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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：
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.

项目总结