The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but a similar reference has lacked for epigenomic studies. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection to-date of human epigenomes for primary cells and tissues. Here, we describe the integrative analysis of 111 reference human epigenomes generated as part of the program, profiled for histone modification patterns, DNA accessibility, DNA methylation, and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically-relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation, and human disease.

1-15 [Author affiliations appear at the end of the paper.]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 MeDIPseq 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 MREseq 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.

Recent advancements in sequencing-based DNA methylation profiling methods provide an unprecedented opportunity to map complete DNA methylomes. These include whole-genome bisulfite sequencing (WGBS, MethylC-seq, or BS-seq), reduced-representation bisulfite sequencing (RRBS), and enrichment-based methods such as MeDIP-seq, MBD-seq, and MRE-seq. These methods yield largely comparable results but differ significantly in extent of genomic CpG coverage, resolution, quantitative accuracy, and cost, at least while using current algorithms to interrogate the data. None of these existing methods provides single-CpG resolution, comprehensive genome-wide coverage, and cost feasibility for a typical laboratory. We introduce methylCRF, a novel conditional random fields-based algorithm that integrates methylated DNA immunoprecipitation (MeDIP-seq) and methylation-sensitive restriction enzyme (MRE-seq) sequencing data to predict DNA methylation levels at single-CpG resolution. Our method is a combined computational and experimental strategy to produce DNA methylomes of all 28 million CpGs in the human genome for a fraction (<10%) of the cost of whole-genome bisulfite sequencing methods. methylCRF was benchmarked for accuracy against Infinium arrays, RRBS, WGBS sequencing, and locus-specific bisulfite sequencing performed on the same human embryonic stem cell line. methylCRF transformation of MeDIP-seq/MRE-seq was equivalent to a biological replicate of WGBS in quantification, coverage, and resolution. We used conventional bisulfite conversion, PCR, cloning, and sequencing to validate loci where our predictions do not agree with whole-genome bisulfite data, and in 11 out of 12 cases, methylCRF predictions of methylation level agree better with validated results than does whole-genome bisulfite sequencing. Therefore, methylCRF transformation of MeDIPseq/MRE-seq data provides an accurate, inexpensive, and widely accessible strategy to create full DNA methylomes. [Supplemental material is available for this article.]The haploid human genome contains ;28 million CpGs that exist in methylated, hydroxymethylated, or unmethylated states. The methylation status of cytosines in CpGs influences protein-DNA interactions, gene expression, and chromatin structure and stability; and plays a vital role in the regulation of cellular processes including host defense against endogenous parasitic sequences, embryonic development, transcription, X-chromosome inactivation, and genomic imprinting, as well as possibly playing a role in learning and memory (Robertson 2005;Suzuki and Bird 2008;Laird 2010;Jones 2012). Understanding the role of DNA methylation in development and disease requires accurate assessment of the genomic distribution of these modifications (Laird 2010). Recent advancements in sequencing-based DNA methylation profiling methods provide an unprecedented opportunity to map complete DNA methylomes. Techniques for high-throughput detection of cytosine methylation include bisulfite conversion of unmethylated cytosines to uracil, immunop...

The distal portion of chromosome 1p is one of the most commonly affected regions in human cancer. In this study of hereditary and sporadic colorectal cancer, a region of frequent deletion was identified at 32.2 centimorgans from 1ptel. Deletion breakpoints clustered in the vicinity of or inside the gene RIZ, which encodes a retinoblastoma protein-interacting zinc finger protein. Sequence analysis revealed frequent frameshift mutations of the RIZ gene. The mutations consisted of 1-or 2-bp deletions of a coding (A)8 or (A) 9 tract and were confined to microsatellite-unstable colorectal tumors, being present in 9 of 24 (37.5%) primary tumors and in 6 of 11 (54.5%) cell lines; in 2 cell lines the mutation was homozygous͞hemizygous. The mutations apparently were selected clonally in tumorigenesis, because similar poly(A) tracts in other genes were not affected. Two alternative products of the gene exist, RIZ1, which contains a PR (PRDI-BF1-RIZ1) domain implicated in tumor suppressor function, and RIZ2, which is lacking this motif. Furthermore, the C-terminal region, which contains the poly(A) tracts, includes a PR-binding motif, possibly mediating interactions with other proteins or with RIZ itself (oligomerization). Four of eleven microsatellite-unstable colorectal cancer cell lines, three of which had frameshifts, showed reduced or absent mRNA expression of RIZ1. In a cell line that is homozygous͞hemizygous for the typical frameshift mutation, immunoblotting showed truncated RIZ protein, whereas adenovirus-mediated RIZ1 expression caused G2͞M arrest and apoptosis. We propose that RIZ is a target of the observed 1p alterations, with impairment of the PR domainmediated function through either frameshift mutation or genomic deletion.S poradic cancer arises as a result of a series of somatic mutations and epigenetic changes that silence tumor suppressor genes or activate oncogenes (1). As such, the APC-RAS-P53 pathway in colorectal cancer is well established (2), but many of its components are not fully understood (3). Recently, two pathways, CIN, a chromosomal instability pathway, and MIN, a microsatellite instability pathway, have been proposed. Loss of heterozygosity (LOH) is a hallmark of the CIN pathway, whereas microsatellite instability (MSI) characterizes the MIN pathway (4). In the MIN pathway, mutations or epigenetic silencing of one of the DNA mismatch repair genes lead to widespread accumulation of mutations, followed by clonal selection (5). The MSI(ϩ) phenotype is easily distinguishable by allelic changes of repetitive regions throughout the genome (6).Some genes contain repetitive regions in their coding sequences that are often targets of MSI. Insertion or deletion in these repetitive regions leads to frameshift and protein truncation. In colorectal cancer, the TGFBRII gene (7) and BAX gene (8) are examples of genes mutated in this way and whose loss of function is believed to contribute to tumorigenesis. Other examples include the DNA mismatch repair genes MSH6 and MSH3, and IGFR2 (9). In this paper, w...