Dataset Information

Integrated Analysis of Tissue-Specific Promoter Methylation and Gene Expression Profile in Complex Diseases.

ABSTRACT: This study investigated whether the promoter region of DNA methylation positively or negatively regulates tissue-specific genes (TSGs) and if it correlates with disease pathophysiology. We assessed tissue specificity metrics in five human tissues, using sequencing-based approaches, including 52 whole genome bisulfite sequencing (WGBS), 52 RNA-seq, and 144 chromatin immunoprecipitation sequencing (ChIP-seq) data. A correlation analysis was performed between the gene expression and DNA methylation levels of the TSG promoter region. The TSG enrichment analyses were conducted in the gene-disease association network (DisGeNET). The epigenomic association analyses of CpGs in enriched TSG promoters were performed using 1986 Infinium MethylationEPIC array data. A correlation analysis showed significant associations between the promoter methylation and 449 TSGs' expression. A disease enrichment analysis showed that diabetes- and obesity-related diseases were high-ranked. In an epigenomic association analysis based on obesity, 62 CpGs showed statistical significance. Among them, three obesity-related CpGs were newly identified and replicated with statistical significance in independent data. In particular, a CpG (cg17075888 of PDK4), considered as potential therapeutic targets, were associated with complex diseases, including obesity and type 2 diabetes. The methylation changes in a substantial number of the TSG promoters showed a significant association with metabolic diseases. Collectively, our findings provided strong evidence of the relationship between tissue-specific patterns of epigenetic changes and metabolic diseases.

SUBMITTER: Lee K

PROVIDER: S-EPMC7404266 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated Analysis of Tissue-Specific Promoter Methylation and Gene Expression Profile in Complex Diseases.

Lee Kibaick K Moon Sanghoon S Park Mi-Jin MJ Koh In-Uk IU Choi Nak-Hyeon NH Yu Ho-Yeong HY Kim Young Jin YJ Kong Jinhwa J Kang Hee Gyung HG Kim Song Cheol SC Kim Bong-Jo BJ

International journal of molecular sciences 20200717 14

This study investigated whether the promoter region of DNA methylation positively or negatively regulates tissue-specific genes (TSGs) and if it correlates with disease pathophysiology. We assessed tissue specificity metrics in five human tissues, using sequencing-based approaches, including 52 whole genome bisulfite sequencing (WGBS), 52 RNA-seq, and 144 chromatin immunoprecipitation sequencing (ChIP-seq) data. A correlation analysis was performed between the gene expression and DNA methylation ...[more]

PMID: 32709145

Similar Datasets

Project description:BackgroundTissue specific promoters may be utilized for a variety of applications, including programmed gene expression in cell types, tissues and organs of interest, for developing different cell culture models or for use in gene therapy. We report a novel, tissue-specific promoter that was identified and engineered from the native upstream regulatory region of the human gene NDUFV1 containing an endogenous retroviral sequence.ResultsAmong seven established human cell lines and five primary cultures, this modified NDUFV1 upstream sequence (mNUS) was active only in human undifferentiated germ-derived cells (lines Tera-1 and EP2102), where it demonstrated high promoter activity (approximately twice greater than that of the SV40 early promoter, and comparable to the routinely used cytomegaloviral promoter). To investigate the potential applicability of the mNUS promoter for biotechnological needs, a construct carrying a recombinant cytosine deaminase (RCD) suicide gene under the control of mNUS was tested in cell lines of different tissue origin. High cytotoxic effect of RCD with a cell-death rate approximately 60% was observed only in germ-derived cells (Tera-1), whereas no effect was seen in a somatic, kidney-derived control cell line (HEK293). In further experiments, we tested mNUS-driven expression of a hyperactive Sleeping Beauty transposase (SB100X). The mNUS-SB100X construct mediated stable transgene insertions exclusively in germ-derived cells, thereby providing further evidence of tissue-specificity of the mNUS promoter.ConclusionsWe conclude that mNUS may be used as an efficient promoter for tissue-specific gene expression in human germ-derived cells in many applications. Our data also suggest that the 91 bp-long sequence located exactly upstream NDUFV1 transcriptional start site plays a crucial role in the activity of this gene promoter in vitro in the majority of tested cell types (10/12), and an important role--in the rest two cell lines.

