scholarly journals New differentially expressed genes and differential DNA methylation underlying refractory epilepsy

Oncotarget ◽  
2016 ◽  
Vol 7 (52) ◽  
pp. 87402-87416 ◽  
Author(s):  
Xi Liu ◽  
Shu Ou ◽  
Tao Xu ◽  
Shiyong Liu ◽  
Jinxian Yuan ◽  
...  
2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiao-Liang Xing ◽  
Zhi-Yong Yao ◽  
Chaoqun Xing ◽  
Zhi Huang ◽  
Jing Peng ◽  
...  

Abstract Background Colorectal cancer (CRC) is the second most prevalent cancer, as it accounts for approximately 10% of all annually diagnosed cancers. Studies have indicated that DNA methylation is involved in cancer genesis. The purpose of this study was to investigate the relationships among DNA methylation, gene expression and the tumor-immune microenvironment of CRC, and finally, to identify potential key genes related to immune cell infiltration in CRC. Methods In the present study, we used the ChAMP and DESeq2 packages, correlation analyses, and Cox regression analyses to identify immune-related differentially expressed genes (IR-DEGs) that were correlated with aberrant methylation and to construct a risk assessment model. Results Finally, we found that HSPA1A expression and CCRL2 expression were positively and negatively associated with the risk score of CRC, respectively. Patients in the high-risk group were more positively correlated with some types of tumor-infiltrating immune cells, whereas they were negatively correlated with other tumor-infiltrating immune cells. After the patients were regrouped according to the median risk score, we could more effectively distinguish them based on survival outcome, clinicopathological characteristics, specific tumor-immune infiltration status and highly expressed immune-related biomarkers. Conclusion This study suggested that the risk assessment model constructed by pairing immune-related differentially expressed genes correlated with aberrant DNA methylation could predict the outcome of CRC patients and might help to identify those patients who could benefit from antitumor immunotherapy.


Author(s):  
И.Н. Рыболовлев ◽  
И.Н. Власов ◽  
А.Х. Алиева ◽  
П.А. Сломинский ◽  
М.И. Шадрина

Болезнь Паркинсона (БП) является многофакторным гетерогенным нейродегенеративным заболеванием. Поскольку этиопатогенез БП недостаточно изучен, кроме поиска и анализа изменений на уровне ДНК, необходимо распространить фокус исследований на другие уровни: транскриптом и метилом. Изменения на уровне эпигенома можно исследовать у лиц с идентичной генетической конституцией, такой «моделью» являются дискордантные по этому заболеванию монозиготные близнецы. В исследовании приняло участие 3 пары фенотипически и генотипически монозиготных близнецов русского происхождения; В исследовании приняло участие 3 пары фенотипически и генотипически монозиготных близнецов русского происхождения. БП была уточнена у одного из каждой пары близнецов; длительность течения болезни у близнеца с БП составило по меньшей мере 7 лет.; длительность течения болезни у близнеца с БП составила по меньшей мере 7 лет. Были проанализированы метиломы крови и отобраны точки варьирующегося метилирования. Нами было найдено 8 дифференциально экспрессирующихся генов, которые могут быть дифференциально метилированы. Были выявлены различия между здоровым близнецом и близнецом с БП по уровню метилирования ДНК для ряда этих генов в клеточных линиях фибробластов. Полученные нами данные могут указывать на участие процесса ДНК-метилирования в регуляции транскрипции кандидатных генов-участников патогенеза БП. In recent years it has been convincingly demonstrated that genetic factors play an important role in progression of Parkinson’s disease (PD). Since the etiology of PD has not been elucidated completely yet, it is crucial to shift focus of the research to the broader areas - to dive into investigations of methylome and transcriptome. Epigenetic regulation of gene expression may take part in pathogenesis of PD. Changes in epigenome can be conveniently investigated in case of individuals with almost identical genetic makeup, and monozygotic twins discordant for PD may be such “model”. 3 pairs phenotypically and genotypically monozygous twins of Russian ancestry were enrolled in the study. PD was diagnosed in one of each pair. The disease duration was at least 7 years. Data on blood methylomes was analyzed. Points of variable methylation in blood methylomes were selected. With this approach, 8 differentially expressed genes were found that also may be differentially methylated. Changes in methylation level for some of this genes were found in monozygotic twins discordant for PD fibroblasts cell-lines between healthy and afflicted siblings. Acquired data might suggest participation of DNA-methylation in transcription regulation of PD pathogenesis-related candidate genes.


