The promoters of mammalian genes are commonly regulated by multiple distal enhancers, which physically interact within discrete chromatin domains. How such domains form and how the regulatory elements within them interact in single cells is not understood. To address this we developed Tri-C, a new chromosome conformation capture (3C) approach, to characterize concurrent chromatin interactions at individual alleles. Analysis by Tri-C identifies heterogeneous patterns of single-allele interactions between CTCF boundary elements, indicating that the formation of chromatin domains likely results from a dynamic process. Within these domains, we observe specific higher-order structures that involve simultaneous interactions between multiple enhancers and promoters. Such regulatory hubs provide a structural basis for understanding how multiple cis-regulatory elements act together to establish robust regulation of gene expression.
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All sequencing data have been submitted to the Gene Expression Omnibus under accession number GSE107940.
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This work was supported by the Wellcome Trust (Wellcome Trust Genomic Medicine and Statistics PhD Programme, reference 105281/Z/14/Z, A.M.O.; Wellcome Trust Strategic Award, reference 106130/Z/14/Z, D.R.H. and J.R.H.), the Medical Research Council (MRC Core Funding and Project Grant, reference MR/N00969X/1, V.J.B. and J.R.H.; MRC Clinician Scientist Fellowship, reference MR/R008108, J.O.J.D.) and the National Institutes of Health (reference R01 HG003143, J.D.). J.D. is an investigator of the Howard Hughes Medical Institute. We thank D. Hay and M. Kassouf for advice and R. Gibbons and H. Ayyub for help with Oxford Nanopore MinION sequencing.
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Integrated supplementary information
Supplementary Figure 1 Organization of the extended globin loci into self-interacting domains is tissue specific.
a,b, Hi-C contact matrices (40-kb resolution) of the α-globin (a) and β-globin (b) locus in erythroid (top) and ES (bottom) cells. Matrices represent normalized interaction counts. Topologically associating domains (TADs), insulation indices, and gene annotation (active genes in black, inactive genes in gray, globin genes highlighted in red) are shown in the middle, and the TADs containing the active globin loci are highlighted in dashed gray boxes. Note that the Hi-C data in the extended β-globin locus in ES cells are rather sparse owing to suboptimal alignment of this region in ES cells (Cast/129 strain) to the reference genome. Coordinates (mm9): chr11:29,900,000–33,200,000 (α-globin) and chr7:109,300,000–112,600,000 (β-globin).
Supplementary Figure 2 Characterization of the interaction landscape of the regulatory elements of the β-globin locus.
High-resolution Capture-C interaction profiles of the β-globin locus from the viewpoints (indicated by blue arrows) of the β-globin promoters, the HS2 enhancer, and CTCF-binding sites 3′HS1 and HS-60 in erythroid (red) and ES (gray) cells. Profiles represent the mean number of normalized unique interactions per restriction fragment in three replicates. Statistically significant differential interactions (derived using DESeq2) between erythroid and ES cells are highlighted in bold colors. Gene annotation (β-globin genes highlighted in red), erythroid DNase I hypersensitivity (DHS) and CTCF occupancy are shown at the top, with the orientation of the CTCF-binding motifs indicated by arrowheads (forward orientation in red; reverse orientation in blue). Coordinates (mm9): chr7:110,912,000–111,112,000.
Contact matrices (4-kb resolution) of the β-globin locus derived from Capture-C experiments with viewpoints closely spaced across the domain in erythroid (top) and ES (bottom) cells. Matrices represent the mean number of normalized unique interactions in three replicates. Gene annotation (β-globin genes highlighted in red), erythroid DNase I hypersensitivity (DHS) and CTCF occupancy are shown in the middle. Coordinates (mm9): chr7:110,840,000–111,140,000.
Supplementary Figure 4 Fragment size distributions of restriction enzymes commonly used in 3C experiments.
a–d, Histograms showing the fragment size distributions of NlaIII in the mouse mm9 reference genome (a), DpnII in the mouse mm9 reference genome (b), NlaIII in the human hg18 reference genome (c) and DpnII in the human hg18 reference genome (d). Fragments with suitable (dark green) and optimal (bright green) sizes for Tri-C viewpoints are highlighted and the median fragment sizes are indicated (red). As different (restriction) enzymes can be used to fragment chromatin, Tri-C allows for the analysis of a very wide range of viewpoint fragments in the genome. Note that the distribution of restriction fragment sizes is very similar between mouse and human, but remarkably different between the two restriction enzymes, which both have a 4-bp recognition sequence (NlaIII, CATG; DpnII, GATC).
