Integrative Analysis Of DNA Methylation Research Articles

Altered methylation of imprinted genes in neuroblastoma: implications for prognostic refinement

BackgroundNeuroblastoma (NB) is a complex disease, and the current understanding of NB biology is limited. Deregulation in genomic imprinting is a common event in malignancy. Since imprinted genes play crucial roles in early fetal growth and development, their role in NB pathogenesis could be suggested.MethodsWe examined alterations in DNA methylation patterns of 369 NB tumours at 49 imprinted differentially methylated regions (DMRs) and assessed its association with overall survival probabilities and selected clinical and genomic features of the tumours. In addition, an integrated analysis of DNA methylation and allele-specific copy number alterations (CNAs) was performed, to understand the correlation between the two molecular events.ResultsSeveral imprinted regions with aberrant methylation patterns in NB were identified. Regions that underwent loss of methylation in > 30% of NB samples were DMRs annotated to the genes NDN, SNRPN, IGF2, MAGEL2 and HTR5A and regions with gain of methylation were NNAT, RB1 and GPR1. Methylation alterations at six of the 49 imprinted DMRs were statistically significantly associated with reduced overall survival: MIR886, RB1, NNAT/BLCAP, MAGEL2, MKRN3 and INPP5F. RB1, NNAT/BLCAP and MKRN3 were further able to stratify low-risk NB tumours i.e. tumours that lacked MYCN amplification and 11q deletion into risk groups. Methylation alterations at NNAT/BLCAP, MAGEL2 and MIR886 predicted risk independently of MYCN amplification or 11q deletion and age at diagnosis. Investigation of the allele-specific CNAs demonstrated that the imprinted regions that displayed most alterations in NB tumours harbor true epigenetic changes and are not result of the underlying CNAs.ConclusionsAberrant methylation in imprinted regions is frequently occurring in NB tumours and several of these regions have independent prognostic value. Thus, these could serve as potentially important clinical epigenetic markers to identify individuals with adverse prognosis. Incorporation of methylation status of these regions together with the established risk predictors may further refine the prognostication of NB patients.

Integrated Genome-Wide Analysis of DNA Methylation and Gene Expression in the Hippocampi of 5xFAD Alzheimer's Disease Mouse Model.

DNA methylation forms 5-methylcytosine and its regulation in the hippocampus is critical for learning and memory. Indeed, dysregulation of DNA methylation is associated with neurological diseases. Alzheimer's disease (AD) is the predominant of dementia and a neurodegenerative disorder. We examined the learning and memory function in 3- and 9-month-old wild-type and 5xfamiliar Alzheimer's disease (5xFAD) transgenic mice by performing the object recognition memory and Y-maze tests, and identified the hippocampal amyloid beta burden. To investigate the epigenetically regulated genes involved in the development or neuropathology of AD, we performed genome-wide DNA methylation sequencing and RNA sequencing analyses in the hippocampus of 9-month-old wild-type and 5xFAD tg mice. To validate the genes inversely regulated by epigenetics, we confirmed their methylation status and mRNA levels. At 9 months of age, 5xFAD tg mice showed significant cognitive impairment and amyloid-beta plaques in the hippocampus. DNA methylation sequencing identified a total of 13,777 differentially methylated regions, including 4484 of hyper- and 9293 of hypomethylated regions, that are associated with several gene ontology (GO) terms including 'nervous system development' and 'axon guidance'. In RNA sequencing analysis, we confirmed a total of 101 differentially expressed genes, including 52 up- and 49 downregulated genes, associated with GO functions such as 'positive regulation of synaptic transmission, glutamatergic' and 'actin filament organization'. Through further integrated analysis of DNA methylation and RNA sequencing, three epigenetically regulated genes were selected: thymus cell antigen 1, theta (Thy1), myosin VI (Myo6), and filamin A-interacting protein 1-like (Filip1l). The methylation level of Thy1 decreased and its mRNA levels increased, whereas that of Myo6 and Filip1l increased and their mRNA levels decreased. The common functions of these three genes may be associated with the neural cytoskeleton and synaptic plasticity. We suggest that the candidate genes epigenetically play a role in AD-associated neuropathology (i.e., amyloid-beta plaques) and memory deficit by influencing neural structure and synaptic plasticity. Furthermore, counteracting dysregulated epigenetic changes may delay or ameliorate AD onset or symptoms.

