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.

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.

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.

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.

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.

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.

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.

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.

DNA methylation profiling of human chromosomes 6, 20 and 22.

DNA methylation is the most stable type of epigenetic modification modulating the transcriptional plasticity of mammalian genomes. Using bisulfite DNA sequencing, we report high-resolution methylation profiles of human chromosomes 6, 20 and 22, providing a resource of about 1.9 million CpG methylation values derived from 12 different tissues. Analysis of six annotation categories showed that evolutionarily conserved regions are the predominant sites for differential DNA methylation and that a core region surrounding the transcriptional start site is an informative surrogate for promoter methylation. We find that 17% of the 873 analyzed genes are differentially methylated in their 5' UTRs and that about one-third of the differentially methylated 5' UTRs are inversely correlated with transcription. Despite the fact that our study controlled for factors reported to affect DNA methylation such as sex and age, we did not find any significant attributable effects. Our data suggest DNA methylation to be ontogenetically more stable than previously thought.

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.

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.

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.

Human aging-associated DNA hypermethylation occurs preferentially at bivalent chromatin domains.

There is a growing realization that some aging-associated phenotypes/diseases have an epigenetic basis. Here, we report the first genome-scale study of epigenomic dynamics during normal human aging. We identify aging-associated differentially methylated regions (aDMRs) in whole blood in a discovery cohort, and then replicate these aDMRs in sorted CD4(+) T-cells and CD14(+) monocytes in an independent cohort, suggesting that aDMRs occur in precursor haematopoietic cells. Further replication of the aDMRs in buccal cells, representing a tissue that originates from a different germ layer compared with blood, demonstrates that the aDMR signature is a multitissue phenomenon. Moreover, we demonstrate that aging-associated DNA hypermethylation occurs predominantly at bivalent chromatin domain promoters. This same category of promoters, associated with key developmental genes, is frequently hypermethylated in cancers and in vitro cell culture, pointing to a novel mechanistic link between aberrant hypermethylation in cancer, aging, and cell culture.

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.

Genome-wide identification of targets and function of individual MicroRNAs in mouse embryonic stem cells.

Mouse Embryonic Stem (ES) cells express a unique set of microRNAs (miRNAs), the miR-290-295 cluster. To elucidate the role of these miRNAs and how they integrate into the ES cell regulatory network requires identification of their direct regulatory targets. The difficulty, however, arises from the limited complementarity of metazoan miRNAs to their targets, with the interaction requiring as few as six nucleotides of the miRNA seed sequence. To identify miR-294 targets, we used Dicer1-null ES cells, which lack all endogenous mature miRNAs, and introduced just miR-294 into these ES cells. We then employed two approaches to discover miR-294 targets in mouse ES cells: transcriptome profiling using microarrays and a biochemical approach to isolate mRNA targets associated with the Argonaute2 (Ago2) protein of the RISC (RNA Induced Silencing Complex) effector, followed by RNA-sequencing. In the absence of Dicer1, the RISC complexes are largely devoid of mature miRNAs and should therefore contain only transfected miR-294 and its base-paired targets. Our data suggest that miR-294 may promote pluripotency by regulating a subset of c-Myc target genes and upregulating pluripotency-associated genes such as Lin28.

Smicl is required for phosphorylation of RNA polymerase II and affects 3'-end processing of RNA at the midblastula transition in Xenopus.

Smicl (Smad-interacting CPSF 30-like) is an unusual protein that interacts with transcription factors as well as with the cleavage and polyadenylation specificity factor (CPSF). Previous work has shown that Smicl is expressed maternally in the Xenopus embryo and is later required for transcription of Chordin. In this paper we search for additional targets of Smicl. We identify many genes whose onset of expression at the midblastula transition (MBT) requires Smicl and is correlated with the translocation of Smicl from cytoplasm to nucleus. At least one such gene, Xiro1, is regulated via 3'-end processing. In searching for a general mechanism by which Smicl might regulate gene expression at the MBT, we have discovered that it interacts with the tail of Rpb1, the largest subunit of RNA polymerase II. Our results show that Smicl is required for the phosphorylation of the Rpb1 tail at serine 2 of the repeated heptapeptide YSPTSPS. This site becomes hyperphosphorylated at the MBT, thus allowing the docking of proteins required for elongation of transcription and RNA processing. Our work links the onset of zygotic gene expression in the Xenopus embryo with the translocation of Smicl from cytoplasm to nucleus, the phosphorylation of Rpb1 and the 3'-end processing of newly transcribed mRNAs.