2015 ◽  
Vol 9 (4) ◽  
pp. 1691-1698 ◽  
Author(s):  
HEUN-SIK LEE ◽  
JUN HO YUN ◽  
JUNGHEE JUNG ◽  
YOUNG YANG ◽  
BONG-JO KIM ◽  
...  

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Cheng Zhang ◽  
Bingye Zhang ◽  
Di Meng ◽  
Chunlin Ge

Abstract Background The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis. Methods The gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein–protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database. Results We identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA. Conclusions Our study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3671-3671
Author(s):  
Michael Getman ◽  
Jeffrey Malik ◽  
James Palis ◽  
Laurie A Steiner

Abstract The molecular mechanisms that drive the maturation of a committed erythroid progenitor to a functional red blood cell are incompletely understood. LSD1 (Lysine-Specific Histone Demethylase 1) is a widely expressed histone demethylase that plays an important role in erythroid maturation (Kereyni, elife, 2013). Although LSD1 is important for a number of biologic processes ranging from embryonic development to leukemogenesis, the molecular mechanisms underlying the influence of LSD1 on gene expression are incompletely understood. The goal of our study is to elucidate the molecular mechanisms by which LSD1 regulates erythroid gene expression and influences erythroid maturation. We hypothesize that LSD1 promotes specific patterns of histone and DNA methylation that facilitate gene expression changes necessary for normal erythroid maturation to occur. To address this hypothesis, the functional and molecular consequences of LSD1 knockdown were assessed in Extensively Self Renewing Erythroblasts (ESREs), a non-transformed, karyotypically normal model of terminal erythroid maturation (England, Blood, 2011). Primary fetal liver was cultured in the presence of EPO, SCF, IGF1 and dexamethasone to derive ESREs. The ESREs were capable of extensive ex-vivo expansion, doubling daily at the proerythroblast phase, however when matured, >90% of cells became benzidine positive and >65% enucleated within 3 days. Lentiviral-mediated shRNA was used to knock down LSD1 in expanding ESREs. Imaging flow cytometry done on maturation day 3 demonstrated that the knockdown cells had impairments in multiple facets of maturation, with larger cell and nuclear areas, higher kit expression, and lower rates of enucleation than the scramble control. LSD1 knockdown was also associated with impaired hemoglobin accumulation (78% vs. 95% benzidine positive; p<0.005). Treatment of ESREs with an inhibitor to LSD1 (Tranylcypromine; TCP) resulted in similar abnormalities in cell and nuclear size, kit expression, hemoglobin accumulation, and enucleation (40% vehicle vs.1% TCP). The functional deficits in maturation, including abnormal kit expression and low rates of enucleation, persisted on maturation day 4. To delineate the molecular mechanisms underlying this maturation impairment, RNA-seq was done in LSD1 knockdown and scramble control samples, and 230 differentially expressed genes (FDR<0.01) were identified using cuffdiff (Trapnell, Nat Biotech, 2013). Consistent with LSD1’s role in erythroid maturation, Ingenuity Pathway Analysis identified multiple networks involving hemoglobin synthesis, and GATA1, EPO, and KLF1 were all predicted as upstream regulators (p-values of 8.24e10-11, 7.25 e10-6, and 3.86e10-4, respectively). To better understand how LSD1 influences gene expression, chromatin immunoprecipitation coupled with high throughput sequencing was used to identify sites of H3K4me2 binding in the differentially expressed genes. 214/230 differentially expressed genes were associated with sites of H3K4me2 occupancy. Quantitative ChIP demonstrated that LSD1 inhibition was associated with increases in H3K4me2 levels at a subset of these sites, however consistent with previous studies, global levels of H3K4me2, determined by Enzyme Linked Immunosorbent Assay (ELIZA), did not change significantly. Although it is known that LSD1 demethylates and stabilizes the maintenance DNA methyltransferase DNMT1 (Wang, Nat Genet 2009), the consequences of LSD1 loss on DNA methylation (5-methyl cytosine; 5-mC) have yet to be investigated. To gain a comprehensive understanding of how LSD1 regulates erythroid gene expression, changes in the level of 5-mC were assessed after knockdown or inhibition of LSD1. Global 5-mC levels, determined by ELIZA assay, were ∼30% lower in TCP treated samples than vehicle treated control (p<0.02) and western blot demonstrated a 3-fold decrease in DNMT1 protein in the TCP treated samples. Both methyl binding domain pull-down coupled with quantitative PCR and genome-wide bisulfite sequencing were utilized to assess changes in 5-mC levels in the differentially expressed genes. Loss of LSD1 was associated with significantly lower levels of 5-mC at several differentially expressed, erythroid-specific genes, such as bh1. Taken together, these data support the hypothesis that LSD1 influences both histone and DNA methylation at genes important for erythroid maturation. Disclosures: No relevant conflicts of interest to declare.


