Comparison of Methyl-capture Sequencing vs. Infinium 450K methylation array for methylome analysis in clinical samples

Interindividual variability in the epigenome has gained tremendous attention for its potential in pathophysiological investigation, disease diagnosis, and evaluation of clinical intervention. DNA methylation is the most studied epigenetic mark in epigenome-wide association studies (EWAS) as it can be detected from limited starting material. Infinium 450K methylation array is the most popular platform for high-throughput profiling of this mark in clinical samples, as it is cost-effective and requires small amounts of DNA. However, this method suffers from low genome coverage and errors introduced by probe cross-hybridization. Whole-genome bisulfite sequencing can overcome these limitations but elevates the costs tremendously. Methyl-Capture Sequencing (MC Seq) is an attractive intermediate solution to increase the methylome coverage in large sample sets. Here we first demonstrate that MC Seq can be employed using DNA amounts comparable to the amounts used for Infinium 450K. Second, to provide guidance when choosing between the 2 platforms for EWAS, we evaluate and compare MC Seq and Infinium 450K in terms of coverage, technical variation, and concordance of methylation calls in clinical samples. Last, since the focus in EWAS is to study interindividual variation, we demonstrate the utility of MC Seq in studying interindividual variation in subjects from different ethnicities.     

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.     

Buccals are likely to be a more informative surrogate tissue than blood for epigenome-wide association studies

There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals > 6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs.     

Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population

Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype-phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes.     

Short‐term calorie restriction ameliorates genomewide,age‐related alterations in DNA methylation

DNA methylation plays major roles in many biological processes, including aging, carcinogenesis, and development. Analyses of DNA methylation using next‐generation sequencing offer a new way to profile and compare methylomes across the genome in the context of aging. We explored genomewide DNA methylation and the effects of short‐term calorie restriction (CR) on the methylome of aged rat kidney. Whole‐genome methylation of kidney in young (6 months old), old (25 months old), and OCR (old with 4‐week, short‐term CR) rats was analyzed by methylated DNA immunoprecipitation and next‐generation sequencing (MeDIP‐Seq). CpG islands and repetitive regions were hypomethylated, but 5′‐UTR, exon, and 3′‐UTR hypermethylated in old and OCR rats. The methylation in the promoter and intron regions was decreased in old rats, but increased in OCR rats. Pathway enrichment analysis showed that the hypermethylated promoters in old rats were associated with degenerative phenotypes such as cancer and diabetes. The hypomethylated promoters in old rats related significantly to the chemokine signaling pathway. However, the pathways significantly enriched in old rats were not observed from the differentially methylated promoters in OCR rats. Thus, these findings suggest that short‐term CR could partially ameliorate age‐related methylation changes in promoters in old rats. From the epigenomic data, we propose that the hypermethylation found in the promoter regions of disease‐related genes during aging may indicate increases in susceptibility to age‐related diseases. Therefore, the CR‐induced epigenetic changes that ameliorate age‐dependent aberrant methylation may be important to CR's health‐ and life‐prolonging effects.     

Dynamic stage-specific changes in imprinted differentially methylated regions during early mammalian development and prevalence of non-CpG methylation in oocytes

Mammalian imprinted genes are associated with differentially methylated regions (DMRs) that are CpG methylated on one of the two parental chromosomes. In mice, at least 21 DMRs acquire differential methylation in the germline and many of them act as imprint centres. We previously reported the physical extents of differential methylation at 15 DMRs in mouse embryos at 12.5 days postcoitum. To reveal the ontogeny of differential methylation, we determined and compared methylation patterns of the corresponding regions in sperm and oocytes. We found that the extent of the gametic DMRs differs significantly from that of the embryonic DMRs, especially in the case of paternal gametic DMRs. These results suggest that the gametic DMR sequences should be used to extract the features specifying methylation imprint establishment in the germline: from this analysis, we noted that the maternal gametic DMRs appear as unmethylated islands in male germ cells, which suggests a novel component in the mechanism of gamete-specific marking. Analysis of selected DMRs in blastocysts revealed dynamic changes in allelic methylation in early development, indicating that DMRs are not fully protected from the major epigenetic reprogramming events occurring during preimplantation development. Furthermore, we observed non-CpG methylation in oocytes, but not in sperm, which disappeared by the blastocyst stage. Non-CpG methylation was frequently found at maternally methylated DMRs as well as non-DMR regions, suggesting its prevalence in the oocyte genome. These results provide evidence for a unique methylation profile in oocytes and reveal the surprisingly dynamic nature of DMRs in the early embryo.     

