Identification of Differentially Expressed Genes and Molecular Pathways Involved in Osteoclastogenesis Using RNA-seq

Abstract

Osteoporosis is a disease that is characterised by reduced bone mineral density (BMD) and can be exacerbated by the excessive bone resorption of osteoclasts (OCs). Bioinformatic methods, including functional enrichment and network analysis, can provide information about the underlying molecular mechanisms that participate in the progression of osteoporosis. In this study, we harvested human OC-like cells differentiated in culture and their precursor peripheral blood mononuclear cells (PBMCs) and characterised the transcriptome of the two cell types using RNA-sequencing in order to identify differentially expressed genes. Differential gene expression analysis was performed in RStudio using the edgeR package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to identify enriched GO terms and signalling pathways, with inter-connected regions characterised using protein–protein interaction analysis. In this study, we identified 3201 differentially expressed genes using a 5% false discovery rate; 1834 genes were upregulated, whereas 1367 genes were downregulated. We confirmed a significant upregulation of several well-established OC genes including CTSK, DCSTAMP, ACP5, MMP9, ITGB3, and ATP6V0D2. The GO analysis suggested that upregulated genes are involved in cell division, cell migration, and cell adhesion, while the KEGG pathway analysis highlighted oxidative phosphorylation, glycolysis and gluconeogenesis, lysosome, and focal adhesion pathways. This study provides new information about changes in gene expression and highlights key biological pathways involved in osteoclastogenesis.

Transcriptional reprogramming during human osteoclast differentiation identifies regulators of osteoclast activity

“…f Principal component analysis plot based on genes with differential (FDR < 0.000 1 between at least two timepoints) and reproducible (≥6 donors with Pearson’s correlation >0.8 to the average) expression during human osteoclast differentiation. g Heatmap showing the Pearson correlation for log twofold changes in gene expression during osteoclast differentiation according to Rashid et al 20 h Scatter plot comparing the log twofold changes between OC-like cells and PBMCs from Rashid et al 20 with log twofold changes occurring between Day 9 and Day 2 of osteoclast differentiation in the present study. Genes were selected based on upregulation (FDR < 0.01) within expression data from Rashid et al 20 .…”

“…g Heatmap showing the Pearson correlation for log twofold changes in gene expression during osteoclast differentiation according to Rashid et al 20 h Scatter plot comparing the log twofold changes between OC-like cells and PBMCs from Rashid et al 20 with log twofold changes occurring between Day 9 and Day 2 of osteoclast differentiation in the present study. Genes were selected based on upregulation (FDR < 0.01) within expression data from Rashid et al 20 . i Box plot (band: mean; box: first and third quartiles; whiskers: 1.5 times the interquartile range) of RNA-seq-based gene expression levels for solute carrier family 6 member 7 ( SLC6A7 ) in the present study (left panel) and from Rashid et al 20 (right panel) …”

“…Genes were selected based on upregulation (FDR < 0.01) within expression data from Rashid et al 20 . i Box plot (band: mean; box: first and third quartiles; whiskers: 1.5 times the interquartile range) of RNA-seq-based gene expression levels for solute carrier family 6 member 7 ( SLC6A7 ) in the present study (left panel) and from Rashid et al 20 (right panel) …”

Hydroxychavicol Inhibits In Vitro Osteoclastogenesis via the Suppression of NF-κB Signaling Pathway

“…The induction of osteoclast-specific genes, including DC-STAMP, cathepsin K, and MMP-9, are essential for osteoclast maturation ( Rashid et al ., 2023 ). DC-STAMP plays a key role in the fusion of mononuclear precursor cells into multinuclear osteoclasts ( Langdahl, 2021 ).…”

A novel proteomic signature of osteoclast differentiation unveils the deubiquitinase UCHL1 as a necessary osteoclastogenic driver

“…While this model offers a valuable reductionist surrogate of OC progenitors, substantial differences exist 45 , as exemplified by deregulated, M-CSF-independent proliferation of transformed monocytes, which limit its value and prompt to employ primary BMMs to investigate physiologic OCgenesis. Moreover, few comprehensive phenotypic studies of OCs have been conducted through proteomics 45 , 46 , while most rely exclusively on transcriptomic profiling 47 – 49 . We thus reasoned that a thorough characterization of the proteome phenotypic layer assessed dynamically at different stages of OC differentiation would add valuable insight.…”