GSE183310
Decoding the PITX2 controlled genetic network in atrial fibrillation
Atrial fibrillation (AF), the most common sustained cardiac arrhythmia and a major risk factor for stroke, often arises through ectopic electrical impulses derived from the pulmonary veins (PV). Sequence variants in enhancers controlling expression of the transcription factor PITX2, which is expressed in the cardiomyocytes (CMs) of the PV and left atrium (LA), have been implicated in AF predisposition. Single nuclei multiomic profiling of RNA and analysis of chromatin accessibility combined with spectral clustering uncovered distinct PV- and LA-enriched CM cell states. Pitx2 mutant PV and LA CMs exhibited gene expression changes consistent with cardiac dysfunction through cell-type-distinct, PITX2-directed, cis-regulatory grammars controlling target gene expression. The perturbed network targets in each CM were enriched in distinct human AF-predisposition genes, suggesting combinatorial risk for AF-genesis. Our data further reveals that PV and LA Pitx2 mutant CMs signal to endothelial and endocardial cells through BMP10 signaling with pathogenic potential. This work provides a multiomic framework for interrogating the basis of AF-predisposition in the PV of humans. Overall design: The Tg(Ckmm-cre)5Khn/0 (MCK-cre) mice were crossed to the germline Pitx2tm1Jfm (Pitx2–) allele to generate MCK-cre; Pitx2+/– mice, which are crossed with homozygous Pitx2tm1.1Sac (Pitx2flox/flox) to generate the Pitx2 control (Pitx2flox/+) and Pitx2 mutant (MCK-cre; Pitx2flox/–) mice. Mice were raised to adulthood (6-8 months) and genotypes confirmed by PCR prior to experimentation. For single nuclei RNA and ATAC sequencing (snRNA-seq and snATAC-seq), the left atrium (LA) and the pulmonary vein (PV) were dissected from the adult mouse heart. The LA dissection includes both the chamber and the appendage, while the PV includes the proximal connection to the atrium, the primary PV, and the branches prior to entry into the lungs.  Nuclei were harvested from the two tissue sources in pools of 8 Pitx2 control and 8 Pitx2 mutant mice using a previously published method with modifications (Mo, A. et al. Epigenomic Signatures of Neuronal Diversity in the Mammalian Brain. Neuron 86, 1369–1384 (2015).). In brief, the tissues were minced with sharp scissors in 250µl of HB++ (HB: 0.25M sucrose, 25mM KCl, 5mM MgCl2, 20mM Tricine-KOH, pH 7.8; ++: 0.15mM spermine, 0.5mM spermidine, 1mM DTT) and centrifuged at 500g for 5 minutes to remove excess red blood cells and fat and replaced with 250µl of fresh HB++. Sample was transferred to a 2mL Dounce homogenizer and the tube washed with an additional 250µl of HB++ to collect any remaining sample and transferred. Tissue was homogenized 30 times with loose and tight pestle before adding 32µl of 5% NP40 (in HB) and Dounced with tight pestle an additional 75 times. Sample was strained through a 40µM strainer and washed with 9.5mL of NWB (PBS with 1% BSA and 0.2U RNAse inhibitor) and spun down at 500g at 4°C for 5 minutes. The supernatant removed and nuclei resuspended in 500µl of NWB and 900µl of SCB (90% Nuclei PURE 2M Sucrose Cushion Solution and 10% Nuclei PURE Sucrose Cushion Solution; Sigma NUC-201: S9308 and S9058). The 1400µl of nuclei suspension is layered on top of 500µl SCB in a 2mL LoBind Eppendorf tube and centrifuged at 13,000g at 4°C for 45 minutes. The supernatant removed leaving ~50µl of nuclei pellet, which is resuspended in 1mL of NWB. Pellet nuclei at 500g at 4°C for 5 minutes, remove supernatant leaving ~50µl of nuclei pellet. Nuclei were quantified using the inCyto C-Chip DHC-F01.  The snRNA-seq libraries were generated using the 10x Chromium Single Cell 3' v3 reagent kit and in parallel the snATAC-seq libraries were generated using the 10x Chromium Single Cell ATAC v1 with a target of 10,000 nuclei per library according to the manufacturer's instructions. The libraries were sequenced on an Illumina NovaSeq6000 with the Genome and RNA Profiling Core at Baylor College of Medicine and an Illumina NextSeq 500. Raw sequencing data was handled by the 10x Genomics Cell Ranger software (cellranger-3.0.1 and cellranger-atac-1.2.0) and mapped to the mouse mm10 genome. For snRNA-seq, the gene counts were quantified using cellranger count to the mouse transcriptome including pre-mRNA (v3.0.0) and passed to Seurat for downstream analysis. For snATAC-seq, samples were individually aligned using cellranger-atac count and aggregated using cellranger-atac aggr (--nosecondary --normalize=none) using the peak output from each individual sample. Following initial clustering (see below for downstream analysis) and per cluster and per sample peak calling using MACS2 callpeak (v2.1.1.20160309) with parameters -f BAMPE -g mm -B -q 0.1 samples were re-aggregated using cellranger-atac aggr using a union set of peaks and passed to Seurat and Signac for downstream analysis.