Systematic analysis of functional 3’ UTR genetic variants and their relevance to Alzheimer’s Disease

项目摘要 该项目的目标是识别和表征功能性3‘非编码区基因变异体 转录后调节信使核糖核酸丰度，重点是与 阿尔茨海默病(AD)。最近，越来越多的基因变异被发现 对包括阿尔茨海默病在内的人类疾病的风险进行了分类。然而，它仍然是一个伟大的 识别因果变异并阐明其与疾病相关的潜在功能的挑战 发病机制和进展。与在精确定位遗传变异方面的进展相比， 改变转录调控或蛋白质编码序列，遗传变异如何影响 转录后过程知之甚少。许多新发现的与AD相关的 变异体位于非编码区，如内含子和3‘端非编码区，它们可能赋予调控 对相关基因的作用，特别是在转录后调控水平上。特别是， 人类基因的3‘端非编码区富含许多顺式调控元件 反式因子，如RNA结合蛋白(RBPs)。加在一起，这些顺式元件和 反式因子决定了影响基因最终表达的信使核糖核酸的许多方面。mrna 许多众所周知的AD相关基因的丰度受到限制性商业惯例或microRNAs的调控 绑在他们的3‘UTR上。影响这些调控机制的基因变异将导致 异常的mRNA表达，从而显著改变相关的功能通路。在这 项目中，我们将利用关于RBP-RNA相互作用分析的大量公共数据集， 从AD和对照组收集的RNA-seq和基因分型数据，以及我们的内部数据 一代。我们将开发和应用新的方法来充分利用这些数据集， 辅以进一步的生物信息学预测和高通量实验测试，以 精确定位改变AD患者信使核糖核酸丰度的3‘非编码区基因变异。这项工作将允许 对转录后调控中的遗传变异的理解达到了前所未有的水平 为解决基因功能解释这一紧迫任务提供了新的手段 公元后的变种。

Project Summary The goal of this project is to identify and characterize functional 3’ UTR genetic variants that alter post-transcriptional regulation of mRNA abundance, with a focus on variants relevant to Alzheimer’s disease (AD). Recently, an increasing number of genetic variants have been cataloged that confer risks to human diseases, including AD. However, it remains a great challenge to identify causal variants and elucidate their potential function relevant to disease pathogenesis and progression. Compared to the progress in pinpointing genetic variants that alter transcriptional regulation or protein-coding sequences, how genetic variants may affect post-transcriptional processes is poorly understood. Many of the newly identified AD-associated variants reside in non-coding regions, such as introns and 3’ UTRs, that may confer regulatory function to the related gene, especially at the level of post-transcriptional regulation. In particular, the 3’ UTRs of human genes are enriched with many cis-regulatory elements recognized by trans-factors, such as RNA-binding proteins (RBPs). Together, these cis-elements and trans-factors dictate many aspects of the mRNA that affect the final expression of a gene. mRNA abundance of a number of well-known AD-relevant genes are regulated by RBPs or microRNAs bound to their 3’ UTRs. Genetic variants that affect these regulatory mechanisms will lead to abnormal mRNA expression, thus significantly altering related functional pathways. In this project, we will leverage the large collection of public data sets on RBP-RNA interaction profiling, RNA-seq and genotyping data collected from AD and control subjects, and our in-house data generation. We will develop and apply novel methodologies to make full use of these data sets, complemented by further bioinformatic prediction and high-throughput experimental testing, to pinpoint 3’ UTR genetic variants that alter mRNA abundance in AD. This work will allow a previously unattained level of understanding of genetic variants in post-transcriptional regulation and provide new means to tackle the imperative task of functional interpretation of genetic variants in AD.