Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis
Abstract 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 b...
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doaj-584b8577b8dc40bb9c2fcdc5668c63722021-04-25T11:29:20ZengBMCJournal of Orthopaedic Surgery and Research1749-799X2021-04-0116111010.1186/s13018-021-02390-wIdentification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysisJia-qi Wu0Lin-bo Mao1Ling-feng Liu2Yong-mei Li3Jian Wu4Jiao Yao5Feng-huan Zhang6Ting-yu Liu7Ling Yuan8Rehabilitation Department, Jingjiang People’s HospitalRehabilitation Department, Jingjiang People’s HospitalRehabilitation Department, Jingjiang People’s HospitalRehabilitation Department, Jingjiang People’s HospitalInstitute Office, Jingjiang People’s HospitalRehabilitation Department, Jingjiang People’s HospitalRehabilitation Department, Jingjiang People’s HospitalRehabilitation Department, Jingjiang People’s HospitalRehabilitation Department, Jingjiang People’s HospitalAbstract 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.https://doi.org/10.1186/s13018-021-02390-wDifferentially expressed genesBMP-9Mesenchymal stem cellsEnrichment analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jia-qi Wu Lin-bo Mao Ling-feng Liu Yong-mei Li Jian Wu Jiao Yao Feng-huan Zhang Ting-yu Liu Ling Yuan |
spellingShingle |
Jia-qi Wu Lin-bo Mao Ling-feng Liu Yong-mei Li Jian Wu Jiao Yao Feng-huan Zhang Ting-yu Liu Ling Yuan Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis Journal of Orthopaedic Surgery and Research Differentially expressed genes BMP-9 Mesenchymal stem cells Enrichment analysis |
author_facet |
Jia-qi Wu Lin-bo Mao Ling-feng Liu Yong-mei Li Jian Wu Jiao Yao Feng-huan Zhang Ting-yu Liu Ling Yuan |
author_sort |
Jia-qi Wu |
title |
Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis |
title_short |
Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis |
title_full |
Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis |
title_fullStr |
Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis |
title_full_unstemmed |
Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis |
title_sort |
identification of key genes and pathways of bmp-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis |
publisher |
BMC |
series |
Journal of Orthopaedic Surgery and Research |
issn |
1749-799X |
publishDate |
2021-04-01 |
description |
Abstract 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. |
topic |
Differentially expressed genes BMP-9 Mesenchymal stem cells Enrichment analysis |
url |
https://doi.org/10.1186/s13018-021-02390-w |
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