Abstract
Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture (3C) assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single-cell Hi-C, combined with genome-wide statistical analysis and structural modelling of single-copy X chromosomes, to show that individual chromosomes maintain domain organization at the megabase scale, but show variable cell-to-cell chromosome structures at larger scales. Despite this structural stochasticity, localization of active gene domains to boundaries of chromosome territories is a hallmark of chromosomal conformation. Single-cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organization underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns.
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Acknowledgements
The authors thank I. Clay, S. Wingett, K. Tabbada, D. Bolland, S. Walker, S. Andrews, M. Spivakov, N. Cope, L. Harewood and W. Boucher for assistance. This work was supported by the Medical Research Council, the Biotechnology and Biological Sciences Research Council (to P.F.), the MODHEP project, the Israel Science Foundation (to A.T.) and the Wellcome Trust (to E.D.L.).
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Contributions
T.N. and P.F. devised the single-cell Hi-C method. T.N. performed single-cell Hi-C and DNA FISH experiments. S.S. carried out ensemble Hi-C experiments. W.D. microscopically isolated single cells. Y.L., E.Y. and A.T. processed and statistically analysed the sequence data. T.J.S. and E.D.L. developed the approach to structural modelling and analysed X-chromosome structures. T.J.S. wrote the software for three-dimensional modelling, analysis and visualisation of chromosome structures. T.N., Y.L., T.J.S., E.D.L., A.T. and P.F. contributed to writing the manuscript, with inputs from all other authors.
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Extended data figures and tables
Extended Data Figure 1 Single-cell Hi-C quality controls.
a, Efficiency of biotin labelling at Hi-C ligation junctions for two Hi-C ligation products, showing 90–95% efficiency (Supplementary Information). b, Read-pair classification. c, Discarding the missed RE2 read-pairs removes a uniform ‘blanket’ of non-specific contacts from the map. d, Estimating numbers of multiple covered fends. Shown is the dependency between the number of fend pairs in a sample and the estimated number of autosomal fends covered by more than two fend pairs under different models. The binomial model (grey line) distributes fend pairs to fends randomly without any constraint, as if sampling fend pairs from an infinite number of chromosomes. e, Single-cell Hi-C fragments coverage. Number of fends in each 250-kb genomic bin for BglII or DpnII as RE1. Tail of bins with few fends is for bins of low mappability and near the chromosomes edges. f, Median fend length (distance from RE1 to the first upstream RE2) in each 250-kb genomic bin for BglII or Dpn II as RE1. Values larger than 300 bp are of poorly mappable bins. g, Information on the two restriction enzymes we used for RE1, BglII (6 cutter, which we used predominantly) and DpnII (4 cutter, only used for cell 8). Blind fends do not have a RE2 site in their fragment. Fends in which their first RE2 site starts a non-unique 36-bp sequence are marked as non-unique fends. We discarded both blind and non-unique fends and used only the unique fends. The number of actual fends in a male mouse genome, which have two copies of each autosome and a single X chromosome are shown as well as the median fragment length (chromosome Y and mitochondrial genome were ignored throughout the analysis). h, Information on the ten single-cell data sets that successfully passed the quality control filters. P value of the number of autosomal fends with more than two covering fend-pairs was calculated from the binomial model (panel d and Supplementary Information). i, Percentages of read-pair types. j, Percentage of fend-pair types. k, Distribution of fend-pair coverage (number of read pairs that support each fend pair) in the ten single-cell data sets. l, Distribution of mean contacts per fend calculated for each mappable 1 Mb, normalized by the mean value in each cell, and averaged across autosomal or X chromosomes from the ten single cells.
Extended Data Figure 2 Chromosomal domains.
a, Ratios between intradomain and interdomain contact enrichments over genomic distance. The mean single-cell trend is shown in black. Chromosomes are grouped into four groups: group 1 (chromosomes 1, 8, 15, 16 and X), group 2 (chromosomes 2, 6, 10, 13 and 18), group 3 (chromosomes 3, 5, 11, 14 and 17) and group 4 (chromosomes 4, 7, 9, 12 and 19). The intra- over interdomain enrichment is persistent in all chromosome groups and does not seem to stem from peculiar chromosomes. b, Distribution of correlations between intradomain contact numbers of all domains from pairs of real and reshuffled controls. c, Distribution of the insulation score at each fend in nine single-cell Hi-C data sets (where RE1 is BglII; real cells) is shown in red. Fifty sets of reshuffled cells were produced (see Supplementary Methods) and their insulation score distribution is shown in black. Real cells have a heavier tail of highly insulating loci, which is indicative of non-uniform and cell-specific interdomain contact structure.
