Tackling the epigenome: challenges and opportunities for collaboration

Employing core regulatory circuits to define cell identity

The interplay between extrinsic signaling and downstream gene networks controls the establishment of cell identity during development and its maintenance in adult life. Advances in next-generation sequencing and single-cell technologies have revealed additional layers of complexity in cell identity. Here, we review our current understanding of transcription factor (TF) networks as key determinants of cell identity. We discuss the concept of the core regulatory circuit as a set of TFs and interacting factors that together define the gene expression profile of the cell. We propose the core regulatory circuit as a comprehensive conceptual framework for defining cellular identity and discuss its connections to cell function in different contexts.

Genetic association of molecular traits: A help to identify causative variants in complex diseases

In the past 15 years, major progresses have been made in the understanding of the genetic basis of regulation of gene expression. These new insights have revolutionized our approach to resolve the genetic variation underlying complex diseases. Gene transcript levels were the first expression phenotypes that were studied. They are heritable and therefore amenable to genome-wide association studies. The genetic variants that modulate them are called expression quantitative trait loci. Their study has been extended to other molecular quantitative trait loci (molQTLs) that regulate gene expression at the various levels, from chromatin state to cellular responses. Altogether, these studies have generated a wealth of basic information on the genome-wide patterns of gene expression and their inter-individual variation. Most importantly, molQTLs have become an invaluable asset in the genetic study of complex diseases. Although the identification of the disease-causing variants on the basis of their overlap with molQTLs requires caution, molQTLs can help to prioritize the relevant candidate gene(s) in the disease-associated regions and bring a functional interpretation of the associated variants, therefore, bridging the gap between genotypes and clinical phenotypes.

The NIH Common Fund/Roadmap Epigenomics Program: Successes of a comprehensive consortium

The NIH Roadmap Epigenomics Program was launched to deliver reference epigenomic data from human tissues and cells, develop tools and methods for analyzing the epigenome, discover novel epigenetic marks, develop methods to manipulate the epigenome, and determine epigenetic contributions to diverse human diseases. Here, we comment on the outcomes from this program: the scientific contributions made possible by a consortium approach and the challenges, benefits, and lessons learned from this group science effort.

Cell cycle-resolved chromatin proteomics reveals the extent of mitotic preservation of the genomic regulatory landscape

Regulation of transcription, replication, and cell division relies on differential protein binding to DNA and chromatin, yet it is unclear which regulatory components remain bound to compacted mitotic chromosomes. By utilizing the buoyant density of DNA–protein complexes after cross-linking, we here develop a mass spectrometry-based approach to quantify the chromatin-associated proteome at separate stages of the cell cycle. While epigenetic modifiers that promote transcription are lost from mitotic chromatin, repressive modifiers generally remain associated. Furthermore, while proteins involved in transcriptional elongation are evicted, most identified transcription factors are retained on mitotic chromatin to varying degrees, including core promoter binding proteins. This predicts conservation of the regulatory landscape on mitotic chromosomes, which we confirm by genome-wide measurements of chromatin accessibility. In summary, this work establishes an approach to study chromatin, provides a comprehensive catalog of chromatin changes during the cell cycle, and reveals the degree to which the genomic regulatory landscape is maintained through mitosis.

Mitosis poses a challenge for transcriptional programs, as it is thought that several proteins lose binding on condensed chromosomes. Here, the authors analyze the chromatin-bound proteome through the cell cycle, revealing retention of most transcription factors and preservation of the regulatory landscape.

Considerations for Design and Analysis of DNA Methylation Studies

The number of epigenetic studies is exponentially increasing. There is anticipation that DNA methylation may close gaps in our understanding of disease etiology, and how certain risk factors affect health and disease, but also that it has potential as a biomarker for disease. Human DNA methylation studies require careful considerations for design and analysis including population and tissue selection, population stratification, cell heterogeneity, confounding, temporality, sample size, appropriate statistical analysis, and validation of results. In this chapter, we discuss relevant aspects for the design of DNA methylation studies and delineate essential steps for their analysis. Specifically, we summarize methods used to extricate biologic signals from technical noise, and statistical approaches to capture meaningful variability based on the research hypothesis.

Identification of recurrent combinatorial patterns of chromatin modifications at promoters across various tissue types

Background

Identification and analysis of recurrent combinatorial patterns of multiple chromatin modifications provide invaluable information for understanding epigenetic regulations. Furthermore, as more data becomes available, it is computationally expensive and unnecessary to study combinatorial patterns of all modifications.

