【摘要】 为探索牛卵巢膜细胞（TCs）和大黄体细胞（LLCs）的差异表达基因并揭示其中潜在的生理关系，从NCBI中GEO(GENE EXPRESSION OMNIBUS)数据库中获取GSE83524芯片数据，并利用R软件limma包中的DESeq2进行数据分析，以筛选出TCs和卵巢黄体中LLCs之间的差异性表达基因；使用DAVID软件对上述所获得的差异性表达基因分别进行GO功能富集分析和KEGG信号通路分析；利用String数据库和Cytoscape软件构建了差异表达基因之间的蛋白互作网络（PPI），并通过Cyto-Hubba插件中的MCC算法筛选出连通度最大的前10位的关键基因，结合数据库查找出卵泡发育相关的候选基因。结果显示，经DESeq2分析后，共获得差异性表达基因228个（上调基因143个，下调基因85个）；GO功能富集分析结果显示，富集到生物学过程、细胞组分及分子功能的差异表达基因分别占比33.8%、55.7%和10.5%;KEGG信号通路分析共获得18条信号通路，其中，HTLV-I感染通路中基因富集最多（16个）；PPI网络互作分析并筛选出了连通度最大的前10位的关键基因；进一步通过数据库查找发现PRLR、COL1A1、INHA、GREB1和CYP19A1分别在卵泡发育过程中发挥着重要的作用。本研究结果为进一步探究卵泡膜细胞黄体化以及牛卵泡发育的分子机制奠定基础。更多还原

【Abstract】 To explore the potential physiological relationship between bovine ovarian theca cells(TCs) and large luteal cells(LLCs), we analyzed the differentially expressed genes between the two cells using bioinformatics. The GSE83524 chip data was obtained from the GEO(GENE EXPRESSION OMNIBUS) database in NCBI. Then, R DESeq2 in R software limma was employed to screen differentially expressed genes between TCs and LLCs from GSE83524 chip data. Next, DAVID software was used to analyze GO function enrichment and KEGG signal pathway of the differentially expressed genes obtained; The protein interaction network(PPI) between differentially expressed genes was constructed using String database and Cytoscape software. Finally, the top 10 key genes with the highest connectivity were screened through the MCC algorithm in the Cyto Hubba plug-in and Candidate genes related to follicular development were found according to the database. The results showed that 228 differentially expressed genes(143 up-regulated genes and 85 down-regulated genes) were obtained through DESeq2analysis; The results of GO function enrichment analysis showed that the differentially expressed genes of biological processes,cell components and molecular functions accounted for 33.8%, 55.7% and 10.5% respectively; The results of KEGG signal pathway analysis showed that 18 signal pathways were obtained, mainly focusing on HTLV-I infection pathway. Further analysis of the top 10 key genes screened from PPI network interaction analysis showed that PRLR, COL1A1, INHA, GREB1and CYP19A1 played an important role in follicular development. These results provide a basis for exploring the molecular mechanism of TCs and the development of LLCs.更多还原