DMRforPairs: identifying differentially methylated regions between unique samples using array based methylation profiles

Evaluation of the pooled sample method in Infinium MethylationEPIC BeadChip array by comparison with individual samples

BACKGROUND

The pooled sample method is used in epigenomic research and expression analysis and is a cost-effective screening approach for small amounts of DNA. Evaluation of the pooled sample method in epigenomic studies is performed using the Illumina Infinium Methylation 450K BeadChip array; however, subsequent reports on the updated 850K array are lacking. A previous study demonstrated that the methylation levels obtained from individual samples were accurately replicated using pooled samples but did not address epigenome-wide association study (EWAS) statistics. The DNA quantification method, which is important for the homogeneous mixing of DNA in the pooled sample method, has since become fluorescence-based, and additional factors need to be considered including the resolution of batch effects of microarray chips and the heterogeneity of the cellular proportions from which the DNA samples are derived. In this study, four pooled samples were created from 44 individual samples, and EWAS statistics for differentially methylated positions (DMPs) and regions (DMRs) were conducted for individual samples and compared with the statistics obtained from the pooled samples.

RESULTS

The methylation levels could be reproduced fairly well in the pooled samples. This was the case for the entire dataset and when limited to the top 100 CpG sites, consistent with a previous study using the 450K BeadChip array. However, the statistical results of the EWAS for the DMP by individual samples were not replicated in pooled samples. Qualitative analyses highlighting methylation within an arbitrary candidate gene were replicable. Focusing on chr 20, the statistical results of EWAS for DMR from individual samples showed replicability in the pooled samples as long as they were limited to regions with a sufficient effect size.

CONCLUSIONS

The pooled sample method replicated the methylation values well and can be used for EWAS in DMR. This method is sample amount-effective and cost-effective and can be utilized for screening by carefully understanding the effective features and disadvantages of the pooled sample method and combining it with candidate gene analyses.

Comparative epigenetic analysis of tumour initiating cells and syngeneic EPSC-derived neural stem cells in glioblastoma

Epigenetic mechanisms which play an essential role in normal developmental processes, such as self-renewal and fate specification of neural stem cells (NSC) are also responsible for some of the changes in the glioblastoma (GBM) genome. Here we develop a strategy to compare the epigenetic and transcriptional make-up of primary GBM cells (GIC) with patient-matched expanded potential stem cell (EPSC)-derived NSC (iNSC). Using a comparative analysis of the transcriptome of syngeneic GIC/iNSC pairs, we identify a glycosaminoglycan (GAG)-mediated mechanism of recruitment of regulatory T cells (Tregs) in GBM. Integrated analysis of the transcriptome and DNA methylome of GBM cells identifies druggable target genes and patient-specific prediction of drug response in primary GIC cultures, which is validated in 3D and in vivo models. Taken together, we provide a proof of principle that this experimental pipeline has the potential to identify patient-specific disease mechanisms and druggable targets in GBM.

Whole-Genome Methylation Study of Congenital Lung Malformations in Children

Background and Objectives

The treatment of asymptomatic patients with congenital pulmonary malformations (CPMs) remains controversial, partially because the relationship between congenital lung malformations and malignancy is still undefined. Change in methylation pattern is a crucial event in human cancer, including lung cancer. We therefore studied all differentially methylated regions (DMRs) in a series of CPMs in an attempt to find methylation anomalies in genes already described in association with malignancy.

Methods

The DNA extracted from resected congenital lung malformations and control lung tissue was screened using Illumina MethylationEPIC arrays. Comparisons between the group of malformed samples or the malformed samples of same histology or each malformed sample and the controls and between a pleuropulmonary blastoma (PPB) and controls were performed. Moreover, each malformed sample was pairwise compared with its respective control. All differentially methylated regions (DMRs) with an adjusted p-value <0,05 were studied.

Results

Every comparison highlighted a number of DMRs closed to genes involved either in cell proliferation or in embryonic development or included in the Cancer Gene Census. Their abnormal methylation had been already described in lung tumors.

Conclusions

Methylation anomalies already described in lung tumors and also shared by the PPB were found in congenital lung malformations, regardless the histology. The presence of methylation abnormalities is suggestive of a correlation between congenital lung malformations and some step of malignant transformation.

