RNA sequencing analysis of FGF2-responsive transcriptome in skin fibroblasts
2021
Background Fibroblast growth factor 2 (FGF2) is a highly pleiotropic cytokine with antifibrotic activity in wound healing. During the process of wound healing and fibrosis, fibroblasts are the key players. Although accumulating evidence has suggested the antagonistic effects of FGF2 in the activation process of fibroblasts, the mechanisms by which FGF2 hinders the fibroblast activation remains incompletely understood. This study aimed to identify the key genes and their regulatory networks in skin fibroblasts treated with FGF2. Methods RNA-seq was performed to identify the differentially expressed mRNA (DEGs) and lncRNA between FGF2-treated fibroblasts and control. DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, the networks between mRNAs and lncRNAs were constructed by Pearson correlation analysis and the networkanalyst website. Finally, hub genes were validated by real time-PCR. Results Between FGF2-treated fibroblasts and control fibroblasts, a total of 1475 DEGs was obtained. These DEGs were mainly enriched in functions such as the ECM organization, cell adhesion, and cell migration. They were mainly involved in ECM-receptor interaction, PI3K-Akt signaling, and the Hippo pathway. The hub DEGs included COL3A1, COL4A1, LOX, PDGFA, TGFBI, and ITGA10. Subsequent real-time PCR, as well as bioinformatics analysis, consistently demonstrated that the expression of ITGA10 was significantly upregulated while the other five DEGs (COL3A1, COL4A1, LOX, PDGFA, TGFBI) were downregulated in FGF2-treated fibroblasts. Meanwhile, 213 differentially expressed lncRNAs were identified and three key lncRNAs (HOXA-AS2, H19, and SNHG8) were highlighted in FGF2-treated fibroblasts. Conclusion The current study comprehensively analyzed the FGF2-responsive transcriptional profile and provided candidate mechanisms that may account for FGF2-mediated wound healing.
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
35
References
0
Citations
NaN
KQI