Transcriptional regulatory network analysis of microglia in multiple sclerosis
Objective·To investigate the differential gene expression of microglia in the gray and white matter of multiple sclerosis (MS) using single-nucleus transcriptomic analysis, aiming to explore their roles in disease progression, and identify key transcriptional regulatory networks associated with the...
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Editorial Office of Journal of Shanghai Jiao Tong University (Medical Science)
2025-01-01
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| Series: | Shanghai Jiaotong Daxue xuebao. Yixue ban |
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| Online Access: | https://xuebao.shsmu.edu.cn/article/2025/1674-8115/1674-8115-2025-45-1-29.shtml |
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| author | CAI Qiangwei SUN Feng WU Wenyu SHAO Fuming GAO Zhengliang JIN Shengkai |
| author_facet | CAI Qiangwei SUN Feng WU Wenyu SHAO Fuming GAO Zhengliang JIN Shengkai |
| author_sort | CAI Qiangwei |
| collection | DOAJ |
| description | Objective·To investigate the differential gene expression of microglia in the gray and white matter of multiple sclerosis (MS) using single-nucleus transcriptomic analysis, aiming to explore their roles in disease progression, and identify key transcriptional regulatory networks associated with the disease.Methods·snRNA-seq data of frozen human brain tissue samples from MS patients and control individuals were obtained from the Gene Expression Omnibus (GEO) database. R language, along with R packages such as Seurat, was employed to identify cell types based on specific cell markers. Microglia were extracted from the identified cell populations and classified based on their anatomical origin, either gray matter or white matter. Dimensionality reduction and clustering techniques were utilized to identify distinct microglial subpopulations with differential characteristics. Differentially expressed genes (DEGs) between the MS and control groups at the subpopulation level were analyzed by using the Seurat package. Gene set enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was conducted on the DEGs to further explore the biological significance of these differences. Monocle3 was used for pseudotime analysis to study dynamic changes in microglia subpopulations during disease progression. Single cell regulatory network inference and clustering (SCENIC) method was applied to analyze transcription factor (TF) regulatory networks, aiming to identify key transcription factors potentially involved in MS regulation.Results·After quality control, a total of 149 062 nuclei were retained for analysis. Following dimensional reduction and clustering, 12 238 microglia were identified by using key markers, including DOCK8, CSF1R, P2RY12, and CD74. The results of GO and KEGG pathway analysis showed that in gray matter microglia, functions such as endocytosis, ion homeostasis, and lipid localization were downregulated during disease progression, while in white matter microglia, functions such as protein folding, cytoplasmic translation, and response to thermal stimuli were upregulated. SCENIC analysis revealed that the expression of transcription factors such as FLI1, MITF, and FOXP1 was upregulated in MS.Conclusion·Microglia play a critical role in MS, with white matter microglia being more significantly impacted by MS than their gray matter counterparts. Transcription factors such as FLI1, MITF, and FOXP1 are identified as key regulators involved in disease modulation, with their associated transcriptional regulatory networks playing a central role in disease modulation. |
| format | Article |
| id | doaj-art-b6b0d039b5894c13b48cdf0e47d333f0 |
| institution | DOAJ |
| issn | 1674-8115 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | Editorial Office of Journal of Shanghai Jiao Tong University (Medical Science) |
| record_format | Article |
| series | Shanghai Jiaotong Daxue xuebao. Yixue ban |
| spelling | doaj-art-b6b0d039b5894c13b48cdf0e47d333f02025-08-20T03:13:03ZzhoEditorial Office of Journal of Shanghai Jiao Tong University (Medical Science)Shanghai Jiaotong Daxue xuebao. Yixue ban1674-81152025-01-01451294110.3969/j.issn.1674-8115.2025.01.0041674-8115（2025）01-0029-13Transcriptional regulatory network analysis of microglia in multiple sclerosisCAI Qiangwei0SUN Feng1WU Wenyu2SHAO Fuming3GAO Zhengliang4JIN Shengkai5Institute of Geriatrics, Affiliated Nantong Hospital of Shanghai University, School of Medicine, Shanghai University, Nantong 201613, ChinaInstitute of Geriatrics, Affiliated Nantong Hospital of Shanghai University, School of Medicine, Shanghai University, Nantong 201613, ChinaInstitute of Geriatrics, Affiliated Nantong Hospital of Shanghai University, School of Medicine, Shanghai