Methods

A novel framework is proposed to investigate recurrent combinatorial patterns of a subset of quantitatively selected chromatin modifications. The framework is based on heirarchical clustering and selects subsets of chromatin modifications that form distinct recurrent patterns at regulatory regions. The identified recurrent combinatorial patterns can be further utilized to discover novel regulatory regions. Data is in the form of genome wide maps of histone acetylations, methylations, and histone variant of human skeletal muscular and B-lymphocyte cells both derived from the ENCODE project.

Results

A case study conducted at promoter regions is presented: four out of twelve chromatin modifications were selected, eight different promoter states were identified and the identified patterns of active promoters were further utilized to discover novel promoter regions. Several previously un-annotated promoters were discovered, further investigations confirm their promoter functions.

Conclusions

This framework is approproiately general and could lead to better understanding of epigenetic regulations by discovering previously unknown regulatory regions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1346-5) contains supplementary material, which is available to authorized users.

Quantitative comparison of DNA methylation assays for biomarker development and clinical applications

DNA methylation patterns are altered in numerous diseases and often correlate with clinically relevant information such as disease subtypes, prognosis and drug response. With suitable assays and after validation in large cohorts, such associations can be exploited for clinical diagnostics and personalized treatment decisions. Here we describe the results of a community-wide benchmarking study comparing the performance of all widely used methods for DNA methylation analysis that are compatible with routine clinical use. We shipped 32 reference samples to 18 laboratories in seven different countries. Researchers in those laboratories collectively contributed 21 locus-specific assays for an average of 27 predefined genomic regions, as well as six global assays. We evaluated assay sensitivity on low-input samples and assessed the assays' ability to discriminate between cell types. Good agreement was observed across all tested methods, with amplicon bisulfite sequencing and bisulfite pyrosequencing showing the best all-round performance. Our technology comparison can inform the selection, optimization and use of DNA methylation assays in large-scale validation studies, biomarker development and clinical diagnostics.

Genome-Wide Epigenetic Studies in Human Disease: A Primer on -Omic Technologies

Epigenetic information encoded in covalent modifications of DNA and histone proteins regulates fundamental biological processes through the action of chromatin regulators, transcription factors, and noncoding RNA species. Epigenetic plasticity enables an organism to respond to developmental and environmental signals without genetic changes. However, aberrant epigenetic control plays a key role in pathogenesis of disease. Normal epigenetic states could be disrupted by detrimental mutations and expression alteration of chromatin regulators or by environmental factors. In this primer, we briefly review the epigenetic basis of human disease and discuss how recent discoveries in this field could be translated into clinical diagnosis, prevention, and treatment. We introduce platforms for mapping genome-wide chromatin accessibility, nucleosome occupancy, DNA-binding proteins, and DNA methylation, primarily focusing on the integration of DNA methylation and chromatin immunoprecipitation-sequencing technologies into disease association studies. We highlight practical considerations in applying high-throughput epigenetic assays and formulating analytical strategies. Finally, we summarize current challenges in sample acquisition, experimental procedures, data analysis, and interpretation and make recommendations on further refinement in these areas. Incorporating epigenomic testing into the clinical research arsenal will greatly facilitate our understanding of the epigenetic basis of disease and help identify novel therapeutic targets.

Characterising the epigenome as a key component of the fetal exposome in evaluating in utero exposures and childhood cancer risk

Recent advances in laboratory sciences hold a promise for a 'leap forward' in understanding the aetiology of complex human diseases, notably cancer, potentially providing an evidence base for prevention. For example, remarkable advances in epigenomics have an important impact on our understanding of biological phenomena and importance of environmental stressors in complex diseases. Environmental and lifestyle factors are thought to be implicated in the development of a wide range of human cancers by eliciting changes in the epigenome. These changes, thus, represent attractive targets for biomarker discovery intended for the improvement of exposure and risk assessment, diagnosis and prognosis and provision of short-term outcomes in intervention studies. The epigenome can be viewed as an interface between the genome and the environment; therefore, aberrant epigenetic events associated with environmental exposures are likely to play an important role in the onset and progression of different human diseases. The advent of powerful technologies for analysing epigenetic patterns in both cancer tissues and normal cells holds promise that the next few years will be fundamental for the identification of critical cancer- and exposure-associated epigenetic changes and for their evaluation as new generation of biomarkers. Here, we discuss new opportunities in the current age of 'omics' technologies for studies with prospective design and associated biospecimens that represent exciting potential for characterising the epigenome as a key component of the fetal exposome and for understanding causal pathways and robust predictors of cancer risk and associated environmental determinants during in utero life. Such studies should improve our knowledge concerning the aetiology of childhood cancer and identify both novel biomarkers and clues to causation, thus, providing an evidence base for cancer prevention.

