Stable Caenorhabditis elegans chromatin domains separate broadly expressed and developmentally regulated genes.

Eukaryotic genomes are organized into domains of differing structure and activity. There is evidence that the domain organization of the genome regulates its activity, yet our understanding of domain properties and the factors that influence their formation is poor. Here, we use chromatin state analyses in early embryos and third-larval stage (L3) animals to investigate genome domain organization and its regulation in Caenorhabditis elegans At both stages we find that the genome is organized into extended chromatin domains of high or low gene activity defined by different subsets of states, and enriched for H3K36me3 or H3K27me3, respectively. The border regions between domains contain large intergenic regions and a high density of transcription factor binding, suggesting a role for transcription regulation in separating chromatin domains. Despite the differences in cell types, overall domain organization is remarkably similar in early embryos and L3 larvae, with conservation of 85% of domain border positions. Most genes in high-activity domains are expressed in the germ line and broadly across cell types, whereas low-activity domains are enriched for genes that are developmentally regulated. We find that domains are regulated by the germ-line H3K36 methyltransferase MES-4 and that border regions show striking remodeling of H3K27me1, supporting roles for H3K36 and H3K27 methylation in regulating domain structure. Our analyses of C. elegans chromatin domain structure show that genes are organized by type into domains that have differing modes of regulation.

An interactive genome browser of association results from the UK10K cohorts project.

UNLABELLED: High-throughput sequencing technologies survey genetic variation at genome scale and are increasingly used to study the contribution of rare and low-frequency genetic variants to human traits. As part of the Cohorts arm of the UK10K project, genetic variants called from low-read depth (average 7×) whole genome sequencing of 3621 cohort individuals were analysed for statistical associations with 64 different phenotypic traits of biomedical importance. Here, we describe a novel genome browser based on the Biodalliance platform developed to provide interactive access to the association results of the project. AVAILABILITY AND IMPLEMENTATION: The browser is available at http://www.uk10k.org/dalliance.html. Source code for the Biodalliance platform is available under a BSD license from http://github.com/dasmoth/dalliance, and for the LD-display plugin and backend from http://github.com/dasmoth/ldserv.

A comparison of peak callers used for DNase-Seq data.

Genome-wide profiling of open chromatin regions using DNase I and high-throughput sequencing (DNase-seq) is an increasingly popular approach for finding and studying regulatory elements. A variety of algorithms have been developed to identify regions of open chromatin from raw sequence-tag data, which has motivated us to assess and compare their performance. In this study, four published, publicly available peak calling algorithms used for DNase-seq data analysis (F-seq, Hotspot, MACS and ZINBA) are assessed at a range of signal thresholds on two published DNase-seq datasets for three cell types. The results were benchmarked against an independent dataset of regulatory regions derived from ENCODE in vivo transcription factor binding data for each particular cell type. The level of overlap between peak regions reported by each algorithm and this ENCODE-derived reference set was used to assess sensitivity and specificity of the algorithms. Our study suggests that F-seq has a slightly higher sensitivity than the next best algorithms. Hotspot and the ChIP-seq oriented method, MACS, both perform competitively when used with their default parameters. However the generic peak finder ZINBA appears to be less sensitive than the other three. We also assess accuracy of each algorithm over a range of signal thresholds. In particular, we show that the accuracy of F-Seq can be considerably improved by using a threshold setting that is different from the default value.

Extreme HOT regions are CpG-dense promoters in C. elegans and humans.

