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

功能性 3™ UTR 遗传变异及其与阿尔茨海默病的相关性的系统分析

基本信息

批准号：
10344561
负责人：
Xinshu Grace Xiao
金额：
$ 55.13万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-15 至 2026-11-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10344561
关键词：
3&apos Untranslated Regions Address Affect Alleles Alzheimer&apos s Disease Alzheimer&apos s disease patient Bayesian Analysis Bayesian Modeling Binding Binding Sites Bioinformatics Biological Biological Assay Brain Catalogs Cell Line Cells Code Collection Complement DNA DNA Sequence Alteration Data Data Set Disease Elements Environment Epigenetic Process Event Foundations Future Gene Expression Gene Expression Regulation Generations Genes Genetic Polymorphism Genetic Transcription Genetic Variation Genotype Goals Human Individual Intervention Introns Lead Measures Mediating Messenger RNA Methodology Methods MicroRNAs Modeling Molecular Biology Nucleic Acid Regulatory Sequences Open Reading Frames Pathogenesis Pathologic Pathway interactions Population Post-Transcriptional Regulation Proteins RNA RNA-Binding Proteins Regulation Regulatory Element Reporter Reporting Research Risk Role Sampling Susceptibility Gene System Testing Therapeutic Time Tissues Trans-Activators Transcription Process Transcriptional Regulation Translations Untranslated RNA Variant Work beta-site APP cleaving enzyme 1 causal variant cohort disease phenotype disorder control disorder risk experimental study feature selection genetic analysis genetic variant genome-wide analysis high throughput analysis human disease improved mRNA Expression novel programs promoter risk variant tool transcriptome sequencing

项目摘要

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.

项目概要该项目的目标是识别和表征功能性 3' UTR 遗传变异，这些变异改变了 mRNA丰度的转录后调控，重点关注与相关的变异阿尔茨海默病（AD）。近年来，越来越多的基因变异被研究出来。目录对人类疾病（包括 AD）具有风险。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。与精确定位遗传变异的进展相比改变转录调控或蛋白质编码序列，遗传变异如何影响人们对转录后过程知之甚少。许多新发现的与 AD 相关的变异存在于非编码区域，例如内含子和 3' UTR，这可能会赋予监管相关基因的功能，特别是在转录后调控水平。尤其，人类基因的 3' UTR 富含许多被反式因子，例如 RNA 结合蛋白 (RBP)。这些顺式元素和反式因子决定了影响基因最终表达的 mRNA 的许多方面。信使RNA 许多众所周知的 AD 相关基因的丰度受到 RBP 或 microRNA 的调节绑定到他们的 3'UTR。影响这些调节机制的基因变异将导致 mRNA 表达异常，从而显着改变相关功能途径。在这个项目中，我们将利用 RBP-RNA 相互作用分析的大量公共数据集，从 AD 和对照受试者收集的 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，辅之以进一步的生物信息预测和高通量实验测试，查明改变 AD 中 mRNA 丰度的 3' UTR 遗传变异。这项工作将允许对转录后调控中遗传变异的理解达到了前所未有的水平并提供新的方法来解决遗传功能解释的迫切任务 AD 中的变体。