Chinese Journal of Tissue Engineering Research ›› 2024, Vol. 28 ›› Issue (36): 5811-5816.doi: 10.12307/2024.698
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Linghu Xitao1, Gui Jiaqi2, Liang Zhuozhi2, Wa Qingde1, Huang Shuai2
Received:
2023-10-23
Accepted:
2023-12-04
Online:
2024-12-28
Published:
2024-02-27
Contact:
Huang Shuai, PhD, Associate chief physician, Associate professor, Doctoral supervisor, Department of Orthopedics, Second Affiliated Hospital of Guangzhou Medical University, Guangzhou 510260, Guangdong Province, China
About author:
Linghu Xitao, Master, Physician, Department of Orthopedics, Second Affiliated Hospital of Zunyi Medical University, Zunyi 563000, Guizhou Province, China
Supported by:
CLC Number:
Linghu Xitao, Gui Jiaqi, Liang Zhuozhi, Wa Qingde, Huang Shuai. Bioinformatics analysis of m6A-associated genes in steroid-induced osteonecrosis of the femoral head[J]. Chinese Journal of Tissue Engineering Research, 2024, 28(36): 5811-5816.
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2.2 DEGs的GO功能富集及KEGG通路富集分析结果 对差异表达基因的GO和KEGG富集分析结果进行筛选,富集结果中BP,CC,MF及KEGG通路分别有307,44,18,15条。其中BP主要富集在细胞因子产生的正向调节、骨髓细胞分化、髓细胞发育、活性氧代谢过程、骨髓细胞稳态等条目,CC主要富集在分泌颗粒膜、特定颗粒、富含ficolin-1的颗粒、内吞囊泡、细胞质囊泡腔、富含ficolin-1的颗粒管腔等条目,MF主要富集在免疫受体活性、细胞因子受体活性、C-C趋化因子受体活性、氧化还原酶活性、趋化因子受体及趋化因子结合等条目,见图2A,B。KEGG通路富集结果显示,DEGs主要与破骨细胞分化(P < 0.001)、趋化因子信号通路(P < 0.001)及核转录因子κB信号通路(P < 0.05)等有关。"
2.4 m6A-DEGs基因相关性及GO/KEGG通路富集分析结果 对上述14个激素性股骨头坏死中表达差异的m6A-DEGs进行了Spearman相关性分析,结果显示14个m6A-DEGs存在一定的相关性,其中正相关性最高的是YTHDC2与HNRNPA2B1 (Cor=0.929),负相关性最高的是HNRNPC与ALKBH5(Cor=-0.672),见图4A。此外,对14个m6A-DEGs基因进行了GO/KEGG通路富集分析,共富集到生物学过程245个条目、 细胞组分17个条目、 分子功能41个条目和KEGG 通路10个条目。GO分析结果中BP主要包括了mRNA代谢过程的调控、mRNA稳定性调控、RNA稳定性调节、骨髓细胞分化、骨髓细胞发育,CC主要包括了分泌颗粒膜、特殊颗粒、富含ficolin-1的颗粒,MF主要包括了模式识别受体活性剂、免疫受体活性、细胞因子受体活性,KEGG包括了IL-17信号通路、AMPK信号通路等,结果见图4B,C及表3。"
2.5 m6A-DEGs基因PPI网络及TF-m6A-miRNA预测分析结果 将14个m6A-DEGs基因导入在线工具STRING中,根据score分数> 0.04进行筛选,将在线结果导入Cytoscape软件中绘制PPI 网络图,该网络图包括14个节点和85条交互关系,见图5A。使用Degree算法筛选出连接关系前7个基因作为核心基因:YTHDF1,YTHDF2,YTHDF3,ALKBH5,HNRNPA2B1,HNRNPC及METTL3(Degree度值均为13),见图5B。利用miRTarBase,miRDB,TargetScan数据库预测7个核心基因潜在的miRNA并作交集分析,在3个数据库中共筛选出44个miRNA,交集基因可视化结果见图5C。利用ChIPBase及hTFtarget数据库预测7个核心基因潜在转录因子并作交集分析,共筛选出79个TF,交集结果可视化结果见图5D。"
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