Most vertebrate promoters lie in unmethylated CpG-dense islands, whereas methylation of the more sparsely distributed CpGs in the remainder of the genome is thought to contribute to transcriptional repression. Nonmethylated CG dinucleotides are recognized by CXXC finger protein 1 (CXXC1, also known as CFP1), which recruits SETD1A (also known as Set1) methyltransferase for trimethylation of histone H3 lysine 4, an active promoter mark. Genomic regions enriched for CpGs are thought to be either absent or irrelevant in invertebrates that lack DNA methylation, such as C. elegans; however, a CXXC1 ortholog (CFP-1) is present. Here we demonstrate that C. elegans CFP-1 targets promoters with high CpG density, and these promoters are marked by high levels of H3K4me3. Furthermore, as for mammalian promoters, high CpG content is associated with nucleosome depletion irrespective of transcriptional activity. We further show that highly occupied target (HOT) regions identified by the binding of a large number of transcription factors are CpG-rich promoters in C. elegans and human genomes, suggesting that the unusually high factor association at HOT regions may be a consequence of CpG-linked chromatin accessibility. Our results indicate that nonmethylated CpG-dense sequence is a conserved genomic signal that promotes an open chromatin state, targeting by a CXXC1 ortholog, and H3K4me3 modification in both C. elegans and human genomes.

Synergistic mechanisms of DNA demethylation during transition to ground-state pluripotency.

Pluripotent stem cells (PSCs) occupy a spectrum of reversible molecular states ranging from a naive ground-state in 2i, to metastable embryonic stem cells (ESCs) in serum, to lineage-primed epiblast stem cells (EpiSCs). To investigate the role of DNA methylation (5mC) across distinct pluripotent states, we mapped genome-wide 5mC and 5-hydroxymethycytosine (5hmC) in multiple PSCs. Ground-state ESCs exhibit an altered distribution of 5mC and 5hmC at regulatory elements and dramatically lower absolute levels relative to ESCs in serum. By contrast, EpiSCs exhibit increased promoter 5mC coupled with reduced 5hmC, which contributes to their developmental restriction. Switch to 2i triggers rapid onset of both the ground-state gene expression program and global DNA demethylation. Mechanistically, repression of de novo methylases by PRDM14 drives DNA demethylation at slow kinetics, whereas TET1/TET2-mediated 5hmC conversion enhances both the rate and extent of hypomethylation. These processes thus act synergistically during transition to ground-state pluripotency to promote a robust hypomethylated state.

Binding of TFIIIC to sine elements controls the relocation of activity-dependent neuronal genes to transcription factories.

In neurons, the timely and accurate expression of genes in response to synaptic activity relies on the interplay between epigenetic modifications of histones, recruitment of regulatory proteins to chromatin and changes to nuclear structure. To identify genes and regulatory elements responsive to synaptic activation in vivo, we performed a genome-wide ChIPseq analysis of acetylated histone H3 using somatosensory cortex of mice exposed to novel enriched environmental (NEE) conditions. We discovered that Short Interspersed Elements (SINEs) located distal to promoters of activity-dependent genes became acetylated following exposure to NEE and were bound by the general transcription factor TFIIIC. Importantly, under depolarizing conditions, inducible genes relocated to transcription factories (TFs), and this event was controlled by TFIIIC. Silencing of the TFIIIC subunit Gtf3c5 in non-stimulated neurons induced uncontrolled relocation to TFs and transcription of activity-dependent genes. Remarkably, in cortical neurons, silencing of Gtf3c5 mimicked the effects of chronic depolarization, inducing a dramatic increase of both dendritic length and branching. These findings reveal a novel and essential regulatory function of both SINEs and TFIIIC in mediating gene relocation and transcription. They also suggest that TFIIIC may regulate the rearrangement of nuclear architecture, allowing the coordinated expression of activity-dependent neuronal genes.

Chromatin accessibility data sets show bias due to sequence specificity of the DNase I enzyme.

