GSE117963
Disease-relevant transcriptional signatures identified in individual smooth muscle cells from healthy mouse vessels
Vascular smooth muscle cells (VSMCs) show pronounced heterogeneity across and within vascular beds, with direct implications for their function in injury response and atherosclerosis. Here we combine single-cell transcriptomics with lineage tracing to examine VSMC heterogeneity in healthy mouse vessels. The transcriptional profiles of single VSMCs consistently reflect their region-specific developmental history and show heterogeneous expression of vascular disease-associated genes involved in inflammation, adhesion and migration. We detect a rare population of VSMC-lineage cells that express the multipotent progenitor marker Sca1, progressively downregulate contractile VSMC genes and upregulate genes associated with VSMC response to inflammation and growth factors. We find that Sca1 upregulation is a hallmark of VSMCs undergoing phenotypic switching in vitro and in vivo, and reveal an equivalent population of Sca1-positive VSMC-lineage cells in atherosclerotic plaques. Together, our analyses identify disease-relevant transcriptional signatures in VSMC-lineage cells in healthy blood vessels, with implications for disease susceptibility, diagnosis and prevention. Overall design: This entry contains data from the following analyses: (1) Bulk RNA-seq of mouse VSMCs isolated from aortic arch (AA) and descending thoracic aorta (DT) regions in triplicates. (2)  Pooled RNA-seq of mouse Sca1- VSMCs and Sca1- or Sca1+ adventitial cells in triplicates. (3) Single-cell RNA-seq of VSMCs from the AA and DT regions (143 cells). (4) VSMC lineage label positive and negative cells isolated from the medial layer of mouse aorta, which expressed or did not express the Sca1 protein (155 cells). (5) 10X single-cell RNA-seq analysis of: lineage positive plaque cells isolated from mice following 14 or 18 weeks of high fat diet feeding, cells isolated from the whole aorta and lineage positive VSMCs from the medial layer.