In recent years the Illumina HumanMethylation450 (HM450) BeadChip has provided a user-friendly platform to profile DNA methylation in human samples. However, HM450 lacked coverage of distal regulatory elements. Illumina have now released the MethylationEPIC (EPIC) BeadChip, with new content specifically designed to target these regions. We have used HM450 and whole-genome bisulphite sequencing (WGBS) to perform a critical evaluation of the new EPIC array platform. EPIC covers over 850,000 CpG sites, including >90 % of the CpGs from the HM450 and an additional 413,743 CpGs. Even though the additional probes improve the coverage of regulatory elements, including 58 % of FANTOM5 enhancers, only 7 % distal and 27 % proximal ENCODE regulatory elements are represented. Detailed comparisons of regulatory elements from EPIC and WGBS show that a single EPIC probe is not always informative for those distal regulatory elements showing variable methylation across the region. However, overall data from the EPIC array at single loci are highly reproducible across technical and biological replicates and demonstrate high correlation with HM450 and WGBS data. We show that the HM450 and EPIC arrays distinguish differentially methylated probes, but the absolute agreement depends on the threshold set for each platform. Finally, we provide an annotated list of probes whose signal could be affected by cross-hybridisation or underlying genetic variation. The EPIC array is a significant improvement over the HM450 array, with increased genome coverage of regulatory regions and high reproducibility and reliability, providing a valuable tool for high-throughput human methylome analyses from diverse clinical samples.

The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model. We show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons. The agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing. For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data.

Cytosine methylation within CpG dinucleotides has been implicated in the regulation of gene expression in vertebrates and, in some cases, has been shown to be causative in repression of transcription. We have examined whether methylation of CpG dinucleotides located within the binding site for a specific transcription factor, MLTF or USF, affects its binding to DNA. This HeLa cell factor binds to the adenovirus major late promoter (AdMLP), as well as endogenous cellular genes, and stimulates transcription in an in vitro assay. Synthetic oligonucleotides in which 5-methylcytosine replaces cytosine at specific sites were used to generate duplex DNAs, and the formation of complexes of these oligomers with MLTF was studied using a gel retardation assay. Methylation at a CpG site centrally located within the binding site strongly inhibited complex formation, whereas methylation at a site 6 bases away had no demonstrable effect. Methylation at the central site was also shown to inhibit specific transcription in vitro from the AdMLP. Methylation at the central site on only one strand caused a partial inhibition of binding, the effect being greater when the noncoding strand was methylated. The results indicate that in some cases, site-specific methylation may inhibit gene expression directly by blocking binding to DNA of factors required for optimal transcription. Along with other recent findings, they suggest an interplay between DNA methylation and transcription factors in the regulation of gene expression.

DNA methylation is an important epigenetic modification of DNA in mammalian genomes. DNA methylation patterns are established early in development, modulated during tissue-specific differentiation and disrupted in many disease states, including cancer. To understand further the biological functions of these changes, accurate and reproducible methods are required to fully analyze the DNA methylation sequence. Here, we describe the 'gold-standard' bisulphite conversion protocol that can be used to re-sequence DNA from mammalian cells in order to determine and quantify the methylation state of a gene or genomic region at single-nucleotide resolution. The process of bisulphite treatment exploits the different sensitivities of cytosine and 5-methylcytosine (5-MeC) to deamination by bisulphite under acidic conditions--in which cytosine undergoes conversion to uracil, whereas 5-MeC remains unreactive. Bisulphite conversion of DNA, in either single tubes or in a 96-well format, can be performed in a minimum of 8 h and a maximum of 18 h, depending on the amount and quality of starting DNA.