Integrative Multi-Omics Analysis for Etiology Classification and Biomarker Discovery in Stroke: Advancing towards Precision Medicine.

Recent advancements in high-throughput omics technologies have opened new avenues for investigating stroke at the molecular level and elucidating the intricate interactions among various molecular components. We present a novel approach for multi-omics data integration on knowledge graphs and have applied it to a stroke etiology classification task of 30 stroke patients through the integrative analysis of DNA methylation and mRNA, miRNA, and circRNA. This approach has demonstrated promising performance as compared to other existing single technology approaches.

Hypomethylation of ATP1A1 Is Associated with Poor Prognosis and Cancer Progression in Triple-Negative Breast Cancer.

Dysregulated DNA methylation in cancer is critical in the transcription machinery associated with cancer progression. Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, but no treatment targeting TNBC biomarkers has yet been developed. To identify specific DNA methylation patterns in TNBC, methyl-binding domain protein 2 (MBD) sequencing data were compared in TNBC and the three other major breast cancer subtypes. Integrated analysis of DNA methylation and gene expression identified a gene set showing a correlation between DNA methylation and gene expression. ATPase Na+/K+-transporting subunit alpha 1 (ATP1A1) was found to be specifically hypomethylated in the coding sequence (CDS) region and to show increased expression in TNBC. The Cancer Genome Atlas (TCGA) database also showed that hypomethylation and high expression of ATP1A1 were strongly associated with poor survival in patients with TNBC. Furthermore, ATP1A1 knockdown significantly reduced the viability and tumor-sphere formation of TNBC cells. These results suggest that the hypomethylation and overexpression of ATP1A1 could be a prognostic marker in TNBC and that the manipulation of ATP1A1 expression could be a therapeutic target in this disease.

DNA methylation and gene expression profiling reveal potential association of retinol metabolism related genes with hepatocellular carcinoma development.

Aberrant DNA methylation patterns play a critical role in the development of hepatocellular carcinoma (HCC). However, the molecular mechanisms associated with these aberrantly methylated genes remain unclear. This study aimed to comprehensively investigate the methylation-driven gene expression alterations in HCC using a multi-omics dataset. Whole genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) techniques were used to assess the methylation and gene expression profiles of HCC tissues (HCCs) and normal adjacent tissues (NATs). The candidate genes' potential function was further investigated using single-cell RNA sequencing (scRNA seq) data. We observed widespread hypomethylation in HCCs compared to NATs. Methylation levels in distinct genomic regions exhibited significant differences between HCCs and NATs. We identified 247,632 differentially methylated regions (DMRs) and 4,926 differentially expressed genes (DEGs) between HCCs and NATs. Integrated analysis of DNA methylation and RNA-seq data identified 987 methylation-driven candidate genes, with 970 showing upregulation and 17 showing downregulation. Four genes involved in the retinol metabolic pathway, namely ADH1A, CYP2A6, CYP2C8, and CYP2C19, were identified as hyper-downregulated genes. Their expression levels could stratify HCCs into three subgroups with distinct survival outcomes, immune cell infiltration, and tumor microenvironments. Validation of these findings in an independent dataset yielded similar outcomes, confirming the high concordance and potential prognostic value of these genes. ScRNA seq data revealed the low expression of these genes in immune cells, emphasizing their role in promoting malignant cell proliferation and migration. In conclusion, this study provides insights into the molecular characteristics of HCC, revealing the involvement of retinol metabolism-related genes in the development and progression of HCC. These findings have implications for HCC diagnosis, prognosis prediction, and the development of therapeutic targets.

Integrated DNA Methylation and Transcriptomics Analyses of Lacrimal Glands Identify the Potential Genes Implicated in the Development of Sjögren's Syndrome-Related Dry Eye.

