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目的 通过生物信息学方法分析非梗阻性无精子症(NOA)和正常男性睾丸间质细胞中的差异表达基因及其核心基因。方法 采用生物信息学方法整合GEO(http://www.ncbi.nlm.nih.gov/geo)中的GSE149512数据集，选取无生精障碍的人群为正常组，NOA患者为NOA组。运用R软件(版本4.02)中的Seurat包(版本4.0)整合分析GSE149512的数集，并采用非线性降维UMAP的方法进行细胞聚类分析；通过Find All Markers函数，获取细胞聚类的Marker基因，并查询Human Cell Landscape(HCL)数据库进行细胞注释，并绘制差异表达基因的可视化热图；运用Cytoscape软件(3.6.1版)的ClueGO和CluePedia插件对差异基因的进行GO功能富集和KEGG通路分析；通过String数据库(http://string-db.org),构建差异基因的PPI网络；运用CytoHubba插件中的5种运算方法(Degree、DMNC、EPC、MCC、MNC)识别PPI网络中的核心基因并绘制韦恩图。结果 整合GSE149512数据集，最终形成1个由39 392个细胞、40 210个基因、31个聚类细胞构成的数据集，其中，NOA组有17 415个细胞、正常组有21 977个细胞。通过Find All Markers函数识别聚类细胞的Marker基因发现，NOA组的细胞主要由体细胞构成，其睾丸间质细胞占比最高，为44.4%(7 736/17 415);分析两组研究对象睾丸间质细胞共得到145个差异表达基因，与正常组相比较，NOA组82个基因上调、63个基因下调。GO富集分析结果显示，在生物学过程方面，睾丸间质细胞发挥作用较多，且在免疫抗原提呈功能方面也发挥着重要作用；在细胞组分方面，主要在细胞膜、胞质和核糖体中发挥作用；在分子功能方面，主要发挥细胞周期蛋白激酶的调控、核苷核酸的链接等作用。KEGG通路分析结果显示，主要通过病毒感染、炎症细胞因子等通路发挥显著作用。PPI网络结果显示，差异表达基因构建了158个点和2 132条边的蛋白互作网络，识别出RPS11等10个核心基因。结论 本研究通过生物信息学方法显示了NOA患者睾丸间质细胞中的差异表达基因及核心基因，为后续探讨NOA的新机制奠定了基础。
Abstract：Objective:To analyze differentially expressed genes and their core genes in testicular interstitial cells between non-obstructive azoospermia(NOA) and normal men by using bioinformatics methods. Methods:A bioinformatics approach was used to integrate the GSE149512 dataset in GEO(http://www.ncbi.nlm.nih.gov/geo),selecting individuals without spermatogenic disorders as the normal group, and NOA patients as the NOA group. The number set of GSE149512 were integrated and analyzed by using the Seurat package(version 4.0) in R software(version 4.02),and cell clustering analysis was performed by using nonlinear dimensionality reduction UMAP method. Marker genes for cell clustering were obtained by using the Find All Markers function, and the Human Cell Landscape(HCL) database was inquired for cell annotation, and a visual heatmap of differentially expressed genes was drawn. ClueGO and CluePedia plugins of Cytoscape software(version 3.6.1) was used for GO functional enrichment and KEGG pathway analysis of differential genes. PPI network for differentially expressed genes was constructed through the String database(http://string-db.org). The five computational methods(Degree, DMNC,EPC,MCC,MNC) in the CytoHubba plugin were used to identify core genes in the PPI network, and Wayne diagram was drawn.Results:Integrating the GSE149512 dataset, a dataset consisting of 39 392 cells, 40 210 genes, and 31 clustered cells was formed. Among them, there were 17 415 cells in the NOA group and 2 1977 cells in the normal group. By using the Find All Markers function to identify the Marker genes of clustered cells, it was found that the cells in the NOA group were mainly composed of somatic cells, with the highest proportion of testicular interstitial cells at 44.4%(7 736/17 415). A total of 145 differentially expressed genes were identified in the testicular interstitial cells of two groups of patients. Compared with the normal group, 82 genes were upregulated and 63 genes were downregulated in the NOA group. GO enrichment analysis results showed that testicular interstitial cells played a more important role, and also played an important role in immune antigen presentation function in terms of biological processes. In terms of cell composition, it mainly played a role in the cell membrane, cytoplasm, and ribosome. In terms of molecular function, it mainly played a role in regulating cell cycle protein kinase and linking nucleoside nucleic acids. KEGG pathway analysis results showed that it mainly played a significant role through pathways such as viral infection and inflammatory cytokines. PPI network results showed that differentially expressed genes constructed a protein interaction network with 158 points and 2 132 edges, identifying 10 core genes such as RPS11.Conclusions:This study reveals differentially expressed genes and core genes in testicular interstitial cells of NOA patients by using bioinformatics methods, laying the foundation for further exploration of new mechanisms of NOA.
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基本信息:
中图分类号:R698.2
引用信息:
[1]薛雨非,师帅,柳祖波,等.非梗阻性无精子症与正常人睾丸间质细胞差异表达基因及核心基因的生物信息学分析[J].生殖医学杂志,2023,32(10):1534-1543.
2023-10-15
2023-10-15