背景:骨髓间充质干细胞(BMSCs)成骨和成脂分化过程中RNA甲基化的调控机制尚未完全了解。我们研究的目的是分析和验证RNA甲基化调节剂对大鼠BMSCs成骨和成脂分化的潜在机制的贡献。
方法:我们从基因表达综合(GEO)下载了GSE186026。在R软件(版本3.6.3)中使用DESeq2包筛选差异表达基因(DEGs)。从文献综述和总结中获得的共50个RNA甲基化基因与以前的DEGs交叉获得RNA甲基化基因,它们具有不同的表达式(RM-DEG)。利用基因本体论(GO)分析和京都基因和基因组百科全书(KEGG)分析来揭示功能富集。进行定量实时聚合酶链反应(qRT-PCR)以验证RM-DEGs。使用STRING和Cytoscape进行蛋白质-蛋白质相互作用网络(PPI)分析和视觉分析。构建RM-DEGs调控网络,分析前10个hub基因。RM-DEG之间的关系,还分析了一些富集的GO和途径。通过使用miRWalk和TargetScan建立miRNA和RM-DEGs调控网络。
结果:作为我们研究的一部分,我们检测到m6A调节因子Mettl3和Rbm15以及m7G调节因子Mettl1和Wdr4的不同表达水平,与成骨分化有关,与m6A调节因子Fmr1一起参与成脂分化。构建了49个与成骨分化过程中RNA甲基化相关的差异表达基因(DEGs)的蛋白质-蛋白质相互作用(PPI)网络,和13个DEGs用于成脂分化。此外,计算了top10个hub基因。在成骨分化中,Mettl3通过调控Smad3调控Wnt通路和Hippo通路,Rbm15通过Notch1调控Notch通路,Mettl1通过Gnb4调控PI3K-Akt通路。在成脂分化中,Fmr1通过Egfr调控PI3K-Akt通路。预测Smad3、Notch1和Gnb4的M6A甲基化位点,结果显示这三个基因都可能被m6A甲基化,每个基因超过9个位点可能被甲基化。最后,我们构建了Mettl3、Rbm15、Mettl1、Wdr4和109个miRNAs在成骨分化中的调控网络,Fmr1和118miRNAs在成脂分化中的作用。
结论:Mettl3(m6A),Rbm15(m6A),Wdr4和Mettl1(m7G)在成骨分化中差异表达,而Fmr1(m6A)在成脂分化中差异表达。这些发现为进一步研究RNA甲基化参与BMSCs成骨和成脂分化提供了潜在的候选者。
BACKGROUND: The regulatory mechanisms of RNA methylation during the processes of osteogenic and adipogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) have yet to be fully understood. The objective of our study was to analyze and validate the contribution of RNA methylation regulators to the mechanisms underlying the osteogenic and adipogenic differentiation of rat BMSCs.
METHODS: We downloaded the GSE186026 from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened using the DESeq2 package in R software (version 3.6.3). A total of 50 RNA methylation genes obtained from literature review and summary were intersected with the previous DEGs to obtain RNA methylation genes, which have different expressions (RM-DEGs). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were utilized to reveal the functional enrichment. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate RM-DEGs. Protein-protein interaction network (PPI) analysis and visual analysis were performed using STRING and Cytoscape. RM-DEGs regulatory network was constructed to analyze the top 10 hub genes. The relationship between RM-DEGs, some enriched GO and pathways was also been analyzed. The miRNAs and RM-DEGs regulatory networks were established by using miRWalk and TargetScan.
RESULTS: As part of our research, we detected varying levels of expression for m6A regulators Mettl3 and Rbm15, as well as m7G regulators Mettl1 and Wdr4, in relation to osteogenic differentiation, along with m6A regulator Fmr1 in adipogenic differentiation. The protein-protein interaction (PPI) networks were constructed for 49 differentially expressed genes (DEGs) related to RNA methylation during the process of osteogenic differentiation, and 13 DEGs for adipogenic differentiation. Moreover, top10 hub genes were calculated. In osteogenic differentiation, Mettl3 regulated the Wnt pathway and Hippo pathway by regulating Smad3, Rbm15 regulated the Notch pathway by Notch1, Mettl1 regulated the PI3K-Akt pathway by Gnb4. In adipogenic differentiation, Fmr1 regulated the PI3K-Akt pathway by Egfr. M6A methylation sites of Smad3, Notch1 and Gnb4 were predicted, and the results showed that all three genes were possibly methylated by m6A, and more than 9 sites per gene were possibly methylated. Finally, we constructed the regulatory networks of Mettl3, Rbm15, Mettl1, and Wdr4 and 109 miRNAs in osteogenic differentiation, Fmr1 and 118 miRNAs in adipogenic differentiation.
CONCLUSIONS: Mettl3(m6A), Rbm15(m6A), Wdr4 and Mettl1(m7G) were differentially expressed in osteogenic differentiation, while Fmr1(m6A) was differentially expressed in adipogenic differentiation. These findings offered potential candidates for further research on the involvement of RNA methylation in the osteogenic and adipogenic differentiation of BMSCs.