Gene set enrichment analysis for genome-wide DNA methylation data

DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.

Genome wide methylation profiling of selected matched soft tissue sarcomas identifies methylation changes in metastatic and recurrent disease

In this study we used the Illumina Infinium Methylation array to investigate in a cohort of matched archival human tissue samples (n = 32) from 14 individuals with soft tissue sarcomas if genome-wide methylation changes occur during metastatic and recurrent (Met/Rec) disease. A range of sarcoma types were selected for this study: leiomyosarcoma (LMS), myxofibrosarcoma (MFS), rhabdomyosarcoma (RMS) and synovial sarcoma (SS). We identified differential methylation in all Met/Rec matched samples, demonstrating that epigenomic differences develop during the clonal evolution of sarcomas. Differentially methylated regions and genes were detected, not been previously implicated in sarcoma progression, including at PTPRN2 and DAXX in LMS, WT1-AS and TNXB in SS, VENTX and NTRK3 in pleomorphic RMS and MEST and the C14MC / miR-379/miR-656 in MFS. Our overall findings indicate the presence of objective epigenetic differences across primary and Met/Rec human tissue samples not previously reported.

Hodgkin Lymphoma Monozygotic Triplets Reveal Divergences in DNA Methylation Signatures

We studied DNA methylation profiles in four different cell populations from a unique constellation of monozygotic triplets in whom two had developed Hodgkin Lymphoma (HL). We detected shared differences in DNA methylation signatures when comparing the two HL-affected triplets with the non-affected triplet. The differences were observed in naïve B-cells and marginal zone-like B-cells. DNA methylation differences were also detected when comparing each of the HL-affected triplets against each other. Even though we cannot determine whether treatment and/or disease triggered the observed differences, we believe our data are important on behalf of forthcoming studies, and that it might provide important clues for a better understanding of HL pathogenesis.

Monozygotic Twins Discordant for Immunoglobulin A Nephropathy Display Differences in DNA Methylation and Gene Expression

Introduction

Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis. It involves both genetic and environmental factors, among which DNA methylation, the most studied epigenetic modification, was shown to play a role. Here, we assessed genome-wide DNA methylation and gene expression profiles in 2 pairs of IgAN-discordant monozygotic (MZ) twins, in order to characterize methylation changes and their potential influences on gene expression in IgAN.

Methods

Genome-wide DNA methylation and gene expression profiles were evaluated in peripheral blood mononuclear cells obtained from 2 IgAN-discordant MZ twins. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were detected, and an integrated analysis was performed. Finally, functional enrichment analysis was done for DMR-associated genes and DEGs.

Results

Totally 521 DMRs were detected for 2 IgAN-discordant MZ twins. Among them, 9 DMRs were found to be mapped to genes that differentially expressed in 2 MZ twins, indicating the potential regulatory mechanisms of expression for these 9 genes (MNDA, DYSF, IL1R2, TLR6, TREML2, TREM1, IL32, S1PR5, and ADGRE3) in IgAN. Biological process analysis of them showed that they were mostly involved in the immune system process. Functional enrichment analysis of DEGs and DMR-associated genes both identified multiple pathways relevant to inflammatory and immune responses. And DMR-associated genes were significantly enriched in terms related to T-cell function.

Conclusions

Our findings indicate that changes in DNA methylation patterns were involved in the pathogenesis of IgAN. Nine target genes detected in our study may provide new ideas for the exploration of molecular mechanisms of IgAN.