Sjögren's syndrome-related dry eye (SS-related dry eye) is an intractable autoimmune disease characterized by chronic inflammation of lacrimal glands (LGs), where epigenetic factors are proven to play a crucial role in the pathogenesis of this disease. However, the alteration of DNA methylation in LGs and its role in the pathogenesis of SS-related dry eye is still unknown. Here, we performed an integrated analysis of DNA methylation and RNA-Seq data in LGs to identify novel DNA methylation-regulated differentially expressed genes (MeDEGs) in the pathogenesis of SS-related dry eye. The DNA methylation and transcription profiles of LGs in NOD mice at different stages of SS-related dry eye (4-, 8-, 12- and 16 weeks old) were generated by reduced representation bisulfite sequencing (RRBS) and RNA-Seq. The differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were analyzed by MethylKit R package and edgeR. Correlation analysis between methylation level and mRNA expression was conducted with R software. The functional correlation of DMGs and DEGs was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, LG tissues from another litter of NOD mice were collected for methylation-specific polymerase chain reaction (MSP) and quantitative real-time PCR (qRT-PCR) to validate the methylation and expression levels of key genes. CD4+ cell infiltration of LGs was detected by immunofluorescence staining. Hypermethylation of LGs was identified in NOD mice with the progression of SS-related dry eye and the DMGs were mainly enriched in the GTPases activation and Ras signaling pathway. RNA-seq analysis revealed 1321, 2549, and 3712 DEGs in the 8-, 12- and 16-week-old NOD mice compared with 4-week-old normal control mice. For GO analysis, the DEGs were mainly enriched in T cell immune responses. Further, a total of 140 MeDEGs were obtained by integrated analysis of methylome and transcriptome, which were primarily enriched in T cell activation, proliferation and differentiation. Based on the main GO terms and KEGG pathways of MeDEGs, 8 genes were screened out. The expression levels of these key genes, especially Itgal, Vav1, Irf4 and Icosl, were verified to elevate after the onset of SS-related dry eye in NOD mice and positively correlated with the extent of inflammatory cell infiltration in LGs. Immunofluorescence assay revealed that CD4+ cell infiltration dramatically increased in LGs of SS-related dry eye mice compared with the control mice. And the expression levels of four genes showed significantly positive correlation with the extent of CD4+ cell infiltration in LGs. MSP showed the hypomethylation of the Irf4 and Itgal promoters in NOD mice with SS-related dry eye compared to control group. Our study revealed the critical role of epigenetic regulation of T cell immunity-related genes in the progression of SS-related dry eye and reminded us that DNA methylation-regulated genes such as Itgal, Vav1, Irf4 and Icosl may be used as new targets for SS-related dry eye therapy.

PHF6-altered T-ALL Harbor Epigenetic Repressive Switch at Bivalent Promoters and Respond to 5-Azacitidine and Venetoclax.

To assess the impact of PHF6 alterations on clinical outcome and therapeutical actionability in T-cell acute lymphoblastic leukemia (T-ALL). We described PHF6 alterations in an adult cohort of T-ALL from the French trial Group for Research on Adult Acute Lymphoblastic Leukemia (GRAALL)-2003/2005 and retrospectively analyzed clinical outcomes between PHF6-altered (PHF6ALT) and wild-type patients. We also used EPIC and chromatin immunoprecipitation sequencing data of patient samples to analyze the epigenetic landscape of PHF6ALT T-ALLs. We consecutively evaluated 5-azacitidine efficacy, alone or combined with venetoclax, in PHF6ALT T-ALL. We show that PHF6 alterations account for 47% of cases in our cohort and demonstrate that PHF6ALT T-ALL presented significantly better clinical outcomes. Integrative analysis of DNA methylation and histone marks shows that PHF6ALT are characterized by DNA hypermethylation and H3K27me3 loss at promoters physiologically bivalent in thymocytes. Using patient-derived xenografts, we show that PHF6ALT T-ALL respond to the 5-azacytidine alone. Finally, synergism with the BCL2-inhibitor venetoclax was demonstrated in refractory/relapsing (R/R) PHF6ALT T-ALL using fresh samples. Importantly, we report three cases of R/R PHF6ALT patients who were successfully treated with this combination. Overall, our study supports the use of PHF6 alterations as a biomarker of sensitivity to 5-azacytidine and venetoclax combination in R/R T-ALL.

MGMT Methylation Is Associated with Human Papillomavirus Infection in Cervical Dysplasia: A Longitudinal Study.