Epigenetic modifications as therapeutic targets

Epigenetic modifications work in concert with genetic mechanisms to regulate transcriptional activity in normal tissues and are often dysregulated in disease. Although they are somatically heritable, modifications of DNA and histones are also reversible, making them good targets for therapeutic intervention. Epigenetic changes often precede disease pathology, making them valuable diagnostic indicators for disease risk or prognostic indicators for disease progression. Several inhibitors of histone deacetylation or DNA methylation are approved for hematological malignancies by the US Food and Drug Administration and have been in clinical use for several years. More recently, histone methylation and microRNA expression have gained attention as potential therapeutic targets. The presence of multiple epigenetic aberrations within malignant tissue and the abilities of cells to develop resistance suggest that epigenetic therapies are most beneficial when combined with other anticancer strategies, such as signal transduction inhibitors or cytotoxic treatments. A key challenge for future epigenetic therapies will be to develop inhibitors with specificity to particular regions of chromosomes, thereby potentially reducing side effects.

ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to map histone marks and transcription factor binding throughout the genome. Here we present ChIPmentation, a method that combines chromatin immunoprecipitation with sequencing library preparation by Tn5 transposase (“tagmentation”). ChIPmentation introduces sequencing-compatible adapters in a single-step reaction directly on bead-bound chromatin, which reduces time, cost, and input requirements, thus providing a convenient and broadly useful alternative to existing ChIP-seq protocols.

Uncovering correlated variability in epigenomic datasets using the Karhunen-Loeve transform

BACKGROUND

Larger variation exists in epigenomes than in genomes, as a single genome shapes the identity of multiple cell types. With the advent of next-generation sequencing, one of the key problems in computational epigenomics is the poor understanding of correlations and quantitative differences between large scale data sets.

RESULTS

Here we bring to genomics a scenario of functional principal component analysis, a finite Karhunen-Loève transform, and explicitly decompose the variation in the coverage profiles of 27 chromatin mark ChIP-seq datasets at transcription start sites for H1, one of the most used human embryonic stem cell lines. Using this approach we identify positive correlations between H3K4me3 and H3K36me3, as well as between H3K9ac and H3K36me3, so far undetected by the most commonly used Pearson correlation between read enrichment coverages. We uncover highly negative correlations between H2A.Z, H3K4me3, and several histone acetylation marks, but these occur only between principal components of first and second order. We also demonstrate that levels of gene expression correlate significantly with scores of components of order higher than one, demonstrating that transcriptional regulation by histone marks escapes simple one-to-one relationships. This correlations were higher in significance and magnitude in protein coding genes than in non-coding RNAs.

CONCLUSIONS

In summary, we present a methodology to explore and uncover novel patterns of epigenomic variability and covariability in genomic data sets by using a functional eigenvalue decomposition of genomic data. R code is available at: http://github.com/pmb59/KLTepigenome.

MBRidge: an accurate and cost-effective method for profiling DNA methylome at single-base resolution

Organisms and cells, in response to environmental influences or during development, undergo considerable changes in DNA methylation on a genome-wide scale, which are linked to a variety of biological processes. Using MethylC-seq to decipher DNA methylome at single-base resolution is prohibitively costly. In this study, we develop a novel approach, named MBRidge, to detect the methylation levels of repertoire CpGs, by innovatively introducing C-hydroxylmethylated adapters and bisulfate treatment into the MeDIP-seq protocol and employing ridge regression in data analysis. A systematic evaluation of DNA methylome in a human ovarian cell line T29 showed that MBRidge achieved high correlation (R > 0.90) with much less cost (∼10%) in comparison with MethylC-seq. We further applied MBRidge to profiling DNA methylome in T29H, an oncogenic counterpart of T29's. By comparing methylomes of T29H and T29, we identified 131790 differential methylation regions (DMRs), which are mainly enriched in carcinogenesis-related pathways. These are substantially different from 7567 DMRs that were obtained by RRBS and related with cell development or differentiation. The integrated analysis of DMRs in the promoter and expression of DMR-corresponding genes revealed that DNA methylation enforced reverse regulation of gene expression, depending on the distance from the proximal DMR to transcription starting sites in both mRNA and lncRNA. Taken together, our results demonstrate that MBRidge is an efficient and cost-effective method that can be widely applied to profiling DNA methylomes.

ESCI award lecture: regulation, function and biomarker potential of DNA methylation

Methylation of DNA and modifications of histones have emerged as intricately involved in gene regulation as they cross-talk and respond in multiple ways to the activity of transcription factors. Measuring these epigenome components has become a powerful tool to identify regulatory principles and biomarkers that predict cellular state during development or disease. Here, I will focus on DNA methylation as a reversible epigenetic modification of DNA that has been studied in great detail at the level of the genome. Recent advances in sequencing have identified unexpected dynamics of this modification, which are tightly linked to gene regulation. Understanding how DNA methylation patterns are read and how they contribute to regulation will be critical to interpret and utilize genomic maps of DNA methylation. As these patterns are dynamic during cellular differentiation and perturbed in disease, they present an opportunity to use DNA methylation as a biomarker.

