骨质疏松hub基因筛选验证及互作miRNA预测

doi:10.11958/20220418

天津医药 ›› 2022, Vol. 50 ›› Issue (11): 1158-1164.doi: 10.11958/20220418

骨质疏松hub基因筛选验证及互作miRNA预测

张亦朦¹(), 张宇新¹^,^△(), 田发明¹

1 华北理工大学基础医学院（邮编063201）
2 公共卫生学院

收稿日期:2022-03-29 修回日期:2022-04-26 出版日期:2022-11-15 发布日期:2022-11-11
通讯作者: 张宇新 E-mail:1263870659@qq.com;jpzyx@163.com
作者简介:张亦朦（1993），男，硕士在读，主要从事人体解剖与组织胚胎学和生物信息学分析方面研究。E-mail：1263870659@qq.com
基金资助:
河北省自然科学基金面上项目(H2019209550);河北省青年拔尖人才支持项目(JI-2016-10)

The analysis and verification of osteoporosis associated hub genes and prediction of miRNA interactions

ZHANG Yimeng¹(), ZHANG Yuxin¹^,^△(), TIAN Faming¹

1 School of Basic Medical Sciences, Tangshan 063201, China
2 School of Public Health, North China University of Science and Technology, Tangshan 063201, China

Received:2022-03-29 Revised:2022-04-26 Published:2022-11-15 Online:2022-11-11
Contact: ZHANG Yuxin E-mail:1263870659@qq.com;jpzyx@163.com

张亦朦, 张宇新, 田发明. 骨质疏松hub基因筛选验证及互作miRNA预测[J]. 天津医药, 2022, 50(11): 1158-1164.

ZHANG Yimeng, ZHANG Yuxin, TIAN Faming. The analysis and verification of osteoporosis associated hub genes and prediction of miRNA interactions[J]. Tianjin Medical Journal, 2022, 50(11): 1158-1164.

摘要/Abstract

摘要：

目的筛选老年性骨质疏松症hub基因及其互作的miRNA。方法从GEO数据库下载GSE35956基因芯片数据集，利用R语言筛选骨质疏松症患者骨髓间充质干细胞中的差异表达基因（Degs）。利用DAVID数据库对Degs进行GO富集和KEGG通路分析。采用String数据库和Cytoscape软件分析蛋白互作网络，筛选hub基因。通过Targetscan数据库预测与hub基因存在互作关系的miRNA，并通过funrich数据库对预测出的miRNA进行富集分析。提取并培养3~4月龄（青年组）和18~20月龄（老年组）C57BL/6小鼠的骨髓间充质干细胞，采用荧光定量PCR（qPCR）验证2组小鼠的骨髓间充质干细胞中hub基因表达情况。结果骨质疏松症患者骨髓间充质干细胞中共鉴定出982个上调的Degs和99个下调的Degs。Degs主要富集到质膜黏附分子介导的同型细胞黏附和钙离子结合等生物过程，主要参与了神经活性配体-受体相互作用信号通路。PPI互作网络分析筛选出8个核心基因：瘦素（LEP）、淋巴细胞特异性蛋白酪氨酸激酶（LCK）、WT1转录因子（WT1）、SRY-Box转录因子10（SOX10）、整合素β2（ITGB2）、白蛋白（ALB）、胆囊收缩素（CCK）和骨形态发生蛋白7（BMP7）。Targetscan 预测了105个miRNA和其中6个核心基因存在互作关系。qPCR验证结果表明，老年组小鼠骨髓间充质干细胞中BMP7、CCK、ITGB2、SOX10基因表达水平较青年组上调，与生物信息学分析结果相一致。结论筛选出的核心基因表达水平与老年小鼠骨髓间充质干细胞分化程度相关，鉴定得到的miRNA可能成为老年性骨质疏松症诊断标志物及治疗靶点。

关键词: 骨质疏松, 计算生物学, 微RNAs, 骨髓间充质干细胞, 蛋白互作

Abstract:

Objective To screen hub genes and miRNA interaction in aging osteoporosis. Methods The GSE35956 gene chip data set was downloaded from GEO database, and the differentially expressed genes (Degs) in bone marrow mesenchymal stem cells were screened by R language in patients with osteoporosis. GO enrichment and KEGG pathway were analyzed in Degs using DAVID database. String database and Cytoscape software were used to analyze the protein interaction network and screen hub genes. The mirnas interacting with hub genes were predicted by Targetscan database, and the predicted mirnas were enriched by funrich database. Bone marrow mesenchymal stem cells from 3 to 4 month-old (the young group) and 18 to 20 month-old (the old group) in C57BL/6 mice were extracted and cultured. The expression levels of miRNA in bone marrow mesenchymal stem cells were verified by qPCR technique in the young and the old groups. Results A total of 982 up-regulated Degs and 99 down-regulated degs were identified in patients with osteoporosis. Degs were mainly enriched in plasma membrane adhesion molecule-mediated homologous cell adhesion and calcium ion binding, and were mainly involved in neuroactive ligand-receptor interaction signaling pathways. PPI interaction network analysis identified eight core genes: leptin (LEP), lymphocyte-specific protein tyrosine kinase (LCK), WT1 transcription factor (WT1), SRY-box transcription factor 10 (SOX10), integrin subunit beta 2 (ITGB2), albumin (ALB), cholecystokinin (CCK) and bone morphogenetic protein 7（BMP7). The interaction between 105 miRNA and 6 core genes was predicted by Trargetscan. qPCR results showed that BMP7, CCK, ITGB2 and SOX10 genes in bone marrow mesenchymal stem cells were significantly up-regulated in the old group compared with those of the young group. It is consistent with the results of bioinformatics analysis. Conclusion The expression levels of the selected core genes are related to the differentiation degree of bone marrow mesenchymal stem cells in aged mice. The identified miRNA may be a diagnostic marker and a therapeutic target for aging osteoporosis.

Key words: osteoporosis, computational biology, microRNAs, bone marrow mesenchymal stem cells, protein-protein interaction

中图分类号:

R681.4

图/表 7

表1 qPCR引物序列

Tab.1 Primer sequence for qPCR

基因名称	引物序列（5'→3'）	产物大小（bp）
SOX10	上游：CAAGCTCTGGAGCTGA	92
SOX10	下游：CCGGATGGTCCTTTTTGTGC	92
BMP7	上游：GCTCCAAGACGCCAAAGAAC	144
BMP7	下游：GTGCAATGATCCAGTCCTGC	144
ITGB2	上游：CTGGTGCCAGAAGCTGAACT	119
ITGB2	下游：TGCTCCTGGGGTCCATGATA	119
CCK	上游：GAAGCTACGGACCCCGTG	150
CCK	下游：CACCATCCATGCCACTTTGC	150
GAPDH	上游：GATGCTGGTGCTGAGTATGRCG	23
GAPDH	下游：GTGGTGCAGGATGCATTGCTCTGA	23

图1 差异基因火山图及表达水平分析 A：差异基因火山图；B：前20位Degs。

Fig.1 The volcano plot and expression profiles of Degs

图2 差异基因的GO和KEGG富集分析 A：GO功能富集分析；B：KEGG通路富集分析。

Fig.2 GO and KEGG annotations of Degs

图3 核心基因与miRNA互作网络图

Fig.3 Key genes-miRNA interaction network diagram of differential genes

图4 预测miRNA的GO和KEGG富集分析 A：分子功能富集；B：细胞组分富集；C：生物过程富集；D：KEGG富集分析。

Fig.4 GO and KEGG annotations of predicted miRNA

图5 小鼠骨髓间充质干细胞的培养（×40）

Fig.5 The cultivation of bone marrow mesenchymal stem cells (×40)

表2 2组小鼠BMP7、CCK、ITGB2、SOX10基因表达水平比较 (n=3, $\bar{x}\pm s$)

Tab.2 Comparison of expression levels of BMP7, CCK, ITGB2 and SOX10 genes between the two groups of mice

组别	BMP7	CCK	ITGB2	SOX10
青年组	1.00±0.00	1.00±0.00	1.00±0.00	1.00±0.00
老年组	4.24±0.31	3.93±0.38	2.08±0.25	2.92±0.46
t	23.373^＊＊	17.340^＊＊	9.650^＊＊	9.257^＊＊

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骨质疏松hub基因筛选验证及互作miRNA预测

The analysis and verification of osteoporosis associated hub genes and prediction of miRNA interactions

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