A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data

DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods use either differentially methylated CpG sites or combined CpG sites, namely differentially methylated regions, that can be mapped to genes. However, such methylation signal mapping has limitations. To address these limitations, in this study, we introduced a combinatorial framework using linear regression, differential expression, deep learning method for accurate biological interpretation of DNA methylation through integrating DNA methylation data and corresponding TCGA gene expression data. We demonstrated it for uterine cervical cancer. First, we pre-filtered outliers from the data set and then determined the predicted gene expression value from the pre-filtered methylation data through linear regression. We identified differentially expressed genes (DEGs) by Empirical Bayes test using Limma. Then we applied a deep learning method, "nnet" to classify the cervical cancer label of those DEGs to determine all classification metrics including accuracy and area under curve (AUC) through 10-fold cross validation. We applied our approach to uterine cervical cancer DNA methylation dataset (NCBI accession ID: GSE30760, 27,578 features covering 63 tumor and 152 matched normal samples). After linear regression and differential expression analysis, we obtained 6287 DEGs with false discovery rate (FDR) <0.001. After performing deep learning analysis, we obtained average classification accuracy 90.69% (±1.97%) of the uterine cervical cancerous labels. This performance is better than that of other peer methods. We performed in-degree and out-degree hub gene network analysis using Cytoscape. We reported five top in-degree genes (PAIP2, GRWD1, VPS4B, CRADD and LLPH) and five top out-degree genes (MRPL35, FAM177A1, STAT4, ASPSCR1 and FABP7). After that, we performed KEGG pathway and Gene Ontology enrichment analysis of DEGs using tool WebGestalt(WEB-based Gene SeT AnaLysis Toolkit). In summary, our proposed framework that integrated linear regression, differential expression, deep learning provides a robust approach to better interpret DNA methylation analysis and gene expression data in disease study.

BioMethyl: an R package for biological interpretation of DNA methylation data

Motivation

The accumulation of publicly available DNA methylation datasets has resulted in the need for tools to interpret the specific cellular phenotypes in bulk tissue data. Current approaches use either single differentially methylated CpG sites or differentially methylated regions that map to genes. However, these approaches may introduce biases in downstream analyses of biological interpretation, because of the variability in gene length. There is a lack of approaches to interpret DNA methylation effectively. Therefore, we have developed computational models to provide biological interpretation of relevant gene sets using DNA methylation data in the context of The Cancer Genome Atlas.

Results

We illustrate that Biological interpretation of DNA Methylation (BioMethyl) utilizes the complete DNA methylation data for a given cancer type to reflect corresponding gene expression profiles and performs pathway enrichment analyses, providing unique biological insight. Using breast cancer as an example, BioMethyl shows high consistency in the identification of enriched biological pathways from DNA methylation data compared to the results calculated from RNA sequencing data. We find that 12 out of 14 pathways identified by BioMethyl are shared with those by using RNA-seq data, with a Jaccard score 0.8 for estrogen receptor (ER) positive samples. For ER negative samples, three pathways are shared in the two enrichments with a slight lower similarity (Jaccard score = 0.6). Using BioMethyl, we can successfully identify those hidden biological pathways in DNA methylation data when gene expression profile is lacking.

Availability and implementation

BioMethyl R package is freely available in the GitHub repository (https://github.com/yuewangpanda/BioMethyl).

Supplementary information

Supplementary data are available at Bioinformatics online.

Comparing genome-scale DNA methylation and CNV marks between adult human cultured ITGA6+ testicular cells and seminomas to assess in vitro genomic stability

Autologous transplantation of spermatogonial stem cells is a promising new avenue to restore fertility in infertile recipients. Expansion of the initial spermatogonial stem cell pool through cell culturing is a necessary step to obtain enough cells for effective repopulation of the testis after transplantation. Since in vitro propagation can lead to (epi-)genetic mutations and possibly malignant transformation of the starting cell population, we set out to investigate genome-wide DNA methylation status in uncultured and cultured primary testicular ITGA6+ sorted cells and compare them with germ cell tumor samples of the seminoma subtype. Seminomas displayed a severely global hypomethylated profile, including loss of genomic imprinting, which we did not detect in cultured primary testicular ITGA6+ cells. Differential methylation analysis revealed altered regulation of gamete formation and meiotic processes in cultured primary testicular ITGA6+ cells but not in seminomas. The pivotal POU5F1 marker was hypomethylated in seminomas but not in uncultured or cultured primary testicular ITGA6+ cells, which is reflected in the POU5F1 mRNA expression levels. Lastly, seminomas displayed a number of characteristic copy number variations that were not detectable in primary testicular ITGA6+ cells, either before or after culture. Together, the data show a distinct DNA methylation patterns in cultured primary testicular ITGA6+ cells that does not resemble the pattern found in seminomas, but also highlight the need for more sensitive methods to fully exclude the presence of malignant cells after culture and to further study the epigenetic events that take place during in vitro culture.

