Discovery and interrogation of genetic regulatory variation impacting Atrial Fibrillation risk

影响心房颤动风险的基因调控变异的发现和询问

• 批准号: 10593080
• 负责人: Xin He
• 金额: $ 80.31万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10593080
• 关键词: ATAC-seq; Address; Adult; Affect; Alleles; Arrhythmia; Atrial Fibrillation; Biological; Biological Assay; Cardiac; Cardiac Myocytes; Cell physiology; Cells; Cellular Structures; Chromatin; Chromosomes; Complex; DNA; Data; Data Set; Disease; Electrophysiology (science); Enhancers; Etiology; Functional disorder; Gene Expression; Gene Expression Regulation; Gene Targeting; Genes; Genetic; Genetic Variation; Genomics; Goals; Heart; Heart Atrium; Human; In Vitro; Individual; Link; Maps; Modeling; Molecular; Nucleic Acid Regulatory Sequences; Pathway interactions; Physiology; Pilot Projects; Principal Investigator; Procedures; Regulatory Element; Reporter; Resolution; Risk; Signal Transduction; System; Techniques; Tissues; Translating; Untranslated RNA; Variant; candidate identification; causal variant; cell type; chromosome conformation capture; deep learning; disorder risk; economic cost; experimental study; gene discovery; gene regulatory network; genetic association; genetic variant; genome wide association study; genomic data; improved; insight; multimodality; novel; promoter; risk variant; socioeconomics; trait; transcription factor; transgene expression

Abstract The overall goal of this multi-principal investigator proposal is to facilitate the transition from implication of genetic variants identified in extensive genome wide association studies (GWAS) of Atrial Fibrillation (AF) to the molecular mechanisms underlying AF risk. We hypothesize that a novel genomic and analytic pipeline interrogating regulatory function of genetic variation will identify candidate causative variants and their target genes, enabling the transition from simple associations to causative mechanisms for the arrhythmia. In preliminary studies, we have applied novel single cell approaches to generate cell-type-resolved high-resolution chromosome accessibility maps and taken advantage of coordinated genomic signals to link AF risk variants to candidate causative AF genes. The results describe a highly interconnected gene regulatory network for cardiac atrial gene expression. In our first aim we propose to generate multi-modal single-cell genomics data to provide higher-resolution annotation of variant effects. We will improve our computational procedure to better leverage these datasets for AF variant and gene discovery. In our second aim, we will interrogate the interconnected gene regulatory network in molecular enhancer assays and genomic chromatin conformation capture experiments, to directly examine the impact of nominated genetic variants and their physical association with candidate target genes. In our third aim, we will examine the functionality of high confidence variant SNPs in depth, including their impact on gene regulation in cis, their impact on human cardiomyocyte electrophysiology, and their impact on cardiomyocyte gene expression and chromatin status in trans. We have established a tractable strategy that will help enable the transition from AF risk variants to molecular mechanisms. We anticipate that our approach will help translate the promise of AF genetics into meaningful biological insights for AF and establish a paradigm for the molecular understanding of genetic association studies in any system.

摘要 这一多主要研究者提案的总体目标是促进从暗示的过渡 房颤（AF）广泛基因组关联研究（GWAS）中鉴定的遗传变异， 房颤风险的分子机制。我们假设一种新的基因组和分析管道 询问遗传变异的调节功能将鉴定候选的致病变异体和它们的靶 基因，使从简单的协会转变为心律失常的致病机制。在 在初步研究中，我们应用了新的单细胞方法来产生细胞类型分辨的高分辨率 染色体可及性图谱，并利用协调的基因组信号将AF风险变异与 候选的AF致病基因。结果描述了一个高度相互关联的心脏基因调控网络， 心房基因表达在我们的第一个目标中，我们提出生成多模态单细胞基因组学数据，以提供 更高分辨率的变异效应注释。我们将改进我们的计算程序，以更好地利用 这些数据集用于AF变体和基因发现。在我们的第二个目标中，我们将审问 分子增强子测定和基因组染色质构象捕获中的基因调控网络 实验，以直接检查提名的遗传变异的影响及其物理关联， 候选靶基因。在我们的第三个目标中，我们将检查高置信度变体SNP在以下中的功能： 深度，包括它们对顺式基因调控的影响，它们对人类心肌细胞电生理学的影响， 以及它们对心肌细胞基因表达和染色质状态的影响。 这将有助于实现从AF风险变异到分子机制的转变。我们 预计我们的方法将有助于将AF遗传学的承诺转化为有意义的生物学见解， AF和建立一个范例的分子理解的遗传关联研究在任何系统。