BACKGROUND: DNase I is an enzyme which cuts duplex DNA at a rate that depends strongly upon its chromatin environment. In combination with high-throughput sequencing (HTS) technology, it can be used to infer genome-wide landscapes of open chromatin regions. Using this technology, systematic identification of hundreds of thousands of DNase I hypersensitive sites (DHS) per cell type has been possible, and this in turn has helped to precisely delineate genomic regulatory compartments. However, to date there has been relatively little investigation into possible biases affecting this data. RESULTS: We report a significant degree of sequence preference spanning sites cut by DNase I in a number of published data sets. The two major protocols in current use each show a different pattern, but for a given protocol the pattern of sequence specificity seems to be quite consistent. The patterns are substantially different from biases seen in other types of HTS data sets, and in some cases the most constrained position lies outside the sequenced fragment, implying that this constraint must relate to the digestion process rather than events occurring during library preparation or sequencing. CONCLUSIONS: DNase I is a sequence-specific enzyme, with a specificity that may depend on experimental conditions. This sequence specificity is not taken into account by existing pipelines for identifying open chromatin regions. Care must be taken when interpreting DNase I results, especially when looking at the precise locations of the reads. Future studies may be able to improve the sensitivity and precision of chromatin state measurement by compensating for sequence bias.

Inactive or moderately active human promoters are enriched for inter-individual epialleles.

BACKGROUND: Inter-individual epigenetic variation, due to genetic, environmental or random influences, is observed in many eukaryotic species. In mammals, however, the molecular nature of epiallelic variation has been poorly defined, partly due to the restricted focus on DNA methylation. Here we report the first genome-scale investigation of mammalian epialleles that integrates genomic, methylomic, transcriptomic and histone state information. RESULTS: First, in a small sample set, we demonstrate that non-genetically determined inter-individual differentially methylated regions (iiDMRs) can be temporally stable over at least 2 years. Then, we show that iiDMRs are associated with changes in chromatin state as measured by inter-individual differences in histone variant H2A.Z levels. However, the correlation of promoter iiDMRs with gene expression is negligible and not improved by integrating H2A.Z information. We find that most promoter epialleles, whether genetically or non-genetically determined, are associated with low levels of transcriptional activity, depleted for housekeeping genes, and either depleted for H3K4me3/enriched for H3K27me3 or lacking both these marks in human embryonic stem cells. The preferential enrichment of iiDMRs at regions of relative transcriptional inactivity validates in a larger independent cohort, and is reminiscent of observations previously made for promoters that undergo hypermethylation in various cancers, in vitro cell culture and ageing. CONCLUSIONS: Our work identifies potential key features of epiallelic variation in humans, including temporal stability of non-genetically determined epialleles, and concomitant perturbations of chromatin state. Furthermore, our work suggests a novel mechanistic link among inter-individual epialleles observed in the context of normal variation, cancer and ageing.

The landscape of RNA polymerase II transcription initiation in C. elegans reveals promoter and enhancer architectures.

RNA polymerase transcription initiation sites are largely unknown in Caenorhabditis elegans. The initial 5' end of most protein-coding transcripts is removed by trans-splicing, and noncoding initiation sites have not been investigated. We characterized the landscape of RNA Pol II transcription initiation, identifying 73,500 distinct clusters of initiation. Bidirectional transcription is frequent, with a peak of transcriptional pairing at 120 bp. We assign transcription initiation sites to 7691 protein-coding genes and find that they display features typical of eukaryotic promoters. Strikingly, the majority of initiation events occur in regions with enhancer-like chromatin signatures. Based on the overlap of transcription initiation clusters with mapped transcription factor binding sites, we define 2361 transcribed intergenic enhancers. Remarkably, productive transcription elongation across these enhancers is predominantly in the same orientation as that of the nearest downstream gene. Directed elongation from an upstream enhancer toward a downstream gene could potentially deliver RNA polymerase II to a proximal promoter, or alternatively might function directly as a distal promoter. Our results provide a new resource to investigate transcription regulation in metazoans.

Germline DNA demethylation dynamics and imprint erasure through 5-hydroxymethylcytosine.

