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Exploring long-range genome interactions using the WashU Epigenome Browser
Open accessAbstract
To the Editor : Eukar yotic chromosomes are a highly organized three-dimensional entity folded through a tightly regulated process1,2 with important functions that include bringing distal regulatory elements into the vicinity of their target gene promoters and arranging the chromosomes into distinct compartments3–6. Recent technological innovations, including chromosome conformation capture carbon copy (5C), Hi-C and chromatin interaction analysis by paired-end tag sequencing (ChIA-PET), have facilitated the discovery of chromosomal organization principles and folding architectures at unprecedented scales and resolution. Each technology also comes with corresponding computational tools7,8 to process and visualize its specific data type (Supplementary Note 1). However, visualizing and navigating long-range interaction data, as well as integrating these interactions with other epigenomics data, remains a much-desired capability and a daunting challenge9. We have extended the WashU Epigenome Browser10 (http:// epigenomegateway.wustl.edu/), which currently hosts thousands of epigenome and transcriptome data sets for multiple cell types, tissues, individuals and species, to support multiple types of long-range genome interaction data. This enables investigators to explore epigenomic data in the context of higher-order chromosomal domains and to generate multiple types of intuitive, publication-quality figures of interactions (see tutorial in Supplementary Note 2). In Figure 1 we display the histonemodification profile and long-range interaction data of two human cell lines (IMR90 and K562) side by side and note that regions can exhibit similar interaction patterns while showing different histone modifications (such as the boundary region between domains 1 and 2) (Supplementary Methods). These observations are consistent with the hypothesis that chromatin domains are stable across cell types but can have different epigenetic profiles in different cells. Genes within each domain are regulated epigenetically in a cell type– specific manner5. Integrating higherorder chromatin interaction data with other genomic data could potentially reveal novel insights about mechanisms underlying gene and genome regulation. Pairs of interacting regions can be joined by arcs (Fig. 1b)—a suitable representation for sparse interactions—as is common with ChIA-PET and sometimes found in 5C data sets, or they can be indicated by filled rectangles in a heat map (Fig. 1c) for dense interactions (as is typical for Hi-C and some regions in 5C data sets). Investigators can click on the arcs or heat-map cells to invoke a companion Browser panel (Supplementary Fig. 1), which displays epigenomic data over the distal interacting locus. This companion panel can be navigated independently, enabling comparison of data patterns of interacting loci in the same view. Thus, investigators can observe several loci that are distant in their genomic coordinates but are inferred to be spatially close to each other in the nucleus. Both the “arc” and “heat-map” modes display only interactions that are contained within the current browsing range while omitting interactions beyond the range. To visualize the complete set of interactions, investigators can invoke the “Circlet View” (Supplementary Fig. 2), in which the chromosomal axis curls to form a circle and interactions are displayed as arcs inside the circle. Investigators can choose to display a single chromosome or to include interacting chromosomes to achieve a wholegenome perspective of the interactions. Investigators can also toggle between “thin,” “full” or “density” mode for any data track (Supplementary Figs. 3–5). “Gene Set View” and genomic juxtaposition can be combined with the long-range interaction function to focus on the interaction events in a subregion of the genome (Fig. 1). An investigator’s own long-range interaction data can be displayed on the Browser via the custom track or Data Hub function. The Browser currently hosts over 100 genomewide chromatin interaction data sets for human, mouse and fly. We expect such data to become increasingly available, and the browser will be a helpful tool for exploring how eukaryotic genomes function as nonlinear systems.
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Metadata
- Authors
- Zhou, X., Lowdon, R. F., Li, D., Lawson, H. A., Madden, P. A. F., Costello, J. F., & Wang, T.
- Venue
- Nature Methods
- Published
- 2013-04-29
- Volume
- 10
- Issue
- 5
- Pages
- 375-376
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2094160175
- Cited by
- 213
- References
- 3
- FWCI
- 7.53
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.springer.com/tdm (tdm)
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