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Updated: Jun 23, 2025
Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells
Published on: January 7, 2020
Integrated analysis of single-cell RNA sequencing and bulk RNA data reveals gene regulatory networks and targets in
Min Zhang1, Xin Zhang2, Jiayin Niu3
1Department of Research Ward, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China.
Insights
This study identified key gene regulatory networks driving dilated cardiomyopathy (DCM). Pinpointing dysregulated targets like CDKN1A, SAT1, and ZFP36 improves understanding and may lead to new DCM therapies.
Area of Science:
- Cardiovascular Biology
- Genomics
- Systems Biology
Background:
- Dilated cardiomyopathy (DCM) significantly impacts patient quality of life and survival, despite recent improvements.
- The underlying pathogenesis of DCM remains incompletely understood.
- Gene regulatory networks are increasingly recognized as crucial in disease development.
Purpose of the Study:
- To identify driving factors in DCM pathogenesis using gene regulatory networks.
- To analyze single-cell and bulk RNA sequencing data for disease-specific molecular signatures.
- To pinpoint key dysregulated genes and networks in DCM.
Main Methods:
- Acquired single-cell and bulk RNA sequencing data from the Gene Expression Omnibus (GEO) database.
- Utilized pySCENIC for single-cell data analysis to identify 401 regulons.
- Applied variance decomposition and ssGSEA for differential analysis and cross-dataset validation of regulons.
Main Results:
- Identified 19 significant DCM-responsive regulons from single-cell data.
- Validated differential expression of 9 and 13 regulons across two independent bulk RNA datasets.
- Pinpointed three shared, differentially expressed target genes: CDKN1A, SAT1, and ZFP36.
Conclusions:
- Elucidated 19 gene regulatory networks responsive to DCM, validated across multiple datasets.
- Identified CDKN1A, SAT1, and ZFP36 as key dysregulated targets in DCM.
- Enhanced molecular understanding of DCM pathogenesis, paving the way for targeted therapeutic development.
Abstract:
Dilated cardiomyopathy (DCM) is a common cause of heart failure, thromboembolism, arrhythmias, and sudden cardiac death. The quality of life and long-term survival rates of patients with dilated DCM have greatly improved in recent decades. Nevertheless, the clinical prognosis for DCM patients remains unfavorable. The primary driving factors underlying the pathogenesis of DCM remain incompletely understood. The present study aimed to identify driving factors underlying the pathogenesis of DCM from the perspective of gene regulatory networks. Single-cell RNA sequencing data and bulk RNA data were obtained from the Gene Expression Omnibus (GEO) database. Differential gene analysis, single-cell genomics analysis, and functional enrichment analysis were conducted using R software. The construction of Gene Regulatory Networks was performed using Python. We used the pySCENIC method to analyze the single-cell data and identified 401 regulons. Through variance decomposition, we selected 19 regulons that showed significant responsiveness to DCM. Next, we employed the ssGSEA method to assess regulons in two bulk RNA datasets. Significant statistical differences were observed in 9 and 13 regulons in each dataset. By intersecting these differentiated regulons and identifying shared targets that appeared at least twice, we successfully pinpointed three differentially expressed targets across both datasets. In this study, we assessed and identified 19 gene regulatory networks that were responsive to the disease. Furthermore, we validated these networks using two bulk RNA datasets of DCM. The elucidation of dysregulated regulons and targets (CDKN1A, SAT1, ZFP36) enhances the molecular understanding of DCM, aiding in the development of tailored therapies for patients.