Gene mutations and clonal architecture in myelodysplastic syndromes and changes upon progression to acute myeloid leukaemia and under treatment

Knowledge of the molecular and clonal characteristics in the myelodysplastic syndromes (MDS) and during progression to acute myeloid leukaemia (AML) is essential to understand the disease dynamics and optimize treatment. Sequencing serial bone marrow samples of eight patients, we observed that MDS featured a median of 3 mutations. Mutations in genes involved in RNA-splicing or epigenetic regulation were most frequent, and exclusively present in the major clone. Minor subclones were distinguishable in three patients. As the MDS progressed, a median of one mutation was gained, leading to clonal outgrowth. No AML developed genetically independent of a pre-existing clone. The gained mutation mostly affected genes encoding signalling proteins. Additional acquisition of genomic aberrations frequently occurred. Upon treatment, emergence of new clones could be observed. As confirmed by single-cell sequencing, multiple mutations in identical genes in different clones were present within individual patients. DNA-methylation profiling in patients without identification of novel mutations in AML revealed methylation changes in individual genes. In conclusion, our data complement previous observations on the mutational and clonal characteristics in MDS and at progression. Moreover, DNA-methylation changes may be associated with progression in single patients. Redundancy of mutated genes in different clones suggests fertile grounds promoting clonal selection or acquisition.

Subtle Alterations in DNA Methylation Patterns in Normal Cells in Response to Dietary Stilbenoids

SCOPE

Searching for correlations between dietary polyphenols and risk of chronic diseases has been a challenge due to the lack of quantitative evaluation methods of long-term exposure. We previously observed substantial DNA methylation changes in human cancer cells upon treatment with polyphenols of the stilbenoid class. When induced in normal cells, such molecular changes may persist and reflect chronic exposure.

METHODS AND RESULTS

Illumina 450K microarray is used to delineate a genome wide DNA methylation landscape in MCF10A human immortalized mammary epithelial cells exposed to resveratrol (RSV) at noncytotoxic 15 μM dose for 9 days. Subtle alterations are observed suggesting remodeling of DNA methylation patterns rather than switch on/off changes. Using pyrosequencing, DNA methylation is quantitatively measured at eight CpG sites located within KCNJ4, RNF169, BCHE, DAOA, HOXA9, RUNX3, KRTAP2-1, and TAGAP, upon exposure to RSV or pterostilbene and shows similar differences induced by both stilbenoids. Two of the probes, Runx3 and Kcnj4, are successfully verified in whole blood DNA from healthy rats on diets supplemented with stilbenoids.

CONCLUSIONS

The study provides strong support for testing the utility of polyphenol-mediated changes in DNA methylation as quantitative measures of long-term dietary exposures in nutritional epidemiology and clinical trials.

DNA methylation profiling of asbestos-treated MeT5A cell line reveals novel pathways implicated in asbestos response

Occupational and environmental asbestos exposure is the main determinant of malignant pleural mesothelioma (MPM), however, the mechanisms by which its fibres contribute to cell toxicity and transformation are not completely clear. Aberrant DNA methylation is a common event in cancer but epigenetic modifications involved specifically in MPM carcinogenesis need to be better clarified. To investigate asbestos-induced DNA methylation and gene expression changes, we treated Met5A mesothelial cells with different concentrations of crocidolite and chrysotile asbestos (0.5 ÷ 5.0 µg/cm², 72 h incubation). Overall, we observed 243 and 302 differentially methylated CpGs (≥ 10%) between the asbestos dose at 5 µg/cm² and untreated control, in chrysotile and crocidolite treatment, respectively. To examine the dose-response effect, Spearman's correlation test was performed and significant CpGs located in genes involved in migration/cell adhesion processes were identified in both treatments. Moreover, we found that both crocidolite and chrysotile exposure induced a significant up-regulation of CA9 and SRGN (log2 fold change > 1.5), previously reported as associated with a more aggressive MPM phenotype. However, we found no correlation between methylation and gene expression changes, except for a moderate significant inverse correlation at the promoter region of DKK1 (Spearman rho = - 1, P value = 0.02) after chrysotile exposure. These results describe for the first time the relationship between DNA methylation modifications and asbestos exposure. Our findings provide a basis to further explore and validate asbestos-induced DNA methylation changes, that could influence MPM carcinogenesis and possibly identifying new chemopreventive target.

