Abstract

Types of data available: cell types & epigenetic features

The Reference Epigenome Mapping Consortium is focused on developing reference epigenomic maps for a variety of human primary cells and tissues. As is true with any epigenetic study, a number of considerations are involved when selecting samples for mapping. Each of the specific cell types that make up a tissue probably have different epigenomic profiles. However, it can often be nearly impossible to isolate enough material of a particular purified cell type for analysis. The consortium has made an effort to achieve balance by covering a wide range of disease-relevant tissues, while including more highly purified cell types when possible. Currently, a wide range of adult and fetal cells and tissues are represented, including cells from a number of distinct brain regions and a variety of purified blood cell types. In addition, several pluripotent cell lines are included, such as induced pluripotent stem cells, human embryonic stem cells, as well as some differentiated forms of these cells. Currently, over 120 unique human primary cells, tissues and pluripotent cells are represented in the database (Table 1).

Specific epigenetic modifications can often be associated with a particular function; for example, H3K9me3 is generally found in repressed regions of the genome, while H3K9ac is generally correlated with gene activation. However, simply determining the distribution of one mark is not sufficient, as the function of a given mark may vary depending upon the broader chromatin context in which it resides. Furthermore, these marks must be correlated with a functional outcome, such as altered gene expression. A key strength of this data resource is the fact that for each cell and tissue type represented, multiple features will be ultimately be mapped, including DNA methylation, post-translational histone modifications, chromatin accessibility and RNA. DNA methylation data will be made available for all cell and tissue types represented. Detailed protocols and standards for each of these analyses have been made available to the community online [102].

The consortium employs several methods for the analysis of DNA methylation, each of which have strengths and limitations (several of these were described in some detail by Bock and colleagues [2]). These include reduced representation bisulfite sequencing [3] and a combination of complementary MeDIP-seq/MRE-seq assays [4]. More recently, the consortium has moved towards using MethylC-seq [5] wherever possible, which offers full coverage DNA methyl ation maps at base pair resolution. As methods for high-throughput analysis of 5-hydroxymethylcytosine are being developed, this feature may also be added to a subset of cell types in the future. Two approaches are used for the analysis of histone modifications by chromatin immunoprecipitation with sequencing. A small number of high-value samples, including several embryonic stem cell lines and their differentiated forms, will be analyzed to significant depth, with a large panel of histone modifications. Currently, there are approximately 30 distinct modifications represented in this panel, with additional modifications added as suitable antibodies are identified. The data gained from these more comprehensive analyses are used to inform the selection of a more limited panel of histone modifications, which is applied to the majority of samples being analyzed. Currently, this panel includes H3K27me3, H3K36me3, H3K4me1, H3K4me3, H3K9me3 and H3K27ac. These are the modifications found to be the most informative, namely the ones that are most difficult to predict based on other modifications [Ernst J, Kellis M, Pers. Comm.]. In addition to DNA methylation and histone modifications, most samples will undergo DNase I hypersensitivity mapping [6], to provide a measure of chromatin accessibility. Finally, each sample will be analyzed for RNA content. In many cases, this will be accomplished with expression arrays, but the consortium is moving towards using RNA-sequencing (RNA-seq) [7] when possible. RNA-seq offers the most comprehensive view of RNA expression. It includes small RNAs, provides a measurement of alternative splicing events and enables allelic analyses to be carried out. The most current standards in use for chromatin immunoprecipitation with sequencing, whole-genome bisulfite sequencing, and RNA-seq can be found at the Consortium homepage, under `Protocols and Data Standards' [102].

Navigating the data

In order to maximize community accessibility to the data and resources developed by the program, we have developed several websites for viewing and downloading data and other information, each with unique features. These are summarized in Table 1 and described below.

Reference Epigenome Mapping Consortium homepage

The centerpiece of the program is the Reference Epigenome Mapping Consortium homepage [103], a centralized landing page which houses consortium data, as well as a variety of additional information, including detailed experimental protocols and information about data quality metrics, downloadable tools for processing and analyzing sequencing data, as well as links to other websites associated with consortium data (Figure 1). A list of all consortium publications can also be found here. Tabs located at the top of the page facilitate navigation of the site. This site is continually evolving in an effort to maximize the user experience and facilitate use of the resource by the community.

