High-throughput identification of causal variants underlying cardiac arrhythmia-related GWAS hits

高通量识别心律失常相关 GWAS 命中的因果变异

• 批准号: 10397430
• 负责人: JOSEPH CORBO
• 金额: $ 72.27万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10397430
• 关键词: Address; Affinity; Arrhythmia; Bar Codes; Binding; Binding Sites; Biological Assay; Cardiac; Cardiac Myocytes; Chromatin; Clinical; Complement; DNA; Data; Dependovirus; Diagnosis; Disease; Electrocardiogram; Enhancers; Etiology; Evaluation; Future; Gene Expression; Genes; Genomic Segment; Genotype-Tissue Expression Project; Goals; Heart; Heart Diseases; Human; Human Activities; Human Genome; Individual; Ion Channel; Knowledge; Lead; Libraries; Linkage Disequilibrium; Location; Logic; Maps; Measures; Mediating; Mus; Mutation; Nucleotides; Paired Comparison; Patients; Play; Process; Protein Microchips; Proteins; Regulatory Element; Reporter; Reporter Genes; Resolution; Role; Techniques; Technology; Tissues; Transcript; Untranslated RNA; Variant; base; causal variant; disorder risk; falls; genetic disorder diagnosis; genome wide association study; genome-wide; heart disease risk; human data; improved; in vivo; individual patient; induced pluripotent stem cell derived cardiomyocytes; interest; new technology; novel; promoter; rare variant; risk stratification; sudden cardiac death; trait; transcription factor; transcriptome sequencing

Project Summary Cardiac arrhythmias are a major clinical problem and can predispose to sudden cardiac death. Genome- wide association studies (GWAS) have identified a growing number of sequence variants associated with cardiac arrhythmias and related electrocardiogram (ECG) traits, but the majority of these GWAS hits fall within non- coding regions and their functional effects are difficult to decipher. We hypothesize that the majority of functional non-coding variants related to cardiac arrhythmias fall within cardiac cis-regulatory elements (CREs; i.e., enhancers/promoters), and exert their effects by disrupting transcription factor (TF) binding sites and thereby altering the expression level of genes encoding cardiac proteins, especially ion channels and their regulators. To identify causal variants underlying cardiac arrhythmia-related GWAS hits and to map arrhythmia-related CREs, we propose to implement a technique called CRE-seq (Cis-Regulatory Element analysis by sequencing). In CRE-seq, individual CREs are fused to reporter genes, each containing a unique DNA barcode. The resultant CRE-reporter library, consisting of thousands of constructs, is introduced into living tissue, and reporter gene expression is quantified by counting barcoded transcripts with RNA-seq. CRE-seq promises to greatly accelerate our ability to measure the effects of cis-regulatory variants in cardiac disease. To achieve this goal, we propose two Specific Aims. In Aim 1, we will use CRE-seq to identify causal cis-regulatory variants at all known GWAS loci associated with cardiac arrhythmias and related traits. We will measure the cis-regulatory activity of thousands of wild-type and variant CREs in mouse heart in vivo and in human iPSC-derived cardiomyocytes via adeno-associated virus (AAV)-mediated CRE-seq library delivery. We will then evaluate the functional effects of selected variants on TF binding using protein-microarrays containing all known human TFs. Lastly, we will correlate the results of our CRE-seq analyses with cardiac eQTL data. In Aim 2, we will establish a template for interpreting rare arrhythmia-related variants by mapping the location of human cardiac CREs and elucidating their cis-regulatory logic. We will utilize a 'capture and clone' strategy for CRE-seq library construction, which permits analysis of long (i.e., ~500 bp) tiled reporters at each locus. In this way, we will pinpoint essential TF binding sites (TFBSs) which are the likely targets of rare functional variants. Next, we will use CRE-seq to analyze the effects of introducing all possible single-nucleotide substitutions into identified TFBSs. As in Aim 1, we will perform CRE-seq in both mouse heart and human iPSC-derived cardiomyocytes. Taken together, these two Aims will enable functional interpretation of both common and rare variants in individual human genomes and thereby facilitate assessment of cardiac disease risk in patients.

项目概要 心律失常是一个主要的临床问题，可能导致心源性猝死。基因组- 广泛关联研究（GWAS）已发现越来越多与心脏相关的序列变异 心律失常和相关心电图 (ECG) 特征，但这些 GWAS 命中中的大多数属于非 编码区及其功能作用很难破译。我们假设大多数功能 与心律失常相关的非编码变异属于心脏顺式调节元件（CRE；即 增强子/启动子），并通过破坏转录因子（TF）结合位点发挥其作用，从而 改变编码心脏蛋白的基因的表达水平，特别是离子通道及其调节因子。 识别心律失常相关 GWAS 命中的因果变异并绘制心律失常相关图谱 CRE，我们建议实施一种称为 CRE-seq（顺式调控元件测序分析）的技术。 在 CRE-seq 中，各个 CRE 与报告基因融合，每个基因都包含独特的 DNA 条形码。由此产生的 CRE-报告文库由数千个构建体组成，被引入活体组织和报告基因 通过使用 RNA-seq 对带有条形码的转录本进行计数来量化表达。 CRE-seq有望大大加速 我们有能力测量顺式调节变异对心脏病的影响。为了实现这一目标，我们建议 两个具体目标。在目标 1 中，我们将使用 CRE-seq 来识别所有已知 GWAS 中的因果顺式调控变异 与心律失常和相关特征相关的基因座。我们将衡量顺式监管活动 小鼠心脏体内和人 iPSC 衍生的心肌细胞中数千个野生型和变异 CRE 腺相关病毒（AAV）介导的CRE-seq文库交付。然后我们将评估功能效果 使用包含所有已知人类 TF 的蛋白质微阵列选择 TF 结合的变体。最后，我们将 将我们的 CRE-seq 分析结果与心脏 eQTL 数据关联起来。在目标 2 中，我们将建立一个模板 通过绘制人类心脏 CRE 的位置并阐明来解释罕见的心律失常相关变异 他们的顺式监管逻辑。我们将利用“捕获和克隆”策略进行 CRE-seq 文库构建，这 允许分析每个位点的长（即~500 bp）平铺报告基因。这样我们就可以找到必要的TF 结合位点（TFBS）是罕见功能变异的可能目标。接下来我们将使用CRE-seq来分析 将所有可能的单核苷酸取代引入已识别的 TFBS 中的效果。正如目标 1 一样，我们将 在小鼠心脏和人 iPSC 衍生的心肌细胞中进行 CRE-seq。综合起来，这两个 目标将能够对人类个体基因组中常见和罕见的变异进行功能解释， 从而有助于评估患者的心脏病风险。