Genome wide DNA methylation profiles provide clues to the origin and pathogenesis of germ cell tumors

The cell of origin of the five subtypes (I-V) of germ cell tumors (GCTs) are assumed to be germ cells from different maturation stages. This is (potentially) reflected in their methylation status as fetal maturing primordial germ cells are globally demethylated during migration from the yolk sac to the gonad. Imprinted regions are erased in the gonad and later become uniparentally imprinted according to fetal sex. Here, 91 GCTs (type I-IV) and four cell lines were profiled (Illumina’s HumanMethylation450BeadChip). Data was pre-processed controlling for cross hybridization, SNPs, detection rate, probe-type bias and batch effects. The annotation was extended, covering snRNAs/microRNAs, repeat elements and imprinted regions. A Hidden Markov Model-based genome segmentation was devised to identify differentially methylated genomic regions. Methylation profiles allowed for separation of clusters of non-seminomas (type II), seminomas/dysgerminomas (type II), spermatocytic seminomas (type III) and teratomas/dermoid cysts (type I/IV). The seminomas, dysgerminomas and spermatocytic seminomas were globally hypomethylated, in line with previous reports and their demethylated precursor. Differential methylation and imprinting status between subtypes reflected their presumed cell of origin. Ovarian type I teratomas and dermoid cysts showed (partial) sex specific uniparental maternal imprinting. The spermatocytic seminomas showed uniparental paternal imprinting while testicular teratomas exhibited partial imprinting erasure. Somatic imprinting in type II GCTs might indicate a cell of origin after global demethylation but before imprinting erasure. This is earlier than previously described, but agrees with the totipotent/embryonic stem cell like potential of type II GCTs and their rare extra-gonadal localization. The results support the common origin of the type I teratomas and show strong similarity between ovarian type I teratomas and dermoid cysts. In conclusion, we identified specific and global methylation differences between GCT subtypes, providing insight into their developmental timing and underlying developmental biology. Data and extended annotation are deposited at GEO (GSE58538 and GPL18809).

Seminoma and embryonal carcinoma footprints identified by analysis of integrated genome-wide epigenetic and expression profiles of germ cell cancer cell lines

Background

Originating from Primordial Germ Cells/gonocytes and developing via a precursor lesion called Carcinoma In Situ (CIS), Germ Cell Cancers (GCC) are the most common cancer in young men, subdivided in seminoma (SE) and non-seminoma (NS). During physiological germ cell formation/maturation, epigenetic processes guard homeostasis by regulating the accessibility of the DNA to facilitate transcription. Epigenetic deregulation through genetic and environmental parameters (i.e. genvironment) could disrupt embryonic germ cell development, resulting in delayed or blocked maturation. This potentially facilitates the formation of CIS and progression to invasive GCC. Therefore, determining the epigenetic and functional genomic landscape in GCC cell lines could provide insight into the pathophysiology and etiology of GCC and provide guidance for targeted functional experiments.

Results

This study aims at identifying epigenetic footprints in SE and EC cell lines in genome-wide profiles by studying the interaction between gene expression, DNA CpG methylation and histone modifications, and their function in the pathophysiology and etiology of GCC. Two well characterized GCC-derived cell lines were compared, one representative for SE (TCam-2) and the other for EC (NCCIT). Data were acquired using the Illumina HumanHT-12-v4 (gene expression) and HumanMethylation450 BeadChip (methylation) microarrays as well as ChIP-sequencing (activating histone modifications (H3K4me3, H3K27ac)). Results indicate known germ cell markers not only to be differentiating between SE and NS at the expression level, but also in the epigenetic landscape.

Conclusion

The overall similarity between TCam-2/NCCIT support an erased embryonic germ cell arrested in early gonadal development as common cell of origin although the exact developmental stage from which the tumor cells are derived might differ. Indeed, subtle difference in the (integrated) epigenetic and expression profiles indicate TCam-2 to exhibit a more germ cell-like profile, whereas NCCIT shows a more pluripotent phenotype. The results provide insight into the functional genome in GCC cell lines.