the messenger RNP code in the brain

定义大脑中的信使 RNP 代码

基本信息

批准号：
8605237
负责人：
Eugene Wei-Ming Yeo
金额：
$ 59.39万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-02-15 至 2017-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8605237
关键词：
Affect Alternative Splicing Amyotrophic Lateral Sclerosis Angelman Syndrome Antibodies Antisense Oligonucleotides Behavioral Beryllium Binding Binding Sites Biochemical Bioinformatics Biological Assay Brain Cells Code Complex Defect Development Disease Double-Stranded RNA ES Cell Line Elements Epitopes Event Expression Library Fragile X Syndrome Functional RNA Future Genomics Germ Layers Goals High-Throughput Nucleotide Sequencing Homeostasis Human Human Resources Immunoprecipitation Indium Lead Length Life Machine Learning Maps Mediating Mental disorders Messenger RNA Modeling Molecular Mus Muscular Dystrophies Neurodegenerative Disorders Neurologic Neurons Open Reading Frames Phenotype Pluripotent Stem Cells Problem Solving Process Proteins RNA RNA Binding RNA Interference RNA Processing RNA Splicing RNA Stability RNA, Messenger, Splicing RNA-Binding Proteins Regulation Regulatory Element Resources Ribosomes Role Schizophrenia Spinal Spinal Muscular Atrophy Structure Technology Translations autism spectrum disorder base crosslink genome wide association study genome-wide human RBM5 protein human embryonic stem cell human embryonic stem cell line in vivo insight lentiviral-mediated messenger ribonucleoprotein nerve stem cell nervous system disorder neuroregulation novel predictive modeling protein complex relating to nervous system transcriptome sequencing

项目摘要

DESCRIPTION (provided by applicant): RNA binding proteins (RBPs) interact with functional RNA elements embedded within pre- and mature messenger RNA to form messenger ribonucleoprotein (mRNP) complexes. These interactions result in the faithful execution of RNA processing events such as pre-mRNA alternative splicing, RNA stability and translational control. Aberrant alterations in the interactions between the RBPs and their RNA elements ultimately lead to behavioral abnormalities and neurological developmental defects, which can often manifest as fatal diseases such as Spinal Muscular Atrophy and Amyotrophic Lateral Sclerosis or life-long debilitating behavioral abnormalities such as Prader-Willi/Angelman Syndromes, Schizophrenia and Autism Spectrum Disorder. These findings underscore the importance of investigating the roles of these RBPs in the brain. In particular, our project is aimed at systematically, using genome-wide biochemical and bioinformatic assays, identifying the functional RNA elements that are recognized by RBPs in mouse brain and human neurons. We will develop a novel resource of human pluripotent stem cells stably expressing tagged RBPs that can be differentiated into human neurons. This will enable the identification of RNA binding sites of 50 RBPs in human neural RNAs in a uniform and systematic manner using cutting-edge genomic approaches such as cross-linking and immunoprecipitation followed by high-throughput sequencing (CLIP- seq). To reveal the splicing, stability, and translational changes that are dependent on direct binding of these RBPs we will perform high-throughput sequencing of mRNAs (RNA-seq) and ribosome-protected fragments (RPFs). Finally, we will leverage our computational expertise to build predictive models using this genome-wide, multi-scale, mRNP code in the brain.

描述（由申请人提供）：RNA结合蛋白（RBP）与嵌入前信使RNA和成熟信使RNA中的功能性RNA元件相互作用，形成信使核糖核蛋白（mRNP）复合物。这些相互作用导致 RNA 加工事件的忠实执行，例如前 mRNA 选择性剪接、RNA 稳定性和翻译控制。 RBP与其RNA元件之间相互作用的异常改变最终导致行为异常和神经发育缺陷，这通常表现为致命疾病，如脊髓性肌萎缩症和肌萎缩侧索硬化症，或终生衰弱的行为异常，如普瑞德威利/安格曼综合症、精神分裂症和自闭症谱系障碍。这些发现强调了研究这些 RBP 在大脑中的作用的重要性。具体来说，我们的项目旨在利用全基因组生化和生物信息学分析系统地识别小鼠大脑和人类神经元中 RBP 识别的功能性 RNA 元件。我们将开发一种新的人类多能干细胞资源，该细胞稳定表达标记的 RBP，可以分化为人类神经元。这将能够使用交联和免疫沉淀等尖端基因组方法，然后进行高通量测序 (CLIP-seq)，以统一和系统的方式鉴定人类神经 RNA 中 50 个 RBP 的 RNA 结合位点。为了揭示依赖于这些 RBP 直接结合的剪接、稳定性和翻译变化，我们将对 mRNA (RNA-seq) 和核糖体保护片段 (RPF) 进行高通量测序。最后，我们将利用我们的计算专业知识，使用大脑中的这种全基因组、多尺度的 mRNP 代码来构建预测模型。