摘要
目的通过生物信息学方法分析有氧运动对人骨骼肌全基因组表达的影响及其促进健康的分子机制。方法从美国国立生物技术信息中心(NCBI)公共基因芯片数据平台(GEO)下载GSE9103 mRNA基因芯片数据集,对股外侧肌活检样本进行骨骼肌转录谱分析,样本来源包括10例年轻久坐者、10例老年久坐者、10例年轻训练者和10例老年训练者。采用R语言"limma"函数包筛选差异表达基因(DEGs),设定阈值为logFC≥1且P<0.05。然后用DAVID数据库对靶基因进行GO和KEGG信号通路富集分析,进一步应用STRING数据库构建蛋白质相互作用网络,应用cytoscape对模块中的基因的共表达关系进行可视化以及筛选关键基因。结果年轻组和老年组共筛选出41个DEGs,GO分析显示DEGs生物学功能主要涉及细胞对饥饿的反应、乳酸代谢过程、细胞生长调节,KEGG分析显示DEGs主要和胰高血糖素信号通路、细胞紧密连接和单磷酸腺苷活化蛋白激酶(AMPK)信号通路有关。蛋白质相互作用网络筛选出THRSP、MYH8、MYH1、PDK4、IGFN1、CALML6、PRKAG3、G0S2、ACTN3和FOXO1共10个关键基因。结论生物信息学技术能有效筛选和分析有氧运动与久坐者相关DEGs,为进一步探讨有氧运动对机体的作用机制及靶点提供思路。
Objective To analyze the molecular mechanisms underlying the effects of aerobic exercise in human skeletal muscles,based on network pharmacology and bioinformatic methods.Methods The human mRNA gene chip dataset GSE9103 was downloaded from the common gene chip data platform(gene expression omnibus)from the National Center for Biotechnology Information.Differentially expressed mRNAs were screened using the“Limma”package that is based on R language.Gene ontology(GO)and KEGG signal pathway enrichment analyses were performed using the Database for Annotation,Visualization,and Integrated Discovery.The protein-protein interaction(PPI)network was constructed using the String-db database,and hub genes were obtained using Cytoscape.Results The mRNA gene chip data set GSE9103 showed that 41 mRNAs were differentially expressed(fold change≥2.0,adj.P<0.05).GO analysis indicated that several functional pathways,such as cellular responses to starvation,lactate metabolic processes,and cell growth regulation pathways were enriched.KEGG pathway analysis showed that a few related pathways,including glucagon signaling pathway,tight junction,and the AMPK signaling pathway were involved.Ten hub genes(THRSP,MYH8,MYH1,PDK4,IGFN1,CALML6,PRKAG3,G0S2,ACTN3,and FOXO1)were obtained from the PPI network.Conclusion Bioinformatic methods for screening related differentially expressed genes can provide a new way to better understand the molecular mechanisms underlying the effects of aerobic exercise,by shedding light on the molecular rationale for health remedies.
作者
王子璐
刘立民
孙晓
WANG Zilu;LIU Limin;SUN Xiao(Section of Sports,China Medical University,Shenyang 110122,China;Department of Pharmacy,Shengjing Hospital,China Medical University,Shenyang 110004,China)
出处
《中国医科大学学报》
CAS
CSCD
北大核心
2020年第6期556-560,共5页
Journal of China Medical University
关键词
有氧运动
基因表达
蛋白质相互作用网络
生物信息学
aerobic exercise
gene expression
protein-protein interaction network
bioinformatics