Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation.

Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.

Simultaneous Measurement of DNA Methylation and Nucleosome Occupancy in Single Cells Using scNOMe-Seq.

Single-cell Nucleosome Occupancy and Methylome sequencing (scNOMe-seq) is a multimodal assay that simultaneously measures endogenous DNA methylation and nucleosome occupancy (i.e., chromatin accessibility) in single cells. scNOMe-seq combines the activity of a GpC Methyltransferase, an enzyme which methylates cytosines in GpC dinucleotides, with bisulfite conversion, whereby unmethylated cytosines are converted into thymines. Because GpC Methyltransferase acts only on cytosines present in non-nucleosomal regions of the genome, the subsequent bisulfite conversion step not only detects the endogenous DNA methylation, but also reveals the genome-wide pattern of chromatin accessibility. Implementing this technology at the single-cell level helps to capture the dynamics governing methylation and accessibility vary across individual cells and cell types. Here, we provide a scalable plate-based protocol for preparing scNOMe-seq libraries from single nucleus suspensions.