Extended Data Figure 3 Modelling protocol quality controls.
a, Results of structure calculations using restraints from a space-filling Hilbert curve test structure with 4,096 particles and four typical results of structure modelling using different numbers of restraints are shown (upper panels). Structure calculations of the Hilbert curve from random positions using different sets of 1,024 restraints (lower panel). b, Comparison of r.m.s.d. values from Hilbert curve and single-cell X-chromosome models. Structure calculations for Hilbert curves were repeated 100 times with variable numbers of restraints as shown. The root mean square deviation (r.m.s.d.) values between 100 models (precision) using the indicated number of restrains (mean ± s.d.) are plotted in blue. The r.m.s.d. values between the original Hilbert curve and each of the 100 models (accuracy) for the same numbers of restraints are plotted in green (mean ± s.d.). r.m.s.d. values from 100 repeated calculations of fine-scale (50-kb backbone) X-chromosome structure from the seven single-cell data sets are also plotted (red; mean ± s.d.). c, Restraint violation analysis. The distances between directly restrained positions in fine-scale (50-kb backbone) X-chromosome models are shown. Models for the six single-cell data sets (cell 1 to cell 6; red) show no values exceeding the upper bound (dashed line). Calculations with six shuffled interaction maps (created from cell 1 data set; blue) show significant violations. Structure calculations performed on merged pairs of data sets (yellow; all possible combinations of cell 1 to cell 4) have a few violations and are significantly closer to the upper limit. d, Comparison of structure-derived distance matrix from 200 fine-scale X-chromosome models from cell 1 (orange) and its single-cell Hi-C contacts (black crosses). The orange colour indicates the minimum distance between backbone particles. e, Comparison of X-chromosome structural models for six cells computed using low-resolution (500-kb binned) single-cell Hi-C interaction data. The bundles shown represent minimised structural alignments of five models from repeat calculations for each cell. Colours indicate chromosomal positions as shown. Scale bar, 1 µm.
Extended Data Figure 4 Comparison and investigation of models.
a, Pair-wise comparison of fine-scale X chromosome structural models by r.m.s.d. analysis. Each pixel represents an r.m.s.d. value for a pair-wise comparison of two models. Lighter pixels indicate structures of higher similarity (low r.m.s.d.). Diagonal elements have been excluded. The order of 200 models in each panel was determined by hierarchical clustering of the r.m.s.d. values. Numbers shown are the mean r.m.s.d. values and the standard deviations for all the comparisons for each cell calculated by comparing the Hi-C contact particles. b, Cell-to-cell comparison of 200 fine-scale X chromosome structural models by r.m.s.d. analysis. Each pixel represents an r.m.s.d. value for a pair-wise comparison of two models. c, Fine-scale X-chromosome structures calculated from cell 1 and cell 3 data sets, and a structure from the combined data set. Colours indicate chromosomal positions as shown. Scale bar, 1 µm. d, Typical structure calculated using a randomized data set, where the interacting points for cell 1 have been shuffled with a pairing probability proportional to one over the square root of the sequence separation. Colours and scale as shown in c. e, Distribution of measurements of depth from the surface for five loci P1–P5 (Fig. 3e) in 1,200 X-chromosome models (200 fine-scale models for each of the six cells). Whiskers on box plots define 10th and 90th percentiles and the outliers are shown as individual dots.
Extended Data Figure 5 Epigenomic landscape of chromosomes.
a, Intradomain contact enrichment for each quartile of trans-chromosomal contacting domains. b, Same as a but subtracting the mean quartile enrichment in each genomic distance emphasizing the differences shown in a. c, Using the same sets as in a but plotting the enrichment of interdomain contacts within the same chromosome. d, Same as c but subtracting the mean quartile enrichment in each genomic distance. e, Percentage of cells in which high and low H3K4me3 enriched domains are trans-interacting. For each cell the domains with top 10th percentile trans intensity were defined as trans-interacting in that cell. We then counted for each domain the fraction of cells in which that domain was trans-interacting. Shown are the distributions of these fractions for H3K4me3 enriched and non-enriched domains (the top and bottom 25th percentiles, respectively). f, Distribution of the average lamin B1 (ref. 26) enrichment in chromosomal domains, colour coded according to the enrichment value. g, Domains plotted according to their number of trans- and cis-chromosomal (but excluding intradomain) contacts, colour-coded as in f. The domain lamin B1 enrichment and H3K4me3 peak density are highly anti-correlated (Spearman's correlation = −0.73). h, Intradomain contact enrichment for high versus low quartile of domains stratified by their mean lamin B1 enrichment. Error bars indicate 95% confidence intervals. i, Using the same sets as in h but plotting the enrichment of interdomain contacts within the same chromosome. Error bars as in h. j, Lamin B1 domains show a minor decrease in intradomain contact intensities that might suggest less compacted domains, and significantly increased cis-interdomain contact, maybe owing to lack of trans-chromosomal contacts. Topology of lamin B1, H3K4me3 and trans-contacts on five-model bundles of low-resolution X-chromosome models. Regions of low mappability have been excluded. Scale bar, 1 µm.
