A Human atlas of smooth muscle cell gene expression; insights from the FANTOM consortium CAGE dataset

Abstract Background Under normal physiological conditions, smooth muscle cells (SMC's) have a role in both vessel contraction and generation of the extra-cellular matrix. It has now become apparent that SMCs throughout the vasculature play a key role in several cardiovascular conditions including hypertension, atherosclerosis, vasculopathy and myocardial infarction. However, how SMC gene expression compares in different vascular and non-vascular anatomical regions remains unknown. Purpose To create a human SMC gene expression map using data from the FANTOM consortium Cap-analysis gene expression (CAGE) dataset, a primary database of almost 600 human primary cell samples. Methods The gene level expression data was obtained by aggregating expression levels of all the promoters belonging to same gene as defined by the FANTOM CAGE dataset. The anatomical regions (n: 13) included the following vascular sites: aortic, brachiocephalic, carotid, coronary, internal thoracic & pulmonary arteries. Non-vascular regions included colon, oesophagus, prostate, uterine, trachea and bronchial. Weighted correlation network analysis (WGCNA) was used as an unsupervised approach to identify clustering of gene sets. Results Hierarchical clustering (Figure 1) demonstrates a distinct clustering of vascular SMC gene sets (aortic, carotid, coronary, internal thoracic, pulmonary & subclavian arteries). The same pattern of vascular SMC clustering was also seen in WGCNA (Figure 2). Gene ontology enrichment of vascular SMCs that clustered in WGCNA identified common gene sets relating to cytokine and chemokine activity. KEGG pathway analysis highlighted several pathways linked to inflammation (TNF, IL17 & NF-κB signalling) as well as pathways linked to atherosclerosis and lipid metabolism. Conclusion Vascular SMCs distinctly cluster away from non-vascular SMC types in humans and the separation is primarily driven by gene sets relating to inflammation, lipid metabolism & atherosclerosis. Mapping SMC gene expression at various anatomical regions in both healthy and diseased states may give us better insight into the role of SMCs in disease progression and could identify novel mechanistic targets for future therapy. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): British Heart Foundation