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Effect of DNA methylation on gene transcription is associated with the distribution of methylation sites across the genome in osteoarthritis.

ABSTRACT: Genetics and epigenetics are important subjects in the field of osteoarthritis (OA) research. DNA methylation may affect gene transcription, but the specific mechanisms have remained to be fully elucidated. In the present study, the ChAMP methylation analysis package was used to identify differentially methylated genes (DMGs) from the dataset GSE63695 from the Gene Expression Omnibus (GEO) database. The distribution of differentially methylated sites (DMS) and the total array sites across the genome were analyzed by enrichment analysis. Subsequently, two mRNA expression profiling datasets, GSE114007 and GSE113825, were obtained from the GEO database and common differentially expressed genes (DEGs) were identified using the Limma package. Key genes were screened by analyzing the distribution of DMS across the genome consisting of DEGs and DMGs. A total of 1,662 and 1,986 DEGs were identified between OA and normal human cartilage from the GSE113825 and GSE114007 dataset, respectively. A further screening revealed 292 genes with common differences between the two datasets. A total of 574 DMS containing 394 DMGs were observed between OA and normal cartilage. Integrative analysis revealed a corresponding subset of 15 genes. Of these, 6 genes were verified by reverse transcription-quantitative PCR, confirming that the mRNA expression of 5 genes (MAP1B, FNDC1, ANLN, SCNN1A and STC2) in OA cartilage was consistent with the mRNA expression from the analysis of the datasets. Upon treatment with the DNA methylation inhibitor 5-aza-2'-deoxycytidine, the mRNA levels of FNDC1 and SCNN1A were decreased, and no significant alteration in the mRNA levels of MAP1B, ANLN, KCNN4 and STC2 was observed. The incidence of differential methylation varied in subregions of the genome and the effects on transcription were associated with the distribution of DEGs across the genome. The regulation of this appears more complex than initially postulated. Combining the data on epigenetic differences of OA with the genome or transcriptome data for analysis may improve the understanding of the pathophysiological processes of OA. FNDC1 and SCNN1A may potentially be valuable biomarkers for OA.

SUBMITTER: Yi P

PROVIDER: S-EPMC8120505 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objectives Transcriptional changes in cartilage can impact function by causing degradation such as that which occurs during the development of osteoarthritis (OA). Epigenetic regulation may be a key factor leading to transcriptional changes in OA. In this study, we performed a combined analysis of DNA methylation and gene expression microarray datasets and identified key transcription factors (TFs) central to the regulation of gene expression in OA. Methods A DNA methylation profile dataset (GSE63106) and a gene expression profiling dataset (GSE114007) were extracted from the Gene Expression Omnibus (GEO). We used ChAMP methylation analysis and the Limma package to identify differentially methylation genes (DMGs) and differentially expressed genes (DEGs) from normal and human knee cartilage samples in OA. Function enrichment analysis of DMGs was conducted using the DAVID database. A combined analysis of DEGs and DMGs was conducted to identify key TFs in OA. We then validated the mRNA expression of selected TFs in normal and OA cartilage by RT-qPCR. Primary chondrocytes were cultured and treated with the DNA methylation inhibitor 5-Aza-2-deoxycytidine (5-Aza) for functional validation. Results We identified 2,170 differential methylation sites (DMS) containing 1005 genes and 1986 DEGs between normal human and OA cartilage. Functional analysis of DMGs revealed that focal adhesion, extracellular matrix (ECM)-receptor interactions, the PI3K-Akt signaling pathway, and the FoxO signaling pathway were involved in OA. Integrated analysis showed a subset of 17 TFs. Four TFs (ELF3, SOX11, RARA, and FOXD2) were validated. RT-qPCR results showed the mRNA expression of SOX11, RARA, and FOXD2 were consistent with the results from the mRNA expression data. However, the expression of ELF3 could not be validated. Upon 5-Aza-2'-deoxycytidine (5-Aza) treatment, the mRNA levels of ELF3 and SOX11 were down-regulated, whilst RARA was up-regulated, and FOXD2 showed no significant change in expression level. Conclusions the effect of DNA methylation on the transcriptional regulation is related to the distribution of methylated sites across the genome. Epigenetic studies on the positions of DMS in transcriptional units can inform a better understanding of the function of DNA methylation and its transcription regulation.

