Generating Multiple Base-Resolution DNA Methylomes Using Reduced Representation Bisulfite Sequencing

Cell-free DNA methylation in the clinical management of lung cancer

The clinical use of cell-free DNA (cfDNA) methylation in managing lung cancer depends on its ability to differentiate between malignant and healthy cells, assign methylation changes to specific tissue sources, and elucidate opportunities for targeted therapy. From a technical standpoint, cfDNA methylation analysis is primed as a potential clinical tool for lung cancer screening, early diagnosis, prognostication, and treatment, pending the outcome of elaborate validation studies. Here, we discuss the current state of the art in cfDNA methylation analysis, examine the unique features and limitations of these new methods in a clinical context, propose two models for applying cfDNA methylation data for lung cancer screening, and discuss future research directions.

Benchmarking DNA Methylation Analysis of 14 Alignment Algorithms for Whole Genome Bisulfite Sequencing in Mammals

Whole genome bisulfite sequencing (WGBS) is an essential technique for methylome studies. Although a series of tools have been developed to overcome the mapping challenges caused by bisulfite treatment, the latest available tools have not been evaluated on the performance of reads mapping as well as on biological insights in multiple mammals. Herein, based on the real and simulated WGBS data of 14.77 billion reads, we undertook 936 mappings to benchmark and evaluate 14 wildly utilized alignment algorithms from reads mapping to biological interpretation in humans, cattle and pigs: Bwa-meth, BSBolt, BSMAP, Walt, Abismal, Batmeth2, Hisat_3n, Hisat_3n_repeat, Bismark-bwt2-e2e, Bismark-his2, BSSeeker2-bwt, BSSeeker2-soap2, BSSeeker2-bwt2-e2e and BSSeeker2-bwt2-local. Specifically, Bwa-meth, BSBolt, BSMAP, Bismark-bwt2-e2e and Walt exhibited higher uniquely mapped reads, mapped precision, recall and F1 score than other nine alignment algorithms, and the influences of distinct alignment algorithms on the methylomes varied considerably at the numbers and methylation levels of CpG sites, the calling of differentially methylated CpGs (DMCs) and regions (DMRs). Moreover, we reported that BSMAP showed the highest accuracy at the detection of CpG coordinates and methylation levels, the calling of DMCs, DMRs, DMR-related genes and signaling pathways. These results suggested that careful selection of algorithms to profile the genome-wide DNA methylation is required, and our works provided investigators with useful information on the choice of alignment algorithms to effectively improve the DNA methylation detection accuracy in mammals.

Generating Sequencing-Based DNA Methylation Maps from Low DNA Input Samples

Reduced representation bisulfite sequencing (RRBS) is a technique used for assessing genome-wide DNA methylation patterns in eukaryotes. RRBS was introduced to focus on CpG-rich regions that are likely to be of most interest for epigenetic regulation, such as gene promoters and enhancer sequence elements (Meissner et al., Nature 454:766-770, 2008). This "reduced representation" lowers the cost of sequencing and also gives increased depth of coverage, facilitating the resolution of more subtle changes in methylation levels. Here, we describe a modified RRBS sequencing (RRBS-seq) library preparation. Our protocol is optimized for generating single base-resolution libraries when low input DNA is a concern (10-100 ng). Our protocol includes steps to optimize library preparation, such as using deparaffinization solution (when formalin-fixed material is used), and a replacement of gel size-selection with sample purification beads. The described protocol can be accomplished in 3 days and has been successfully applied to tissues or cells from different organisms, including formalin-fixed tissues, to yield robust and reproducible results.

