Open AccessInsight into the potential pathogenesis of human osteoarthritis via single-cell RNA sequencing data on osteoblasts
Author(s) -
Changxiang Huan,
Jiaxin Gao
Publication year - 2022
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2022297
Subject(s) - kegg , biology , microrna , gene , gene expression profiling , gene expression , computational biology , genetics , bioinformatics , transcriptome
Osteoarthritis (OA) is the most common degenerative joint disease caused by osteoblastic lineage cells. However, a comprehensive molecular program for osteoblasts in human OA remains underdeveloped. The single-cell gene expression of osteoblasts and microRNA array data were from human. After processing the single-cell RNA sequencing (scRNA-seq) data, it was subjected to principal component analysis (PCA) and T-Stochastic neighbor embedding analysis (TSNE). Differential expression analysis was aimed to find marker genes. Gene-ontology (GO) enrichment, Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis and Gene set enrichment analysis (GSEA) were applied to characterize the molecular function of osteoblasts with marker genes. Protein–protein interaction (PPI) networks and core module were established for marker genes by using the STRING database and Cytoscape software. All nodes in the core module were considered to be hub genes. Subsequently, we predicted the potential miRNA of hub genes through the miRWalk, miRDB and TargetScan database and experimentally verified the miRNA by GSE105027. Finally, miRNA-mRNA regulatory network was constructed using the Cytoscape software. We characterized the single-cell expression profiling of 4387 osteoblasts from normal and OA sample. The proportion of osteoblasts subpopulations changed dramatically in the OA, with 70.42% of the pre-osteoblasts. 117 marker genes were included and the results of GO analysis show that up-regulated marker genes enriched in collagen-containing extracellular matrix were highly expressed in the pre-osteoblasts cluster. Both KEGG and GSEA analyses results indicated that IL-17 and NOD-like receptor signaling pathways were enriched in down-regulated marker genes. We visualize the weight of marker genes and constructed the core module in PPI network. In potential mRNA-miRNA regulatory network, hsa-miR-449a and hsa-miR-218-5p may be involved in the development of OA. Our study found that alterations in osteoblasts state and cellular molecular function in the subchondral bone region may be involved in the pathogenesis of osteoarthritis.