The overexpression of GRASP might inhibit cell proliferation and invasion in hepatocellular carcinoma

This study aimed to validate the methylation of key genes in hepatocellular carcinoma (HCC) screened by bioinformatics analysis and explore whether they affected HCC cell proliferation, migration, and invasion. Using The Cancer Genome Atlas (TCGA) database, HCC-related differentially methylated positions (DMPs) were screened, genes corresponding to DMPs were selected, and prognosis-related genes were identified. A representative DMP was used to divide the DMPs into hyper- and hypomethylated groups. Expression of key genes in cell lines was detected using quantitative real-time polymerase chain reaction and western blot analysis. After treatment of HepG2 cells with 5-Aza-2′-deoxycytidine (5-Aza-DC), gene expression was observed. Bisulfite sequencing PCR assay was used to detect methylation frequency. Overexpressed GRASP lentiviral vectors were constructed to analyze their influence on cell proliferation, migration, and invasion using cell counting kit-8 and transwell assays. Forty-three HCC prognosis-related genes were screened using the TCGA database. cg00249511 (SCT) was used to divide the DMPs into hyper- and hypomethylated groups, distinguishing between high- and low-risk samples. The prognosis survival model constructed using 12 genes revealed the prognosis type. GRASP messenger RNA was downregulated in HepG2 and upregulated after 5-Aza-DC treatment. In HCC tissues, methylation frequency of GRASP was upregulated. GRASP overexpression inhibited HepG2 cell proliferation, invasion, and G-CSFR expression. Thus, GRASP might be a prognosis-related gene controlled by methylation.     

Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates

DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Recent developments in whole genome bisulfite sequencing (WGBS) technology have enabled genome-wide measurements of DNA methylation at single base pair resolution. Many experiments have been conducted to compare DNA methylation profiles under different biological contexts, with the goal of identifying differentially methylated regions (DMRs). Due to the high cost of WGBS experiments, many studies are still conducted without biological replicates. Methods and tools available for analyzing such data are very limited.We develop a statistical method, DSS-single, for detecting DMRs from WGBS data without replicates. We characterize the count data using a rigorous model that accounts for the spatial correlation of methylation levels, sequence depth and biological variation. We demonstrate that using information from neighboring CG sites, biological variation can be estimated accurately even without replicates. DMR detection is then carried out via a Wald test procedure. Simulations demonstrate that DSS-single has greater sensitivity and accuracy than existing methods, and an analysis of H1 versus IMR90 cell lines suggests that it also yields the most biologically meaningful results. DSS-single is implemented in the Bioconductor package DSS.     

Genome-wide DNA methylation profiling of stomach cancer in the ethnic population of Mizoram,North East India

Stomach cancer is the fifth most common cancer in terms of prevalence and incidence and the fourth leading cause of mortality in men and women worldwide. It is well-established that aberrant DNA methylation in cells can lead to carcinogenesis. The primary objective of our study was to investigate the aberrant DNA methylation status of genes associated with stomach cancer with a particular reference to the ethnic population of Mizoram, North East India. The site-level analysis identified 2883 CpG sites differentially methylated, representing ～922 genes. Out of which 476 Differentially Methylated Positions (DMPs) were promoter-associated, 452 DMPs were hypermethylated, and 24 were hypomethylated. The region-level analysis identified 462 Differentially Methylated Regions (DMRs) corresponding to ～320 genes, of which ～281 genes were hypermethylated and ～40 genes were hypomethylated. TCGA analysis showed that some of the genes had been previously implicated in other cancers including stomach cancer. Five hypermethylated genes were selected as candidate genes for further investigations and they have shown to be novel and could serve as candidate hypermethylation biomarkers for stomach cancer in this particular ethnic group.     

A Comparison of the Whole Genome Approach of MeDIP-Seq to the Targeted Approach of the Infinium HumanMethylation450 BeadChip? for Methylome Profiling

DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.     

Comparative DNA methylome analysis of endometrial carcinoma reveals complex and distinct deregulation of cancer promoters and enhancers

Background

Aberrant DNA methylation is a hallmark of many cancers. Classically there are two types of endometrial cancer, endometrioid adenocarcinoma (EAC), or Type I, and uterine papillary serous carcinoma (UPSC), or Type II. However, the whole genome DNA methylation changes in these two classical types of endometrial cancer is still unknown.

