Nature CommunicationsGenomicsPeer-reviewed journal article
Vascular smooth muscle cell atherosclerosis trajectories characterized at single cell resolution identify causal transcriptomic and epigenomic mechanisms of disease risk
Daniel Yuhang LiiD, Soumya KunduiD, Paul P. ChengiD, Wenduo GuiD, Matthew D. WorssamiD, William Jackson, Quanyi ZhaoiD, Trieu NguyeniD, A. Y-C. Yu, João P MonteiroiD, Roxanne Diaz Caceres, Stanley Dale, Brian T. PalmisanoiD, Chad S. WeldyiD, Markus O RamsteiD, Ramendra Krishna KunduiD, Anshul Bharat KundajeiD, Robert C. WirkaiD, Thomas QuertermousiD
Abstract
Vascular smooth muscle cells (SMC) contribute to heritable coronary artery disease (CAD) risk and undergo complex cell state transitions to multiple disease related phenotypes. To investigate the genetic basis of SMC state trajectories that underlie the SMC component of CAD causality we have developed a dense timecourse single cell transcriptomic and epigenetic map of atherosclerosis in a murine disease animal model. Cellular trajectories were derived from the temporal data and probabilistic fate modeling with Waddington-Optimal Transport (WOT). We created transcription factor (TF) centered regulons mapped across the developmental timeline and through network-based prioritization with WOT predicted TFs and in silico TF perturbation, identified key drivers of cell state changes associated with EMT, vascular development, and circadian clock functions. Integration of mouse disease data with human CAD genetic findings identified transition SMC phenotypes that mediate disease risk and point to causal disease mechanisms. Parallel studies using knockout of the validated CAD gene Tcf21 revealed its impact on SMC transition cellular phenotypes and disease risk genes, due in part to a role regulating the transition of SMC precursor cells in the secondary heart field. Together, these studies characterize atherosclerosis trajectories at single cell resolution and identify genetic causal transcriptomic and epigenomic mechanisms of CAD risk.
- organism: mouse
- assay: scRNA-seq
- assay: ATAC-seq
- research focus: trajectory inference
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: contrastive learning
- Citations
- 10
- FWCI
- 23.98
- Field percentile
- top 1%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Genetic regulatory mechanisms of smooth muscle cells map to coronary artery disease risk loci
Boxiang Liu, Milos Pjanic, … Thomas Quertermous·The American Journal of Human GeneticsPeer-reviewed·Aug 23, 2018
- Mapping atherogenesis mechanisms in smooth muscle cells by targeting genes linked to coronary artery disease
Julián Albarrán-Juárez, Anton Markov, … Jacob Fog Bentzon·iSciencePeer-reviewed·Oct 5, 2025
- Coronary Artery Disease Risk Gene PRDM16 is Preferentially Expressed in Vascular Smooth Muscle Cells and a Potential Novel Regulator of Smooth Muscle Homeostasis
- Cell-specific chromatin landscape of human coronary artery resolves regulatory mechanisms of disease risk
Adam W. Turner, Shengen Shawn Hu, … Clint L. Miller·Nature GeneticsPeer-reviewed·May 19, 2022
- Integrative single-cell meta-analysis reveals disease-relevant vascular cell states and markers in human atherosclerosis
José Verdezoto Mosquera, Gaelle E Auguste, … Clint L. Miller·Cell ReportsPeer-reviewed·Nov 1, 2023
- Quantitative trait loci mapped for TCF21 binding, chromatin accessibility and chromosomal looping in coronary artery smooth muscle cells reveal molecular mechanisms of coronary disease loci
Quanyi Zhao, Michael Dacre, … Thomas Quertermous·Genome biologyPeer-reviewed·Jun 8, 2020