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基于GEO数据库对类风湿性关节炎相关基因筛选及生物信息学分析
引用本文:陈龙梅,杨振华. 基于GEO数据库对类风湿性关节炎相关基因筛选及生物信息学分析[J]. 现代检验医学杂志, 2021, 0(2): 49-52. DOI: doi:10.3969/j.issn.1671-7414.2021.02.012
作者姓名:陈龙梅  杨振华
作者单位:(上海市宝山区中西医结合医院检验科,上海 201900)
摘    要:目的 基于生物信息学筛选类风湿性关节炎(rheumatoid arthritis, RA)的差异表达基因,并分析差异表达基因的生物学功能及其调控通路。方法 从GEO(gene expression omnibus)数据库检索并下载了基因芯片GSE94519,通过GEO数据库的在线分析工具GEO2R以P<0.05,|logFC>1.5|为条件筛选RA的差异基因,以DAVID6.8对筛选出的RA差异基因开展GO功能注释和KEGG信号通路富集分析。通过STRING在线分析工具和Cytoscape软件挖掘在RA生物学过程中发挥至关重要作用的关键基因。结果 该研究共发现差异表达基因278个,GO功能在生物学方面主要介导血小板脱颗粒、病毒过程、氧化还原过程和GTPase活性正调节的转导过程,在细胞功能方面主要参与胞外小体、胞浆、薄膜及细胞质的调控,在分子功能方面主要富集于GTPase活性、泛素蛋白连接酶结合、钙黏蛋白结合参与细胞之间的黏附。KEGG的分析RA差异表达的基因结果表明其主要的信号通路是调节氧化磷酸化以及帕金森病,在蛋白互作网络中筛选出10个Hub基因分别为ACTB,RHOA,PPBP,B2M,MT-CYB,PF4,CFL1,MT-ATP6,VCL和TPM1。结论 利用生物信息学和R语言能有效分析GEO数据库的原始基因芯片数据,获得芯片内在的生物学信息;通过关键差异基因分析不仅能识别目前已知的类风湿关节炎相关信号通路,还能发现一些新的通路或生物学过程。

关 键 词:关节炎  类风湿  生物信息学  GEO数据库

Gene Screening and Bioinformatics Analysis of Rheumatoid Arthritis Based on GEO Database
CHEN Long-mei,YANG Zhen-hua. Gene Screening and Bioinformatics Analysis of Rheumatoid Arthritis Based on GEO Database[J]. Journal of Modern Laboratory Medicine, 2021, 0(2): 49-52. DOI: doi:10.3969/j.issn.1671-7414.2021.02.012
Authors:CHEN Long-mei  YANG Zhen-hua
Affiliation:(Department of Clinical Laboratory, the Baoshan District Traditional Chinese and Western Medicine Hospital of Shanghai City, Shanghai 201900, China)
Abstract:Objective To screen differentially expressed genes in rheumatoid arthritis(RA)based on bioinformatics,and analyze the biological function and regulatory pathway of differentially expressed genes.Methods The gene chip GSE94519 was retrieved and downloaded from the gene expression omnibus database(GEO).The differential gene of RA was screened by the online analysis tool GEO2R with P<0.05 and|logFC>1.5|,and the function annotation of GO and enrichment analysis of KEGG signal pathway were carried out by DAVID6.8.The key genes that play an important role in the biological process of RA were mined by string online analysis tool and Cytoscape software.Results In this study,278 differentially expressed genes were found.Go function mainly mediates the processes of platelet degranulation,virus process,redox process and positive regulation of GTPase activity in biology.It mainly participates in the regulation of extracellular corpuscles,cytoplasm,membrane and cytoplasm in cell function,In the aspect of and cytoplasm in cell and cytoplasm in cell function,In the aspect of molecular function,GTPase activity,ubiquitin protein ligase binding and cadherin binding are mainly involved in cell adhesion.KEGG analysis of RA differentially expressed genes showed that the main signaling pathway was to regulate oxidative phosphorylation and Parkinson's disease.There were ten hub genes were screened out among the protein interaction network:ACTB,RHOA,PPBP,B2M,MT-CYB,PF4,CFL1,MT-ATP6,VCL and TPM1.Conclusion Bioinformatics and R language can effectively analyze the original gene chip data of geo database and obtain the biological information inside the chip.Key differential gene analysis can not only identify the known signal pathways of rheumatoid arthritis,but also find some new pathways or biological processes.
Keywords:arthritis  rheumatoid  bioinformatics  GEO database
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