Construction of dynamic ceRNA regulatory networks in osteogenesis during fracture healing based on transcriptomic analysis

Fracture healing is a complex biological process. This study aimed to investigate the key molecules involved in fracture healing and their potential competing endogenous RNA (ceRNA) regulatory mechanisms within the first 28 days post-fracture using bioinformatics methods. The experiment was conducted on 15 adult male SD rats, with tibia callus tissue samples collected at days 0, 3, 7, 14, and 28 (n = 3) post-fracture. RNA-Seq was used for high-throughput transcriptome sequencing, followed by differential expression analysis to identify differentially expressed genes (DEGs), long non-coding RNA (DELs), and microRNA (DEMs) at different stages. Protein-protein interaction (PPI) networks were constructed using the STRING database and visualized with Cytoscape. GO and KEGG enrichment analyses were performed to explore potential biological mechanisms. miRNA-mRNA interactions were predicted using TargetScan, miRWalk, and miRDB, while RNA22 v2 was used for lncRNA-miRNA interactions. These interactions were integrated into ceRNA networks. Finally, qRT-PCR validated key molecules within the ceRNA network. We identified 4,997 DEGs, 315 DELs, and 89 DEMs at day 3; 5,087 DEGs, 300 DELs, and 84 DEMs at day 7; 3,073 DEGs, 235 DELs, and 68 DEMs at day 14; and 2,609 DEGs, 197 DELs, and 90 DEMs at day 28. Further analysis revealed hub osteogenic genes and their ceRNA regulatory networks at each time point. The networks consisted of 2 mRNAs, 3 miRNAs, and 9 lncRNAs at day 3; 2 mRNAs, 3 miRNAs, and 8 lncRNAs at days 7 and 14; and 1 mRNA, 3 miRNAs, and 10 lncRNAs at day 28. We validated two key lncRNAs (AABR07030366.1 and AABR07057997.1) along with their interacting miRNAs and mRNAs: rno-miR-9a-5p/Col9a1 (day 3), rno-miR-181c-5p/Comp (day 7), rno-miR-423-5p/Col1a1 (day 14), and rno-miR-185-5p/Ctsk (day 28). In summary, our study leveraged bioinformatics to construct ceRNA networks involved in osteogenesis post-fracture, offering insights into their dynamic regulatory role in healing and underlying molecular mechanisms.

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Publication Details

Journal
Scientific Reports
Published
2025-07-24
DOI
https://doi.org/10.1038/s41598-025-12505-6
Citations
1
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.94

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article

Construction of dynamic ceRNA regulatory networks in osteogenesis during fracture healing based on transcriptomic analysis

Xiaofeng Yin, Xinyi Zeng, Xinyi Gu, Chen Huang et al.
1 citations
Scientific Reports
Cancer-related molecular mechanisms research
0.94
article

Construction of dynamic ceRNA regulatory networks in osteogenesis during fracture healing based on transcriptomic analysis

Xiaofeng Yin, Xinyi Zeng, Xinyi Gu, Chen Huang, Shen Wang, Shuhang Guo, Qingguo Lü, Jin Deng, Shaoxun Yuan
article en
1 citations

Abstract

Fracture healing is a complex biological process. This study aimed to investigate the key molecules involved in fracture healing and their potential competing endogenous RNA (ceRNA) regulatory mechanisms within the first 28 days post-fracture using bioinformatics methods. The experiment was conducted on 15 adult male SD rats, with tibia callus tissue samples collected at days 0, 3, 7, 14, and 28 (n = 3) post-fracture. RNA-Seq was used for high-throughput transcriptome sequencing, followed by differential expression analysis to identify differentially expressed genes (DEGs), long non-coding RNA (DELs), and microRNA (DEMs) at different stages. Protein-protein interaction (PPI) networks were constructed using the STRING database and visualized with Cytoscape. GO and KEGG enrichment analyses were performed to explore potential biological mechanisms. miRNA-mRNA interactions were predicted using TargetScan, miRWalk, and miRDB, while RNA22 v2 was used for lncRNA-miRNA interactions. These interactions were integrated into ceRNA networks. Finally, qRT-PCR validated key molecules within the ceRNA network. We identified 4,997 DEGs, 315 DELs, and 89 DEMs at day 3; 5,087 DEGs, 300 DELs, and 84 DEMs at day 7; 3,073 DEGs, 235 DELs, and 68 DEMs at day 14; and 2,609 DEGs, 197 DELs, and 90 DEMs at day 28. Further analysis revealed hub osteogenic genes and their ceRNA regulatory networks at each time point. The networks consisted of 2 mRNAs, 3 miRNAs, and 9 lncRNAs at day 3; 2 mRNAs, 3 miRNAs, and 8 lncRNAs at days 7 and 14; and 1 mRNA, 3 miRNAs, and 10 lncRNAs at day 28. We validated two key lncRNAs (AABR07030366.1 and AABR07057997.1) along with their interacting miRNAs and mRNAs: rno-miR-9a-5p/Col9a1 (day 3), rno-miR-181c-5p/Comp (day 7), rno-miR-423-5p/Col1a1 (day 14), and rno-miR-185-5p/Ctsk (day 28). In summary, our study leveraged bioinformatics to construct ceRNA networks involved in osteogenesis post-fracture, offering insights into their dynamic regulatory role in healing and underlying molecular mechanisms.

Scientific ReportsVol. 15(1)
Nanjing University of Chinese Medicine (CN), Peking University (CN), Peking University People's Hospital (CN)
National Natural Science Foundation of China, Peking University, Peking University People's Hospital
Zero hunger
Openalex Percentile: Top 22%
Cancer-related molecular mechanisms research
0.94
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