Cervical premalignancy/malignancy, as detected by cervical cytology or biopsy, can develop as a result of human papillomavirus (HPV) infection. Meanwhile, DNA methylation is known to be associated with carcinogenesis. In this study, we thus attempted to identify the association between MGMT methylation and persistent HPV infection using an Epi-TOP MPP assay. Integrative analysis of DNA methylation was carried out here using longitudinal cervical cytology samples of seven patients with atypical squamous cells of undetermined significance/low-grade squamous intraepithelial lesion (ASC-US/LSIL). Then, a gene expression analysis using the longitudinal cervical cytology samples and a public database (The Cancer Genome Atlas (TCGA)) was performed. Upon comparing the ASC-US or LSIL samples at the 1st collection and the paired samples at the 2nd collection more than 6 months later, we found that they became hypermethylated over time. Then, using the longitudinal data, we found that the MGMT methylation was associated with HPV infection. Moreover, TCGA dataset revealed an association between downregulated MGMT mRNA expression and poor overall survival. This decreased MGMT mRNA expression was observed to have an inverse relationship with MGMT methylation levels. In this study, we found that the MGMT methylation level could potentially serve as a valuable prognostic indicator for the transition from ASC-US/LSIL to cervical cancer.

Metabolic rewiring and epigenetic reprogramming in leptin receptor-deficient db/db diabetic nephropathy mice

BackgroundDiabetic nephropathy (DN) is the leading cause of end-stage renal disease in the United States. Emerging evidence suggests that mitochondrial metabolism and epigenetics play an important role in the development and progression of DN and its complications. For the first time, we investigated the regulation of cellular metabolism, DNA methylation, and transcriptome status by high glucose (HG) in the kidney of leptin receptor-deficient db/db mice using multi-omics approaches. MethodsThe metabolomics was performed by liquid-chromatography–mass spectrometry (LC-MS), while epigenomic CpG methylation coupled with transcriptomic gene expression was analyzed by next-generation sequencing. ResultsLC-MS analysis of glomerular and cortex tissue samples of db/db mice showed that HG regulated several cellular metabolites and metabolism-related signaling pathways, including S-adenosylmethionine, S-adenosylhomocysteine, methionine, glutamine, and glutamate. Gene expression study by RNA-seq analysis suggests transforming growth factor beta 1 (TGFβ1) and pro-inflammatory pathways play important roles in early DN. Epigenomic CpG methyl-seq showed HG revoked a list of differentially methylated regions in the promoter region of the genes. Integrated analysis of DNA methylation in the promoter regions of genes and gene expression changes across time points identified several genes persistently altered in DNA methylation and gene expression. Cyp2d22, Slc1a4, and Ddah1 are some identified genes that could reflect dysregulated genes involved in renal function and DN. ConclusionOur results suggest that leptin receptor deficiency leading to HG regulates metabolic rewiring, including SAM potentially driving DNA methylation and transcriptomic signaling that could be involved in the progression of DN.

Gene Set Based Integrated Methylome and Transcriptome Analysis Reveals Potential Molecular Mechanisms Linking Cigarette Smoking and Related Diseases.

Advanced integrative analysis of DNA methylation and transcriptomics data may provide deeper insights into smoke-induced epigenetic alterations, their effects on gene expression and related biological processes, linking cigarette smoking and related diseases. We hypothesize that accumulation of DNA methylation changes in CpG sites across genomic locations of different genes might have biological significance. We tested the hypothesis by performing gene set based integrative analysis of blood DNA methylation and transcriptomics data to identify potential transcriptomic consequences of smoking via changes in DNA methylation in the Young Finns Study (YFS) participants (n = 1114, aged 34-49 years, women: 54%, men: 46%). First, we performed epigenome-wide association study (EWAS) of smoking. We then defined sets of genes based on DNA methylation status within their genomic regions, for example, sets of genes containing hyper- or hypomethylated CpG sites in their body or promoter regions. Gene set analysis was performed using transcriptomics data from the same participants. Two sets of genes, one containing 49 genes with hypomethylated CpG sites in their body region and the other containing 33 genes with hypomethylated CpG sites in their promoter region, were differentially expressed among the smokers. Genes in the two gene sets are involved in bone formation, metal ion transport, cell death, peptidyl-serine phosphorylation, and cerebral cortex development process, revealing epigenetic-transcriptomic pathways to smoking-related diseases such as osteoporosis, atherosclerosis, and cognitive impairment. These findings contribute to a deeper understanding of the pathophysiology of smoking-related diseases and may provide potential therapeutic targets.

