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DNA methylation plays key roles in diverse biological processes such as X chromosome inactivation, transposable element repression, genomic imprinting, and tissue-specific gene expression. Sequencing-based DNA methylation profiling provides an unprecedented opportunity to map and compare complete DNA methylomes. This includes one of the most widely applied technologies for measuring DNA methylation: methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq), coupled with a complementary method, methylation-sensitive restriction enzyme sequencing (MRE-seq). A computational approach that integrates data from these two different but complementary assays and predicts methylation differences between samples has been unavailable. Here, we present a novel integrative statistical framework M&M (for integration of MeDIP-seq and MRE-seq) that dynamically scales, normalizes, and combines MeDIP-seq and MRE-seq data to detect differentially methylated regions. Using sample-matched whole-genome bisulfite sequencing (WGBS) as a gold standard, we demonstrate superior accuracy and reproducibility of M&M compared to existing analytical methods for MeDIP-seq data alone. M&M leverages the complementary nature of MeDIP-seq and MRE-seq data to allow rapid comparative analysis between whole methylomes at a fraction of the cost of WGBS. Comprehensive analysis of nineteen human DNA methylomes with M&M reveals distinct DNA methylation patterns among different tissue types, cell types, and individuals, potentially underscoring divergent epigenetic regulation at different scales of phenotypic diversity. We find that differential DNA methylation at enhancer elements, with concurrent changes in histone modifications and transcription factor binding, is common at the cell, tissue, and individual levels, whereas promoter methylation is more prominent in reinforcing fundamental tissue identities.

DNA methylation plays key roles in diverse biological processes such as X chromosome inactivation, transposable element repression, genomic imprinting, and tissue-specific gene expression. Sequencing-based DNA methylation profiling provides an unprecedented opportunity to map and compare complete DNA methylomes. This includes one of the most widely applied technologies for measuring DNA methylation: methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq), coupled with a complementary method, methylation-sensitive restriction enzyme sequencing (MRE-seq). A computational approach that integrates data from these two different but complementary assays and predicts methylation differences between samples has been unavailable. Here, we present a novel integrative statistical framework M&M (for integration of MeDIP-seq and MRE-seq) that dynamically scales, normalizes, and combines MeDIP-seq and MRE-seq data to detect differentially methylated regions. Using sample-matched whole-genome bisulfite sequencing (WGBS) as a gold standard, we demonstrate superior accuracy and reproducibility of M&M compared to existing analytical methods for MeDIP-seq data alone. M&M leverages the complementary nature of MeDIP-seq and MRE-seq data to allow rapid comparative analysis between whole methylomes at a fraction of the cost of WGBS. Comprehensive analysis of nineteen human DNA methylomes with M&M reveals distinct DNA methylation patterns among different tissue types, cell types, and individuals, potentially underscoring divergent epigenetic regulation at different scales of phenotypic diversity. We find that differential DNA methylation at enhancer elements, with concurrent changes in histone modifications and transcription factor binding, is common at the cell, tissue, and individual levels, whereas promoter methylation is more prominent in reinforcing fundamental tissue identities.

Primary triple-negative breast cancers (TNBCs), a tumour type defined by lack of oestrogen receptor, progesterone receptor and ERBB2 gene amplification, represent approximately 16% of all breast cancers. Here we show in 104 TNBC cases that at the time of diagnosis these cancers exhibit a wide and continuous spectrum of genomic evolution, with some having only a handful of coding somatic aberrations in a few pathways, whereas others contain hundreds of coding somatic mutations. High-throughput RNA sequencing (RNA-seq) revealed that only approximately 36% of mutations are expressed. Using deep re-sequencing measurements of allelic abundance for 2,414 somatic mutations, we determine for the first time-to our knowledge-in an epithelial tumour subtype, the relative abundance of clonal frequencies among cases representative of the population. We show that TNBCs vary widely in their clonal frequencies at the time of diagnosis, with the basal subtype of TNBC showing more variation than non-basal TNBC. Although p53 (also known as TP53), PIK3CA and PTEN somatic mutations seem to be clonally dominant compared to other genes, in some tumours their clonal frequencies are incompatible with founder status. Mutations in cytoskeletal, cell shape and motility proteins occurred at lower clonal frequencies, suggesting that they occurred later during tumour progression. Taken together, our results show that understanding the biology and therapeutic responses of patients with TNBC will require the determination of individual tumour clonal genotypes.

The active acquisition of epigenetic changes is a poorly understood but important process in development, differentiation, and disease. Our work has shown that repression of the p16/pRb pathway in human epithelial cells, a condition common to stem cells and many tumor cells, induces dynamic epigenetic remodeling resulting in the targeted methylation of a selected group of CpG islands. We hypothesized that cells in this epigenetically plastic state could be programmed by the microenvironment to acquire epigenetic changes associated with tumorigenesis. Here, we describe an in vitro model system where epigenetically plastic cells were placed in an environment that induced epithelial to mesenchymal transition (EMT) and led to a program of acquired de novo DNA methylation at targeted sites. In this model, we found that repression of E-cadherin transcription preceded the subsequent acquisition of methylated CpG sites. Furthermore, the induction of EMT was accompanied by de novo methylation of several other gene promoters, including those of the estrogen receptor and Twist. These data demonstrate that signals from the microenvironment can induce phenotypic and gene expression changes associated with targeted de novo epigenetic alterations important in tumor progression, and that these alterations occur through a deterministic, rather than stochastic, mechanism. Given the dynamic epigenetic reprogramming that occurs in these cells, DNA methylation profiles observed in human tumors may reflect the history of environmental exposures during the genesis of a tumor.

Alterations in DNA methylation are important in cancer, but the acquisition of these alterations is poorly understood. Using an unbiased global screen for CpG island methylation events, we have identified a non-random pattern of DNA hypermethylation acquired in p16-repressed cells. Interestingly, this pattern included loci located upstream of a number of homeobox genes. Upon removal of p16(INK4A) activity in primary human mammary epithelial cells, polycomb repressors, EZH2 and SUZ12, are up-regulated and recruited to HOXA9, a locus expressed during normal breast development and epigenetically silenced in breast cancer. We demonstrate that at this targeted locus, the up-regulation of polycomb repressors is accompanied by the recruitment of DNA methyltransferases and the hypermethylation of DNA, an endpoint, which we show to be dependent on SUZ12 expression. These results demonstrate a causal role of p16(INK4A) disruption in modulating DNA hypermethylation, and identify a dynamic and active process whereby epigenetic modulation of gene expression is activated as an early event in breast tumor progression.