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：
10563224
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/10563224
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 Dedications 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 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 RNA-Protein Interaction 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 risk experimental study feature selection genetic analysis genetic variant genome-wide analysis high throughput analysis human disease improved mRNA Expression novel posttranscriptional programs promoter risk variant tool transcriptome sequencing variant detection

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.

项目摘要该项目的目的是识别和表征变化的功能3'UTR遗传变异 mRNA丰度的转录后调节，重点是与阿尔茨海默氏病（AD）。最近，越来越多的遗传变异分类了包括AD在内的人类疾病的会议风险。但是，它仍然很棒挑战以识别因果变异并阐明其潜在功能与疾病有关发病机理和进展。与精确指出遗传变异的进展相比改变转录调控或蛋白质编码序列，遗传变异如何影响转录后的过程知之甚少。许多新确定的广告相关变体位于非编码区域，例如介绍和3’UTR，可能赋予调节性相关基因的功能，尤其是在转录后调节水平上。尤其，人类基因的3'UTR富含许多由顺式调节的元素认可的跨因素，例如RNA结合蛋白（RBP）。这些顺式元素一起跨因素决定了影响基因最终表达的mRNA的许多方面。 mRNA 许多众所周知的与广告相关的基因的抽象受RBP或microRNA的调节绑定到他们的3英尺UTR。影响这些调节机制的遗传变异将导致 MRNA表达异常，因此显着改变了相关的功能途径。在这个项目，我们将利用RBP-RNA交互分析的大量公共数据集，从AD和控制受试者收集的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颖的方法来充分利用这些数据集，通过进一步的生物信息学预测和高通量实验测试完成精确3’UTR遗传变异，会改变AD中的mRNA丰度。这项工作将允许在转录后调节中，以前未经鉴定的对遗传变异的理解水平并提供新的手段来应对通用功能解释的当务之急广告中的变体。