GEO series
The epigenomic landscape of single vascular cells reflects developmental origin and identifies disease risk loci
GSE296197
Mus musculus
Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing
12 samples
2025/07/29
GPL24247
Summary
Vascular sites have distinct susceptibility to atherosclerosis and aneurysm, yet the biological underpinning of vascular site-specific disease risk is largely unknown. Vascular tissues have different developmental origins that may influence global chromatin accessibility, and understanding differential chromatin accessibility, gene expression profiles, and gene regulatory networks (GRN) on single cell resolution may give key insight into vascular site-specific disease risk. Here, we performed single cell chromatin accessibility (scATACseq) and gene expression profiling (scRNAseq) of healthy adult mouse vascular tissue from three vascular sites, 1) aortic root and ascending aorta, 2) brachiocephalic and carotid artery, and 3) descending thoracic aorta. Through a comprehensive analysis at single cell resolution, we discovered key regulatory enhancers to not only be cell type, but vascular site specific in vascular smooth muscle (SMC), fibroblasts, and endothelial cells. We revealed an epigenetic ‘memory’ of embryonic origin with differential chromatin accessibility of key developmental transcription factors such as Tbx20, Hand2, Gata4, and Hoxb family members and discovered transcription factor motif accessibility to be cell type and vascular site specific. Notably, we identify ascending fibroblasts to have distinct epigenomic patterns, highlighting SMAD2/3 function to suggest a differential susceptibility to TGF, a finding we confirmed through in vitro culture of primary adventitial fibroblasts. Finally, to understand how vascular site-specific enhancers may regulate human genetic risk to disease, we integrated genome wide association study (GWAS) data for ascending and descending aortic dimension, and through using a novel technique, we employed ChromBPNet, a distinct base resolution deep learning model to predict variant effect on chromatin accessibility We trained nine ChromBPNet models to predict variant effect in SMC, Fibroblasts, and Endothelial cells within ascending aorta, carotid, and descending aorta sites of origin. We reveal that although cell type remains a primary influence on variant effect, vascular site modifies effect within cell type and highlights genomic regions that are enriched for specific TF motif footprints — including MEF2A, SMAD3, and HAND2. This work supports a paradigm that the epigenomic and transcriptional landscapes of vascular cells are cell type and vascular site-specific and that these vascular site-specific enhancers govern complex genetic drivers of vascular site-specific disease risk.
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Paper (PMID 40931195) ↗
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