Clonal proliferation of smooth muscle cell in human atherosclerosis

Two different coronary artery samples with erosion plaques were selected from female heterozygous for the deletion BGN. Hybridization of target RNA-specific probes was used to visualize the spatial distribution of mutants. After determine the leison with clonality and non-clonal SMC proliferation, spatial transcriptomics was used to identify differentially expressed transcripts within clonal and non-clonal regions. Spatial transcriptomics analysis. Sample selection for 10X Genomics Visium V1 FFPE assay was based on the erosion plaque phenotypes selected for the detection of BGN using BaseScope (ACD). Adjacent section was selected from two of the coronary artery FFPE blocks corresponding to the erosion phenotypes. Total RNA was isolated from ten 5 µm sections from the FFPE blocks using RNeasy FFPE kit (Qiagen). RNA was analyzed using TapeStation (Agilent) and DV200 of ≥50% was observed for generating successful Visium spatial gene expression libraries. Next, the FFPE blocks for two erosion plaque phenotypes were sectioned at 5-8 µm thickness and mounted within a single 6.5 × 6.5 mm capture area on the Visium v1 spatial gene expression slide. Spatial transcriptomics assay using Visium V1 spatial gene expression slide and reagent kits were used according to instructions outlined by 10X Genomics (Pleasanton, CA). Visium Spatial Gene Expression was performed for FFPE sectioned tissues that produce spatially barcoded, Illumina® sequencer-ready libraries that are dual indexed. The generated libraries were loaded on a NovaSeq 6000 System (Illumina) and sequencing was performed using the following read protocol: read 1, 28 cycles (spatial barcode, UMI); i7 index read, 10 cycles (sample index); i5 index read, 10 cycles (sample index); read 2, 91 cycles (insert). Visium v1 raw data processing: Raw FASTQ files for a given capture area and corresponding capture area histology images were processed with Space Ranger software version 1.3.0 (10X Genomics, Pleasanton CA). Space Ranger Pipeline was used to align Fastq reads to human hg38 reference genome, and the probe set reference file specific only to human FFPE tissues because the synthetic probe DNA was sequenced rather than cDNA of a captured transcript. For FFPE samples, Space Ranger counts oligo ligation events to build the feature-barcode matrix. Gene expression analysis. The data files of raw transcriptomics were posted at NCBI’s Gene Expression Omnibus public database. Sequencing data was then imported into Partek Flow Enterprise Edition software (Partek Inc., Louis, MO). The data was filtered to exclude features where value <= 1.0 in at least 99.0 % of the cells and further normalized to CPM (counts per million) at Add: 1.0, Log: 2.0. A subset of SMCs was selected from the normalized counts by selecting for ACTA2 positive cells. Principle Component analysis (PCA) was then performed on these SMCs and for visualization, dimensionality reduction was performed using Uniform Manifold Approximation and Projection (UMAP) for the top 20 principal components from the graph-based clustering for ACTA2 positive cells. The data was further classified as with attributes for ACTA2 positive cells expressing BGN. We selected two regions each of WT-Clonal, Del-Clonal and non-clonal ROIs from two erosion sections as described in Supplemental Figure S5 (total 6 ROIs/section x2 = 12 ROIs). FDR (false discovery rate) < 0.05 and fold change < -1 or > 1. Marker genes identified were differentially expressed genes (DEGs) identified by one-to-one comparison of each cluster with all other clusters with P-values < 0.05 for regions of no clonality to clonality (Clonal WT + Del) to generate hierarchical cluster mapping (dot plot).