Integrative Analysis of DNA Methylation and Gene Expression Data Identifies Potential Biomarkers and Functional Epigenetic Modules for SARS-CoV-2.

To integrate gene expression and DNA methylation data and find the potential role of DNA methylation in the invasion and replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We first conducted differential expression and methylation analysis between the coronavirus disease of 2019 (COVID-19) and healthy controls. FEM was employed to identify functional epigenetic modules, from which a diagnostic model for COVID-19 was built. SKA1 and WSB1 modules were identified, with SKA1 module enriched in COVID-19 replication and transcription, and WSB1 module related to ubiquitin-protein activity. The differentially expressed or differentially methylated genes in these two modules could be used to distinguish COVID-19 from healthy controls, with AUC reaching 1 and 0.98 for SKA1 and WSB1 modules, respectively. Two epigenetically activated genes (CENPM and KNL1) from the SKA1 module were upregulated in HPV- or HBV-positive tumor samples and were found to be significantly associated with the survival of tumor patients. In conclusion, the identified FEM modules and potential signatures play an essential role in the replication and transcription of coronavirus.

A novel DNA methylation-related gene signature for the prediction of overall survival and immune characteristics of ovarian cancer patients

BackgroundOvarian cancer (OC) is one of the most life-threatening cancers affecting women worldwide. Recent studies have shown that the DNA methylation state can be used in the diagnosis, treatment and prognosis prediction of diseases. Meanwhile, it has been reported that the DNA methylation state can affect the function of immune cells. However, whether DNA methylation-related genes can be used for prognosis and immune response prediction in OC remains unclear.MethodsIn this study, DNA methylation-related genes in OC were identified by an integrated analysis of DNA methylation and transcriptome data. Prognostic values of the DNA methylation-related genes were investigated through least absolute shrinkage and selection operator (LASSO) and Cox progression analyses. Immune characteristics were investigated by CIBERSORT, correlation analysis and weighted gene co-expression network analysis (WGCNA).ResultsTwelve prognostic genes (CA2, CD3G, HABP2, KCTD14, PI3, SERPINB5, SLAMF7, SLC9A2, STC2, TBP, TREML2 and TRIM27) were identified and a risk score signature and a nomogram based on prognostic genes and clinicopathological features were constructed for the survival prediction of OC patients in the training and two validation cohorts. Subsequently, the differences in the immune landscape between the high- and low-risk score groups were systematically investigated.ConclusionsTaken together, our study explored a novel efficient risk score signature and a nomogram for the survival prediction of OC patients. In addition, the differences of the immune characteristics between the two risk groups were clarified preliminarily, which will guide the further exploration of synergistic targets to improve the efficacy of immunotherapy in OC patients.

Integrative analysis of DNA methylation and gene expression through machine learning identifies stomach cancer diagnostic and prognostic biomarkers.

DNA methylation is an early event in tumorigenesis. Here, by integrative analysis of DNA methylation and gene expression and utilizing machine learning approaches, we introduced potential diagnostic and prognostic methylation signatures for stomach cancer. Differentially-methylated positions (DMPs) and differentially-expressed genes (DEGs) were identified using The Cancer Genome Atlas (TCGA) stomach adenocarcinoma (STAD) data. A total of 256 DMPs consisting of 140 and 116 hyper- and hypomethylated positions were identified between 443 tumour and 27 nontumour STAD samples. Gene expression analysis revealed a total of 2821 DEGs with 1247 upregulated and 1574 downregulated genes. By analysing the impact of cis and trans regulation of methylation on gene expression, a dominant negative correlation between methylation and expression was observed, while for trans regulation, in hypermethylated and hypomethylated genes, there was mainly a negative and positive correlation with gene expression, respectively. To find diagnostic biomarkers, we used 28 hypermethylated probes locating in the promoter of 27 downregulated genes. By implementing a feature selection approach, eight probes were selected and then used to build a support vector machine diagnostic model, which had an area under the curve of 0.99 and 0.97 in the training and validation (GSE30601 with 203 tumour and 94 nontumour samples) cohorts, respectively. Using 412 TCGA-STAD samples with both methylation and clinical data, we also identified four prognostic probes by implementing univariate and multivariate Cox regression analysis. In summary, our study introduced potential diagnostic and prognostic biomarkers for STAD, which demands further validation.