Measuring cell-type specific differential methylation in human brain tissue

The behavior of epigenetic mechanisms in the brain is obscured by tissue heterogeneity and disease-related histological changes. Not accounting for these confounders leads to biased results. We develop a statistical methodology that estimates and adjusts for celltype composition by decomposing neuronal and non-neuronal differential signal. This method provides a conceptual framework for deconvolving heterogeneous epigenetic data from postmortem brain studies. We apply it to find cell-specific differentially methylated regions between prefrontal cortex and hippocampus. We demonstrate the utility of the method on both Infinium 450k and CHARM data.     

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.     

Measuring the methylome in clinical samples: Improved processing of the Infinium Human Methylation450 BeadChip Array

The Infinium Human Methylation450 BeadChip Array^TM (Infinium 450K) is an important tool for studying epigenetic patterns associated with disease. This array offers a high-throughput, low cost alternative to more comprehensive sequencing-based methodologies. Here we compare data generated by interrogation of the same seven clinical samples by Infinium 450K and reduced representation bisulfite sequencing (RRBS). This is the largest data set comparing Infinium 450K array to the comprehensive RRBS methodology reported so far. We show good agreement between the two methodologies. A read depth of four or more reads in the RRBS data was sufficient to achieve good agreement with Infinium 450K. However, we observe that intermediate methylation values (20–80%) are more variable between technologies than values at the extremes of the bimodal methylation distribution. We describe careful processing of Infinium 450K data to correct for known limitations and batch effects. Using methodologies proposed by others and newly implemented and combined in this report, agreement of Infinium 450K data with independent techniques can be vastly improved.     

Genetic evidence for common pathways in human age‐related diseases

Aging is the single largest risk factor for chronic disease. Studies in model organisms have identified conserved pathways that modulate aging rate and the onset and progression of multiple age‐related diseases, suggesting that common pathways of aging may influence age‐related diseases in humans as well. To determine whether there is genetic evidence supporting the notion of common pathways underlying age‐related diseases, we analyzed the genes and pathways found to be associated with five major categories of age‐related disease using a total of 410 genomewide association studies (GWAS). While only a small number of genes are shared among all five disease categories, those found in at least three of the five major age‐related disease categories are highly enriched for apoliprotein metabolism genes. We found that a more substantial number of gene ontology (GO) terms are shared among the 5 age‐related disease categories and shared GO terms include canonical aging pathways identified in model organisms, such as nutrient‐sensing signaling, translation, proteostasis, stress responses, and genome maintenance. Taking advantage of the vast amount of genetic data from the GWAS, our findings provide the first direct evidence that conserved pathways of aging simultaneously influence multiple age‐related diseases in humans as has been demonstrated in model organisms.     

Consistent and Heritable Alterations of DNA Methylation Are Induced by Tissue Culture in Maize

Plants regenerated from tissue culture and their progenies are expected to be identical clones, but often display heritable molecular and phenotypic variation. We characterized DNA methylation patterns in callus, primary regenerants, and regenerant-derived progenies of maize using immunoprecipitation of methylated DNA (meDIP) to assess the genome-wide frequency, pattern, and heritability of DNA methylation changes. Although genome-wide DNA methylation levels remained similar following tissue culture, numerous regions exhibited altered DNA methylation levels. Hypomethylation events were observed more frequently than hypermethylation following tissue culture. Many of the hypomethylation events occur at the same genomic sites across independent regenerants and cell lines. The DNA methylation changes were often heritable in progenies produced from self-pollination of primary regenerants. Methylation changes were enriched in regions upstream of genes and loss of DNA methylation at promoters was associated with altered expression at a subset of loci. Differentially methylated regions (DMRs) found in tissue culture regenerants overlap with the position of naturally occurring DMRs more often than expected by chance with 8% of tissue culture hypomethylated DMRs overlapping with DMRs identified by profiling natural variation, consistent with the hypotheses that genomic stresses similar to those causing somaclonal variation may also occur in nature, and that certain loci are particularly susceptible to epigenetic change in response to these stresses. The consistency of methylation changes across regenerants from independent cultures suggests a mechanistic response to the culture environment as opposed to an overall loss of fidelity in the maintenance of epigenetic states.     

