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

基本信息

批准号：
10615090
负责人：
JOSEPH CORBO
金额：
$ 72.08万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10615090
关键词：
Acceleration 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 General Population Genes Genomic Segment Genotype-Tissue Expression Project Goals Heart Heart Diseases Human Human Activities Human Genome Individual Ion Channel Knowledge 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 candidate identification 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

项目摘要

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.

项目摘要心脏心律不齐是一个主要的临床问题，可能会诱发心脏猝死。基因组广泛的关联研究（GWAS）已经确定了越来越多的序列变体心律不齐和相关心电图（ECG）特征，但这些GWAS中的大多数都属于非 - 编码区域及其功能效果很难破译。我们假设大多数功能与心脏心律失常有关的非编码变体属于心脏顺式调节元件（CRES；即，增强剂/启动子），并通过破坏转录因子（TF）结合位点发挥作用改变编码心脏蛋白的基因的表达水平，尤其是离子通道及其调节剂。确定心律不齐相关的GWAS命中的基础因果变体并绘制与心律不齐相关的 CRES，我们建议实施一种称为CRE-SEQ（顺序调节元件分析）的技术。在Cre-Seq中，单个CRE融合到报告基因，每个基因都包含独特的DNA条形码。结果由数千种结构组成的Cre-Reporter库被引入活组织中，并记录基因通过用RNA-seq计数条形码转录本来量化表达。 Cre-Seq有望大大加速我们测量顺式调节变体对心脏病的影响的能力。为了实现这一目标，我们提出两个具体的目标。在AIM 1中，我们将使用Cre-Seq识别所有已知GWAS的因果顺式调节变体与心律不齐和相关性状相关的基因座。我们将测量小鼠心脏中的成千上万种野生型和变体CRE在体内和人IPSC衍生的心肌细胞中通过腺相关病毒（AAV）介导的Cre-Seq库的传递。然后，我们将评估使用包含所有已知人类TF的蛋白质微阵列在TF结合上的选定变体。最后，我们会的将我们的Cre-Seq分析结果与心脏EQTL数据相关联。在AIM 2中，我们将建立一个模板通过绘制人类心脏的位置并阐明稀有心律失常相关的变体他们的顺式调节逻辑。我们将利用“捕获和克隆”策略进行Cre-Seq库的构建，该策略允许分析每个基因座的长（即〜500 bp）瓷砖记者。这样，我们将确定必需的TF 结合位点（TFBS）是稀有功能变体的可能目标。接下来，我们将使用Cre-Seq分析将所有可能的单核苷酸取代引入确定的TFBS的影响。就像在AIM 1中一样，我们将在小鼠心脏和人类IPSC衍生的心肌细胞中执行Cre-Seq。两者一起，这两个目标将在人类基因组中对共同变体和稀有变体的功能解释以及从而有助于评估患者心脏病风险。