Methylome analysis identifies a Wilms tumor epigenetic biomarker detectable in blood

Background

Wilms tumor is the most common pediatric renal malignancy and there is a clinical need for a molecular biomarker to assess treatment response and predict relapse. The known mutated genes in this tumor type show low mutation frequencies, whereas aberrant methylation at 11p15 is by far the most common aberration. We therefore analyzed the epigenome, rather than the genome, to identify ubiquitous tumor-specific biomarkers.

Results

Methylome analysis of matched normal kidney and Wilms tumor identifies 309 preliminary methylation variable positions which we translate into three differentially methylated regions (DMRs) for use as tumor-specific biomarkers. Using two novel algorithms we show that these three DMRs are not confounded by cell type composition. We further show that these DMRs are not methylated in embryonic blastema but are intermediately methylated in Wilms tumor precursor lesions. We validate the biomarker DMRs using two independent sample sets of normal kidney and Wilms tumor and seven Wilms tumor histological subtypes, achieving 100% and 98% correct classification, respectively. As proof-of-principle for clinical utility, we successfully use biomarker DMR-2 in a pilot analysis of cell-free circulating DNA to monitor tumor response during treatment in ten patients.

Conclusions

These findings define the most common methylated regions in Wilms tumor known to date which are not associated with their embryonic origin or precursor stage. We show that this tumor-specific methylated DNA is released into the blood circulation where it can be detected non-invasively showing potential for clinical utility.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0434-y) contains supplementary material, which is available to authorized users.     

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

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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

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Whole genome sequencing and methylome analysis of the wild guinea pig

Background

DNA methylation is a heritable mechanism that acts in response to environmental changes, lifestyle and diseases by influencing gene expression in eukaryotes. Epigenetic studies of wild organisms are mandatory to understand their role in e.g. adaptational processes in the great variety of ecological niches. However, strategies to address those questions on a methylome scale are widely missing. In this study we present such a strategy and describe a whole genome sequence and methylome analysis of the wild guinea pig.

Results

We generated a full Wild guinea pig (Cavia aperea) genome sequence with enhanced coverage of methylated regions, benefiting from the available sequence of the domesticated relative Cavia porcellus. This new genome sequence was then used as reference to map the sequence reads of bisulfite treated Wild guinea pig sequencing libraries to investigate DNA-methylation patterns at nucleotide-specific level, by using our here described method, named ‘DNA-enrichment-bisulfite-sequencing’ (MEBS). The results achieved using MEBS matched those of standard methods in other mammalian model species. The technique is cost efficient, and incorporates both methylation enrichment results and a nucleotide-specific resolution even without a whole genome sequence available. Thus MEBS can be easily applied to extend methylation enrichment studies to a nucleotide-specific level.

Conclusions

The approach is suited to study methylomes of not yet sequenced mammals at single nucleotide resolution. The strategy is transferable to other mammalian species by applying the nuclear genome sequence of a close relative. It is therefore of interest for studies on a variety of wild species trying to answer evolutionary, adaptational, ecological or medical questions by epigenetic mechanisms.

Electronic supplementary material

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Whole Methylome Analysis by Ultra-Deep Sequencing Using Two-Base Encoding

Methylation, the addition of methyl groups to cytosine (C), plays an important role in the regulation of gene expression in both normal and dysfunctional cells. During bisulfite conversion and subsequent PCR amplification, unmethylated Cs are converted into thymine (T), while methylated Cs will not be converted. Sequencing of this bisulfite-treated DNA permits the detection of methylation at specific sites. Through the introduction of next-generation sequencing technologies (NGS) simultaneous analysis of methylation motifs in multiple regions provides the opportunity for hypothesis-free study of the entire methylome. Here we present a whole methylome sequencing study that compares two different bisulfite conversion methods (in solution versus in gel), utilizing the high throughput of the SOLiD™ System. Advantages and disadvantages of the two different bisulfite conversion methods for constructing sequencing libraries are discussed. Furthermore, the application of the SOLiD™ bisulfite sequencing to larger and more complex genomes is shown with preliminary in silico created bisulfite converted reads.     

