基于生物信息学分析多囊卵巢综合征中影响卵巢生长发育的关键差异基因
Analysis of key differential genes affecting ovarian growth and development in polycystic ovary syndrome based on bioinfor-matics
沈蓓蕾 1李娜 1李聚学 2刘煜1
作者信息
- 1. 南京医科大学附属逸夫医院内分泌科,江苏南京 211166
- 2. 南京医科大学生物化学与分子生物学系,江苏南京 211166
- 折叠
摘要
目的 采用生物信息学方法从基因表达数据库(gene expression omnibus,GEO)中分析发掘有关多囊卵巢综合征(polycystic ovarian syndrome,PCOS)的重要基因并对其进行富集分析,为研究PCOS的发病机制提供新的靶点.方法 首先从GEO数据库选取两个数据集(GSE171431和GSE59456),使用R语言进行差异分析并获取两个数据集共有的差异基因,然后进行基因本体论(Gene Ontology,GO)和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)分析.根据差异倍数和卵巢功能相关(例如排卵、细胞凋亡、卵泡生长和黄体形成等)筛选出候选关键差异基因,构建了 PCOS小鼠模型并用实时定量聚合酶链反应(real-time quantitative polymerase chain reaction,RT-qPCR)法验证这些基因.最后运用比较毒理基因组学数据库(Comparative Toxicogenomics Data-base,CTD)查找与基因相关的疾病.结果 本研究从两个数据集中筛选出27个共有差异基因,根据差异倍数和卵巢功能确定4个下调基因为候选关键差异基因,分别为分泌卷曲相关蛋白4(secreted frizzled-related protein 4,Sfrp4)、信号素 3D(Semaphorin-3D,Sema3d)、FK506 结合蛋白 5(FK506 binding protein 5,Fkbp5)和丝氨酸蛋白酶 35(serine protease 35,Prss35),并在小鼠mRNA水平获得验证.此外,CTD数据库结果显示这些基因与生殖疾病关系密切.结论 应用生物信息学技术筛选获得的与PCOS发生发展的4个差异基因,分别是Sfrp4,Sema3d,Fkbp5,Prss35,它们与细胞增殖分化、卵泡生长、排卵及代谢稳态有关.这些候选基因为深入探究PCOS的发病机制提供了相关的前期基础.
Abstract
Objective Bioinformatics methods were applied to excavate important genes related to polycystic ovary syndrome from the GEO database.We analyze their biological function to provide theoretical basis for the diagnosis,treatment and prognosis of PCOS.Methods We selected two data sets(GSE171431 and GSE59456)from the GEO da-tabase.Using R language to screen DEGs and obtain common genes of the two data sets,and then perform GO and KEGG enrichment.Some genes were screened based on fold change and ovarian function(such as ovulation,apoptosis,follicle growth and luteal formation,etc.).We constructed a PCOS mouse model.Then these genes were verified using real-time quantitative polymerase chain reaction(RT-qPCR)in this model.Finally,the Comparative Toxicogenomics Da-tabase(CTD)was used to find correlations between genes and diseases.Results Twenty-seven common genes were screened from the two data sets and four down-regulated genes including Sfrp4,Sema3d,Fkbp5,Prss35 were selected based on fold difference and ovarian function.Real-time quantitative PCR(RT-qPCR)was used to verify these genes.In addition,the results of CTD database show that these genes are closely related to reproductive diseases.Conclusion Bioinformatics technology was applied to explore four related genes that may be involved in the occurrence and develop-ment of PCOS,namely Sfrp4,Sema3d,Fkbp5 and Prss35,which are related to cell proliferation and differentiation,follicular growth,ovulation and metabolic homeostasis.This finding provides theoretical basis for further research on the pathogenesis of PCOS.
关键词
多囊卵巢综合征/生物信息学/差异表达基因/富集分析Key words
polycystic ovarian syndrome/bioinformation/differentially expressed genes/enrichment analysis引用本文复制引用
基金项目
国家重点研发计划(2022YFA0806103)
南京医科大学科技发展基金一般项目(NMUB20220049)
出版年
2024
NETL
NSTL
万方数据