Protocol for isolation of nuclei from murine cardiac tissue for single-nucleus multiomic sequencing

Figure 1. Schematic representation of the proposed workflow for isolation of nuclei from frozen murine ventricular tissue for single-nucleus multiomic sequencing Frozen cardiac tissue is homogenized, filtered, and subjected to cushion centrifugation to enrich for cardiac nuclei. Further debris and aggregates removal is based on FANS yielding nuclei suitable for single-nucleus multiomic sequencing.

Figure 2. Flow Activated Nuclei Sorting (FANS) workflow for capturing intact cardiac nuclei populations and removing all unstained debris (A and B) Forward scatter (FSC) and side scatter (SSC) parameters are used to identify the nuclei populations based on their size. (C) Fluorescent gating with 7AAD distinguishes stained nuclei (7AAD-positive) from non-nuclear debri (7AAD-negative). (D) A third gate, based on FSC width/height, discriminates single nuclei from aggregates. (E) Histogram of sorted nuclei based on the 7AAD positive signal.

Figure 3. UMAP visualization of snRNA-seq, snATAC-seq, and WNN-integrated snMultiome clustering and cell type composition across the dataset and individual samples (A) UMAP projections based on snRNA-seq (left), snATAC-seq (middle), and integrated snMultiome/WNN analysis (right), showing the cardiac cell populations. (B) Overall cell type composition across all nuclei included in the analysis. (C) Cell type composition shown separately for each sample.

Figure 4. Assessment of nuclear membrane during single-nuclei isolation (A) Representative trypan blue staining of nuclei suspension prior to FANS. (B) Representative trypan blue staining of nuclei suspension after FANS, showing good separation between nuclei and absence of nuclei aggregates. (C) Example of suboptimal nuclei isolation resulting in large nuclear aggregates, shown by trypan blue staining. (D) Representative brightfield images of isolated nuclei. (E) Representative images of fluorescence microscopy images of nuclei tagged with anti-LaminB1(green) and DAPI(blue). (F) Representative images of fluorescence microscopy images of nuclei tagged with WGA(red) and DAPI(blue).

Figure 5. Examples of library pool QC traces (A and B) Shown are the representative traces of successful QC analyses for snRNAseq, at the cDNA amplification step (A), and snATACseq trace (B).

Figure 6. Quality control assessment of snRNA-seq and snATAC-seq data (A) Violin plots showing the distribution of per-nucleus RNA nCount values before filtering and after removal of low-quality nuclei. (B) Violin plots showing the distribution of per-nucleus RNA nFeature values before filtering and after removal of low-quality nuclei. (C) Violin plots showing the distribution of per-nucleus ATAC nCount values and TSS enrichment scores before filtering and after removal of low-quality nuclei.

Figure 7. Visualization of cluster-specific genomic regions Pseudobulk chromatin accessibility tracks at the Myh6 locus, with peak-to-gene linkage analysis showing correlations between accessible chromatin regions (peaks) and expression of nearby genes.

Figure 8. Cell-type specific transcription factors colored by RNA expression (left) and motif accesibility (right) Representative UMAP visualization showing unique transcription factors for the cardiomyocytes (A) and fibroblasts (B), based on combined RNA expression and ATAC motif accessibility analyses. Cells are colored according to normalized RNA expression levels (left) and corresponding motif accessibility scores (right).