Results

Here we described complete genome-wide DNA methylome maps of EAC, UPSC, and normal endometrium by applying a combined strategy of methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylation-sensitive restriction enzyme digestion sequencing (MRE-seq). We discovered distinct genome-wide DNA methylation patterns in EAC and UPSC: 27,009 and 15,676 recurrent differentially methylated regions (DMRs) were identified respectively, compared with normal endometrium. Over 80% of DMRs were in intergenic and intronic regions. The majority of these DMRs were not interrogated on the commonly used Infinium 450K array platform. Large-scale demethylation of chromosome X was detected in UPSC, accompanied by decreased XIST expression. Importantly, we discovered that the majority of the DMRs harbored promoter or enhancer functions and are specifically associated with genes related to uterine development and disease. Among these, abnormal methylation of transposable elements (TEs) may provide a novel mechanism to deregulate normal endometrium-specific enhancers derived from specific TEs.

Conclusions

DNA methylation changes are an important signature of endometrial cancer and regulate gene expression by affecting not only proximal promoters but also distal enhancers.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-868) contains supplementary material, which is available to authorized users.     

Calling differentially methylated regions from whole genome bisulphite sequencing with DMRcate

Whole genome bisulphite sequencing (WGBS) permits the genome-wide study of single molecule methylation patterns. One of the key goals of mammalian cell-type identity studies, in both normal differentiation and disease, is to locate differential methylation patterns across the genome. We discuss the most desirable characteristics for DML (differentially methylated locus) and DMR (differentially methylated region) detection tools in a genome-wide context and choose a set of statistical methods that fully or partially satisfy these considerations to compare for benchmarking. Our data simulation strategy is both biologically informed—employing distribution parameters derived from large-scale consortium datasets—and thorough. We report DML detection ability with respect to coverage, group methylation difference, sample size, variability and covariate size, both marginally and jointly, and exhaustively with respect to parameter combination. We also benchmark these methods on FDR control and computational time. We use this result to backend and introduce an expanded version of DMRcate: an existing DMR detection tool for microarray data that we have extended to now call DMRs from WGBS data. We compare DMRcate to a set of alternative DMR callers using a similarly realistic simulation strategy. We find DMRcate and RADmeth are the best predictors of DMRs, and conclusively find DMRcate the fastest.     

Genome-Wide Bisulphite Sequencing Uncovered the Contribution of DNA Methylation to Rice Short-Term Drought Memory Formation

Rice is the important crop for more than half of the world population. However, drought can have a devastating impact on rice growth and reduce yield drastically. Understanding the response of rice to drought stress is especially important for crop breeding. Previously we found that rice enhanced its tolerance to drought stresses via stress memory mechanisms. Numerous memory genes were identified to play important roles in the process. DNA methylation was reported to mediate tolerance via regulating gene expression and enhances the survival rate of rice encountering drought stress. However, how DNA methylation involved in stress memory is still not clear. In this study, genome-wide bisulphite sequencing at a single base resolution methylome profiling level was performed and analyzed in rice cultivar under recurrent drought stresses and recovery treatments. We found that rice drought stress memory-related differentially methylated regions (DMRs) showed dynamic and distinct patterns. The drought-memory DMRs may regulate Transposable elements and gene expression to cope with short-term repeated drought stresses. Our findings of drought-memory DMRs can explain mechanisms of rice drought stress memory in a new perspective on global methylome details. Using epigenetic markers to breed drought-resistant rice would become a feasible way in the future research.

     

Bisulfite sequencing and dinucleotide content analysis of 15 imprinted mouse differentially methylated regions (DMRs): paternally methylated DMRs contain less CpGs than maternally methylated DMRs

Imprinted genes in mammals show monoallelic expression dependent on parental origin and are often associated with differentially methylated regions (DMRs). There are two classes of DMR: primary DMRs acquire gamete-specific methylation in either spermatogenesis or oogenesis and maintain the allelic methylation differences throughout development; secondary DMRs establish differential methylation patterns after fertilization. Targeted disruption of some primary DMRs showed that they dictate the allelic expression of nearby imprinted genes and the establishment of the allelic methylation of secondary DMRs. However, how primary DMRs are recognized by the imprinting machinery is unknown. As a step toward elucidating the sequence features of the primary DMRs, we have determined the extents and boundaries of 15 primary mouse DMRs (including 12 maternally methylated and three paternally methylated DMRs) in 12.5-dpc embryos by bisulfite sequencing. We found that the average size of the DMRs was 3.2 kb and that their average G+C content was 54%. Dinucleotide content analysis of the DMR sequences revealed that, although they are generally CpG rich, the paternally methylated DMRs contain less CpGs than the maternally methylated DMRs. Our findings provide a basis for the further characterization of DMRs.     

