If a variant lies within a gene and changes a protein sequence, it can be relatively straightforward to formulate testable hypotheses about its effects. But most of the variants that are significantly associated with T2D—and with complex diseases in general—lie within noncoding regions of the genome and are likely to affect regulation of genes that could be far removed from the chromosomal position of the variant. It can be difficult to find clues about which genes are affected by these distant, noncoding changes, but now, we present a new type of data in the T2DKP that can help address this challenge.
The pattern of epigenetic modifications within a genomic region can provide important clues about its regulatory role. The distribution of these position-specific and tissue-specific marks—for example, covalent modifications of the histone proteins that package DNA—is characteristic of elements such as enhancers or transcription start sites. The Roadmap Epigenomics Consortium has developed methods for detecting these modifications genome-wide (hence the term “epigenomics”) and integrating their positional data, using the ChromHMM algorithm, to categorize genomic regions into “chromatin states”. The presence of these states in a given genomic region in different tissue types can give hints about whether that region might be involved in regulation of specific genes or pathways.
Now, you can view the tissue-specific chromatin states spanning the position of each variant on Variant pages within the Portal. We have incorporated epigenomic data from a study (Varshney et al., 2017) in which the locations of 13 distinct chromatin states were determined across a diverse set of cell lines and tissues, including pancreatic islets. The new “Epigenomic annotations” section of each Variant page (see an example) presents information about chromatin states in three different ways.
1. An interactive table listing chromatin states in this region, the tissue or cell line in which they were observed, and their genomic coordinates. Filter the table by chromatin state or by tissue to find states of particular interest.
2. A matrix displaying chromatin states by tissue type. This graphic gives a quick indication of chromatin states that are present in this region, across the whole panel of tissues.
3. A graphic showing the positions of chromatin states relative to the position of the variant.
These new features represent only the first phase of incorporating this new data type into the Portal. In the future, we will be adding more of these data along with more versatile interfaces for exploring them. Please check out our new epigenomic annotations and send us your feedback!