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Figure 1

The NIH Roadmap Epigenomic Mapping Consortium homepage

Users interested in browsing data, protocols and other program resources should start here, at the consortium homepage. This site also links to additional program websites, which each offer unique features for data viewing or analysis [103].

This site also features an easy-to-use interface to browse consortium data. Clicking on the `Data' tab will open a matrix-style data browser. Cell and tissue types are grouped into anatomic categories for easy navigation. Available data types are indicated as shaded squares. Clicking on any of these squares will open a track selection window on a consortium-hosted University of California-Santa Cruz (UCSC; CA, USA) Genome Browser Mirror site [104] where the user can select specific data tracks to be viewed for that cell type. Once tracks of interest are selected, the user must change the `maximum display mode' to full, using the drop down menu, and click `submit'. Users can also choose to view all available data for a particular epigenetic feature across all cell types by using the drop down menu found at the top of the matrix browser (`select assay to view cell/tissue data'). This site also offers a unique visual data browser, which displays cell types with available data in an anatomical context.

The consortium's goal is to provide a complete data set for each cell type analyzed. As described earlier, this data set – referred to as a `complete epigenome' – would contain DNA methylation data, RNA expression data, a panel of histone modifications and DNase I hypersensitivity profiles where possible. Definitions of the various classes of complete epigenomes used by the consortium can be found on this site by clicking the `Complete Epigenomes' tab at the top of the page. This page will also be updated with a list of all cell/tissue types that have reached completed status.

Future perspective

The NIH Roadmap Epigenomic Mapping Consortium has made great strides in developing reasonably comprehensive epigenomic maps for a variety of normal human cell and tissue type [112]. The next challenge is to refine these maps even further. Each of our organs are made up of many distinct, specialized cell types. For some cell types, such as hematopoetic cells, one can obtain a highly purified cell type in sufficient quantities to allow for genome-wide epigenetic analyses, but for most cell types this remains a significant technical challenge. The consortium has made an effort to strike a balance between highly purified cell types and more hetero geneous tissues in selecting samples to be mapped, but as technologies continue to rapidly improve, so will the ability to define the epigenomes of these unique cell types.

As the NIH Roadmap Epigenomics Program nears completion in 2013, the data available to the community continues to grow. The next step will be in applying these data to understanding human disease. How are these normal epigenetic programs disrupted in disease, and if changes are observed, are they a cause or a consequence of disease? In a separate initiative, the NIH Roadmap Epigenomics Program has also funded a number of investigators tackling this question, who are seeking to clarify the role of epigenetics in the pathogenesis of a variety of complex human diseases, including Alzheimer's disease, glaucoma, atherosclerosis, bipolar disorder, asthma and autism [113]. As these and other similar studies begin to bear fruit, we will begin to be able to answer this question.

An additional challenge is, how we can leverage the data in this resource to understand the role of genetic variants in disease? Some intriguing data arising from the ENCODE program suggest how genome-wide information about chromatin state may be used to identify functional genomic elements linked to hits arising from GWAS [13]. One of the major challenges that has arisen in these studies is that SNPs strongly associated with the disease of interest are often found in regions of the genome with no obvious functional significance. Ernst and Kellis used a novel bioinformatics method to identify six general classes of chromatin states; specific combinations of epigenetic modi fications associated with a functional state, such as promoter, enhancer, insulator, transcribed, repressed and inactive [14]. They found that in a number of existing GWAS data sets, disease-associated SNPs fell into regions identified as cell-type-specific enhancers in a biologically relevant cell type. Going forward, the reference epigenomic maps developed by the Roadmap Epigenomic Mapping Consortium, which cover a far broader range of human primary cells and tissues than currently represented in ENCODE, will be incredibly valuable for investigators trying to understand how specific genetic variants contribute to disease.

Finally, once we have determined what constitutes a `normal' epigenome, we can begin to investigate how epigenetic profiles change in response to the environment. As the agouti viable yellow (A^vy) mouse has demonstrated so strikingly [15–17], the epigenome is exquisitely sensitive to external factors, such as diet or environmental chemicals. The reference epigenomes developed by the consortium will form a foundation for future studies aimed at understanding how the epigenome is perturbed, to identify biomarkers of exposure, and ultimately moving towards the development of intervention strategies to minimize the health impact in exposed populations.

Acknowledgements

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