Comparison of the Capture-C interaction profile (purple) from the viewpoint of the R2 enhancer in the α-globin locus to pairwise interactions derived from Tri-C data. The first Tri-C profile (maroon) shows pairwise interactions derived from all unique Tri-C reads; the tracks below compare pairwise interactions detected in unique Tri-C reads in which two (red), three (orange) or multiple (yellow) interacting fragments were detected. The interaction profiles are very similar, demonstrating that detection of multiple ligation events simultaneously does not skew the data. The subtle differences between the Capture-C and Tri-C profiles are likely related to the use of different restriction enzymes during 3C library preparation (DpnII in Capture-C; NlaIII in Tri-C). Gene annotation (α-globin genes highlighted in red) and erythroid DNase I hypersensitivity (DHS) are shown at the top. Coordinates (mm9): chr11:32,000,000–32,300,000.
a, C-Trap is a novel 3C approach, which can analyze multi-way interactions occurring simultaneously with an interaction between two fragments of interest. It uses long-range PCR amplification with primers targeting these two fragments to enrich for ligation products in the 3C library that contain the interaction of interest and ‘trap’ the intervening fragments that were interacting simultaneously. After size selection to deplete PCR products <700 bp, the Nanopore MinION long-read sequencing platform is used to identify all trapped fragments. b, Overview of the number of trapped fragments per read detected in a C-Trap experiment in which the interaction between the R2 enhancer and the α-globin promoters was targeted in erythroid cells (two replicates). Read numbers represent reads in which both primer sequences could be detected at the ends. These numbers are much lower than for a Tri-C experiment (MEP_L_fig3Fig. 3b), owing to the relatively low output and read quality of the Nanopore MinION sequencing platform. The sensitivity of C-Trap is therefore ~100-fold lower than for Tri-C. Although C-Trap has the advantage of being capable of identifying many simultaneously interacting fragments in ligation products, the majority of the reads contain only a few trapped fragments. This could reflect the strength of the interaction between the R2 enhancer and the α-globin promoters, which are therefore often in close proximity in 3C ligation products, with few intervening fragments. It might also be related to a PCR amplification skew towards preferential enrichment of shorter fragments and lower quality of longer Nanopore reads. c, Comparison of multi-way interaction profiles generated from C-Trap reads containing interacting fragments with the R2 enhancer and the α-globin promoters, and from Tri-C reads containing both the R2 viewpoint and the α-globin promoters, in primary erythroid cells. The profiles look very similar: interactions are confined to the strongly compartmentalized domain and enriched over the enhancers. This confirms the validity of the multi-way interactions detected by Tri-C. Gene annotation (α-globin genes highlighted in red) and erythroid DNase I hypersensitivity (DHS) are shown at the top. The location of the C-Trap primers is indicated by green arrows. Coordinates (mm9): chr11:32,095,000–32,245,000.
We have previously shown that 3C concatemers comprise ligated restriction fragments derived from individual alleles. By performing Capture-C experiments in F1 hybrid crosses between C57BL/6 and CBA/J mice from viewpoint restriction fragments containing heterozygous SNPs, we demonstrated that >95% of SNPs in the fragments interacting with these viewpoints were in phase41. To confirm that multi-way interactions identified by Tri-C are also allele specific, we analyzed the distribution of SNPs in the β-globin locus in ES cells. a, E14 ES cells are heterozygous for SNPs rs37451653 (C/T) and rs46598598 (G/C), which are located downstream of the β-globin genes. The minor variant of rs37451653 creates a new NlaIII cut site (CACG/CATG). Gene annotation (β-globin genes highlighted in red), erythroid DNase I hypersensitivity (DHS) and CTCF occupancy are shown at the top. Coordinates (mm9): chr7:110,713,500–111,213,500. b, The small NlaIII fragment created by the minor rs37451653 variant (T) is predominantly captured with the minor rs46598598 variant (C) in unique reads containing both SNPs in two independent ES replicates.
a, Comparison of Tri-C contact matrices showing multi-way interactions with R2 in three replicates of erythroid (right top half) and ES (left bottom half) cells. Matrices represent normalized, unique interaction counts, displayed at 500-bp resolution, with proximity contacts around the R2 viewpoint excluded (gray diagonal) and are annotated with erythroid DNase I hypersensitivity. Coordinates (mm9): chr11:32,040,000–32,240,000. b, Correlations of multi-way interaction frequencies detected from the R2 viewpoint between individual erythroid (left) and ES (right) replicates. c, Correlation matrices showing Pearson correlation coefficients (r) of multi-way interaction counts detected from the R2 viewpoint between three replicates of erythroid (left) and ES (right) cells.