Integrative analysis of 111 reference human epigenomes

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, 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.

Identification and computational analysis of gene regulatory elements

Over the last two decades, advances in experimental and computational technologies have greatly facilitated genomic research. Next-generation sequencing technologies have made de novo sequencing of large genomes affordable, and powerful computational approaches have enabled accurate annotations of genomic DNA sequences. Charting functional regions in genomes must account for not only the coding sequences, but also noncoding RNAs, repetitive elements, chromatin states, epigenetic modifications, and gene regulatory elements. A mix of comparative genomics, high-throughput biological experiments, and machine learning approaches has played a major role in this truly global effort. Here we describe some of these approaches and provide an account of our current understanding of the complex landscape of the human genome. We also present overviews of different publicly available, large-scale experimental data sets and computational tools, which we hope will prove beneficial for researchers working with large and complex genomes.

Comprehensive analysis of DNA methylation data with RnBeads

RnBeads is a software tool for large-scale analysis and interpretation of DNA methylation data, providing a user-friendly analysis workflow that yields detailed hypertext reports (http://rnbeads.mpi-inf.mpg.de/). Supported assays include whole-genome bisulfite sequencing, reduced representation bisulfite sequencing, Infinium microarrays and any other protocol that produces high-resolution DNA methylation data. Notable applications of RnBeads include the analysis of epigenome-wide association studies and epigenetic biomarker discovery in cancer cohorts.

The meta-epigenomic structure of purified human stem cell populations is defined at cis-regulatory sequences

The mechanism and significance of epigenetic variability in the same cell type between healthy individuals are not clear. Here, we purify human CD34+ hematopoietic stem and progenitor cells (HSPCs) from different individuals and find that there is increased variability of DNA methylation at loci with properties of promoters and enhancers. The variability is especially enriched at candidate enhancers near genes transitioning between silent and expressed states, and encoding proteins with leukocyte differentiation properties. Our findings of increased variability at loci with intermediate DNA methylation values, at candidate “poised” enhancers, and at genes involved in HSPC lineage commitment suggest that CD34+ cell subtype heterogeneity between individuals is a major mechanism for the variability observed. Epigenomic studies performed on cell populations, even when purified, are testing collections of epigenomes, or meta-epigenomes. Our findings show that meta-epigenomic approaches to data analysis can provide insights into cell subpopulation structure.

High-resolution digital profiling of the epigenome

The widespread adoption of short-read DNA sequencing as a digital epigenomic readout platform has motivated the development of genome-wide tools that achieve base-pair resolution. New methods for footprinting and affinity purification of nucleosomes, RNA polymerases, chromatin remodellers and transcription factors have increased the resolution of epigenomic profiling by two orders of magnitude, leading to new insights into how the chromatin landscape affects gene regulation. These digital epigenomic tools have also been applied to directly profile both turnover kinetics and transcription in situ. In this Review, we describe how these new genome-wide tools allow interrogation of diverse aspects of the epigenome.

Statistical methods for detecting differentially methylated loci and regions

DNA methylation, the reversible addition of methyl groups at CpG dinucleotides, represents an important regulatory layer associated with gene expression. Changed methylation status has been noted across diverse pathological states, including cancer. The rapid development and uptake of microarrays and large scale DNA sequencing has prompted an explosion of data analytic methods for processing and discovering changes in DNA methylation across varied data types. In this mini-review, we present a compact and accessible discussion of many of the salient challenges, such as experimental design, statistical methods for differential methylation detection, critical considerations such as cell type composition and the potential confounding that can arise from batch effects. From a statistical perspective, our main interests include the use of empirical Bayes or hierarchical models, which have proved immensely powerful in genomics, and the procedures by which false discovery control is achieved.

Identifying and mapping cell-type-specific chromatin programming of gene expression

A problem of substantial interest is to systematically map variation in chromatin structure to gene-expression regulation across conditions, environments, or differentiated cell types. We developed and applied a quantitative framework for determining the existence, strength, and type of relationship between high-resolution chromatin structure in terms of DNaseI hypersensitivity and genome-wide gene-expression levels in 20 diverse human cell types. We show that ∼25% of genes show cell-type-specific expression explained by alterations in chromatin structure. We find that distal regions of chromatin structure (e.g., ±200 kb) capture more genes with this relationship than local regions (e.g., ±2.5 kb), yet the local regions show a more pronounced effect. By exploiting variation across cell types, we were capable of pinpointing the most likely hypersensitive sites related to cell-type-specific expression, which we show have a range of contextual uses. This quantitative framework is likely applicable to other settings aimed at relating continuous genomic measurements to gene-expression variation.