Integrated transcriptome and methylome analyses reveal the molecular regulation of drought stress in wild strawberry (Fragaria nilgerrensis)

BackgroundFragaria nilgerrensis, which is a diploid wild strawberry with excellent drought-resistance, would provide useful candidate genes for improving drought resistance of cultivated strawberry. So far, its molecular regulatory networks involved in drought stress are unclear. We therefore investigated the drought response regulatory networks of F. nilgerrensis based on the integrated analysis of DNA methylation, transcriptome and physiological traits during four time points under drought stress. ResultsThe most differentially expressed genes and the physiological changes were found at 8 days (T8) compared with 0 day (T0, control). Methylome analysis revealed slight dynamic changes in genome-wide mC levels under drought conditions, while the most hypomethylated and hypermethylated regions were identified at T4 and T8. Association analysis of the methylome and transcriptome revealed that unexpressed genes exhibited expected hypermethylation levels in mCHG and mCHH contexts, and highly expressed genes exhibited corresponding hypomethylation levels in the gene body, but mCG contexts showed the opposite trend. Then, 835 differentially methylated and expressed genes were identified and grouped into four clustering patterns to characterize their functions. The genes with either negative or positive correlation between methylation and gene expression were mainly associated with kinases, Reactive Oxygen Species (ROS) synthesis, scavenging, and the abscisic acid (ABA) signal pathway. Consistently, weighted gene co-expression network analysis (WGCNA) revealed Hub genes including NCED, CYP707A2, PP2Cs and others that play important roles in the ABA signaling pathway.ConclusionF. nilgerrensis drought is dominated by ABA-dependent pathways, possibly accompanied by ABA-independent crosstalk. DNA methylation may affect gene expression, but their correlation was more subtle and multiple types of association exist. Maintaining the balance between ROS regeneration and scavenging is an important factor in drought resistance in F. nilgerrensis. These results deepen our understanding of drought resistance and its application in breeding in strawberry plants.

Integrative sperm DNA methylation and miRomics analysis highlights interaction of two epigenetic patterns of pseudomale inheritance in teleost

Proper DNA methylation in spermatozoa is essential for the normal development of fertilized embryos through gene expression regulation. Abnormal sperm DNA methylation is associated with male fertility impairment, offspring quality decline, and disease susceptibility. Compared with other epigenetic regulatory mechanisms (e.g., histone modification), DNA methylation is a stable regulator for the long-term transcriptional activity of genes. Sperm DNA methylation is crucial to offspring’s survival, development, and reproduction. However, it has not been well studied in teleost to a large extent, especially in some species with sex deviation or congenital sex abnormality in offspring. In the present study, DNA methylation profiles of pseudomale (ZW) and male (ZZ) tongue sole (Cynoglossus semilaevis) spermatozoa were characterized for differential methylation regions (DMRs) screening. The global methylation levels of the two sperm groups were highly methylated with no significant differences. For all kinds of genomic elements, the mean methylation level of the ZW group was higher than that of the ZZ group. The total numbers of Covered C annotated on the W chromosome of both groups were extremely small, suggesting that W-type sperm did not exist in pseudomales. A comparison of methylation levels on 20 sex-related genes between sperm and gonad showed that the heterogeneity between tissue resources was greater than that between sexes, and the methylation level of most genes in gonads was lower than that in sperm. For integrative analysis of DNA methylation and miRomic profiles, 11 sex-related DMRs associated with 15 differentials micro RNAs (miRNAs) in spermatozoa were identified to present targeting relationships and regulatory trends of the two distinct epigenetic patterns. This study provides valuable and potential targets of coordination between two epigenetic mechanisms in the process of C. semilaevis sex congenital bias.