Mouse primordial germ cells (PGCs) undergo sequential epigenetic changes and genome-wide DNA demethylation to reset the epigenome for totipotency. Here, we demonstrate that erasure of CpG methylation (5mC) in PGCs occurs via conversion to 5-hydroxymethylcytosine (5hmC), driven by high levels of TET1 and TET2. Global conversion to 5hmC initiates asynchronously among PGCs at embryonic day (E) 9.5 to E10.5 and accounts for the unique process of imprint erasure. Mechanistically, 5hmC enrichment is followed by its protracted decline thereafter at a rate consistent with replication-coupled dilution. The conversion to 5hmC is an important component of parallel redundant systems that drive comprehensive reprogramming in PGCs. Nonetheless, we identify rare regulatory elements that escape systematic DNA demethylation in PGCs, providing a potential mechanistic basis for transgenerational epigenetic inheritance.

Guthrie card methylomics identifies temporally stable epialleles that are present at birth in humans.

A major concern in common disease epigenomics is distinguishing causal from consequential epigenetic variation. One means of addressing this issue is to identify the temporal origins of epigenetic variants via longitudinal analyses. However, prospective birth-cohort studies are expensive and time consuming. Here, we report DNA methylomics of archived Guthrie cards for the retrospective longitudinal analyses of in-utero-derived DNA methylation variation. We first validate two methodologies for generating comprehensive DNA methylomes from Guthrie cards. Then, using an integrated epigenomic/genomic analysis of Guthrie cards and follow-up samplings, we identify interindividual DNA methylation variation that is present both at birth and 3 yr later. These findings suggest that disease-relevant epigenetic variation could be detected at birth, i.e., before overt clinical disease. Guthrie card methylomics offers a potentially powerful and cost-effective strategy for studying the dynamics of interindividual epigenomic variation in a range of common human diseases.

A functional methylome map of ulcerative colitis.

The etiology of inflammatory bowel diseases is only partially explained by the current genetic risk map. It is hypothesized that environmental factors modulate the epigenetic landscape and thus contribute to disease susceptibility, manifestation, and progression. To test this, we analyzed DNA methylation (DNAm), a fundamental mechanism of epigenetic long-term modulation of gene expression. We report a three-layer epigenome-wide association study (EWAS) using intestinal biopsies from 10 monozygotic twin pairs (n = 20 individuals) discordant for manifestation of ulcerative colitis (UC). Genome-wide expression scans were generated using Affymetrix UG 133 Plus 2.0 arrays (layer 1). Genome-wide DNAm scans were carried out using Illumina 27k Infinium Bead Arrays to identify methylation variable positions (MVPs, layer 2), and MeDIP-chip on Nimblegen custom 385k Tiling Arrays to identify differentially methylated regions (DMRs, layer 3). Identified MVPs and DMRs were validated in two independent patient populations by quantitative real-time PCR and bisulfite-pyrosequencing (n = 185). The EWAS identified 61 disease-associated loci harboring differential DNAm in cis of a differentially expressed transcript. All constitute novel candidate risk loci for UC not previously identified by GWAS. Among them are several that have been functionally implicated in inflammatory processes, e.g., complement factor CFI, the serine protease inhibitor SPINK4, and the adhesion molecule THY1 (also known as CD90). Our study design excludes nondisease inflammation as a cause of the identified changes in DNAm. This study represents the first replicated EWAS of UC integrated with transcriptional signatures in the affected tissue and demonstrates the power of EWAS to uncover unexplained disease risk and molecular events of disease manifestation.

Genome wide analysis of acute myeloid leukemia reveal leukemia specific methylome and subtype specific hypomethylation of repeats.