Recommendations for the design and analysis of epigenome-wide association studies

Epigenome-wide association studies (EWAS) hold promise for the detection of new regulatory mechanisms that may be susceptible to modification by environmental and lifestyle factors affecting susceptibility to disease. Epigenome-wide screening methods cover an increasing number of CpG sites, but the complexity of the data poses a challenge to separating robust signals from noise. Appropriate study design, a detailed a priori analysis plan and validation of results are essential to minimize the danger of false positive results and contribute to a unified approach. Epigenome-wide mapping studies in homogenous cell populations will inform our understanding of normal variation in the methylome that is not associated with disease or aging. Here we review concepts for conducting a stringent and powerful EWAS, including the choice of analyzed tissue, sources of variability and systematic biases, outline analytical solutions to EWAS-specific problems and highlight caveats in interpretation of data generated from samples with cellular heterogeneity.

Mapping the new molecular landscape: social dimensions of epigenetics

Epigenetics is the study of changes in gene expression caused by mechanisms other than changes in the DNA itself. The field is rapidly growing and being widely promoted, attracting attention in diverse arenas. These include those of the social sciences, where some researchers have been encouraged by the resonance between imaginaries of development within epigenetics and social theory. Yet, sustained attention from science and technology studies (STS) scholars to epigenetics and the praxis it propels has been lacking. In this article, we reflexively consider some of the ways in which epigenetics is being constructed as an area of biomedical novelty and discuss the content and logics underlying the ambivalent promises being made by scientists working in this area. We then reflect on the scope, limits and future of engagements between epigenetics and the social sciences. Our discussion is situated within wider literatures on biomedicine and society, the politics of "interventionist STS," and on the problems of "caseness" within empirical social science.

A method to detect differentially methylated loci with next-generation sequencing

Epigenetic changes, especially DNA methylation at CpG loci have important implications in cancer and other complex diseases. With the development of next-generation sequencing (NGS), it is feasible to generate data to interrogate the difference in methylation status for genome-wide loci using case-control design. However, a proper and efficient statistical test is lacking. There are several challenges. First, unlike methylation experiments using microarrays, where there is one measure of methylation for one individual at a particular CpG site, here we have the counts of methylation allele and unmethylation allele for each individual. Second, due to the nature of sample preparation, the measured methylation reflects the methylation status of a mixture of cells involved in sample preparation. Therefore, the underlying distribution of the measured methylation level is unknown, and a robust test is more desirable than parametric approach. Third, currently NGS measures methylation at over 2 million CpG sites. Any statistical tests have to be computationally efficient in order to be applied to the NGS data. Taking these challenges into account, we propose a test for differential methylation based on clustered data analysis by modeling the methylation counts. We performed simulations to show that it is robust under several distributions for the measured methylation levels. It has good power and is computationally efficient. Finally, we apply the test to our NGS data on chronic lymphocytic leukemia. The results indicate that it is a promising and practical test.

Enabling interspecies epigenomic comparison with CEpBrowser

SUMMARY

We developed the Comparative Epigenome Browser (CEpBrowser) to allow the public to perform multi-species epigenomic analysis. The web-based CEpBrowser integrates, manages and visualizes sequencing-based epigenomic datasets. Five key features were developed to maximize the efficiency of interspecies epigenomic comparisons.

AVAILABILITY

CEpBrowser is a web application implemented with PHP, MySQL, C and Apache. URL: http://www.cepbrowser.org/.

Analysing and interpreting DNA methylation data

DNA methylation is an epigenetic mark that has suspected regulatory roles in a broad range of biological processes and diseases. The technology is now available for studying DNA methylation genome-wide, at a high resolution and in a large number of samples. This Review discusses relevant concepts, computational methods and software tools for analysing and interpreting DNA methylation data. It focuses not only on the bioinformatic challenges of large epigenome-mapping projects and epigenome-wide association studies but also highlights software tools that make genome-wide DNA methylation mapping more accessible for laboratories with limited bioinformatics experience.

EpiExplorer: live exploration and global analysis of large epigenomic datasets

Epigenome mapping consortia are generating resources of tremendous value for studying epigenetic regulation. To maximize their utility and impact, new tools are needed that facilitate interactive analysis of epigenome datasets. Here we describe EpiExplorer, a web tool for exploring genome and epigenome data on a genomic scale. We demonstrate EpiExplorer's utility by describing a hypothesis-generating analysis of DNA hydroxymethylation in relation to public reference maps of the human epigenome. All EpiExplorer analyses are performed dynamically within seconds, using an efficient and versatile text indexing scheme that we introduce to bioinformatics. EpiExplorer is available at http://epiexplorer.mpi-inf.mpg.de.

