权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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.

项目摘要心律失常是一个主要的临床问题，易导致心脏性猝死。基因组- 广谱关联研究发现了越来越多与心脏疾病相关的序列变异。心律失常和相关的心电图(ECG)特征，但这些GWA中的大多数属于非编码区及其功能效应很难破译。我们假设大多数功能性的与心律失常相关的非编码变体落入心脏顺式调节元件(CRE；即，增强子/启动子)，并通过破坏转录因子(TF)结合位点发挥它们的作用，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。识别与心律失常相关的GWAITS的原因变异，并绘制与心律失常相关的图谱 CRES，我们建议实施一种称为CRE-SEQ(顺式-顺式序列调控元件分析)的技术。在Cre-seq中，单个CRE与报告基因融合，每个基因包含一个唯一的DNA条形码。由此产生的 Cre-Report文库由数千个构建体组成，被引入到活体组织中，报告基因通过用RNA-seq计数条码转录本来量化表达。CRE-SEQ承诺大大加快我们测量心脏疾病中顺式调控变异效应的能力。为了实现这一目标，我们建议有两个明确的目标。在目标1中，我们将使用cre-seq在所有已知的GWAs中识别因果顺式调控变体与心律失常相关的基因座及相关特征。我们将衡量顺式监管活动数以千计的野生型和变异型Cre在小鼠心脏和人iPSC来源的心肌细胞中通过腺相关病毒(AAV)介导的Cre-seq文库传递。然后，我们将评估其功能效果使用包含所有已知人类TF的蛋白质微阵列对TF结合的选定变体。最后，我们将将我们的CRE-SEQ分析结果与心脏eQTL数据相关联。在目标2中，我们将为通过定位和阐明人类心脏核心蛋白基因的位置来解释罕见的心律失常相关变异他们的顺势监管逻辑。我们将利用“捕获和克隆”策略构建cre-seq文库。允许分析每个地点的长(即~500个BP)平铺记者。通过这种方式，我们将精确定位Essential Tf 结合位点(TFBs)是稀有功能变异的可能靶点。接下来，我们将使用CRE-seq来分析将所有可能的单核苷酸替换引入已鉴定的TFBs的效果。在目标1中，我们将在小鼠心脏和人IPSC来源的心肌细胞中进行CRE-seq。加在一起，这两个 AIMS将使对单个人类基因组中常见和罕见变异的功能解释成为可能从而便于评估患者的心脏病风险。