Identification of DNA methylation-regulated differentially expressed genes in RA by integrated analysis of DNA methylation and RNA-Seq data

ObjectiveTo identify novel DNA methylation-regulated differentially expressed genes (MeDEGs) in RA by integrated analysis of DNA methylation and RNA-Seq data.MethodsThe transcription and DNA methylation profiles of 9 RA and 15 OA synovial tissue were generated by RNA-Seq and Illumina 850K DNA methylation BeadChip. Gene set enrichment analysis (GSEA) and Weighted gene co-expression network analysis (WGCNA) were used to analyze methylation-regulated expressed genes by R software. The differentially expressed genes (DEGs), differentially methylated probes (DMPs), differentially methylated genes (DMGs) were analyzed by DESeq and ChAMP R package. The functional correlation of MeDEGs was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein–protein interaction (PPI) network of MeDEGs was constructed by STRING and Reactome FI Cytoscape Plugin. Correlation analysis between methylation level and mRNA expression was conducted with R software.ResultsA total of 17,736 genes, 25,578 methylated genes and 755,852 methylation probes were detected. A total of 16,421 methylation-regulated expressed genes were obtained. The GSEA showed that these genes are associated with activation of immune response, adaptive immune response, Inflammatory response in C5 (ontology gene sets). For KEGG analysis, these genes are associated with rheumatoid arthritis, NF-kappa B signaling pathway, T cell receptor signaling pathway. The WGCNA showed that the turquoise module exhibited the strongest correlation with RA (R = 0.78, P = 1.27 × 10− 05), 660 genes were screened in the turquoise module. A total of 707 MeDEGs were obtained. GO analysis showed that MeDEGs were enriched in signal transduction, cell adhesion for BP, enriched in plasma membrane, integral component of membrane for CC, and enriched in identical protein binding, calcium ion binding for MF. The KEGG pathway analysis showed that the MeDEGs were enriched in calcium signaling pathway, T cell receptor signaling pathway, NF-kappa B signaling pathway, Rheumatoid arthritis. The PPI network containing 706 nodes and 882 edges, and the enrichment p value < 1.0 × 10− 16. With Cytoscape, based on the range of more than 10 genes, a total of 8 modules were screened out. Spearman correlation analysis showed RGS1(cg10718027), RGS1(cg02586212), RGS1(cg10861751) were significantly correlated with RA.ConclusionsRGS1 can be used as novel methylated biomarkers for RA.

Integrated analysis of DNA methylation, transcriptome, and global metabolites in interspecific heterotic Capsicum F1 hybrid

SummaryHybrid breeding is one of the efficacious methods of crop improvement. Here, we report our work towards understanding the molecular basis of F1 hybrid heterosis from Capsicum chinense and C. frutescens cross. Bisulfite sequencing identified a total of 70597 CG, 108797 CHG, and 38418 CHH differentially methylated regions (DMRs) across F1 hybrid and parents, and of these, 4891 DMRs showed higher methylation in F1 compared to the mid-parental methylation values (MPMV). Transcriptome analysis showed higher expression of 46–55% differentially expressed genes (DE-Gs) in the F1 hybrid. The qRT-PCR analysis of 24 DE-Gs with negative promoter methylation revealed 91.66% expression similarity with the transcriptome data. A few metabolites and 65–72% enriched genes in metabolite biosynthetic pathways showed overall increased expression in the F1 hybrid compared to parents. These findings, taken together, provided insights into the integrated role of DNA methylation, and genes and metabolites expression in the manifestation of heterosis in Capsicum.

An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis

Background: Abnormal DNA methylation of gene promoters is an important feature in lung adenocarcinoma (LUAD). However, the prognostic value of DNA methylation remains to be further explored. Objectives. We sought to explore DNA methylation characteristics and develop a quantifiable criterion related to DNA methylation to improve survival prediction for LUAD patients. Methods: Illumina Human Methylation450K array data, level 3 RNA-seq data and corresponding clinical information were obtained from TCGA. Cox regression analysis and the Akaike information criterion were used to construct the best-prognosis methylation signature. Receiver operating characteristic curve analysis was used to validate the prognostic ability of the DNA methylation-related feature score. qPCR was used to measure the transcription levels of the identified genes upon methylation. Results: We identified a set of DNA methylation features composed of 11 genes (MYEOV, KCNU1, SLC27A6, NEUROD4, HMGB4, TACR3, GABRA5, TRPM8, NLRP13, EDN3 and SLC34A1). The feature score, calculated based on DNA methylation features, was independent of tumor recurrence and TNM stage in predicting overall survival. Of note, the combination of this feature score and TNM stage provided a better overall survival prediction than either of them individually. The transcription levels of all the hypermethylated genes were significantly increased after demethylation, and the expression levels of 3 hypomethylated proteins were significantly higher in tumor tissues than in normal tissues, as indicated by immunohistochemistry data from the Human Protein Atlas. Our results suggested that these identified genes with prognostic features were regulated by DNA methylation of their promoters. Conclusion: Our studies demonstrated the potential application of DNA methylation markers in the prognosis of LUAD.