The Mouse Papillomavirus Epigenetic Signature Is Characterised by DNA Hypermethylation after Lesion Regression

Papillomaviruses (PVs) are double-stranded DNA tumour viruses that can infect cutaneous and mucosal epidermis. Human papillomavirus (HPV) types have been linked to the causality of cutaneous squamous cell carcinoma (cSCC); however, HPV DNA is not always detected in the resultant tumour. DNA methylation is an epigenetic change that can contribute to carcinogenesis. We hypothesise that the DNA methylation pattern in cells is altered following PV infection. We tested if DNA methylation was altered by PV infection in the mouse papillomavirus (MmuPV1) model. Immunosuppressed mice were infected with MmuPV1 on cutaneous tail skin. Immunosuppression was withdrawn for some mice, causing lesions to spontaneously regress. Reduced representation bisulphite sequencing was carried out on DNA from the actively infected lesions, visibly regressed lesions, and mock-infected control mice. DNA methylation libraries were generated and analysed for differentially methylated regions throughout the genome. The presence of MmuPV1 sequences was also assessed. We identified 834 predominantly differentially hypermethylated fragments in regressed lesions, and no methylation differences in actively infected lesions. The promoter regions of genes associated with tumorigenicity, including the tumour suppressor protein DAPK1 and mismatch repair proteins MSH6 and PAPD7, were hypermethylated. Viral DNA was detected in active lesions and in some lesions that had regressed. This is the first description of the genome-wide DNA methylation landscape for active and regressed MmuPV1 lesions. We propose that the DNA hypermethylation in the regressed lesions that we report here may increase the susceptibility of cells to ultraviolet-induced cSCC.

Genome-wide DNA methylation of the liver reveals delayed effects of early-life exposure to 17-α-ethinylestradiol in the self-fertilizing mangrove rivulus

Organisms exposed to endocrine disruptors in early life can show altered phenotype later in adulthood. Although the mechanisms underlying these long-term effects remain poorly understood, an increasing body of evidence points towards the potential role of epigenetic processes. In the present study, we exposed hatchlings of an isogenic lineage of the self-fertilizing fish mangrove rivulus for 28 days to 4 and 120 ng/L of 17-α-ethinylestradiol. After a recovery period of 140 days, reduced representation bisulphite sequencing (RRBS) was performed on the liver in order to assess the hepatic genome-wide methylation landscape. Across all treatment comparisons, a total of 146 differentially methylated fragments (DMFs) were reported, mostly for the group exposed to 4 ng/L, suggesting a non-monotonic effect of EE2 exposure. Gene ontology analysis revealed networks involved in lipid metabolism, cellular processes, connective tissue function, molecular transport and inflammation. The highest effect was reported for nipped-B-like protein B (NIPBL) promoter region after exposure to 4 ng/L EE2 (+ 21.9%), suggesting that NIPBL could be an important regulator for long-term effects of EE2. Our results also suggest a significant role of DNA methylation in intergenic regions and potentially in transposable elements. These results support the ability of early exposure to endocrine disruptors of inducing epigenetic alterations during adulthood, providing plausible mechanistic explanations for long-term phenotypic alteration. Additionally, this work demonstrates the usefulness of isogenic lineages of the self-fertilizing mangrove rivulus to better understand the biological significance of long-term alterations of DNA methylation by diminishing the confounding factor of genetic variability.

Comparison of Global DNA Methylation Patterns in Human Melanoma Tissues and Their Derivative Cell Lines

Simple Summary

Cancer cell lines are a defined population of cells, originally sourced from tumour tissue, that can be maintained in culture for an extended period of time. They are a critical laboratory-based model, and are frequently used to unravel mechanisms of cancer cell biology. In all cells, gene activity is in part regulated by DNA methylation, the epigenetic process by which methyl groups are added to DNA. In this study, we demonstrate that at a global level, DNA methylation profiles are globally well conserved, but we identify specific sites that are consistently more methylated in tumour-derived cell lines compared to the original tumour tissue. The genes associated with these common differentially methylated regions are involved in important cellular processes and are strongly enriched for epigenetic mechanisms associated with suppression of gene activity. This study provides a valuable resource for identifying false positives due to cell culture and for better interpretation of future cancer epigenetics studies.