2021 ◽  
Vol 12 ◽  
Author(s):  
Yihuan Pu ◽  
Xuenuo Chen ◽  
Yangmei Chen ◽  
Lingzhao Zhang ◽  
Jiayi Chen ◽  
...  

Vitiligo is an pigmentation disorder caused by a variety of pathogenic factors; its main pathophysiological conditions include oxidative stress, immune activation, and genetic background. Additionally, DNA methylation is often associated with the pathogenesis of vitiligo; however, the underlying mechanism remains unknown. In the present study, we used the Human Methylation 850K BeadChip platform to detect DNA methylation changes in the vitiligo melanocytes. We then integrated the results with the transcriptome data of vitiligo melanocytes and lesions to analyse the correlation between differentially methylated levels and differentially expressed genes. The results showed that there was a significant negative correlation between methylation levels and differentially expressed genes. Subsequently, we enriched GO and KEGG based on methylated differentially expressed genes (MDEGs) using R package ClusterProfiler, and the results were closely related to the pathogenesis of vitiligo. In addition, we also constructed a PPI network of MDEGs and excavated three important functional epigenetic modules, involving a total of 12 (BCL2L1, CDK1, ECT2, HELLS, HSP90AA1, KIF23, MC1R, MLANA, PBK, PTGS2, SOX10, and TYRP1) genes. These genes affect melanocyte melanogenesis, cellular oxidative stress and other important biological processes. Our comprehensive analysis results support the significant contribution of the status of DNA methylation modification to vitiligo, which will help us to better understand the molecular mechanism of vitiligo and explore new therapeutic strategies.


2020 ◽  
Author(s):  
Shijie Gao ◽  
Guowang Li ◽  
Hao Yu ◽  
Shiyang Yuan ◽  
Wenxiang Li ◽  
...  

Abstract Background DNA methylation is a common epigenetic regulatory way, and it plays a critical role in various human diseases. However, the potential role of how DNA methylation impacts Ewing’s sarcoma (ES) is not clear. This study aimed to explore the regulatory role of DNA methylation in ES. Methods The microarray data of gene expression and methylation were downloaded from Gene Expression Omnibus (GEO) database, and analyzed via GEO2R. Venn analysis was then applied to identify aberrantly methylated differentially expressed genes (DEGs). Subsequently, Function and pathway enrichment analysis was conducted. Protein-protein interaction (PPI) network was constructed. Hub genes were determined. Besides, a connectivity map (CMap) analysis was performed to screen bioactive compounds for ES treatment. Results A total of 135 hypomethylated high expression genes and 523 hypermethylated low expression genes were identified. The hypomethylated high expression genes were enriched in signal transduction and the apoptosis process. Meanwhile, hypermethylated low expression genes were related to DNA replication and transcription regulation. We next determined 10 hub genes through PPI analysis, among them, C3, TF, and TCEB1 might serve as diagnostic and therapeutic targets. Furthermore, CMap analysis revealed 6 chemicals as potential options for ES treatment. Conclusions For the first time, we jointly analyzed gene profiling and methylation data about ES. The introduction of DNA methylation characteristics over DEGs is helpful to understand the pathogenesis of ES. The identified hub aberrantly methylated DEGs and chemicals might provide some novel insights on ES treatment.


