Massively parallel identification of functional 3' UTR variants in asthma

哮喘功能性 3 UTR 变异的大规模并行鉴定

• 批准号: 8901295
• 负责人: David J Erle
• 金额: $ 54.87万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8901295
• 关键词: 3' Untranslated Regions; Address; Affect; African; American; Americas; Asthma; Beryllium; Binding; Biological Assay; Biology; CD4 Positive T Lymphocytes; Cell Line; Cell model; Cells; Code; Communities; Computing Methodologies; Data; Disease; Elements; Ensure; Epithelial; Face; Frequencies; Funding; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Translation; Genetic Variation; Genetic study; Genome; Genomics; Health; Human Genetics; Incidence; Individual; Libraries; Maps; Measures; Messenger RNA; Methods; MicroRNAs; Oligonucleotides; Pathogenesis; Phenotype; Population; Process; Production; Proteins; Regulatory Element; Regulatory Pathway; Research Personnel; Role; Sampling; Staging; T-Lymphocyte; Technology; Testing; United States National Institutes of Health; Untranslated RNA; Untranslated Regions; Variant; abstracting; base; cell type; computerized tools; disorder risk; functional genomics; gene function; genetic association; genetic variant; genome sequencing; genome wide association study; improved; in vivo; interest; mRNA Stability; multidisciplinary; novel; rare variant; respiratory smooth muscle; tool

DESCRIPTION (provided by applicant): Asthma is a common disease with a prominent genetic component. Genetic studies have identified many sequence variants associated with asthma and other diseases. The human genetics community now faces the major challenge of moving from associated variants to causal variants. Addressing this challenge requires improved strategies for identifying how changes in gene sequence affect gene function. Most genetic variants associated with asthma and other common diseases are found in non-coding regions, but our understanding of how non-coding variants affect gene function remains very limited. This project focuses on dramatically advancing our ability to measure and predict how variants in 3' untranslated regions (3' UTRs) affect gene regulation. 3' UTRs contain cis-regulatory elements that control mRNA stability and translation by binding to specific proteins and miRNAs. We understand so little about 3' UTR function that it is impossible to accurately predict which 3' UTR variants affect gene function. We developed a novel massively parallel experimental method for functional annotation of sequences from three-prime UTRs (fast-UTR). Fast-UTR simultaneously measures the effects of very large numbers of 3' UTR sequence variants on mRNA levels, mRNA stability, and protein production in cells of interest. We propose to apply this method to understanding the role of 3' UTR sequence variation in asthma. In aim 1, we will select appropriate cellular models that represent key cell types known to be important in asthma and miRNAs that are abundant in those cells. In aim 2, we will use fast-UTR to study hundreds of thousands of 3' UTR variants found in the 1000 Genomes Project and the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) study. The CAAPA study includes whole genome sequencing of samples from 1005 highly diverse individuals from understudied populations with a high incidence of asthma. In aim 3, we will use fast-UTR results to improve methods for predicting effects of any 3' UTR variant and we will develop and implement methods for using fast-UTR fine-mapping information to help analyze cis-eQTL studies, the CAAPA study, and other GWAS and sequencing studies. This project will demonstrate how massively parallel assay technology can be harnessed to identify functional variants thereby addressing one of the most pressing issues facing the human genetics community today.

描述（由申请人提供）：哮喘是一种常见疾病，具有显着的遗传因素。遗传学研究已经鉴定出许多与哮喘和其他疾病相关的序列变异。人类遗传学界现在面临着从相关变异转向因果变异的重大挑战。应对这一挑战需要改进策略来确定基因序列的变化如何影响基因功能。大多数与哮喘和其他常见疾病相关的遗传变异都存在于非编码区域，但我们对非编码变异如何影响基因功能的了解仍然非常有限。该项目的重点是显着提高我们测量和预测 3' 非翻译区 (3' UTR) 变异如何影响基因调控的能力。 3' UTR 包含顺式调控元件，通过与特定蛋白质和 miRNA 结合来控制 mRNA 稳定性和翻译。我们对 3' UTR 功能了解甚少，因此无法准确预测哪些 3' UTR 变异会影响基因功能。我们开发了一种新颖的大规模并行实验方法，用于对三素 UTR（fast-UTR）序列进行功能注释。 Fast-UTR 同时测量大量 3' UTR 序列变体对感兴趣细胞中 mRNA 水平、mRNA 稳定性和蛋白质产生的影响。我们建议应用这种方法来了解 3' UTR 序列变异在哮喘中的作用。在目标 1 中，我们将选择合适的细胞模型，这些模型代表已知对哮喘很重要的关键细胞类型以及这些细胞中丰富的 miRNA。在目标 2 中，我们将使用 fast-UTR 来研究千基因组计划和美洲非洲裔哮喘联盟 (CAAPA) 研究中发现的数十万个 3' UTR 变异。 CAAPA 研究包括对来自哮喘高发人群的 1005 名高度多样化个体的样本进行全基因组测序。在目标 3 中，我们将使用快速 UTR 结果来改进预测任何 3' UTR 变体效果的方法，并且我们将开发和实施使用快速 UTR 精细作图信息来帮助分析 cis-eQTL 研究（CAAPA 研究）的方法，以及其他 GWAS 和测序研究。该项目将展示如何利用大规模并行检测技术来识别功能变异，从而解决当今人类遗传学界面临的最紧迫的问题之一。