Abstract

DNA methylation is a heritable epigenetic mark that is fundamental to mammalian development. Aberrant DNA methylation is an epigenetic hallmark of cancer cells. Cell lines are a critical in vitro model and very widely used to unravel mechanisms of cancer cell biology. However, limited data are available to assess whether DNA methylation patterns in tissues are retained when cell lines are established. Here, we provide the first genome-scale sequencing-based methylation map of metastatic melanoma tumour tissues and their derivative cell lines. We show that DNA methylation profiles are globally conserved in vitro compared to the tumour tissue of origin. However, we identify sites that are consistently hypermethylated in cell lines compared to their tumour tissue of origin. The genes associated with these common differentially methylated regions are involved in cell metabolism, cell cycle and apoptosis and are also strongly enriched for the H3K27me3 histone mark and PRC2 complex-related genes. Our data indicate that although global methylation patterns are similar between tissues and cell lines, there are site-specific epigenomic differences that could potentially impact gene expression. Our work provides a valuable resource for identifying false positives due to cell culture and for better interpretation of cancer epigenetics studies in the future.

Extensive Inter-Cyst DNA Methylation Variation in Autosomal Dominant Polycystic Kidney Disease Revealed by Genome Scale Sequencing

Autosomal dominant polycystic kidney disease (ADPKD) is a heritable disease characterized by bilateral renal enlargement due to the growth of cysts throughout the kidneys. Inheritance of a disease-causing mutation is required to develop ADPKD, which results in end-stage kidney disease and is associated with a high morbidity. The pathology underlying cyst formation is not well understood. To address this, we have previously shown the global methylome is altered in ADPKD tissue, suggesting a role of DNA methylation in disease-state renal tissue. As cysts are believed to arise independently, we hypothesize that DNA methylation changes vary accordingly. Here we further investigate the role of DNA methylation within independent cysts to characterize key intra-individual changes. We demonstrate that fragments within CpG islands and gene bodies harbor the greatest amount of variation across the ADPKD kidney, while intergenic fragments are comparatively stable. A proportion of variably methylated genes were also differentially methylated in ADPKD tissue. Our data provide evidence that individual molecular mechanisms are operating in the development of each cyst.

Genome-wide miRNA methylome analysis in oral cancer: possible biomarkers associated with patient survival

AIM

The methylome associated with miRNA loci was investigated in oral cancer to explore tobacco specific methylation and potential biomarkers for patient survival.

METHODS

Methylome data was generated from 16 pairs of cancer-normal tissues by reduced representation bisulfite sequencing method. Differentially methylated regions were identified using the DMAP pipeline. In silico validation and Kaplan-Meier survival analyses were performed on The Cancer Genome Atlas data based on our miRNA methylome data.

RESULTS

A total of 4310 unique differentially methylated regions, mapping to 144 miRNA loci, were identified. Three distinct groups of miRNAs were differentially methylated in cancer tissues from smokers, chewers and mixed habitués. Hypermethylation of miR-503, miR-200a/b, miR-320b and miR-489 was associated with worse 5-year survival.

CONCLUSION

Differential methylation patterns in miRNA loci are associated with poor survival underscoring their potential as predictive and prognostic biomarkers in oral cancer.

DNA Methylation Analysis

DNA methylation is a process by which methyl groups are added to cytosine or adenine. DNA methylation can change the activity of the DNA molecule without changing the sequence. Methylation of 5-methylcytosine (5mC) is widespread in both eukaryotes and prokaryotes, and it is a very important epigenetic modification event, which can regulate gene activity and influence a number of key processes such as genomic imprinting, cell differentiation, transcriptional regulation, and chromatin remodeling. Profiling DNA methylation across the genome is critical to understanding the influence of methylation in normal biology and diseases including cancer. Recent discoveries of 5-methylcytosine (5mC) oxidation derivatives including 5-hydroxymethylcytosine (5hmC), 5-formylcytsine (5fC), and 5-carboxycytosine (5caC) in mammalian genome further expand our understanding of the methylation regulation. Genome-wide analyses such as microarrays and next-generation sequencing technologies have been used to assess large fractions of the methylome. A number of different quantitative approaches have also been established to map the DNA epigenomes with single-base resolution, as represented by the bisulfite-based methods, such as classical bisulfite sequencing, pyrosequencing etc. These methods have been used to generate base-resolution maps of 5mC and its oxidation derivatives in genomic samples. The focus of this chapter is to provide the methodologies that have been developed to detect the cytosine derivatives in the genomic DNA.

