Analysis of mRNA Expression and DNA Methylation Datasets According to the Genomic Distribution of CpG Sites in Osteoarthritis

Abstract 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.

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DDR1 methylation is associated with bipolar disorder and the isoform expression and methylation of myelin genes

Epigenomics ◽

10.2217/epi-2021-0006 ◽

2021 ◽

Author(s):

Beatriz Garcia-Ruiz ◽

Manuel Castro de Moura ◽

Gerard Muntané ◽

Lourdes Martorell ◽

Elena Bosch ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Bipolar Disorder ◽

Mrna Expression ◽

Gene Expression Analysis ◽

Mrna Levels ◽

Healthy Controls ◽

Genome Wide ◽

Isoform Expression

Aim: To investigate DDR1 methylation in the brains of bipolar disorder (BD) patients and its association with DDR1 mRNA levels and comethylation with myelin genes. Materials & methods: Genome-wide profiling of DNA methylation (Infinium MethylationEPIC BeadChip) corrected for glial composition and DDR1 gene expression analysis in the occipital cortices of individuals with BD (n = 15) and healthy controls (n = 15) were conducted. Results: DDR1 5-methylcytosine levels were increased and directly associated with DDR1b mRNA expression in the brains of BD patients. We also observed that DDR1 was comethylated with a group of myelin genes. Conclusion: DDR1 is hypermethylated in BD brain tissue and is associated with isoform expression. Additionally, DDR1 comethylation with myelin genes supports the role of this receptor in myelination.

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Integrated DNA Methylation and Gene Expression Analysis Identified S100A8 and S100A9 in the Pathogenesis of Obesity

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.631650 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ningyuan Chen ◽

Liu Miao ◽

Wei Lin ◽

Donghua Zou ◽

Ling Huang ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Mrna Expression ◽

Regulatory Networks ◽

Enrichment Analysis ◽

Microarray Dataset ◽

Functional Enrichment Analysis ◽

Normal Subjects ◽

Functional Enrichment ◽

Differentially Methylated Genes

Background: To explore the association of DNA methylation and gene expression in the pathology of obesity.Methods: (1) Genomic DNA methylation and mRNA expression profile of visceral adipose tissue (VAT) were performed in a comprehensive database of gene expression in obese and normal subjects. (2) Functional enrichment analysis and construction of differential methylation gene regulatory networks were performed. (3) Validation of the two different methylation sites and corresponding gene expression was done in a separate microarray dataset. (4) Correlation analysis was performed on DNA methylation and mRNA expression data.Results: A total of 77 differentially expressed mRNAs matched with differentially methylated genes. Analysis revealed two different methylation sites corresponding to two unique genes—s100a8-cg09174555 and s100a9-cg03165378. Through the verification test of two interesting different expression positions [differentially methylated positions (DMPs)] and their corresponding gene expression, we found that methylation in these genes was negatively correlated to gene expression in the obesity group. Higher S100A8 and S100A9 expressions in obese subjects were validated in a separate microarray dataset.Conclusion: This study confirmed the relationship between DNA methylation and gene expression and emphasized the important role of S100A8 and S100A9 in the pathogenesis of obesity.

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Integrated DNA Methylation and Gene Expression Analysis Identified S100A8 and S100A9 in the Pathogenesis of Obesity

10.21203/rs.3.rs-68833/v1 ◽

2020 ◽

Author(s):

Ningyuan Chen ◽

Liu Miao ◽

Wei Lin ◽

Dong-Hua Zhou ◽

Ling Huang ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Mrna Expression ◽

Microarray Data ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Normal Subjects ◽

Functional Enrichment ◽

Data Set ◽

Differentially Methylated Genes

Abstract Background: To explore the association of DNA methylation and gene expression in the pathology of obesity.Methods: (1) Genomic DNA methylation and mRNA expression profile of visceral adipose tissue (VAT) were performed in a comprehensive database of gene expression in obese and normal subjects; (2) functional enrichment analysis and construction of differential methylation gene regulatory network were performed; (3) Validation of the two different methylation sites and corresponding gene expression was done in a separate microarray data set; and (4) correlation analysis was performed on DNA methylation and mRNA expression data.Results: A total of 77 differentially expressed mRNA matched with differentially methylated genes. Analysis revealed two different methylation sites corresponding to two unique genes-s100a8-cg09174555 and s100a9-cg03165378. Through the verification test of two interested different expression positions (DMPS) and their corresponding gene expression, we found that the methylation in these genes was negatively correlated to gene expression in the obesity group. Higher S100A8 and S100A9 expression in obese subjects were validated in a separate microarray data set.Conclusion: This study confirmed the relationship between DNA methylation and gene expression and emphasized the important role of S100A8 and S100A9 in the pathogenesis of obesity.