2021 ◽  
Vol 11 ◽  
Author(s):  
Yu Liang ◽  
Bin Ma ◽  
Peng Jiang ◽  
Hong-Mei Yang

BackgroundIn recent years, DNA methylation modification has been shown to be a critical mechanism in the field of epigenetics.MethodsHepatocellular carcinoma (HCC) data were obtained from The Cancer Genome Atlas project, including RNA expression profiles, Illumina Human Methylation 450K BeadChip data, clinical information, and pathological features. Then, differentially expressed genes (DEGs) and differentially methylated genes were identified using R software. Methylation-regulated DEGs (MeDEGs) were further analyzed using Spearman’s correlation analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the DAVID database and ClueGO in Cytoscape software. Kaplan–Meier survival analysis explored the relationship between methylation, expression of MeDEGs, and survival time. Gene set enrichment analysis (GSEA) was conducted to predict the function of prognosis-related MeDEGs.ResultsA total of nine up-regulated and 72 down-regulated MeDEGs were identified. GO and KEGG pathway analyses results indicated that multiple cancer-related terms were enriched. Kaplan–Meier survival analysis showed that the methylation status of four MeDEGs (CTF1, FZD8, PDK4, and ZNF334) was negatively associated with overall survival. Moreover, the methylation status of CDF1 and PDK4 was identified as an independent prognostic factor. According to GSEA, hypermethylation of prognosis-related MeDEGs was enriched in pathways that included “Spliceosome”, “Cell cycle”, “RNA degradation”, “RNA polymerase”, “DNA replication”, “Mismatch repair”, “Base excision repair”, “Nucleotide excision repair”, “Homologous recombination”, “Protein export”, and “Pyrimidine metabolism”.ConclusionsAberrant DNA methylation plays a critical role in malignant progression of HCC. Prognosis-related MeDEGs identified in this research may be potential biomarkers and targets in diagnosis and treatment.


2021 ◽  
Author(s):  
Shijie Gao ◽  
Guowang Li ◽  
Hao Yu ◽  
Shiyang Yuan ◽  
Wenxiang Li ◽  
...  

Abstract Background: DNA methylation is a common epigenetic regulatory way, and it plays a critical role in various human diseases. However, the potential role of how DNA methylation impacts Ewing’s sarcoma (ES) is not clear. This study aimed to explore the regulatory role of DNA methylation in ES.Methods: The microarray data of gene expression and methylation were downloaded from Gene Expression Omnibus (GEO) database, and analyzed via GEO2R. Venn analysis was then applied to identify aberrantly methylated differentially expressed genes (DEGs). Subsequently, Function and pathway enrichment analysis was conducted. Protein-protein interaction (PPI) network was constructed. Hub genes were determined. Besides, a connectivity map (CMap) analysis was performed to screen bioactive compounds for ES treatment.Results: A total of 135 hypomethylated high expression genes and 523 hypermethylated low expression genes were identified. The hypomethylated high expression genes were enriched in signal transduction and the apoptosis process. Meanwhile, hypermethylated low expression genes were related to DNA replication and transcription regulation. We next determined 10 hub genes through PPI analysis, among them, C3, TF, and TCEB1 might serve as diagnostic and therapeutic targets. Furthermore, CMap analysis revealed 6 chemicals as potential options for ES treatment. Conclusions: For the first time, we jointly analyzed gene profiling and methylation data about ES. The introduction of DNA methylation characteristics over DEGs is helpful to understand the pathogenesis of ES. The identified hub aberrantly methylated DEGs and chemicals might provide some novel insights on ES treatment.


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