Extended Data Figure 6 Interchromosomal contacts.
a, Comparison of observed coverage of the trans-chromosomal 1-Mb square bins of each cell (red lines), versus predicted coverage assuming a binomial model (random uniform distribution of contacts to bins; black dashed line). Observed coverage is consistently higher than the uniform model, indicating the highly non-random distribution of trans-chromosomal contacts to genomic bins. b, Trans-chromosomal contact enrichment around observed trans-contacts as a function of the contacts total distance on both chromosomes (Manhattan distance in the contact map). Observed and expected (by random uniform contact distribution) numbers of contacts are counted around each trans-contact, and their ratio is shown for the 9 real cells (blue; where RE1 is BglII) and reshuffled cells (red), at two different scales. c, Left panel, trans-contacts were classified according to H3K4me3 density of the domains they associate: High and low for top and bottom 25th percentiles, respectively, mid for 25th–75th percentiles. Shown is the log ratio of the contingency table counts with the expected counts generated by multiplying the corresponding marginal probabilities for each group (chi-squared test; P = 5.8 × 10−18). To make sure these phenomena are not caused by the trans enrichment of active domains and depletion of non-active ones, only the top 15th percentile trans enriched domains from each cell were used. Middle panel, similar to left panel but contacts are classified by their associated domain gene density (chi-squared test; P = 2.3 × 10−12). Right panel, similar to left panel but using domains in the top 40th percentile of gene density, classifying by their H3K4me3 density, to test H3K4me3 enrichment beyond gene density (chi-squared test; P = 3.6 × 10−06). In all cases active or gene-rich domains preferentially interact with each other, although active domains (high H3K4me3 density) show greater interaction than expected from their gene density.
Extended Data Figure 7 Chromosomal interfaces.
a, The number of interacting chromosomes per chromosome is depicted in circles sized according to the number of single cells the value was observed in, and the order of chromosomes is shown by the number of transcription start sites (TSSs) in each chromosome (blue bars). Only autosomes are displayed. Spearman correlation between the number of TSSs and the mean value of the number of interacting chromosomes per chromosome is 0.18. Two chromosomes were defined as interacting when they had at least one domain–domain interaction (see main text) supported by two or more contacts. The number of interacting chromosomes per chromosome rises together with the number of TSSs. However, the change is small, and the number of interacting autosomal chromosomes per chromosome (the plotted value divided by two) remains between 4 and 6. b, Same as a except that chromosomes ordered by the number of active H3K4me3 domains (the top 25th percentile H3K4me3 peak density domains). c, Same as a except that chromosomes are ordered by the number of non-lamin-associated domains (non-LAD) base pairs in the chromosome. The fraction of a chromosome covered by LADs ranges from 31% to 53% and is correlated with chromosome size (0.52 Spearman). Thus, chromosome lengths span a range of 3.2-fold change, while their non-LAD fraction spans a smaller range of 2.8-fold change. d, Examination of the number of contacts between two chromosomes and the chromosomes sizes. The mean number of contacts of each chromosome with others it interacts with is shown for the ten single cells, with chromosomes ordered by their size. Chromosome size is correlated with the number of contacts it has, but the dynamic range of this number is small. e, The number of interacting chromosomes per chromosome is depicted in circles sized as the number of single cells the value was observed in, and the ten single-cell data sets are ordered by the number of trans-contacts in each data set, shown by blue bars. Only autosomes are displayed. Spearman correlations between the number of trans-contacts in each data set and the mean value of the number of interacting chromosomes per chromosome is 0.73. The number of interacting chromosomes per chromosome rises together with the coverage. However, the change is small, and the number of interacting autosomal chromosomes per chromosome (the plotted value divided by two) remains between 4 and 6. f, Example of multi-way chromosomal interfaces. Contact map of chromosomes 3 and 15 in cell 5. Shown is the number of contacts in 1-Mb size bins. Top and bottom 30th percentiles of H3K4me3 peak density domains are marked in light pink and light grey, respectively. Note the grid-like trans-contacts arrangement, and the correspondence between the two large trans-contact clusters and the organization of cis-contacts in both chromosomes to large ‘mega domains’.
Supplementary information
Supplementary Information
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Supplementary Data
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Bundle of five low-resolution X chromosome models with epigenomic features coloured as indicated for cell-1
Bundle of five low-resolution X chromosome models with epigenomic features coloured as indicated for cell-1. (MOV 6422 kb)
Bundle of five low-resolution X chromosome models with epigenomic features coloured as indicated for cell-2
Bundle of five low-resolution X chromosome models with epigenomic features coloured as indicated for cell-2. (MOV 9144 kb)
Surface rendered fine-scale X chromosome models with genomic and epigenomic features coloured as indicated for cell-1
Surface rendered fine-scale X chromosome models with genomic and epigenomic features coloured as indicated for cell-1. (MOV 18241 kb)
Surface rendered fine-scale X chromosome models with genomic and epigenomic features coloured as indicated for cell-2
Surface rendered fine-scale X chromosome models with genomic and epigenomic features coloured as indicated for cell-2. (MOV 18242 kb)
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Nagano, T., Lubling, Y., Stevens, T. et al. Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. Nature 502, 59–64 (2013). https://doi.org/10.1038/nature12593
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DOI: https://doi.org/10.1038/nature12593