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Use of integrative epigenetic and mRNA expression analyses to identify significantly changed genes and functional pathways in osteoarthritic cartilage

Bone and Joint Research ◽

10.1302/2046-3758.75.bjr-2017-0284.r1 ◽

2018 ◽

Vol 7 (5) ◽

pp. 343-350 ◽

Cited By ~ 6

Author(s):

A. He ◽

Y. Ning ◽

Y. Wen ◽

Y. Cai ◽

K. Xu ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Mrna Expression ◽

Expression Profiles ◽

Enrichment Analysis ◽

Signalling Pathway ◽

Pathway Enrichment Analysis ◽

Osteoarthritic Cartilage ◽

Pathway Enrichment ◽

Genome Wide

Aim Osteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage. Patients and Methods Genome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Results We identified 1265 differentially methylated genes, of which 145 are associated with significant changes in gene expression, such as DLX5, NCOR2 and AXIN2 (all p-values of both DNA methylation and mRNA expression < 0.05). Pathway enrichment analysis identified 26 OA-associated pathways, such as mitogen-activated protein kinase (MAPK) signalling pathway (p = 6.25 × 10-4), phosphatidylinositol (PI) signalling system (p = 4.38 × 10-3), hypoxia-inducible factor 1 (HIF-1) signalling pathway (p = 8.63 × 10-3 pantothenate and coenzyme A (CoA) biosynthesis (p = 0.017), ErbB signalling pathway (p = 0.024), inositol phosphate (IP) metabolism (p = 0.025), and calcium signalling pathway (p = 0.032). Conclusion We identified a group of genes and biological pathwayswhich were significantly different in both DNA methylation and mRNA expression profiles between patients with OA and controls. These results may provide new clues for clarifying the mechanisms involved in the development of OA. Cite this article: A. He, Y. Ning, Y. Wen, Y. Cai, K. Xu, Y. Cai, J. Han, L. Liu, Y. Du, X. Liang, P. Li, Q. Fan, J. Hao, X. Wang, X. Guo, T. Ma, F. Zhang. Use of integrative epigenetic and mRNA expression analyses to identify significantly changed genes and functional pathways in osteoarthritic cartilage. Bone Joint Res 2018;7:343–350. DOI: 10.1302/2046-3758.75.BJR-2017-0284.R1.

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Integrated DNA methylation and gene expression analysis identified S100A8 and S100A9 in the pathogenesis of obesity

10.21203/rs.3.rs-68833/v2 ◽

2020 ◽

Author(s):

Ningyuan Chen ◽

Liu Miao ◽

Wei Lin ◽

Dong-Hua Zhou ◽

Ling Huang ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Mrna Expression ◽

Microarray Data ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Normal Subjects ◽

Functional Enrichment ◽

Data Set ◽

Differentially Methylated Genes

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Regulation of gene expression by the APP family in the adult cerebral cortex

Scientific Reports ◽

10.1038/s41598-021-04027-8 ◽

2022 ◽

Vol 12 (1) ◽

Author(s):

Hye Ji Cha ◽

Jie Shen ◽

Jongkyun Kang

Keyword(s):

