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Gain- and loss-of-function RNA-seq analysis reveals DDIT4-driven transcriptional programs in human coronary artery smooth muscle cells

ABSTRACT: This dataset profiles the transcriptomic changes resulting from DDIT4 manipulation in human coronary artery smooth muscle cells (HCASMCs). We performed RNA sequencing on HCASMCs following adenovirus-mediated DDIT4 overexpression or shRNA-mediated DDIT4 knockdown. Our analysis reveals that DDIT4 is both necessary and sufficient to drive a transcriptional program characteristic of VSMC dedifferentiation, establishing its critical role in phenotypic switching. These findings provide mechanistic insight into how this stress-responsive gene promotes proliferative arterial disease.

ORGANISM(S): Homo sapiens

PROVIDER: GSE310361 | GEO | 2026/06/06

REPOSITORIES: GEO

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Project description:Although numerous genetic loci have been associated with coronary artery disease (CAD) with genome wide association studies (GWAS), efforts are needed to identify the causal genes in these loci and link them into fundamental signaling pathways. Toward that end, experiments reported here extend our investigation of the disease mechanism of CAD associated gene SMAD3, a central transcriptional intermediate in the TGFb pathway, investigating its role in smooth muscle biology. In vitro studies in human coronary artery smooth muscle cells (HCASMC) revealed that SMAD3 modulates cell state decisions in this cell type, promoting expression of differentiation marker genes and migration while inhibiting proliferation. RNA and chromatin immunoprecipitation sequencing (ChIPseq) studies in HCASMC identified downstream genes that reside in pathways which mediate vascular development and disease processes, including those related to atherosclerosis pathophysiology, expanding understanding of the TGFb canonical pathway in this cell type. ChIPseq studies also found colocalization of SMAD3 binding in loci targeted by TCF21, a CAD associated transcription factor that has been shown to produce a CAD protective de-differentiation program in HCASMC. In loci where these factors are juxtaposed on DNA, SMAD3 binding was anti-correlated with TCF21, and increased in cells depleted of TCF21, as shown by ChIPseq and ChIP experiments. Further, reporter gene studies revealed that while SMAD3 increased transcription at a SERPINE1 enhancer, and this effect was blocked by TCF21. Together, these data suggest that SMAD3 regulation of gene expression is modulated by TCF21, through independent regulation of jointly occupied genes and through epigenetic and possibly direct protein-protein interactions. Finally, eQTL studies in HCASMC indicated that SMAD3 expression is directly associated with increased disease risk, opposing the known protective effect of TCF21. We propose that the pro-differentiation function of SMAD3 inhibits HCASMC dedifferentiation of these cells as they respond to vascular stresses and expand and migrate to stabilize the plaque, and that SMAD3 function is directly opposed at the transcriptional level by the disease protective expression of TCF21, which promotes dedifferentiation and phenotypic modulation. Methods: Primary human coronary artery smooth muscle cells (HCASMCs) were purchased from three different manufacturers, PromoCell, Lonza and Cell Applications at passage 2 and were cultured in smooth muscle cell basal media along with hEGF, insulin, hFGF-B and fetal bovine serum (FBS) (Lonza # CC-3182) according to the manufacturer’s instructions. HCASMCs between passages 5-8 were used for all the experiments. SMAD3 (s8401 and s8402) silencer select siRNAs were purchased from Life Technologies. siRNA transfection was performed using Lipofectamine RNAiMAX (Life Technologies). For each well treated with the SMAD3 siRNA or scrambled control (Life technologies, #4390843), the final concentration was 20 nM. HCASMCs were seeded in 6 well plates and grown to 75% confluence before siRNA transfection. HCASMCs were transfected with the SMAD3 siRNA or scrambled control for 12 hours and subsequently collected and processed for RNA isolation after 48 hrs of transfection using the RNeasy kit (Qiagen). Three experimental and three control samples were generated and sequenced on a HiSeq 4000 machine, 125 bp paired end reads. Reads were processed using rnaSeqFPro, a workflow for full processing of RNASeq data starting from fastq files. In brief, the quality control was performed using FastQC, mapping to the human genome hg19 was performed using STAR second pass mapping to increase the percentage of mapped reads, and counting was done with featureCounts using GENCODE gtf annotation. Next, rnaSeqFPro performed differential analysis using DESeq2, conducted principal component analysis and hierarchical clustering using standard R functions, plotPCA and heatmap.2 and generated graphs using gglot2. DESeq2 gave 493 differentially expressed (DE) genes (FDR < 0.05).

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Gain- and loss-of-function RNA-seq analysis reveals DDIT4-driven transcriptional programs in human coronary artery smooth muscle cells

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