Methylated DNA immunoprecipitation followed by high-throughput sequencing (MeDIP-seq) has the potential to identify changes in DNA methylation important in cancer development. In order to understand the role of epigenetic modulation in the development of acute myeloid leukemia (AML) we have applied MeDIP-seq to the DNA of 12 AML patients and 4 normal bone marrows. This analysis revealed leukemia-associated differentially methylated regions that included gene promoters, gene bodies, CpG islands and CpG island shores. Two genes (SPHKAP and DPP6) with significantly methylated promoters were of interest and further analysis of their expression showed them to be repressed in AML. We also demonstrated considerable cytogenetic subtype specificity in the methylomes affecting different genomic features. Significantly distinct patterns of hypomethylation of certain interspersed repeat elements were associated with cytogenetic subtypes. The methylation patterns of members of the SINE family tightly clustered all leukemic patients with an enrichment of Alu repeats with a high CpG density (P<0.0001). We were able to demonstrate significant inverse correlation between intragenic interspersed repeat sequence methylation and gene expression with SINEs showing the strongest inverse correlation (R(2) = 0.7). We conclude that the alterations in DNA methylation that accompany the development of AML affect not only the promoters, but also the non-promoter genomic features, with significant demethylation of certain interspersed repeat DNA elements being associated with AML cytogenetic subtypes. MeDIP-seq data were validated using bisulfite pyrosequencing and the Infinium array.

Identification of type 1 diabetes-associated DNA methylation variable positions that precede disease diagnosis.

Monozygotic (MZ) twin pair discordance for childhood-onset Type 1 Diabetes (T1D) is ∼50%, implicating roles for genetic and non-genetic factors in the aetiology of this complex autoimmune disease. Although significant progress has been made in elucidating the genetics of T1D in recent years, the non-genetic component has remained poorly defined. We hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology and, thus, performed an epigenome-wide association study (EWAS) for this disease. We generated genome-wide DNA methylation profiles of purified CD14+ monocytes (an immune effector cell type relevant to T1D pathogenesis) from 15 T1D-discordant MZ twin pairs. This identified 132 different CpG sites at which the direction of the intra-MZ pair DNA methylation difference significantly correlated with the diabetic state, i.e. T1D-associated methylation variable positions (T1D-MVPs). We confirmed these T1D-MVPs display statistically significant intra-MZ pair DNA methylation differences in the expected direction in an independent set of T1D-discordant MZ pairs (P = 0.035). Then, to establish the temporal origins of the T1D-MVPs, we generated two further genome-wide datasets and established that, when compared with controls, T1D-MVPs are enriched in singletons both before (P = 0.001) and at (P = 0.015) disease diagnosis, and also in singletons positive for diabetes-associated autoantibodies but disease-free even after 12 years follow-up (P = 0.0023). Combined, these results suggest that T1D-MVPs arise very early in the etiological process that leads to overt T1D. Our EWAS of T1D represents an important contribution toward understanding the etiological role of epigenetic variation in type 1 diabetes, and it is also the first systematic analysis of the temporal origins of disease-associated epigenetic variation for any human complex disease.

Comparative methylomics reveals gene-body H3K36me3 in Drosophila predicts DNA methylation and CpG landscapes in other invertebrates.

In invertebrates that harbor functional DNA methylation enzymatic machinery, gene-bodies are the primary targets for CpG methylation. However, virtually all other aspects of invertebrate DNA methylation have remained a mystery until now. Here, using a comparative methylomics approach, we demonstrate that Nematostella vectensis, Ciona intestinalis, Apis mellifera, and Bombyx mori show two distinct populations of genes differentiated by gene-body CpG density. Genome-scale DNA methylation profiles for A. mellifera spermatozoa reveal CpG-poor genes are methylated in the germline, as predicted by the depletion of CpGs. We find an evolutionarily conserved distinction between CpG-poor and GpC-rich genes: The former are associated with basic biological processes, the latter with more specialized functions. This distinction is strikingly similar to that recently observed between euchromatin-associated genes in Drosophila that contain intragenic histone 3 lysine 36 trimethylation (H3K36me3) and those that do not, even though Drosophila does not display CpG density bimodality or methylation. We confirm that a significant number of CpG-poor genes in N. vectensis, C. intestinalis, A. mellifera, and B. mori are orthologs of H3K36me3-rich genes in Drosophila. We propose that over evolutionary time, gene-body H3K36me3 has influenced gene-body DNA methylation levels and, consequently, the gene-body CpG density bimodality characteristic of invertebrates that harbor CpG methylation.