Integrative analysis of DNA methylation and gene expression data for the diagnosis and underlying mechanism of Parkinson's disease.

Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder and the leading cause of disability in the daily activities. In the management of PD, accurate and specific biomarkers in blood for the early diagnosis of PD are urgently needed. DNA methylation is one of the main epigenetic mechanisms and associated with the gene expression and disease initiation of PD. We aimed to construct a methylation signature for the diagnosis of PD patients, and explore the potential value of DNA methylation in therapeutic options. Whole blood DNA methylation and gene expression data of PD patients as well as healthy controls were extracted from Gene Expression Omnibus database. Next, differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between PD patients and healthy controls were identified. Least absolute shrinkage and selection operator cox regression analysis was carried out to construct a diagnostic signature based on the overlapped genes. And, the receiver operating characteristic (ROC) curves were drawn and the area under the curve (AUC) was used to assess the diagnostic performance of the signature in both the training and testing datasets. Finally, gene ontology and gene set enrichment analysis were subsequently carried out to explore the underlying mechanisms. We obtained a total of 9,596 DMGs, 1,058 DEGs, and 237 overlapped genes in the whole blood between PD patients and healthy controls. Eight methylation-driven genes (HIST1H4L, CDC42EP3, KIT, GNLY, SLC22A1, GCM1, INO80B, and ARHGAP26) were identified to construct the gene expression signature. The AUCs in predicting PD patients were 0.84 and 0.76 in training dataset and testing dataset, respectively. Additionally, eight methylation-altered CpGs were also identified to construct the CpGs signature which showed a similarly robust diagnostic capability, with AUCs of 0.8 and 0.73 in training dataset and testing dataset, respectively. We conducted an integrated analysis of the gene expression and DNA methylation data, and constructed a methylation-driven genes signature and a methylation-altered CpGs signature to distinguish the patients with PD from healthy controls. Both of them had a robust prediction power and provide a new insight into personalized diagnostic and therapeutic strategies for PD.

Multiomic Signatures of Chronic Beryllium Disease Bronchoalveolar Lavage Cells Relate to T-Cell Function and Innate Immunity.

Chronic beryllium disease (CBD) is a Th1 granulomatous lung disease preceded by sensitization to beryllium (BeS). We profiled the methylome, transcriptome, and selected proteins in the lung to identify molecular signatures and networks associated with BeS and CBD. BAL cell DNA and RNA were profiled using microarrays from CBD (n = 30), BeS (n = 30), and control subjects (n = 12). BAL fluid proteins were measured using Olink Immune Response Panel proteins from CBD (n = 22) and BeS (n = 22) subjects. Linear models identified features associated with CBD, adjusting for covariation and batch effects. Multiomic integration methods identified correlated features between datasets. We identified 1,546 differentially expressed genes in CBD versus control subjects and 204 in CBD versus BeS. Of the 101 shared transcripts, 24 have significant cis relationships between gene expression and DNA methylation, assessed using expression quantitative trait methylation analysis, including genes not previously identified in CBD. A multiomic model of top DNA methylation and gene expression features demonstrated that the first component separated CBD from other samples and the second component separated control subjects from remaining samples. The top features on component one were enriched for T-lymphocyte function, and the top features on component two were enriched for innate immune signaling. We identified six differentially abundant proteins in CBD versus BeS, with two (SIT1 and SH2D1A) selected as important RNA features in the multiomic model. Our integrated analysis of DNA methylation, gene expression, and proteins in the lung identified multiomic signatures of CBD that differentiated it from BeS and control subjects.