De novo identification of differentially methylated regions in the human genome

Background: 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. Results: 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. Conclusions: 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

Acetylation of H2A.Z is a key epigenetic modification associated with gene deregulation and epigenetic remodeling in cancer

Histone H2A.Z (H2A.Z) is an evolutionarily conserved H2A variant implicated in the regulation of gene expression; however, its role in transcriptional deregulation in cancer remains poorly understood. Using genome-wide studies, we investigated the role of promoter-associated H2A.Z and acetylated H2A.Z (acH2A.Z) in gene deregulation and its relationship with DNA methylation and H3K27me3 in prostate cancer. Our results reconcile the conflicting reports of positive and negative roles for histone H2A.Z and gene expression states. We find that H2A.Z is enriched in a bimodal distribution at nucleosomes, surrounding the transcription start sites (TSSs) of both active and poised gene promoters. In addition, H2A.Z spreads across the entire promoter of inactive genes in a deacetylated state. In contrast, acH2A.Z is only localized at the TSSs of active genes. Gene deregulation in cancer is also associated with a reorganization of acH2A.Z and H2A.Z nucleosome occupancy across the promoter region and TSS of genes. Notably, in cancer cells we find that a gain of acH2A.Z at the TSS occurs with an overall decrease of H2A.Z levels, in concert with oncogene activation. Furthermore, deacetylation of H2A.Z at TSSs is increased with silencing of tumor suppressor genes. We also demonstrate that acH2A.Z anti-correlates with promoter H3K27me3 and DNA methylation. We show for the first time, that acetylation of H2A.Z is a key modification associated with gene activity in normal cells and epigenetic gene deregulation in tumorigenesis

ELF5 suppresses estrogen sensitivity and underpins the acquisition of antiestrogen resistance in luminal breast cancer.

We have previously shown that during pregnancy the E-twenty-six (ETS) transcription factor ELF5 directs the differentiation of mammary progenitor cells toward the estrogen receptor (ER)-negative and milk producing cell lineage, raising the possibility that ELF5 may suppress the estrogen sensitivity of breast cancers. To test this we constructed inducible models of ELF5 expression in ER positive luminal breast cancer cells and interrogated them using transcript profiling and chromatin immunoprecipitation of DNA followed by DNA sequencing (ChIP-Seq). ELF5 suppressed ER and FOXA1 expression and broadly suppressed ER-driven patterns of gene expression including sets of genes distinguishing the luminal molecular subtype. Direct transcriptional targets of ELF5, which included FOXA1, EGFR, and MYC, accurately classified a large cohort of breast cancers into their intrinsic molecular subtypes, predicted ER status with high precision, and defined groups with differential prognosis. Knockdown of ELF5 in basal breast cancer cell lines suppressed basal patterns of gene expression and produced a shift in molecular subtype toward the claudin-low and normal-like groups. Luminal breast cancer cells that acquired resistance to the antiestrogen Tamoxifen showed greatly elevated levels of ELF5 and its transcriptional signature, and became dependent on ELF5 for proliferation, compared to the parental cells. Thus ELF5 provides a key transcriptional determinant of breast cancer molecular subtype by suppression of estrogen sensitivity in luminal breast cancer cells and promotion of basal characteristics in basal breast cancer cells, an action that may be utilised to acquire antiestrogen resistance

Discovery pipeline for epigenetically deregulated miRNAs in cancer: integration of primary miRNA transcription

<p>Abstract</p> <p>Background</p> <p>Cancer is commonly associated with widespread disruption of DNA methylation, chromatin modification and miRNA expression. In this study, we established a robust discovery pipeline to identify epigenetically deregulated miRNAs in cancer.</p> <p>Results</p> <p>Using an integrative approach that combines primary transcription, genome-wide DNA methylation and H3K9Ac marks with microRNA (miRNA) expression, we identified miRNA genes that were epigenetically modified in cancer. We find miR-205, miR-21, and miR-196b to be epigenetically repressed, and miR-615 epigenetically activated in prostate cancer cells.</p> <p>Conclusions</p> <p>We show that detecting changes in primary miRNA transcription levels is a valuable method for detection of local epigenetic modifications that are associated with changes in mature miRNA expression.</p

Impact of the Genome on the Epigenome Is Manifested in DNA Methylation Patterns of Imprinted Regions in Monozygotic and Dizygotic Twins

