Age-related Changes In Gene Expression Patterns Of Mouse Ovarian Secondary Follicles And Functional Validation Of Selected DEGs

Object: Explore the different gene expression profiles be tween the old a nd young mouse ovarian seconda ry follicles to understand the age-related molecular changes in the process of folliculogenesis.Methods:(1)We performed microarray gene expression profile analysis using total RNA extracted from young(9 weeks old)and old(32 weeks old)mouse ovarian secondary follicles(each with 3 replicate samples)on the Affymetrix Mouse Genome 430 2.0 platfor m.Then the different ially expressed genes(DEGs)between the old and young mouse ovarian secondary follicles were ide ntified.After that,the Gene Ontology(GO)enrichment analysis and KEGG pathway analysis of the DEGs were carried out with the DAVID online tools.And the protein-protein interaction(PPI)network among the DEGs was performed with the Search Tool for the Retrieval of Interacting Genes(STRING)online da tabase and the C ytoscape software.In the end,the gene regulator y network was carried out with the C ytoscape software.(2)We selected some DEGs based on the analys is of the bioinfor matics and relevant background information to perform q RT-PCR.The protein level of CTNNB1 in the 9 weeks old and 32 weeks old mouse ovaris was analysed using IHC(immuno histoc hemistry).And the C TNNB1 was targeted with XAV-939 in the in vitro culture of the mouse ovarian secondary follicles to see its role in the growth of follicles.Results:(1)There were 371 differentially expressed genes between the two groups,while 174 genes were upregulated and 197 genes were downregulated in the secondary follicles from the old mouse ovaries compared to those from the young mouse ovaries.(2)GO term enrichment analysis showed that the upregulated genes were significantly enriched in immune system process in the biological processes and RNA and DNA binding in the molecular function category.While the analysis of the do wnregulated genes revealed that the most significant categories of biological processes were invo lved in transcription and its regulation and molecular functions were involved in protein,RNA and DNA binding.KEGG pa thway analys is showed that most of the upregul ated genes took part in virus related signaling pathway,Toll-like receptor signa ling pathway and RIG-I like receptor signaling pathway.In the meanwhile,downregulated genes mainly participated in PI3K-Akt signaling pathway and Adherens junction.(3)In total,187 nodes and 572 edges were mapped in the PPI network of ide ntifed diferentially expressed genes using STRING with the minimum required interaction score > 0.7.The 10 nodes with highest degree were regarded as hub gene s: Stat1,Ifit1,Ifit3,Irf7,Usp18,Oasl2,Ifit2,Ubc,Ddx58,Ifih1.The most signifcant module with p-value < 0.001 contained 35 nodes and 286 edges.And all genes in the mod ule were upregulated.(4)The ana lysis of the expression of the selected DEGs in t he young and old mouse ovaries reaveled that the expression of these genes except Fos and Stat1 was significantly different between the two groups.And the cha nges of Cyp11a1,H3f3 a,Ranbp9,Ctnnb1,Jun,Crk,Thbs1 and Hspa4 were in accordance to the microarray data,while the changes of Ddx58,Eif2ak2 and Ifih1 were not.(5)The protein level of CTNNB1 was significantly reduced in the 32 weeks old mouse ovarian secondary follicles compared with 9 weeks old mouse ovarian seconda ry follicles.(6)Downregulating CTNNB1 with XAV-939 resulted in the grow th restraction of the in vitro culture mouse ovarian secondary follicles.Conclusion:(1)The folliculogenesis may change signi ficantly in the process of ovarian ageing.(2)The immune system,especially innate immune system may play a vital role in the process of ovarian ageing.(3)The connection between the oocyte and granulose cell may reduce in the proc ess of ovarian ageing causing the growth of follicles abnormal.And this may be one of the underlying mechanisms of ovarian ageing.(4)The ovarian ageing is a complex and integrated process,affected by many biology processes which may interact with each other.So,we can target some genes or biology processes in the same time when we appr oach to intervene the process of ovarian ageing.