Marked Global DNA Hypomethylation Is Associated with Constitutive PD-L1 Expression in Melanoma

Constitutive expression of the immune checkpoint, PD-L1, inhibits anti-tumor immune responses in cancer, although the factors involved in PD-L1 regulation are poorly understood. Here we show that loss of global DNA methylation, particularly in intergenic regions and repeat elements, is associated with constitutive (PD-L1_CON), versus inducible (PD-L1_IND), PD-L1 expression in melanoma cell lines. We further show this is accompanied by transcriptomic up-regulation. De novo epigenetic regulators (e.g., DNMT3A) are strongly correlated with PD-L1 expression and methylome status. Accordingly, decitabine-mediated inhibition of global methylation in melanoma cells leads to increased PD-L1 expression. Moreover, viral mimicry and immune response genes are highly expressed in lymphocyte-negative plus PD-L1-positive melanomas, versus PD-L1-negative melanomas in The Cancer Genome Atlas (TCGA). In summary, using integrated genomic analysis we identified that global DNA methylation influences PD-L1 expression in melanoma, and hence melanoma's ability to evade anti-tumor immune responses. These results have implications for combining epigenetic therapy with immunotherapy.

A streamlined method for analysing genome-wide DNA methylation patterns from low amounts of FFPE DNA

Background

Formalin fixed paraffin embedded (FFPE) tumor samples are a major source of DNA from patients in cancer research. However, FFPE is a challenging material to work with due to macromolecular fragmentation and nucleic acid crosslinking. FFPE tissue particularly possesses challenges for methylation analysis and for preparing sequencing-based libraries relying on bisulfite conversion. Successful bisulfite conversion is a key requirement for sequencing-based methylation analysis.

Methods

Here we describe a complete and streamlined workflow for preparing next generation sequencing libraries for methylation analysis from FFPE tissues. This includes, counting cells from FFPE blocks and extracting DNA from FFPE slides, testing bisulfite conversion efficiency with a polymerase chain reaction (PCR) based test, preparing reduced representation bisulfite sequencing libraries and massively parallel sequencing.

Results

The main features and advantages of this protocol are:

An optimized method for extracting good quality DNA from FFPE tissues.

An efficient bisulfite conversion and next generation sequencing library preparation protocol that uses 50 ng DNA from FFPE tissue.

Incorporation of a PCR-based test to assess bisulfite conversion efficiency prior to sequencing.

Conclusions

We provide a complete workflow and an integrated protocol for performing DNA methylation analysis at the genome-scale and we believe this will facilitate clinical epigenetic research that involves the use of FFPE tissue.

Electronic supplementary material

The online version of this article (10.1186/s12920-017-0290-1) contains supplementary material, which is available to authorized users.

Comparative assessment of DNA methylation patterns between reduced representation bisulfite sequencing and Sequenom EpiTyper methylation analysis

AIM

Validation of sequencing-based DNA methylation data is an important step for meaningful translation of findings. However, there has been limited assessment of different platforms to validate methylation data from next generation sequencing.

METHODS

We performed a comparative methylation analysis between the genome-wide platform of reduced representation bisulfite sequencing with a targeted, Sequenom EpiTyper platform (four genes were analyzed in 15 cell lines covering 52 CpG sites).

RESULTS

We show that the accuracy of validation substantially improves if results from multiple and adjacent CpG sites are combined rather than at single CpG sites. We demonstrate increased read number improves accuracy of reduced representation bisulfite sequencing results. Further, by using series of replicates, we document variation in samples analyzed by Sequenom EpiTyper, indicating the importance of including replicates to increase precision.

CONCLUSION

The results reveal potential sources of bias and provide a guideline for refining study design for DNA methylation analysis.