Measuring the methylome in clinical samples: Improved processing of the Infinium Human Methylation450 BeadChip Array

The Infinium Human Methylation450 BeadChip Array^TM (Infinium 450K) is an important tool for studying epigenetic patterns associated with disease. This array offers a high-throughput, low cost alternative to more comprehensive sequencing-based methodologies. Here we compare data generated by interrogation of the same seven clinical samples by Infinium 450K and reduced representation bisulfite sequencing (RRBS). This is the largest data set comparing Infinium 450K array to the comprehensive RRBS methodology reported so far. We show good agreement between the two methodologies. A read depth of four or more reads in the RRBS data was sufficient to achieve good agreement with Infinium 450K. However, we observe that intermediate methylation values (20–80%) are more variable between technologies than values at the extremes of the bimodal methylation distribution. We describe careful processing of Infinium 450K data to correct for known limitations and batch effects. Using methodologies proposed by others and newly implemented and combined in this report, agreement of Infinium 450K data with independent techniques can be vastly improved.     

Maternal genome-wide DNA methylation patterns and congenital heart defects

The majority of congenital heart defects (CHDs) are thought to result from the interaction between multiple genetic, epigenetic, environmental, and lifestyle factors. Epigenetic mechanisms are attractive targets in the study of complex diseases because they may be altered by environmental factors and dietary interventions. We conducted a population based, case-control study of genome-wide maternal DNA methylation to determine if alterations in gene-specific methylation were associated with CHDs. Using the Illumina Infinium Human Methylation27 BeadChip, we assessed maternal gene-specific methylation in over 27,000 CpG sites from DNA isolated from peripheral blood lymphocytes. Our study sample included 180 mothers with non-syndromic CHD-affected pregnancies (cases) and 187 mothers with unaffected pregnancies (controls). Using a multi-factorial statistical model, we observed differential methylation between cases and controls at multiple CpG sites, although no CpG site reached the most stringent level of genome-wide statistical significance. The majority of differentially methylated CpG sites were hypermethylated in cases and located within CpG islands. Gene Set Enrichment Analysis (GSEA) revealed that the genes of interest were enriched in multiple biological processes involved in fetal development. Associations with canonical pathways previously shown to be involved in fetal organogenesis were also observed. We present preliminary evidence that alterations in maternal DNA methylation may be associated with CHDs. Our results suggest that further studies involving maternal epigenetic patterns and CHDs are warranted. Multiple candidate processes and pathways for future study have been identified.     

Comparison of novel and existing methods for detecting differentially methylated regions

Background

Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes. Methods to detect differentially methylated regions (DMRs) (clusters of neighboring probes associated with a phenotype) may provide more power to detect associations between DNA methylation and diseases or phenotypes of interest.

Results

We proposed a novel approach, GlobalP, and perform comparisons with 3 methods—DMRcate, Bumphunter, and comb-p—to identify DMRs associated with log triglycerides (TGs) in real GAW20 data before and after fenofibrate treatment. We applied these methods to the summary statistics from an EWAS performed on the methylation data. Comb-p, DMRcate, and GlobalP detected very similar DMRs near the gene CPT1A on chromosome 11 in both the pre- and posttreatment data. In addition, GlobalP detected 2 DMRs before fenofibrate treatment in the genes ETV6 and ABCG1. Bumphunter identified several DMRs on chromosomes 1 and 20, which did not overlap with DMRs detected by other methods.

Conclusions

Our novel method detected the same DMR identified by two existing methods and detected two additional DMRs not identified by any of the existing methods we compared.