Project description:BACKGROUND:Osteoarthritis is a chronic musculoskeletal disease characterized by age-related gradual thinning and a high risk in females. Recent studies have shown that DNA methylation plays important roles in osteoarthritis. However, the genome-wide pattern of methylation in enhancers in osteoarthritis remains unclear. METHODS:To explore the function of enhancers in osteoarthritis, we quantified CpG methylation in human enhancers based on a public dataset that included methylation profiles of 470,870 CpG probes in 108 samples from patients with hip and knee osteoarthritis and hip tissues from healthy individuals. Combining various bioinformatics analysis tools, we systematically analyzed aberrant DNA methylation of the enhancers throughout the genome in knee osteoarthritis and hip osteoarthritis. RESULTS:We identified 16,816 differentially methylated CpGs, and nearly half (8111) of them were from enhancers, suggesting major DNA methylation changes in both types of osteoarthritis in the enhancer regions. A detailed analysis of hip osteoarthritis identified 2426 differentially methylated CpGs in enhancers between male and female patients, and 84.5% of them were hypomethylated in female patients and enriched in phenotypes related to hip osteoarthritis in females. Next, we explored the enhancer methylation dynamics among patients with knee osteoarthritis and identified 280 differentially methylated enhancer CpGs that were enriched in the human phenotypes and disease ontologies related to osteoarthritis. Finally, a comparison of enhancer methylation between knee osteoarthritis and hip osteoarthritis revealed organ source-dependent differences in enhancer methylation. CONCLUSION:Our findings indicate that aberrant methylation of enhancers is related to osteoarthritis phenotypes, and a comprehensive atlas of enhancer methylation is useful for further analysis of the epigenetic regulation of osteoarthritis and the development of clinical drugs for treatment of osteoarthritis.

Project description:Although DNA methylation is the best characterized epigenetic mark, the mechanism by which it is targeted to specific regions in the genome remains unclear. Recent studies have revealed that local DNA methylation profiles might be dictated by cis-regulatory DNA sequences that mainly operate via DNA-binding factors. Consistent with this finding, we have recently shown that disruption of CTCF-binding sites by rare single nucleotide variants (SNVs) can underlie cis-linked DNA methylation changes in patients with congenital anomalies. These data raise the hypothesis that rare genetic variation at transcription factor binding sites (TFBSs) might contribute to local DNA methylation patterning. In this work, by combining blood genome-wide DNA methylation profiles, whole genome sequencing-derived SNVs from 247 unrelated individuals along with 133 predicted TFBS motifs derived from ENCODE ChIP-Seq data, we observed an association between the disruption of binding sites for multiple TFs by rare SNVs and extreme DNA methylation values at both local and, to a lesser extent, distant CpGs. While the majority of these changes affected only single CpGs, 24% were associated with multiple outlier CpGs within ±1kb of the disrupted TFBS. Interestingly, disruption of functionally constrained sites within TF motifs lead to larger DNA methylation changes at nearby CpG sites. Altogether, these findings suggest that rare SNVs at TFBS negatively influence TF-DNA binding, which can lead to an altered local DNA methylation profile. Furthermore, subsequent integration of DNA methylation and RNA-Seq profiles from cardiac tissues enabled us to observe an association between rare SNV-directed DNA methylation and outlier expression of nearby genes. In conclusion, our findings not only provide insights into the effect of rare genetic variation at TFBS on shaping local DNA methylation and its consequences on genome regulation, but also provide a rationale to incorporate DNA methylation data to interpret the functional role of rare variants.

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Effect of DNA methylation on gene transcription is associated with the distribution of methylation sites across the genome in osteoarthritis.

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