Modeling of epigenome dynamics identifies transcription factors that mediate Polycomb targeting

Although changes in chromatin are integral to transcriptional reprogramming during cellular differentiation, it is currently unclear how chromatin modifications are targeted to specific loci. To systematically identify transcription factors (TFs) that can direct chromatin changes during cell fate decisions, we model the relationship between genome-wide dynamics of chromatin marks and the local occurrence of computationally predicted TF binding sites. By applying this computational approach to a time course of Polycomb-mediated H3K27me3 marks during neuronal differentiation of murine stem cells, we identify several motifs that likely regulate the dynamics of this chromatin mark. Among these, the sites bound by REST and by the SNAIL family of TFs are predicted to transiently recruit H3K27me3 in neuronal progenitors. We validate these predictions experimentally and show that absence of REST indeed causes loss of H3K27me3 at target promoters in trans, specifically at the neuronal progenitor state. Moreover, using targeted transgenic insertion, we show that promoter fragments containing REST or SNAIL binding sites are sufficient to recruit H3K27me3 in cis, while deletion of these sites results in loss of H3K27me3. These findings illustrate that the occurrence of TF binding sites can determine chromatin dynamics. Local determination of Polycomb activity by REST and SNAIL motifs exemplifies such TF based regulation of chromatin. Furthermore, our results show that key TFs can be identified ab initio through computational modeling of epigenome data sets using a modeling approach that we make readily accessible.

Quantitative cross-validation and content analysis of the 450k DNA methylation array from Illumina, Inc

BACKGROUND

The newly released 450k DNA methylation array from Illumina, Inc. offers the possibility to analyze more than 480,000 individual CpG sites in a user friendly standardized format. In this study the relationship between the β-values provided by the Illumina, Inc. array for each individual CpG dinucleotide and the quantitative methylation levels obtained by pyrosequencing were analyzed. In addition, the representation of microRNA genes and imprinted loci on the Illumina, Inc. array was assessed in detail. Genomic DNA from 4 human breast cancer cell lines (IPH-926, HCC1937, MDA-MB-134, PMC42) and 18 human breast cancer specimens as well as 4 normal mammary epithelial fractions was analyzed on 450k DNA methylation arrays. The β-values for 692 individual CpG sites from 62 different genes were cross-validated using conventional quantitative pyrosequencing.

FINDINGS

The newly released 450k methylation array from Illumina, Inc. shows a high concordance with quantitative pyrosequencing if identical CpG sites are analyzed in cell lines (Spearman r = 0.88, p ≪ 0.0001), which is somewhat reduced in primary tumor specimens (Spearman r = 0.86, p ≪ 0.0001). 80.7% of the CpG sites show an absolute difference in methylation level of less than 15 percentage points. If different CpG sites in the same CpG islands are targeted the concordance is lower (r = 0.83 in cell lines and r = 0.7 in primary tumors). The number of CpG sites representing microRNA genes and imprinted loci is very heterogeneous (range: 1 - 70 CpG sites for microRNAs and 1 - 288 for imprinted loci).

CONCLUSIONS

The newly released 450k methylation array from Illumina, Inc. provides a genome-wide quantitative representation of DNA methylation aberrations in a convenient format. Overall, the congruence with pyrosequencing data is very good. However, for individual loci one should be careful to translate the β-values directly into percent methylation levels.

Epigenetic regulation in cell reprogramming revealed by genome-wide analysis

Cell reprogramming has been known to accompany cell type-specific epigenetic alterations of the genome. Chromatin structure and dynamics influenced by epigenetic factors such as covalent histone modifications, histone variants, DNA methylation, ncRNAs and chromatin remodeling play an important role in determining cell fate. The rapid progress made with the development of high-throughput technology and the systematic assessment of accumulated data has enabled the identification of previously unknown biological processes and disease states in terms of whole-genome profiles of epigenetic signatures at a high resolution. In this article, we discuss the fundamental advances and challenges over the past several years in our knowledge of chromatin state and gene transcription programs associated with epigenetic changes during cell reprogramming processes. In particular, histone modifications, DNA methylation and transcriptome analyses in genome-scale studies will be reviewed to characterize a functional cross-talk between epigenetic and transcriptional regulations in cell reprogramming.