Supplementary Figure 9 Analysis of multi-way interactions between enhancers and promoters in the β-globin locus.
Tri-C matrices represent the mean number of normalized, unique interaction counts in ten erythroid or seven ES replicates, displayed at 500-bp resolution, with proximity contacts around the HS2 viewpoint excluded (gray diagonal). Matrices are annotated with gene positions (β-globin genes highlighted in red), erythroid DNase I hypersensitivity (DHS) and/or CTCF occupancy. Coordinates (mm9): chr7:110,930,000–111,070,000. a, Contact matrix showing multi-way interactions with HS2 in erythroid cells. b, Contact matrix showing multi-way interactions with HS2 in ES cells. c, Contact matrix showing differential multi-way interactions with HS2 that are enriched in erythroid (red) or ES (blue) cells. Statistically significant enriched interactions in erythroid cells (derived using DESeq2) are highlighted in black (P < 0.001) and grey (P < 0.01) circles. d, Venn diagram illustrating the proportion of HS2–HS1–Hbb triplets relative to all triplets containing pairwise HS2–HS1 and HS2–Hbb interactions in erythroid and ES cells. Numbers represent normalized counts of unique reads containing the specified three-way or pairwise interactions. e, Comparison of the absolute numbers of HS2–HS1–Hbb triplets (shown on the y axis) and the proportion of these relative to all triplets containing pairwise HS2–HS1 and HS2–Hbb interactions (represented as percentages in the bar graphs) in erythroid and ES cells. Bar graphs represent average normalized unique read counts in ten erythroid and seven ES replicates, with individual data points overlaid as dot plots. Both absolute and relative HS2–HS1–Hbb triplet counts are significantly enriched in erythroid cells (~20-fold, P = 7.24 × 10–7 and ~10-fold, P = 5.18 × 10–7, respectively; statistics derived using unpaired, two-tailed t tests). f, Contact matrix (4-kb resolution) showing enrichment of multi-way interactions with HS2 in erythroid cells over pairwise contact frequencies derived from multiplexed Capture-C data in three replicates. Statistically significant enriched multi-way interactions (derived using unpaired, two-tailed t tests, corrected for multiple comparisons) are highlighted. g, Comparison of a double-anchored interaction profile containing fragments interacting with both the HS2 and HS1 enhancers (red) to the conventional HS2 interaction profile (gray) in erythroid cells. Enrichment of multi-way HS2–HS1 interactions over pairwise HS2 interactions is shown in the differential profile at the bottom (black), with the HS2–HS1–Hbb interactions highlighted (magenta). Profiles represent windowed, normalized, unique interaction counts in ten replicates. Statistically significant enriched multi-way interactions with cis-regulatory elements of β-globin (derived using DESeq2) are indicated.
Supplementary Figure 10 Analysis of multi-way interactions between CTCF-binding sites in the β-globin locus.
Tri-C matrices represent the mean number of normalized, unique interaction counts in ten erythroid or seven ES replicates, displayed at 500-bp resolution, with proximity contacts around the 3′HS1 viewpoint excluded (gray diagonal). Matrices are annotated with gene positions (β-globin genes highlighted in red), erythroid DNase I hypersensitivity (DHS) and CTCF occupancy, with the orientation of the CTCF-binding motifs indicated by arrowheads (forward orientation in red; reverse orientation in blue). Coordinates (mm9): chr7:110,870,000–111,070,000. a, Contact matrix showing multi-way interactions with 3′HS1 in erythroid cells. b, Contact matrix showing multi-way interactions with 3′HS1 in ES cells. c, Contact matrix showing differential multi-way interactions with 3′HS1 that are enriched in erythroid (red) or ES (blue) cells. Although the diffuse interactions with the region spanning the other side of the β-globin domain are enriched in erythroid cells (highlighted), there are no significant enrichments of specific interactions between multiple CTCF-binding sites (P > 0.5; statistics derived using DESeq2).
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Oudelaar, A.M., Davies, J.O.J., Hanssen, L.L.P. et al. Single-allele chromatin interactions identify regulatory hubs in dynamic compartmentalized domains. Nat Genet 50, 1744–1751 (2018). https://doi.org/10.1038/s41588-018-0253-2
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