RNA Structurome in Post-Transcriptional Regulation

转录后调控中的 RNA 结构组

• 批准号: 9754213
• 负责人: Zhengqing Ouyang
• 金额: $ 3万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9754213
• 关键词: Academic Medical Centers; Affect; Biological Models; Biological Process; Cancer cell line; Cell model; Characteristics; Collaborations; Communities; Data Set; Development; Diagnosis; Disease; Dissection; Embryonic Development; Etiology; Future; Goals; Hospitals; Human; Logic; Play; Post-Transcriptional Regulation; Proteins; RNA; RNA chemical synthesis; RNA-Protein Interaction; Research; Role; Stem cells; Structure; Transcript; Translational Regulation; Translations; Vision; clinical Diagnosis; effective therapy; high throughput technology; human disease; in vivo; malignant neurologic neoplasms; nervous system disorder; novel; outcome forecast; programs; public health relevance; self-renewal; transcriptome

PROJECT SUMMARY/ABSTRACT My research program focuses on development and application of computational approaches to determine the relationship between RNA structure and function for all RNA transcripts, or the transcriptome. RNA structure plays key roles in almost every step of RNA synthesis and function, and has significant impacts on biological processes and human diseases. Recent high-throughput technologies have begun to revolutionize dissection of RNA structures at the transcriptome level (termed RNA structuromes). However, little is known of the relationship between RNA structure and function, largely because current computational approaches lack the capacity to fully utilize the available high-throughput datasets to reveal the characteristics and functions of RNA structuromes. To overcome these limitations, I am building a unique research program to develop novel computational approaches to characterize, analyze and interpret the function of RNA structuromes. Over the next five years, the goals of my research program are to comprehensively elucidate RNA structuromes and precisely predict the functions of RNA structure in RNA-protein interactions and control of translation of RNA into proteins. We will develop a novel analytic framework for inferring RNA structuromes that integrates available high-throughput datasets and enables analysis of in vivo RNA structures. We will use this framework for analyses using specific cellular model systems, including characterizing the diversity of specific RNA structures that regulate RNA-protein interactions in a human cancer cell line, and dissecting the roles of RNA structure in modulating interactions between RNA and proteins shown to be essential for translational regulation of stem cell self-renewal and early embryogenesis. We will validate our computational predictions by collaborating with experimental biologists with relevant expertise. In the immediate future we will apply our approaches to study the roles of RNA structure in human diseases by collaborating with biologists working on the mechanisms of human diseases, including neurological disorders and cancer. Successful development of our approaches will allow us, and the research community, to elucidate the logic from RNA structure to RNA function and reveal their contributions to the etiology of numerous seemingly intractable human diseases. The overall vision of my research program is to build our burgeoning network of collaborations with colleagues at academic medical centers and hospitals across the nation that will, in the future, enable me to incorporate our computational approaches (using RNA structurome analysis as a springboard) to advance our capacity to render more accurate clinical diagnoses and prognoses, and develop novel, more effective therapies.

项目总结/文摘