Targeted sequence capture as a powerful tool for evolutionary analysis

Next-generation sequencing technologies (NGS) have revolutionized biological research by significantly increasing data generation while simultaneously decreasing the time to data output. For many ecologists and evolutionary biologists, the research opportunities afforded by NGS are substantial; even for taxa lacking genomic resources, large-scale genome-level questions can now be addressed, opening up many new avenues of research. While rapid and massive sequencing afforded by NGS increases the scope and scale of many research objectives, whole genome sequencing is often unwarranted and unnecessarily complex for specific research questions. Recently developed targeted sequence enrichment, coupled with NGS, represents a beneficial strategy for enhancing data generation to answer questions in ecology and evolutionary biology. This marriage of technologies offers researchers a simple method to isolate and analyze a few to hundreds, or even thousands, of genes or genomic regions from few to many samples in a relatively efficient and effective manner. These strategies can be applied to questions at both the infra- and interspecific levels, including those involving parentage, gene flow, divergence, phylogenetics, reticulate evolution, and many more. Here we provide a brief overview of targeted sequence enrichment, and emphasize the power of this technology to increase our ability to address a wide range of questions of interest to ecologists and evolutionary biologists, particularly for those working with taxa for which few genomic resources are available.

Exploring the role of the epigenome in multiple sclerosis: a window onto cell-specific transcriptional potential

The field of epigenomics involves the study of chromatin, the three dimensional complex of DNA, protein and non-coding RNAs that determines the accessibility of DNA by the transcriptional machinery. The epigenome varies from cell to cell and reflects the effect of external stimuli on cell fate and cell state. Thanks to emerging platforms and analysis methods, the systematic characterization of chromatin conformation throughout the genome has begun and has yielded several reference epigenome maps for a growing number of cell types. Such maps are enabling insights into the correlation architecture of different epigenomic marks: a number of discrete chromatin states are found across different cell types. The combination of these reference maps and robust platforms for genome-wide data generation has introduced a new era in which studies of human disease are becoming feasible. Little is known about the role of the epigenome in MS, but it is likely that, as in other inflammatory disease, susceptibility factors and events along the course of the disease will alter the chromatin state of different cell types in patients with MS. Here, we review different strategies for the characterization of the epigenome and how these strategies could be used to implement new studies to explore how alterations of chromatin architecture establish a dysregulated transcriptional state in the context of MS.

Bioinformatics for personal genome interpretation

An international consortium released the first draft sequence of the human genome 10 years ago. Although the analysis of this data has suggested the genetic underpinnings of many diseases, we have not yet been able to fully quantify the relationship between genotype and phenotype. Thus, a major current effort of the scientific community focuses on evaluating individual predispositions to specific phenotypic traits given their genetic backgrounds. Many resources aim to identify and annotate the specific genes responsible for the observed phenotypes. Some of these use intra-species genetic variability as a means for better understanding this relationship. In addition, several online resources are now dedicated to collecting single nucleotide variants and other types of variants, and annotating their functional effects and associations with phenotypic traits. This information has enabled researchers to develop bioinformatics tools to analyze the rapidly increasing amount of newly extracted variation data and to predict the effect of uncharacterized variants. In this work, we review the most important developments in the field--the databases and bioinformatics tools that will be of utmost importance in our concerted effort to interpret the human variome.

Relevance and implication of genetic determinants to asthma pathophysiology

PURPOSE OF REVIEW

The number of single nucleotide polymorphisms (SNPs) found to be associated with asthma and related phenotypes outnumbers those with functional impacts. In this review we briefly described some of the approaches used to investigate functionality of SNPs, and summarized recent findings related to the characterization of functional SNPs in asthma.

RECENT FINDINGS

For disease-associated SNPs residing in the promoter or 3' untranslated regions, differential protein binding affinity between the major and minor alleles is often the first logical area of investigation. In this review, we described SNPs associated with asthma or related phenotypes in five genes which in the past 12 months have new data implicating potential mechanisms in asthma development.

SUMMARY

Variability in treatment responses poses a great challenge in asthma management. It is established that the genetic makeup of individuals plays a role in asthma development, yet the mechanisms remain unclear. Investigations on the functional impacts of disease-associated SNPs will help us gain insights into potential disease mechanisms, and ultimately lead to effective therapies for those who suffer from asthma.

DNA-binding factors shape the mouse methylome at distal regulatory regions

Methylation of cytosines is an essential epigenetic modification in mammalian genomes, yet the rules that govern methylation patterns remain largely elusive. To gain insights into this process, we generated base-pair-resolution mouse methylomes in stem cells and neuronal progenitors. Advanced quantitative analysis identified low-methylated regions (LMRs) with an average methylation of 30%. These represent CpG-poor distal regulatory regions as evidenced by location, DNase I hypersensitivity, presence of enhancer chromatin marks and enhancer activity in reporter assays. LMRs are occupied by DNA-binding factors and their binding is necessary and sufficient to create LMRs. A comparison of neuronal and stem-cell methylomes confirms this dependency, as cell-type-specific LMRs are occupied by cell-type-specific transcription factors. This study provides methylome references for the mouse and shows that DNA-binding factors locally influence DNA methylation, enabling the identification of active regulatory regions.

Using genomics for birth defects epidemiology: can epigenetics cut the GxE Gordian knot?