Project description:In order to better understand the etiology of obese type 2 diabetes (T2D) at the molecular level, the present study investigated the gene expression and DNA methylation profiles associated with T2D via systemic analysis. Gene expression (GSE64998) and DNA methylation profiles (GSE65057) from liver tissues of healthy controls and obese patients with T2D were downloaded from the Gene Expression Omnibus database. Differentially?expressed genes (DEGs) and differentially?methylated genes (DMGs) were identified using the Limma package, and their overlapping genes were additionally determined. Enrichment analysis was performed using the BioCloud platform on the DEGs and the overlapping genes. Using Cytoscape software, protein?protein interaction (PPI), transcription factor target networks and microRNA (miRNA) target networks were then constructed in order to determine associated hub genes. In addition, a further GSE15653 dataset was utilized in order to validate the DEGs identified in the GSE64998 dataset analyses. A total of 251 DEGs, including 124 upregulated and 127 downregulated genes, were detected, and a total of 9,698 genes were demonstrated to be differentially methylated in obese patients with T2D compared with non?obese healthy controls. A total of 103 overlapping genes between the two datasets were revealed, including 47 upregulated genes and 56 downregulated genes. The identified overlapping genes were revealed to be strongly associated with fatty acid and glucose metabolic pathways, in addition to oxidation/reduction. The overlapping genes cyclin D1 (CCND1), PPARG coactivator ? (PPARGC1A), fatty acid synthase (FASN), glucokinase (GCK), steraroyl?coA desaturase (SCD) and tyrosine aminotransferase (TAT) had higher degrees in the PPI, transcription target networks and miRNA target networks. In addition, among the 251 DEGs, a total of 35 DEGs were validated to be being shared genes between the datasets, which included a number of key genes in the PPI network, including CCND1, FASN and TAT. Abnormal gene expression and DNA methylation patterns that were implicated in fatty acid and glucose metabolic pathways and oxidation/reduction reactions were detected in obese patients with T2D. Furthermore, the CCND1, PPARGC1A, FANS, GCK, SCD and TAT genes may serve a role in the development of obesity?associated T2D.

Project description:BackgroundAs downstream mediators of PI3K /PTEN /AKT /mTORC1 pathway, the AKT isoforms play critical roles in tumorgenesis. Although the pleiotropic effects of AKT1 in breast cancer have been reported, the genetic and epigenetic characteristics of AKT1 promoter region in breast cancer remains to be identified. In this study we aimed to investigate the promoter mutation spectrum, methylation and gene expression pattern of AKT1 and their relationship with breast cancer.MethodsBy using PCR target sequence enrichment and next-generation sequencing technology, we sequenced AKT1 promoter region in pairs of breast tumor and normal tissues from 95 unselected Chinese breast cancer patients. The methylation of the promoter region and the expression profile of AKT1 in the same cohort were detected with bisulfite next-generation sequencing and qPCR, respectively.ResultsWe identified 28 somatic mutations in 23 of the 95 (24.2%) breast cancer samples. And 19 of the 28 mutations were located in transcription factor (TF) binding sites. In the 23 patients with somatic mutations, no significant change of methylation or expression was found comparing with other patients. AKT1 promoter region was significantly hypo-methylated in tumor compared with matched normal tissue (P = 0.0014) in the 95 patients. The expression of AKT1 was significantly suppressed in tumor tissue (P = 0.0375). In clinicopathological factor analysis, AKT1 showed significant hypo-methylation (P = 0.0249) and suppressed expression (P = 0.0375) in HER2 negative subtype. And a trend of decrease in expression level (P = 0.0624) of AKT1 in the ER negative subtype was observed, which is significantly decreased in basal-like breast tumor (P = 0.0328).ConclusionsHypo-methylation and suppressed expression of AKT1 was observed to be associated with breast cancer in our cohort. The methylation and expression of AKT1 were both significantly associated with HER2 status. The promoter mutation of AKT1 did not show significant association with its methylation and expression status. These results suggested that the promoter mutation, methylation and gene expression of AKT1 may play distinct roles in tumorgenesis of breast cancer and the integrated analysis of methylation and expression of AKT1 might serve as potential biomarkers for diagnosis and classification of breast cancer.

Project description:BACKGROUND: The computational prediction of DNA methylation has become an important topic in the recent years due to its role in the epigenetic control of normal and cancer-related processes. While previous prediction approaches focused merely on differences between methylated and unmethylated DNA sequences, recent experimental results have shown the presence of much more complex patterns of methylation across tissues and time in the human genome. These patterns are only partially described by a binary model of DNA methylation. In this work we propose a novel approach, based on profile analysis of tissue-specific methylation that uncovers significant differences in the sequences of CpG islands (CGIs) that predispose them to a tissue- specific methylation pattern. RESULTS: We defined CGI methylation profiles that separate not only between constitutively methylated and unmethylated CGIs, but also identify CGIs showing a differential degree of methylation across tissues and cell-types or a lack of methylation exclusively in sperm. These profiles are clearly distinguished by a number of CGI attributes including their evolutionary conservation, their significance, as well as the evolutionary evidence of prior methylation. Additionally, we assess profile functionality with respect to the different compartments of protein coding genes and their possible use in the prediction of DNA methylation. CONCLUSION: Our approach provides new insights into the biological features that determine if a CGI has a functional role in the epigenetic control of gene expression and the features associated with CGI methylation susceptibility. Moreover, we show that the ability to predict CGI methylation is based primarily on the quality of the biological information used and the relationships uncovered between different sources of knowledge. The strategy presented here is able to predict, besides the constitutively methylated and unmethylated classes, two more tissue specific methylation classes conserving the accuracy provided by leading binary methylation classification methods.

Dataset Information

Integrated Analysis of Tissue-Specific Promoter Methylation and Gene Expression Profile in Complex Diseases.

Publications

Integrated Analysis of Tissue-Specific Promoter Methylation and Gene Expression Profile in Complex Diseases.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets