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Bone & Joint Research
Vol. 12, Issue 7 | Pages 433 - 446
7 Jul 2023
Guo L Guo H Zhang Y Chen Z Sun J Wu G Wang Y Zhang Y Wei X Li P

Aims

To explore the novel molecular mechanisms of histone deacetylase 4 (HDAC4) in chondrocytes via RNA sequencing (RNA-seq) analysis.

Methods

Empty adenovirus (EP) and a HDAC4 overexpression adenovirus were transfected into cultured human chondrocytes. The cell survival rate was examined by real-time cell analysis (RTCA) and EdU and flow cytometry assays. Cell biofunction was detected by Western blotting. The expression profiles of messenger RNAs (mRNAs) in the EP and HDAC4 transfection groups were assessed using whole-transcriptome sequencing (RNA-seq). Volcano plot, Gene Ontology, and pathway analyses were performed to identify differentially expressed genes (DEGs). For verification of the results, the A289E/S246/467/632 A sites of HDAC4 were mutated to enhance the function of HDAC4 by increasing HDAC4 expression in the nucleus. RNA-seq was performed to identify the molecular mechanism of HDAC4 in chondrocytes. Finally, the top ten DEGs associated with ribosomes were verified by quantitative polymerase chain reaction (QPCR) in chondrocytes, and the top gene was verified both in vitro and in vivo.


Bone & Joint Research
Vol. 12, Issue 2 | Pages 147 - 154
20 Feb 2023
Jia Y Qi X Ma M Cheng S Cheng B Liang C Guo X Zhang F

Aims

Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD.

Methods

We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects.


Bone & Joint Research
Vol. 7, Issue 4 | Pages 298 - 307
1 Apr 2018
Zhang X Bu Y Zhu B Zhao Q Lv Z Li B Liu J

Objectives

The aim of this study was to identify key pathological genes in osteoarthritis (OA).

Methods

We searched and downloaded mRNA expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) of joint synovial tissues from OA and normal individuals. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were used to assess the function of identified DEGs. The protein-protein interaction (PPI) network and transcriptional factors (TFs) regulatory network were used to further explore the function of identified DEGs. The quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the result of bioinformatics analysis. Electronic validation was performed to verify the expression of selected DEGs. The diagnosis value of identified DEGs was accessed by receiver operating characteristic (ROC) analysis.