1D genome analysis. Mapping various genomic and chromatin features along chromosomes yields 1D data. The top part of the figure shows a screenshot of the Genome browser (http://genome.ucsc.edu/), presenting genome tracks for the ENCODE region Enm005. All data were generated by the ENCODE pilot project and are publicly available through the UCSC genome browser (ENCODE-consortium, 2007). Methods used to collect data are indicated on the left. Tracks indicate the presence of genes (GENCODE genes); the presence of DNase-I-hypersensitive sites (P-values are from HeLa cells; data from the ENCODE group at Duke University, led by Greg Crawford); the level of RNA (expression profiling data from HeLa cells; generated by the ENCODE group at Affymetrix, led by Tom Gingeras); the level of acetylated H3 (H3Ac; generated by ChIP-chip by the ENCODE group at the Sanger Institute, led by Ian Dunham); and levels of RNA polymerase II (Pol2) binding, and levels of acetylated H4 (H4Ac) and methylated H3 (H3K27me3) in HeLa cells as determined by ChIP-chip (data from the ENCODE group at Yale University, led by Michael Snyder). The bottom part of the figure shows an analysis of chromosomal domains, by using a combination of wavelet analysis and Hidden-Markov-Model segmentation of 1D datasets, including replication timing, DNase I hypersensitivity and histone modifications (adapted with permission from Thurman et al., 2006); see text for details.

3D genome analysis. The spatial organization of genomes can be studied using single-cell methods or using population-based methods, and at different resolutions or length scales (A-D). (A) A hypothetical pair of metaphase chromosomes. 1D compartmentalization is indicated: constitutive heterochromatin domains include the centromere (cen), pericentromeric heterochromatin (subcen het) and telomeres (tel). Chromosome arms further consist of alternating active and repressed domains (indicated by different colors). Numbers indicate (chromosomal) regions to be analysed by 3D methods in panels B, C and D. (B) Spatial organization of chromosomes shown in A in the interphase nucleus. Chromosomal regions that are located far apart on the same chromosome (2 and 3) or located on different chromosomes (1 and 2, 1 and 3) can colocalize in 3D to form spatial compartments. (C) A higher-resolution (Mb scale) analysis of cis and trans associations of chromosomal regions 1 to 3 shown in B. At this resolution, associations of groups of genes can be detected surrounding subnuclear structures such as transcription factories (green circles) and splicing bodies [characterized by the presence of the splicing factor SC35 (red)]. For example, a trans interaction between regions 1 and 2 can occur through colocalization to the same transcription factory (Osborne et al., 2004) or to two different transcription factories that are both associated with one SC35 granule (Brown et al., 2008). (D) High-resolution (Kb scale) analysis of 3D folding and long-range associations that can be studied using 3C-based methods. At this scale, specific looping interactions can be detected between genes and regulatory elements. This scheme provides an example of a 3C analysis in which the interaction probability of a single defined genomic element is mapped throughout the larger region 3 (right). Peaks in this 3C map indicate long-range interactions that suggest a looped conformation (indicated on the left). Visual representation of the chromosomes and nucleus were inspired by Fig. 4J of the article published by Solovei and colleagues (Solovei et al., 2009).

Integration of 1D and 3D genome annotations. Data collected by 1D and 3D approaches supplement and complement one another. 1D genome annotations – for example, transcription factor (TF)-binding sites, obtained by ChIP-sequencing – indicate the locations of potential regulatory elements. (Top panel) Binding profiles for two TFs (red and yellow), which show association of TF red with regulatory elements A, B and C (red bars), and association of TF yellow with regulatory element B only (yellow bars). Note that these binding profiles do not identify the target genes controlled by these elements because the target genes can be located elsewhere in the genome. (Middle panel) 3D annotations, such as looping interactions between genes and elements detected by 3C-based techniques, can help to assign regulatory elements to their target genes. Here we show an example of long-range interactions between the three regulatory elements A, B and C indicated in the top panel. Red and yellow colors indicate which transcription factor was detected on each element by ChIP-sequencing. (Bottom panel) Both 1D data and 3C-based 3D data are obtained from large cell populations (millions) and represent the sum of all interactions that occur in that population. Single-cell 3D analysis (e.g. determining colocalization of loci by microscopic methodologies) shows the real quantitative spatial relationships between genomic regions. The bottom panel shows four individual nuclei that each have differential subnuclear localization of elements A, B and C, illustrating that different combinations of long-range interactions between loci occur in different cells. By combining the information from the three panels shown in this figure – i.e. by integrating 1D and 3D studies – a more comprehensive model of the functional state of the chromatin can be obtained. In this example, one can hypothesize that TF red binds to element B (asterisk, upper panel) only indirectly, through a looping interaction with elements A and/or C (see middle panel). Further single-cell analysis of colocalization of these elements and bound transcription factors (obtained by combining DNA FISH and immunofluorescence-mediated detection of proteins) can resolve this issue. For instance, if binding of TF red to element B – as detected by ChIP – is an indirect effect, single-cell observations should reveal that TF red is only found at element B when element B colocalizes with element A or C.