Gene Expression ◽

Cerebral Cortex ◽

Target Genes ◽

Regulation Of Gene Expression ◽

Mrna Levels ◽

Rna Seq ◽

Cellular Functions ◽

Organization Learning ◽

Transcriptional Changes

AbstractAmyloid precursor protein (APP) is associated with both familial and sporadic forms of Alzheimer’s disease. APP has two homologs, amyloid precursor-like protein 1 and 2 (APLP1 and APLP2), and they have functional redundancy. APP intracellular c-terminal domain (AICD), produced by sequential α- or β- and γ-secretase cleavages, is thought to control gene expression, similarly as the ICD of Notch. To investigate the role of APP family in transcriptional regulation, we examined gene expression changes in the cerebral cortex of APP/APLP1/APLP2 conditional triple knockout (cTKO) mice, in which APP family members are selectively inactivated in excitatory neurons of the postnatal forebrain. Of the 12 previously reported AICD target genes, only Nep and Npas4 mRNA levels were significantly reduced in the cerebral cortex of cTKO mice, compared to littermate controls. We further examined global transcriptional changes by RNA-seq and identified 189 and 274 differentially expressed genes in the neocortex and hippocampus, respectively, of cTKO mice relative to controls. Gene Ontology analysis indicated that these genes are involved in a variety of cellular functions, including extracellular organization, learning and memory, and ion channels. Thus, inactivation of APP family alters transcriptional profiles of the cerebral cortex and affects wide-ranging molecular pathways.

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Integrative blood-derived epigenetic and transcriptomic analysis reveals the potential regulatory role of DNA methylation in ankylosing spondylitis

Arthritis Research & Therapy ◽

10.1186/s13075-021-02697-3 ◽

2022 ◽

Vol 24 (1) ◽

Author(s):

Min Xiao ◽

Xuqi Zheng ◽

Xiaomin Li ◽

Xinyu Wu ◽

Yefei Huang ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Cell Differentiation ◽

Ankylosing Spondylitis ◽

Mrna Expression ◽

Signaling Pathway ◽

Th17 Cell ◽

Tcr Signaling ◽

Th17 Cell Differentiation ◽

Independent Cohort

Abstract Background The currently known risk loci could explain a small proportion of the heritability of ankylosing spondylitis (AS). Epigenetics might account for the missing heritability. We aimed to seek more novel AS-associated DNA methylation alterations and delineate the regulatory effect of DNA methylation and gene expression with integrated analysis of methylome and transcriptome. Methods Epigenome-wide DNA methylation and mRNA expression were profiled in peripheral blood mononuclear cells (PBMCs) from 45 individuals (AS: health controls (HCs) = 30:15) with high-throughput array. The methylome was validated in an independent cohort (AS: HCs = 12:12). Pearson correlation analysis and causal inference tests (CIT) were conducted to determine potentially causative regulatory effects of methylation on mRNA expression. Results A total of 4794 differentially methylated positions (DMPs) were identified associated with AS, 2526 DMPs of which were validated in an independent cohort. Both cohorts highlighted T cell receptor (TCR) signaling and Th17 differentiation pathways. Besides, AS patients manifested increased DNA methylation variability. The methylation levels of 158 DMPs were correlated with the mRNA expression levels of 112 genes, which formed interconnected network concentrated on Th17 cell differentiation and TCR signaling pathway (LCK, FYN, CD3G, TCF7, ZAP70, CXCL12, and PLCG1). We also identified several cis-acting DNA methylation and gene expression changes associated with AS risk, which might regulate the cellular mechanisms underlying AS. Conclusions Our studies outlined the landscapes of epi-signatures of AS and several methylation-gene expression-AS regulatory axis and highlighted the Th17 cell differentiation and TCR signaling pathway, which might provide innovative molecular targets for therapeutic interventions for AS.

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Integrated Analysis of DNA Methylation and mRNA Expression Profiles Data to Identify Key Genes in Lung Adenocarcinoma

BioMed Research International ◽

10.1155/2016/4369431 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 10

Author(s):

Xiang Jin ◽

Xingang Liu ◽

Xiaodan Li ◽

Yinghui Guan

Keyword(s):

Dna Methylation ◽

Lung Adenocarcinoma ◽

Mrna Expression ◽

Early Stage ◽

Expression Profiles ◽

Enrichment Analysis ◽

Integrated Analysis ◽

Tissue Samples ◽

Ppi Networks ◽

Key Genes

Introduction. Lung adenocarcinoma (LAC) is the most frequent type of lung cancer and has a high metastatic rate at an early stage. This study is aimed at identifying LAC-associated genes.Materials and Methods. GSE62950 downloaded from Gene Expression Omnibus included a DNA methylation dataset and an mRNA expression profiles dataset, both of which included 28 LAC tissue samples and 28 adjacent normal tissue samples. The differentially expressed genes (DEGs) were screened by Limma package in R, and their functions were predicted by enrichment analysis using TargetMine online tool. Then, protein-protein interaction (PPI) network was constructed using STRING and Cytoscape. Finally, LAC-associated methylation sites were identified by CpGassoc package in R and mapped to the DEGs to obtain LAC-associated DEGs.Results. Total 913 DEGs were identified in LAC tissues. In the PPI networks,MAD2L1,AURKB,CCNB2,CDC20,andWNT3Ahad higher degrees, and the first four genes might be involved in LAC through interaction. Total 8856 LAC-associated methylation sites were identified and mapped to the DEGs. And there were 29 LAC-associated methylation sites located in 27 DEGs (e.g.,SH3GL2,BAI3,CDH13,JAM2,MT1A,LHX6,andIGFBP3).Conclusions. These key genes might play a role in pathogenesis of LAC.