One of the best studied read-outs of epigenetic change is the differential expression of imprinted genes, controlled by differential methylation of imprinted control regions (ICRs). To address the impact of genotype on the epigenome, we performed a detailed study in 128 pairs of monozygotic (MZ) and 128 pairs of dizygotic (DZ) twins, interrogating the DNA methylation status of the ICRs of IGF2, H19, KCNQ1, GNAS and the non-imprinted gene RUNX1. While we found a similar overall pattern of methylation between MZ and DZ twins, we also observed a high degree of variability in individual CpG methylation levels, notably at the H19/IGF2 loci. A degree of methylation plasticity independent of the genome sequence was observed, with both local and regional CpG methylation changes, discordant between MZ and DZ individual pairs. However, concordant gains or losses of methylation, within individual twin pairs were more common in MZ than DZ twin pairs, indicating that de novo and/or maintenance methylation is influenced by the underlying DNA sequence. Specifically, for the first time we showed that the rs10732516 [A] polymorphism, located in a critical CTCF binding site in the H19 ICR locus, is strongly associated with increased hypermethylation of specific CpG sites in the maternal H19 allele. Together, our results highlight the impact of the genome on the epigenome and demonstrate that while DNA methylation states are tightly maintained between genetically identical and related individuals, there remains considerable epigenetic variation that may contribute to disease susceptibility

Bisulfite sequencing of chromatin immunoprecipitated DNA (BisChIP-seq) directly informs methylation status of histone-modified DNA

The complex relationship between DNA methylation, chromatin modification, and underlying DNA sequence is often difficult to unravel with existing technologies. Here, we describe a novel technique based on high-throughput sequencing of bisulfite-treated chromatin immunoprecipitated DNA (BisChIP-seq), which can directly interrogate genetic and epigenetic processes that occur in normal and diseased cells. Unlike most previous reports based on correlative techniques, we found using direct bisulfite sequencing of Polycomb H3K27me3-enriched DNA from normal and prostate cancer cells that DNA methylation and H3K27me3-marked histones are not always mutually exclusive, but can co-occur in a genomic region-dependent manner. Notably, in cancer, the co-dependency of marks is largely redistributed with an increase of the dual repressive marks at CpG islands and transcription start sites of silent genes. In contrast, there is a loss of DNA methylation in intergenic H3K27me3-marked regions. Allele-specific methylation status derived from the BisChIP-seq data clearly showed that both methylated and unmethylated alleles can simultaneously be associated with H3K27me3 histones, highlighting that DNA methylation status in these regions is not dependent on Polycomb chromatin status. BisChIP-seq is a novel approach that can be widely applied to directly interrogate the genomic relationship between allele-specific DNA methylation, histone modification, or other important epigenetic regulators

COBRA-Seq: Sensitive and Quantitative Methylome Profiling

Combined Bisulfite Restriction Analysis (COBRA) quantifies DNA methylation at a specific locus. It does so via digestion of PCR amplicons produced from bisulfite-treated DNA, using a restriction enzyme that contains a cytosine within its recognition sequence, such as TaqI. Here, we introduce COBRA-seq, a genome wide reduced methylome method that requires minimal DNA input (0.1–1.0 mg) and can either use PCR or linear amplification to amplify the sequencing library. Variants of COBRA-seq can be used to explore CpG-depleted as well as CpG-rich regions in vertebrate DNA. The choice of enzyme influences enrichment for specific genomic features, such as CpG-rich promoters and CpG islands, or enrichment for less CpG dense regions such as enhancers. COBRA-seq coupled with linear amplification has the additional advantage of reduced PCR bias by producing full length fragments at high abundance. Unlike other reduced representative methylome methods, COBRA-seq has great flexibility in the choice of enzyme and can be multiplexed and tuned, to reduce sequencing costs and to interrogate different numbers of sites. Moreover, COBRA-seq is applicable to non-model organisms without the reference genome and compatible with the investigation of non-CpG methylation by using restriction enzymes containing CpA, CpT, and CpC in their recognition site

Genome-wide nucleosome occupancy and DNA methylation profiling of four human cell lines

DNA methylation and nucleosome positioning are two key mechanisms that contribute to the epigenetic control of gene expression. During carcinogenesis, the expression of many genes is altered alongside extensive changes in the epigenome, with repressed genes often being associated with local DNA hypermethylation and gain of nucleosomes at their promoters. However the spectrum of alterations that occur at distal regulatory regions has not been extensively studied. To address this we used Nucleosome Occupancy and Methylation sequencing (NOMe-seq) to compare the genome-wide DNA methylation and nucleosome occupancy profiles between normal and cancer cell line models of the breast and prostate. Here we describe the bioinformatic pipeline and methods that we developed for the processing and analysis of the NOMe-seq data published by (Taberlay et al., 2014 [1]) and deposited in the Gene Expression Omnibus with accession GSE57498