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.

iMotifs: an integrated sequence motif visualization and analysis environment.

MOTIVATION: Short sequence motifs are an important class of models in molecular biology, used most commonly for describing transcription factor binding site specificity patterns. High-throughput methods have been recently developed for detecting regulatory factor binding sites in vivo and in vitro and consequently high-quality binding site motif data are becoming available for increasing number of organisms and regulatory factors. Development of intuitive tools for the study of sequence motifs is therefore important. iMotifs is a graphical motif analysis environment that allows visualization of annotated sequence motifs and scored motif hits in sequences. It also offers motif inference with the sensitive NestedMICA algorithm, as well as overrepresentation and pairwise motif matching capabilities. All of the analysis functionality is provided without the need to convert between file formats or learn different command line interfaces. The application includes a bundled and graphically integrated version of the NestedMICA motif inference suite that has no outside dependencies. Problems associated with local deployment of software are therefore avoided. AVAILABILITY: iMotifs is licensed with the GNU Lesser General Public License v2.0 (LGPL 2.0). The software and its source is available at http://wiki.github.com/mz2/imotifs and can be run on Mac OS X Leopard (Intel/PowerPC). We also provide a cross-platform (Linux, OS X, Windows) LGPL 2.0 licensed library libxms for the Perl, Ruby, R and Objective-C programming languages for input and output of XMS formatted annotated sequence motif set files. CONTACT: matias.piipari@gmail.com; imotifs@googlegroups.com.

Assessing computational methods of cis-regulatory module prediction.

Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites while knowledge of the specific interactions involved remains limited. Without a comprehensive comparison of their performance, the reliability and accuracy of these tools remains unclear. Faced with a large number of different tools that address this problem, we summarized and categorized them based on search strategy and input data requirements. Twelve representative methods were chosen and applied to predict CRMs from the Drosophila CRM database REDfly, and across the human ENCODE regions. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. When discriminating CRMs from non-coding regions, those methods considering evolutionary conservation have a stronger predictive power than methods designed to be run on a single genome. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs. Furthermore, most methods appear to be sensitive to the composition and structure of the genome to which they are applied. We analyze the principal features that distinguish the methods that performed well, identify weaknesses leading to poor performance, and provide a guide for users. We also propose key considerations for the development and evaluation of future CRM-prediction methods.

Metamotifs--a generative model for building families of nucleotide position weight matrices.

BACKGROUND: Development of high-throughput methods for measuring DNA interactions of transcription factors together with computational advances in short motif inference algorithms is expanding our understanding of transcription factor binding site motifs. The consequential growth of sequence motif data sets makes it important to systematically group and categorise regulatory motifs. It has been shown that there are familial tendencies in DNA sequence motifs that are predictive of the family of factors that binds them. Further development of methods that detect and describe familial motif trends has the potential to help in measuring the similarity of novel computational motif predictions to previously known data and sensitively detecting regulatory motifs similar to previously known ones from novel sequence. RESULTS: We propose a probabilistic model for position weight matrix (PWM) sequence motif families. The model, which we call the 'metamotif' describes recurring familial patterns in a set of motifs. The metamotif framework models variation within a family of sequence motifs. It allows for simultaneous estimation of a series of independent metamotifs from input position weight matrix (PWM) motif data and does not assume that all input motif columns contribute to a familial pattern. We describe an algorithm for inferring metamotifs from weight matrix data. We then demonstrate the use of the model in two practical tasks: in the Bayesian NestedMICA model inference algorithm as a PWM prior to enhance motif inference sensitivity, and in a motif classification task where motifs are labelled according to their interacting DNA binding domain. CONCLUSIONS: We show that metamotifs can be used as PWM priors in the NestedMICA motif inference algorithm to dramatically increase the sensitivity to infer motifs. Metamotifs were also successfully applied to a motif classification problem where sequence motif features were used to predict the family of protein DNA binding domains that would interact with it. The metamotif based classifier is shown to compare favourably to previous related methods. The metamotif has great potential for further use in machine learning tasks related to especially de novo computational sequence motif inference. The metamotif methods presented have been incorporated into the NestedMICA suite.