Genome3D: a viewer-model framework for integrating and visualizing multi-scale epigenomic information within a three-dimensional genome

Abstract

Background: New technologies are enabling the measurement of many types of genomic and epigenomic information at scales ranging from the atomic to nuclear. Much of this new data is increasingly structural in nature, and is often difficult to coordinate with other data sets. There is a legitimate need for integrating and visualizing these disparate data sets to reveal structural relationships not apparent when looking at these data in isolation.

Results: We have applied object-oriented technology to develop a downloadable visualization tool, Genome3D, for integrating and displaying epigenomic data within a prescribed three-dimensional physical model of the human genome. In order to integrate and visualize large volume of data, novel statistical and mathematical approaches have been developed to reduce the size of the data. To our knowledge, this is the first such tool developed that can visualize human genome in three-dimension. We describe here the major features of Genome3D and discuss our multi-scale data framework using a representative basic physical model. We then demonstrate many of the issues and benefits of multi-resolution data integration.

Conclusions: Genome3D is a software visualization tool that explores a wide range of structural genomic and epigenetic data. Data from various sources of differing scales can be integrated within a hierarchical framework that is easily adapted to new developments concerning the structure of the physical genome. In addition, our tool has a simple annotation mechanism to incorporate non-structural information. Genome3D is unique is its ability to manipulate large amounts of multi-resolution data from diverse sources to uncover complex and new structural relationships within the genome.

Figure 1

The Genome3D application. Four screen captures of Genome3D main windows showing progressive "drill-down" views of the same model of multi-resolution genomic data. All images were generated using a single instance of Genome3D and are differentiated solely by user-controlled display settings. A The lowest resolution is the nuclear scale and displays the steps of each giant loop random walk (see MM). B The 30 nm fiber scale of chromosomes corresponding to the giant loops shown in A. C At nucleosome resolution, a limited amount of DNA can be loaded and displayed. This image shows a segment of 100 K bp with approximate cylindrical NCPs and DNA strands represented as lines. D The highest resolution is the DNA scale which can resolve individual atoms. A single NCP is displayed here with bp-level annotations used to color each bp. Additionally, the image shows the atomic protein backbone structure of the NCP histones.

Figure 2

Two examples of nucleosome epigenomic variation. A Top view of 4 SNP variants rs6055249, rs7508868, rs6140378, and rs2064267 (numbered 1-4 respectively) within a non-coding histone of chromosome 20:7602872-7603018. The histone position was obtained from [18], the SNPs were taken from a recent study examining variants associated with HDL cholesterol [19]. Such images may reveal structural relationships between non-coding region SNPs and histone phasing. B Side view of A. C A series of histone trimethylations within ENCODE region ENr111 on chromosome 13:29668500-29671000 [27]. The histone bp positions are from [18]. Each histone protein is shown as an approximate cylinder wedge: H2A (yellow), H2B (red), H3 (blue), H4 (green). The CA backbones of the H3 and H4 N-terminal tails are modeled using the crystal structure of the NCP (PDB 1A0I) [28]. The bright yellow spheres indicate H3K4me3 and H3K9me3, and the orange spheres are H3K27me3, H3K36me3 and H3K79me3.

Figure 3

A sample microarray expression data set superimposed on a chromosome model. The figure integrates p53 knock-out expression data [23] and p53 binding site information within chromosome 19. It demonstrates how array data can be annotated on an existing physical model, and how large structural effects could be observed. The colored spheres show the magnitude of gene expression change when p53 is disrupted (green +/red -). Each sphere represents the transcription start site (TSS) of a gene. Cubes are placed at p53 binding sites, and are colored orange if close (< 10 kbp) to a measured gene expression TSS, yellow otherwise.