BACKGROUND: The purpose of present study was to identify the differentially expressed genes (DEGs) associated with BMP-9-induced osteogenic differentiation of mesenchymal stem cells (MSCs) by using bioinformatics methods. METHODS: Gene expression profiles of BMP-9-induced MSCs were compared between with GFP-induced MSCs and BMP-9-induced MSCs. GSE48882 containing two groups of gene expression profiles, 3 GFP-induced MSC samples and 3 from BMP-9-induced MSCs, was downloaded from the Gene Expression Omnibus (GEO) database. Then, DEGs were clustered based on functions and signaling pathways with significant enrichment analysis. Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that the identified DEGs were potentially involved in cytoplasm, nucleus, and extracellular exosome signaling pathway. RESULTS: A total of 1967 DEGs (1029 upregulated and 938 downregulated) were identified from GSE48882 datasets. R/Bioconductor package limma was used to identify the DEGs. Further analysis revealed that there were 35 common DEGs observed between the samples. GO function and KEGG pathway enrichment analysis, among which endoplasmic reticulum, protein export, RNA transport, and apoptosis was the most significant dysregulated pathway. The result of protein-protein interaction (PPI) network modules demonstrated that the Hspa5, P4hb, Sec61a1, Smarca2, Pdia3, Dnajc3, Hyou1, Smad7, Derl1, and Surf4 were the high-degree hub nodes. CONCLUSION: Taken above, using integrated bioinformatical analysis, we have identified DEGs candidate genes and pathways in BMP-9 induced MSCs, which could improve our understanding of the key genes and pathways for BMP-9-induced osteogenic of MSCs.
BACKGROUND: The purpose of present study was to identify the differentially expressed genes (DEGs) associated with BMP-9-induced osteogenic differentiation of mesenchymal stem cells (MSCs) by using bioinformatics methods. METHODS: Gene expression profiles of BMP-9-induced MSCs were compared between with GFP-induced MSCs and BMP-9-induced MSCs. GSE48882 containing two groups of gene expression profiles, 3 GFP-induced MSC samples and 3 from BMP-9-induced MSCs, was downloaded from the Gene Expression Omnibus (GEO) database. Then, DEGs were clustered based on functions and signaling pathways with significant enrichment analysis. Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that the identified DEGs were potentially involved in cytoplasm, nucleus, and extracellular exosome signaling pathway. RESULTS: A total of 1967 DEGs (1029 upregulated and 938 downregulated) were identified from GSE48882 datasets. R/Bioconductor package limma was used to identify the DEGs. Further analysis revealed that there were 35 common DEGs observed between the samples. GO function and KEGG pathway enrichment analysis, among which endoplasmic reticulum, protein export, RNA transport, and apoptosis was the most significant dysregulated pathway. The result of protein-protein interaction (PPI) network modules demonstrated that the Hspa5, P4hb, Sec61a1, Smarca2, Pdia3, Dnajc3, Hyou1, Smad7, Derl1, and Surf4 were the high-degree hub nodes. CONCLUSION: Taken above, using integrated bioinformatical analysis, we have identified DEGs candidate genes and pathways in BMP-9 induced MSCs, which could improve our understanding of the key genes and pathways for BMP-9-induced osteogenic of MSCs.
Authors: Q Kang; M H Sun; H Cheng; Y Peng; A G Montag; A T Deyrup; W Jiang; H H Luu; J Luo; J P Szatkowski; P Vanichakarn; J Y Park; Y Li; R C Haydon; T-C He Journal: Gene Ther Date: 2004-09 Impact factor: 5.250