Whole genome bisulfite sequencing of cell-free DNA and its cellular contributors uncovers placenta hypomethylated domains

BackgroundCirculating cell-free fetal DNA has enabled non-invasive prenatal fetal aneuploidy testing without direct discrimination of the maternal and fetal DNA. Testing may be improved by specifically enriching the sample material for fetal DNA. DNA methylation may allow for such a separation of DNA; however, this depends on knowledge of the methylomes of circulating cell-free DNA and its cellular contributors.ResultsWe perform whole genome bisulfite sequencing on a set of unmatched samples including circulating cell-free DNA from non-pregnant and pregnant female donors and genomic DNA from maternal buffy coat and placenta samples. We find CpG cytosines within longer fragments are more likely to be methylated. Comparison of the methylomes of placenta and non-pregnant circulating cell-free DNA reveal many of the 51,259 identified differentially methylated regions are located in domains exhibiting consistent placenta hypomethylation across millions of consecutive bases. We find these placenta hypomethylated domains are consistently located within regions exhibiting low CpG and gene density. Differentially methylated regions identified when comparing placenta to non-pregnant circulating cell-free DNA are recapitulated in pregnant circulating cell-free DNA, confirming the ability to detect differential methylation in circulating cell-free DNA mixtures.ConclusionsWe generate methylome maps for four sample types at single-base resolution, identify a link between DNA methylation and fragment length in circulating cell-free DNA, identify differentially methylated regions between sample groups, and uncover the presence of megabase-size placenta hypomethylated domains.

Electronic supplementary material

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The potential role of Alu Y in the development of resistance to SN38 (Irinotecan) or oxaliplatin in colorectal cancer

Background

Irinotecan (SN38) and oxaliplatin are chemotherapeutic agents used in the treatment of colorectal cancer. However, the frequent development of resistance to these drugs represents a considerable challenge in the clinic. Alus as retrotransposons comprise 11% of the human genome. Genomic toxicity induced by carcinogens or drugs can reactivate Alus by altering DNA methylation. Whether or not reactivation of Alus occurs in SN38 and oxaliplatin resistance remains unknown.

Results

We applied reduced representation bisulfite sequencing (RRBS) to investigate the DNA methylome in SN38 or oxaliplatin resistant colorectal cancer cell line models. Moreover, we extended the RRBS analysis to tumor tissue from 14 patients with colorectal cancer who either did or did not benefit from capecitabine + oxaliplatin treatment. For the clinical samples, we applied a concept of ‘DNA methylation entropy’ to estimate the diversity of DNA methylation states of the identified resistance phenotype-associated methylation loci observed in the cell line models. We identified different loci being characteristic for the different resistant cell lines. Interestingly, 53% of the identified loci were Alu sequences- especially the Alu Y subfamily. Furthermore, we identified an enrichment of Alu Y sequences that likely results from increased integration of new copies of Alu Y sequence in the drug-resistant cell lines. In the clinical samples, SOX1 and other SOX gene family members were shown to display variable DNA methylation states in their gene regions. The Alu Y sequences showed remarkable variation in DNA methylation states across the clinical samples.

Conclusion

Our findings imply a crucial role of Alu Y in colorectal cancer drug resistance. Our study underscores the complexity of colorectal cancer aggravated by mobility of Alu elements and stresses the importance of personalized strategies, using a systematic and dynamic view, for effective cancer therapy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1552-y) contains supplementary material, which is available to authorized users.     

