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）：哮喘是一种具有突出遗传成分的常见疾病。遗传研究已经确定了许多与哮喘和其他疾病相关的序列变异。现在，人类遗传学界面临着从相关变体转向因果变体的主要挑战。应对这一挑战需要改进的策略来确定基因序列的变化如何影响基因功能。在非编码区域中发现了与哮喘和其他常见疾病相关的大多数遗传变异，但是我们对非编码变体如何影响基因功能的理解仍然非常有限。该项目的重点是极大地促进我们测量和预测3'未翻译区域（3'UTR）中的变体如何影响基因调节的能力。 3'UTR包含顺式调节元件，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函数的了解很少，因此无法准确预测哪些3'UTR变体会影响基因函数。我们开发了一种新颖的平行实验方法，用于从三个prime UTR（Fast-UTR）的序列功能注释。快速UTR同时测量了大量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。我们建议将此方法应用于了解哮喘中3'UTR序列变化的作用。在AIM 1中，我们将选择适当的细胞模型，这些模型代表关键细胞类型在这些细胞中丰富的哮喘和miRNA中很重要的细胞类型。在AIM 2中，我们将使用Fast-UTR来研究1000个基因组项目中发现的数十万个3'UTR变体，以及美洲非洲 - 委托人种群中哮喘的财团（CAAPA）研究。 CAAPA研究包括来自1005个高度不同人群中哮喘病率高的人群的样本的整个基因组测序。在AIM 3中，我们将使用快速UTR结果来改善预测任何3'UTR变体效果的方法，我们将开发和实施使用快速UTR细胞映射信息的方法，以帮助分析CIS-EQTL研究，CAAPA研究，其他GWAS研究以及其他GWAS和测序研究。该项目将证明如何利用大量平行的测定技术来识别功能变体，从而解决当今人类遗传学界面临的最紧迫的问题之一。