University, Nantong 201613, ChinaShanghai YangZhi Rehabilitation Hospital, Tongji University School of Medicine, Shanghai 200065, ChinaInstitute of Geriatrics, Affiliated Nantong Hospital of Shanghai University, School of Medicine, Shanghai University, Nantong 201613, ChinaDepartment of Anesthesiology, Shanghai Gongli Hospital, Naval Military Medical University, Shanghai 200135, ChinaObjective·To investigate the differential gene expression of microglia in the gray and white matter of multiple sclerosis (MS) using single-nucleus transcriptomic analysis, aiming to explore their roles in disease progression, and identify key transcriptional regulatory networks associated with the disease.Methods·snRNA-seq data of frozen human brain tissue samples from MS patients and control individuals were obtained from the Gene Expression Omnibus (GEO) database. R language, along with R packages such as Seurat, was employed to identify cell types based on specific cell markers. Microglia were extracted from the identified cell populations and classified based on their anatomical origin, either gray matter or white matter. Dimensionality reduction and clustering techniques were utilized to identify distinct microglial subpopulations with differential characteristics. Differentially expressed genes (DEGs) between the MS and control groups at the subpopulation level were analyzed by using the Seurat package. Gene set enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was conducted on the DEGs to further explore the biological significance of these differences. Monocle3 was used for pseudotime analysis to study dynamic changes in microglia subpopulations during disease progression. Single cell regulatory network inference and clustering (SCENIC) method was applied to analyze transcription factor (TF) regulatory networks, aiming to identify key transcription factors potentially involved in MS regulation.Results·After quality control, a total of 149 062 nuclei were retained for analysis. Following dimensional reduction and clustering, 12 238 microglia were identified by using key markers, including DOCK8, CSF1R, P2RY12, and CD74. The results of GO and KEGG pathway analysis showed that in gray matter microglia, functions such as endocytosis, ion homeostasis, and lipid localization were downregulated during disease progression, while in white matter microglia, functions such as protein folding, cytoplasmic translation, and response to thermal stimuli were upregulated. SCENIC analysis revealed that the expression of transcription factors such as FLI1, MITF, and FOXP1 was upregulated in MS.Conclusion·Microglia play a critical role in MS, with white matter microglia being more significantly impacted by MS than their gray matter counterparts. Transcription factors such as FLI1, MITF, and FOXP1 are identified as key regulators involved in disease modulation, with their associated transcriptional regulatory networks playing a central role in disease modulation.https://xuebao.shsmu.edu.cn/article/2025/1674-8115/1674-8115-2025-45-1-29.shtmlmultiple sclerosismicrogliasingle nucleus rna sequencingenrichment analysistranscriptional regulatory network |
| spellingShingle | CAI Qiangwei SUN Feng WU Wenyu SHAO Fuming GAO Zhengliang JIN Shengkai Transcriptional regulatory network analysis of microglia in multiple sclerosis Shanghai Jiaotong Daxue xuebao. Yixue ban multiple sclerosis microglia single nucleus rna sequencing enrichment analysis transcriptional regulatory network |
| title | Transcriptional regulatory network analysis of microglia in multiple sclerosis |
| title_full | Transcriptional regulatory network analysis of microglia in multiple sclerosis |
| title_fullStr | Transcriptional regulatory network analysis of microglia in multiple sclerosis |
| title_full_unstemmed | Transcriptional regulatory network analysis of microglia in multiple sclerosis |
| title_short | Transcriptional regulatory network analysis of microglia in multiple sclerosis |
| title_sort | transcriptional regulatory network analysis of microglia in multiple sclerosis |
| topic | multiple sclerosis microglia single nucleus rna sequencing enrichment analysis transcriptional regulatory network |
| url | https://xuebao.shsmu.edu.cn/article/2025/1674-8115/1674-8115-2025-45-1-29.shtml |
| work_keys_str_mv | AT caiqiangwei transcriptionalregulatorynetworkanalysisofmicrogliainmultiplesclerosis AT sunfeng transcriptionalregulatorynetworkanalysisofmicrogliainmultiplesclerosis AT wuwenyu transcriptionalregulatorynetworkanalysisofmicrogliainmultiplesclerosis AT shaofuming transcriptionalregulatorynetworkanalysisofmicrogliainmultiplesclerosis AT gaozhengliang transcriptionalregulatorynetworkanalysisofmicrogliainmultiplesclerosis AT jinshengkai transcriptionalregulatorynetworkanalysisofmicrogliainmultiplesclerosis |