Advanced methylome analysis after bisulfite deep sequencing: an example in Arabidopsis

Deep sequencing after bisulfite conversion (BS-Seq) is the method of choice to generate whole genome maps of cytosine methylation at single base-pair resolution. Its application to genomic DNA of Arabidopsis flower bud tissue resulted in the first complete methylome, determining a methylation rate of 6.7% in this tissue. BS-Seq reads were mapped onto an in silico converted reference genome, applying the so-called 3-letter genome method. Here, we present BiSS (Bisufite Sequencing Scorer), a new method applying Smith-Waterman alignment to map bisulfite-converted reads to a reference genome. In addition, we introduce a comprehensive adaptive error estimate that accounts for sequencing errors, erroneous bisulfite conversion and also wrongly mapped reads. The re-analysis of the Arabidopsis methylome data with BiSS mapped substantially more reads to the genome. As a result, it determines the methylation status of an extra 10% of cytosines and estimates the methylation rate to be 7.7%. We validated the results by individual traditional bisulfite sequencing for selected genomic regions. In addition to predicting the methylation status of each cytosine, BiSS also provides an estimate of the methylation degree at each genomic site. Thus, BiSS explores BS-Seq data more extensively and provides more information for downstream analysis.     

Biased estimates of clonal evolution and subclonal heterogeneity can arise from PCR duplicates in deep sequencing experiments

Accurate allele frequencies are important for measuring subclonal heterogeneity and clonal evolution. Deep-targeted sequencing data can contain PCR duplicates, inflating perceived read depth. Here we adapted the Illumina TruSeq Custom Amplicon kit to include single molecule tagging (SMT) and show that SMT-identified duplicates arise from PCR. We demonstrate that retention of PCR duplicate reads can imply clonal evolution when none exists, while their removal effectively controls the false positive rate. Additionally, PCR duplicates alter estimates of subclonal heterogeneity in tumor samples. Our method simplifies PCR duplicate identification and emphasizes their removal in studies of tumor heterogeneity and clonal evolution.

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Adaptation of the CHARM DNA methylation platform for the rat genome reveals novel brain region-specific differences

Comprehensive High-throughput Arrays for Relative Methylation (CHARM) was recently developed as an experimental platform and analytic approach to assess DNA methylation (DNAm) at a genome-wide level. Its initial implementation was for human and mouse. We adapted it for rat and sought to examine DNAm differences across tissues and brain regions in this model organism. We extracted DNA from liver, spleen, and three brain regions: cortex, hippocampus, and hypothalamus from adult Sprague Dawley rats. DNA was digested with McrBC, and the resulting methyl-depleted fraction was hybridized to the rat CHARM array along with a mock-treated fraction. Differentially methylated regions (DMRs) between tissue types were detected using normalized methylation log-ratios. In validating 24 of the most significant DMRs by bisulfite pyrosequencing, we detected large mean differences in DNAm, ranging from 33-59%, among the most significant DMRs in the across-tissue comparisons. The comparable figures for the hippocampus vs. hypothalamus DMRs were 14-40%, for the cortex vs. hippocampus DMRs, 12-29%, and for the cortex vs. hypothalamus DMRs, 5-35%, with a correlation of r² = 0.92 between the methylation differences in 24 DMRs predicted by CHARM and those validated by bisulfite pyrosequencing. Our adaptation of the CHARM array for the rat genome yielded highly robust results that demonstrate the value of this method in detecting substantial DNAm differences between tissues and across different brain regions. This platform should prove valuable in future studies aimed at examining DNAm differences in particular brain regions of rats exposed to environmental stimuli with potential epigenetic consequences.     

DNA-Methylation Patterns in Trisomy 21 Using Cells from Monozygotic Twins

DNA methylation is essential in mammalian development. We have hypothesized that methylation differences induced by trisomy 21 (T21) contribute to the phenotypic characteristics and heterogeneity in Down syndrome (DS). In order to determine the methylation differences in T21 without interference of the interindividual genomic variation, we have used fetal skin fibroblasts from monozygotic (MZ) twins discordant for T21. We also used skin fibroblasts from MZ twins concordant for T21, normal MZ twins without T21, and unrelated normal and T21 individuals. Reduced Representation Bisulfite Sequencing (RRBS) revealed 35 differentially methylated promoter regions (DMRs) (Absolute methylation differences = 25%, FDR < 0.001) in MZ twins discordant for T21 that have also been observed in comparison between unrelated normal and T21 individuals. The identified DMRs are enriched for genes involved in embryonic organ morphogenesis (FDR = 1.60 e -03) and include genes of the HOXB and HOXD clusters. These DMRs are maintained in iPS cells generated from this twin pair and are correlated with the gene expression changes. We have also observed an increase in DNA methylation level in the T21 methylome compared to the normal euploid methylome. This observation is concordant with the up regulation of DNA methyltransferase enzymes (DNMT3B and DNMT3L) and down regulation of DNA demethylation enzymes (TET2 and TET3) observed in the iPSC of the T21 versus normal twin. Altogether, the results of this study highlight the epigenetic effects of the extra chromosome 21 in T21 on loci outside of this chromosome that are relevant to DS associated phenotypes.     