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Integrated analysis of DNA methylome and transcriptome reveals the differences in biological characteristics of porcine mesenchymal stem cells

BMC Genomic Data ◽

10.1186/s12863-021-01016-8 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Zheng Feng ◽

Yalan Yang ◽

Zhiguo Liu ◽

Weimin Zhao ◽

Lei Huang ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Stem Cells ◽

Mesenchymal Stem Cells ◽

Expression Profiles ◽

Adipogenic Differentiation ◽

Enrichment Analysis ◽

Biological Characteristics ◽

Integrated Analysis ◽

Differentiation Potential

Abstract Background Bone marrow (BM) and umbilical cord (UC) are the main sources of mesenchymal stem cells (MSCs). These two MSCs display significant differences in many biological characteristics, yet the underlying regulation mechanisms of these cells remain largely unknown. Results BMMSCs and UCMSCs were isolated from inbred Wuzhishan miniature pigs and the first global DNA methylation and gene expression profiles of porcine MSCs were generated. The osteogenic and adipogenic differentiation ability of porcine BMMSCs is greater than that of UCMSCs. A total of 1979 genes were differentially expressed and 587 genes were differentially methylated at promoter regions in these cells. Integrative analysis revealed that 102 genes displayed differences in both gene expression and promoter methylation. Gene ontology enrichment analysis showed that these genes were associated with cell differentiation, migration, and immunogenicity. Remarkably, skeletal system development-related genes were significantly hypomethylated and upregulated, whereas cell cycle genes were opposite in UCMSCs, implying that these cells have higher cell proliferative activity and lower differentiation potential than BMMSCs. Conclusions Our results indicate that DNA methylation plays an important role in regulating the differences in biological characteristics of BMMSCs and UCMSCs. Results of this study provide a molecular theoretical basis for the application of porcine MSCs in human medicine.

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Global hypermethylation of intestinal epithelial cells is a hallmark feature of neonatal surgical necrotizing enterocolitis

Clinical Epigenetics ◽

10.1186/s13148-020-00983-6 ◽

2020 ◽

Vol 12 (1) ◽

Author(s):

Misty Good ◽

Tianjiao Chu ◽

Patricia Shaw ◽

Lora McClain ◽

Austin Chamberlain ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Epithelial Cell ◽

Necrotizing Enterocolitis ◽

Regulation Of Gene Expression ◽

Intestinal Epithelial ◽

Genome Bisulfite Sequencing ◽

Transcriptional Changes ◽

Considerable Impact ◽

Genomic Regions

Abstract Background Necrotizing enterocolitis (NEC) remains one of the overall leading causes of death in premature infants, and the pathogenesis is unpredictable and not well characterized. The aim of our study was to determine the molecular phenotype of NEC via transcriptomic and epithelial cell-specific epigenomic analysis, with a specific focus on DNA methylation. Methods Using laser capture microdissection, epithelial cell-specific methylation signatures were characterized by whole-genome bisulfite sequencing of ileal and colonic samples at the time of surgery for NEC and after NEC had healed at reanastomosis (n = 40). RNA sequencing was also performed to determine the transcriptomic profile of these samples, and a comparison was made to the methylome data. Results We found that surgical NEC has a considerable impact on the epigenome by broadly increasing DNA methylation levels, although these effects are less pronounced in genomic regions associated with the regulation of gene expression. Furthermore, NEC-related DNA methylation signatures were influenced by tissue of origin, with significant differences being noted between colon and ileum. We also identified numerous transcriptional changes in NEC and clear associations between gene expression and DNA methylation. Conclusions We have defined the intestinal epigenomic and transcriptomic signatures during surgical NEC, which will advance our understanding of disease pathogenesis and may enable the development of novel precision medicine approaches for NEC prediction, diagnosis and phenotyping.

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