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

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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.