MethylPurify: tumor purity deconvolution and differential methylation detection from single tumor DNA methylomes

We propose a statistical algorithm MethylPurify that uses regions with bisulfite reads showing discordant methylation levels to infer tumor purity from tumor samples alone. MethylPurify can identify differentially methylated regions (DMRs) from individual tumor methylome samples, without genomic variation information or prior knowledge from other datasets. In simulations with mixed bisulfite reads from cancer and normal cell lines, MethylPurify correctly inferred tumor purity and identified over 96% of the DMRs. From patient data, MethylPurify gave satisfactory DMR calls from tumor methylome samples alone, and revealed potential missed DMRs by tumor to normal comparison due to tumor heterogeneity.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0419-x) contains supplementary material, which is available to authorized users.     

Epigenome-wide association study reveals longitudinally stable DNA methylation differences in CD4+ T cells from children with IgE-mediated food allergy

Food allergy is mediated by a combination of genetic and environmental risk factors, potentially mediated by epigenetic mechanisms. CD4+ T-cells are key drivers of the allergic response, and may therefore harbor epigenetic variation in association with the disease phenotype. Here we retrospectively examined genome-wide DNA methylation profiles (~450?000 CpGs) from CD4+ T-cells on a birth cohort of 12 children with IgE-mediated food allergy diagnosed at 12-months, and 12 non-allergic controls. DNA samples were available at two time points, birth and 12-months. Case:control comparisons of CD4+ methylation profiles identified 179 differentially methylated probes (DMP) at 12-months and 136 DMP at birth (FDR-adjusted P value < 0.05, delta β > 0.1). Approximately 30% of DMPs were coincident with previously annotated SNPs. A total of 96 allergy-associated non-SNP DMPs were present at birth when individuals were initially disease-free, potentially implicating these loci in the causal pathway. Pathway analysis of differentially methylated genes identified several MAP kinase signaling molecules. Mass spectrometry was used to validate 15 CpG sites at 3 candidate genes. Combined analysis of differential methylation with gene expression profiles revealed gene expression differences at some but not all allergy associated differentially methylated genes. Thus, dysregulation of DNA methylation at MAPK signaling-associated genes during early CD4+ T-cell development may contribute to suboptimal T-lymphocyte responses in early childhood associated with the development of food allergy.     

Changepoint detection in base-resolution methylome data reveals a robust signature of methylated domain landscape

Background

Base-resolution methylome data generated by whole-genome bisulfite sequencing (WGBS) is often used to segment the genome into domains with distinct methylation levels. However, most segmentation methods include many parameters to be carefully tuned and/or fail to exploit the unsurpassed resolution of the data. Furthermore, there is no simple method that displays the composition of the domains to grasp global trends in each methylome.

Results

We propose to use changepoint detection for domain demarcation based on base-resolution methylome data. While the proposed method segments the methylome in a largely comparable manner to conventional approaches, it has only a single parameter to be tuned. Furthermore, it fully exploits the base-resolution of the data to enable simultaneous detection of methylation changes in even contrasting size ranges, such as focal hypermethylation and global hypomethylation in cancer methylomes. We also propose a simple plot termed methylated domain landscape (MDL) that globally displays the size, the methylation level and the number of the domains thus defined, thereby enabling one to intuitively grasp trends in each methylome. Since the pattern of MDL often reflects cell lineages and is largely unaffected by data size, it can serve as a novel signature of methylome.

Conclusions

Changepoint detection in base-resolution methylome data followed by MDL plotting provides a novel method for methylome characterization and will facilitate global comparison among various WGBS data differing in size and even species origin.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1809-5) contains supplementary material, which is available to authorized users.     

Genome-wide methylation profiling identifies hypermethylated biomarkers in high-grade cervical intraepithelial neoplasia

Epigenetic modifications, such as aberrant DNA promoter methylation, are frequently observed in cervical cancer. Identification of hypermethylated regions allowing discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3), or worse, may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions was studied using genome-wide DNA methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methylated DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium. Hypermethylated differentially methylated regions (DMRs) were identified. Validation of nine selected DMRs using BSP and MSP in cervical tissue revealed methylation in 63.2–94.7% high-grade CIN and in 59.3–100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was conducted exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples. Clinical validation of both markers in cervical scrapings from patients with an abnormal cervical smear confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion and that ROC analysis was discriminative. These markers represent the COL25A1 and KATNAL2 and their observed increased methylation upon progression could intimate the regulatory role in carcinogenesis. In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and are candidate biomarkers for early detection.