HAEC transcriptomic profiling discover a heterogenous cell population.

(A), Schematic diagram of the experimental design. ECs were isolated from six human heart transplant donor’s ascending aortic trimmings and treated with IL1B, TGFB2, or siERG (ERG siRNA) for 7 days (B), Weighted Nearest Neighbor UMAP (WNNUMAP) of aggregate cells from all perturbations and donors is shown. Each dot represents a cell, and the proximity between each cell approximates their similarity of both transcriptional and epigenetic profiles. Colors denote cluster membership. (C), The proportion of cells from each donor for each EC subtype. (D), Gene expression across top markers for each cluster including pan EC (ERG), EC1 (KDR), EC2 (TOP2A), and EC4 (COL1A1). (E), Top markers for pan EC (PECAM1, CDH5, ERG), EC1 (KDR, PGF), EC2 (CENPE, TOP2A), EC3 (SEMA3C, ACKR3), EC4 (COL1A1, COL6A1), and EC5 (LRRC17, LAMA2). The size of the dot represents the percentage of cells within each EC subtype that express the given gene, while the shade of the dot represents the level of average expression (“Avg. Expn.” in the legend). (F), Heatmap of pathway enrichment analysis (PEA) results from submitting top 200 differentially expressed genes (DEGs; by ascending p-value) between EC subtypes. Rows (pathways) and columns (EC subtypes) are clustered based on -Log10(P) (G), Violin plots of top Metascape pathway module scores across EC subtypes. Module scores are generated for each cell barcode with Seurat function AddModuleScore().

ECs have epigenetically distinct cell states.

(A), Upset plot of differential peaks across EC subtypes. Intersection size represents the number of genes at each intersection, while set size represents the number of genes for each EC subtype. (B), Genomic annotation for the complete peak set. (C), Heatmap of top transcription factors (TFs) from motif enrichment analysis for marker peaks in each EC subtype. Top TFs for each EC subtype are selected based on ascending p-value. Rows (TFs) and columns (EC subtype) are clustered based on enrichment score (ES). (D), Feature plots and position weight matrices (PWMs) for top TF binding motifs for EC1 (TCF12), EC2 (ETV1), EC3 (GATA5), and EC4 (TEAD3). Per-cell motif activity scores are computed with chromVAR, and motif activities per cell are visualized using Signac function FeaturePlot. (E), PWMs comparing Jaspar 2020 ETV1 motif to ERG motif reported in Hogan et al.

EC activating perturbations modestly shift cells into the EC3 subtype.

(A), The proportion of cells in 7-day control and 7-day IL1B treatment are shown per HAEC donor and cluster on the top and for 7-day control and 7-day TGFB2 on the bottom (B), The proportion of cells in 7-day siSCR control and 7-day siERG knock-down are shown per HAEC donor and cluster. EC1 was omitted in A due to lack of cells in both conditions.

EC activating perturbations in vitro elicit EC subtype-specific transcriptional responses.

(A), Upset plots of up- and down-regulated DEGs across EC subtypes with siERG (grey), IL1B (pink), and TGFB2 (blue). Intersection size represents the number of genes at each intersection. (B), PEA for EC3-4 up- and down-regulated DEGs with TGFB2 compared to control media. (C), PEA for EC2-4 up- and down-regulated DEGs with IL1B compared to control media. (D), PEA for EC1-4 up- and down-regulated DEGs with siERG compared to siSCR. (E), PEA comparing up- and down-regulated DEGs that are mutually exclusive and shared between IL1B and siERG in EC3.

ECs from ex vivo human atherosclerotic plaques show two major populations.

(A), scRNA-seq UMAP of different cell subtypes across 17 samples of ex vivo human atherosclerotic plaques. (B), Dot plot of top markers for each cell type. (C), Heatmap of pathway enrichment analysis (PEA) results generated from submitting 200 differentially expressed genes (DEGs) between Endothelial Cells 1 (Endo1) and Endothelial Cells 2 (Endo2). Rows (pathways) and columns (cell subtypes) are clustered based on -Log10(P). (E), Heatmap displaying expression of genes belonging to ribosome cytoplasmic pathway for Endo1 and Endo2.

EC subtype is a major determinant in the ability to recapitulate ‘omic profiles seen in atherosclerosis.

(A), Heatmap displaying average expression between in vitro perturbation-subtype combinations and ex vivo cell subtypes using all up- and down-regulated genes between IL1B, TGFB2, or siERG versus respective controls. Spearman correlation was used as the distance metric. Rows (in vitro EC subtypes) and columns (ex vivo cell subtypes) are clustered using all significant genes (adjusted p-value < 0.05) induced and attenuated across all in vitro EC subtypes for each perturbation versus its respective control. (B), Heatmap of CAD-associated SNP enrichments across in vitro EC subtypes and perturbation-subtype combinations. Rows (EC subtypes and perturbation-subtype combinations) are clustered using -Log10(P) for enrichment in significant CAD-associated SNPs (p-value < 5×10-8). Note that “diff” represents peaks common to more than one EC subtype; it is found by subtracting EC1-5 subtype-specific peaks from the entire in vitro peak set (termed “panEC”). (C), Coverage plots displaying links for COL4A1/COL4A2 genes to EC4-specific peaks, including one overlapping with CAD-associated SNP rs9515203. (D), Coverage plot showing links for PECAM1 gene to EC4-specific peaks, including one overlapping with CAD-associated SNP rs1108591. (E), Coverage plot showing links for BMP6 gene to EC4-specific peaks, including one overlapping with CAD-associated SNP rs6597292.