Bisulfite Conversion of DNA: Performance Comparison of Different Kits and Methylation Quantitation of Epigenetic Biomarkers that Have the Potential to Be Used in Non-Invasive Prenatal Testing

Introduction

Epigenetic alterations, including DNA methylation, play an important role in the regulation of gene expression. Several methods exist for evaluating DNA methylation, but bisulfite sequencing remains the gold standard by which base-pair resolution of CpG methylation is achieved. The challenge of the method is that the desired outcome (conversion of unmethylated cytosines) positively correlates with the undesired side effects (DNA degradation and inappropriate conversion), thus several commercial kits try to adjust a balance between the two. The aim of this study was to compare the performance of four bisulfite conversion kits [Premium Bisulfite kit (Diagenode), EpiTect Bisulfite kit (Qiagen), MethylEdge Bisulfite Conversion System (Promega) and BisulFlash DNA Modification kit (Epigentek)] regarding conversion efficiency, DNA degradation and conversion specificity.

Methods

Performance was tested by combining fully methylated and fully unmethylated λ-DNA controls in a series of spikes by means of Sanger sequencing (0%, 25%, 50% and 100% methylated spikes) and Next-Generation Sequencing (0%, 3%, 5%, 7%, 10%, 25%, 50% and 100% methylated spikes). We also studied the methylation status of two of our previously published differentially methylated regions (DMRs) at base resolution by using spikes of chorionic villus sample in whole blood.

Results

The kits studied showed different but comparable results regarding DNA degradation, conversion efficiency and conversion specificity. However, the best performance was observed with the MethylEdge Bisulfite Conversion System (Promega) followed by the Premium Bisulfite kit (Diagenode). The DMRs, EP6 and EP10, were confirmed to be hypermethylated in the CVS and hypomethylated in whole blood.

Conclusion

Our findings indicate that the MethylEdge Bisulfite Conversion System (Promega) was shown to have the best performance among the kits. In addition, the methylation level of two of our DMRs, EP6 and EP10, was confirmed. Finally, we showed that bisulfite amplicon sequencing is a suitable approach for methylation analysis of targeted regions.     

Are special read alignment strategies necessary and cost-effective when handling sequencing reads from patient-derived tumor xenografts?

Background

Patient-derived tumor xenografts in mice are widely used in cancer research and have become important in developing personalized therapies. When these xenografts are subject to DNA sequencing, the samples could contain various amounts of mouse DNA. It has been unclear how the mouse reads would affect data analyses. We conducted comprehensive simulations to compare three alignment strategies at different mutation rates, read lengths, sequencing error rates, human-mouse mixing ratios and sequenced regions. We also sequenced a nasopharyngeal carcinoma xenograft and a cell line to test how the strategies work on real data.

Results

We found the "filtering" and "combined reference" strategies performed better than aligning reads directly to human reference in terms of alignment and variant calling accuracies. The combined reference strategy was particularly good at reducing false negative variants calls without significantly increasing the false positive rate. In some scenarios the performance gain of these two special handling strategies was too small for special handling to be cost-effective, but it was found crucial when false non-synonymous SNVs should be minimized, especially in exome sequencing.

Conclusions

Our study systematically analyzes the effects of mouse contamination in the sequencing data of human-in-mouse xenografts. Our findings provide information for designing data analysis pipelines for these data.

Electronic supplementary material

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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.