Epigenome-wide association studies for common human diseases.

Despite the success of genome-wide association studies (GWASs) in identifying loci associated with common diseases, a substantial proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation. Such epigenome-wide association studies (EWASs) present novel opportunities but also create new challenges that are not encountered in GWASs. We discuss EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies. We also discuss how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.

Systematic bias in high-throughput sequencing data and its correction by BEADS.

Genomic sequences obtained through high-throughput sequencing are not uniformly distributed across the genome. For example, sequencing data of total genomic DNA show significant, yet unexpected enrichments on promoters and exons. This systematic bias is a particular problem for techniques such as chromatin immunoprecipitation, where the signal for a target factor is plotted across genomic features. We have focused on data obtained from Illumina's Genome Analyser platform, where at least three factors contribute to sequence bias: GC content, mappability of sequencing reads, and regional biases that might be generated by local structure. We show that relying on input control as a normalizer is not generally appropriate due to sample to sample variation in bias. To correct sequence bias, we present BEADS (bias elimination algorithm for deep sequencing), a simple three-step normalization scheme that successfully unmasks real binding patterns in ChIP-seq data. We suggest that this procedure be done routinely prior to data interpretation and downstream analyses.

Comparative methylome analysis of benign and malignant peripheral nerve sheath tumors.

Aberrant DNA methylation (DNAm) was first linked to cancer over 25 yr ago. Since then, many studies have associated hypermethylation of tumor suppressor genes and hypomethylation of oncogenes to the tumorigenic process. However, most of these studies have been limited to the analysis of promoters and CpG islands (CGIs). Recently, new technologies for whole-genome DNAm (methylome) analysis have been developed, enabling unbiased analysis of cancer methylomes. By using MeDIP-seq, we report a sequencing-based comparative methylome analysis of malignant peripheral nerve sheath tumors (MPNSTs), benign neurofibromas, and normal Schwann cells. Analysis of these methylomes revealed a complex landscape of DNAm alterations. In contrast to what has been reported for other tumor types, no significant global hypomethylation was observed in MPNSTs using methylome analysis by MeDIP-seq. However, a highly significant (P < 10(-100)) directional difference in DNAm was found in satellite repeats, suggesting these repeats to be the main target for hypomethylation in MPNSTs. Comparative analysis of the MPNST and Schwann cell methylomes identified 101,466 cancer-associated differentially methylated regions (cDMRs). Analysis showed these cDMRs to be significantly enriched for two satellite repeat types (SATR1 and ARLα) and suggests an association between aberrant DNAm of these sequences and transition from healthy cells to malignant disease. Significant enrichment of hypermethylated cDMRs in CGI shores (P < 10(-60)), non-CGI-associated promoters (P < 10(-4)) and hypomethylated cDMRs in SINE repeats (P < 10(-100)) was also identified. Integration of DNAm and gene expression data showed that the expression pattern of genes associated with CGI shore cDMRs was able to discriminate between disease phenotypes. This study establishes MeDIP-seq as an effective method to analyze cancer methylomes.

Dalliance: interactive genome viewing on the web.

SUMMARY: Dalliance is a new genome viewer which offers a high level of interactivity while running within a web browser. All data is fetched using the established distributed annotation system (DAS) protocol, making it easy to customize the browser and add extra data. AVAILABILITY AND IMPLEMENTATION: Dalliance runs entirely within your web browser, and relies on existing DAS server infrastructure. Browsers for several mammalian genomes are available at http://www.biodalliance.org/, and the use of DAS means you can add your own data to these browsers. In addition, the source code (Javascript) is available under the BSD license, and is straightforward to install on your own web server and embed within other documents.

Integrated genetic and epigenetic analysis identifies haplotype-specific methylation in the FTO type 2 diabetes and obesity susceptibility locus.

Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10(-4), permutation p = 1.0×10(-3)). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10(-7)). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.