Most birth defects are etiologically complex disorders caused by combinations of genetic and environmental factors, but most studies of birth defect etiology have examined only genetic factors or only environmental factors and have not considered interactions among them. Genome-wide epigenetic studies, which use the same genomic technologies that have revolutionized our ability to identify genetic causes of disease, provide an attractive way to study gene-environment interactions. However, finding an association between epigenetic variation and an etiologically complex birth defect without knowledge of the genetic variation and environmental exposures affecting the individuals who were studied usually provides little or no information regarding the cause of the disorder. In order for genome-wide studies of epigenetic variation to contribute to our understanding of the causes of birth defects, these studies must be combined with studies of environmental exposures and studies of genetic variation in the same subjects. Under such circumstances, epigenetic studies may help to establish the molecular basis for gene-environment interactions.

Maternal-foetal epigenetic interactions in the beginning of cardiovascular damage

Several studies indicate that impaired foetal growth, and in utero exposure to risk factors, especially maternal hypercholesterolaemia, may be relevant for the early onset of cardiovascular damage. The exact molecular mechanisms of such foetal programming are still unclear. Epigenetics may represent one of the possible scientific explanations of the impact of such intrauterine risk factors for the subsequent development of cardiovascular disease (CVD) during adulthood. Translational studies support this hypothesis; however, a direct causality in humans has not been ascertained. This hypothesis could be investigated in primates and in human post-mortem foetal arteries. Importantly, some studies also suggest the transgenerational transmission of epigenetic risk. The recently launched International Human Epigenome Consortium and the NIH Roadmap Epigenomics Mapping Consortium will provide the rationale for a useful clinical scenario for primary prevention and therapy of CVD. Despite the heritable nature of epigenetic modification, the clinically relevant information shows that it could be reversible through therapeutic approaches, including histone deacetylase inhibitors, histone acetyltransferase inhibitors, and commonly used drugs such as statins.

The decade of the epigenomes?

The beginning of this century was not only marked by the publication of the first draft of the human genome but also set off a decade of intense research on epigenetic phenomena. Apart from DNA methylation, it became clear that many other factors including a wide range of histone modifications, different shades of chromatin accessibility, and a vast suite of noncoding RNAs comprise the epigenome. With the recent advances in sequencing technologies, it has now become possible to analyze many of these features in depth, allowing for the first time the establishment of complete epigenomic profiles for basically every cell type of interest. Here, we will discuss the recent advances that allow comprehensive epigenetic mapping, highlight several projects that set out to better understand the epigenome, and discuss the impact that epigenomic mapping can have on our understanding of both healthy and diseased cells.

The biological basis and clinical significance of hormonal imprinting, an epigenetic process

The biological phenomenon, hormonal imprinting, was named and defined by us (Biol Rev, 1980, 55, 47-63) 30 years ago, after many experimental works and observations. Later, similar phenomena were also named to epigenetic imprinting or metabolic imprinting. In the case of hormonal imprinting, the first encounter between a hormone and its developing target cell receptor-usually at the perinatal period-determines the normal receptor-hormone connection for life. However, in this period, molecules similar to the target hormone (members of the same hormone family, synthetic drugs, environmental pollutants, etc), which are also able to bind to the receptor, provoke faulty imprinting also with lifelong-receptorial, behavioral, etc.,-consequences. Faulty hormonal imprinting could also be provoked later in life in continuously dividing cells and in the brain. Faulty hormonal imprinting is a disturbance of gene methylation pattern, which is epigenenetically inherited to the further generations (transgenerational imprinting). The absence of the normal or the presence of false hormonal imprinting predispose to or manifested in different diseases (e.g., malignant tumors, metabolic syndrome) long after the time of imprinting or in the progenies.

Emerging patterns of epigenomic variation

Fuelled by new sequencing technologies, epigenome mapping projects are revealing epigenomic variation at all levels of biological complexity, from species to cells. Comparisons of methylation profiles among species reveal evolutionary conservation of gene body methylation patterns, pointing to the fundamental role of epigenomes in gene regulation. At the human population level, epigenomic changes provide footprints of the effects of genomic variants within the vast nonprotein-coding fraction of the genome, and comparisons of the epigenomes of parents and their offspring point to quantitative epigenomic parent-of-origin effects confounding classical Mendelian genetics. At the organismal level, comparisons of epigenomes from diverse cell types provide insights into cellular differentiation. Finally, comparisons of epigenomes from monozygotic twins help dissect genetic and environmental influences on human phenotypes and longitudinal comparisons reveal aging-associated epigenomic drift. The development of new bioinformatic frameworks for comparative epigenome analysis is putting epigenome maps within the reach of researchers across a wide spectrum of biological disciplines.