Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. This study introduces a method to analyze chromosome structure at the single-cell level, showing that individual chromosomes maintain domain organization at the megabase scale but exhibit variable structures at larger scales. Despite this variability, active gene domains are consistently localized at the boundaries of chromosome territories. Single-cell Hi-C bridges the gap between genomics and microscopy, demonstrating how modular organization underlies dynamic chromosome structure and how this structure is probabilistically linked with genome activity patterns. Chromosome conformation capture methods, including Hi-C, have enabled the detection of chromosome organization in the 3D space of the nucleus. These methods assess millions of cells and are increasingly used to calculate conformations of genomic regions. However, fluorescence in situ hybridization analyses show that genetically and phenotypically identical cells have non-random, but highly variable genome and chromosome conformations, likely due to the dynamic and stochastic nature of chromosomal structures. Therefore, while 3C-based analyses can estimate an average conformation, it cannot be assumed to represent a simple and recurrent chromosomal structure. To move from probabilistic chromosome conformations averaged from millions of cells towards determination of chromosome and genome structure in individual cells, the authors developed single-cell Hi-C, which can detect thousands of simultaneous chromatin contacts in a single cell. They used male, mouse, spleenic CD4+ T cells differentiated into T helper (Th1) cells to produce a population of cells (over 95% CD4+), of which 69% have 2n genome content. Chromatin cross-linking, restriction enzyme digestion, biotin fill-in, and ligation were performed in nuclei. The captured ligation junctions were then digested with a second restriction enzyme and ligated to customized Illumina adapters. Single-cell Hi-C libraries were then PCR amplified, size selected, and characterized by multiplexed, paired-end sequencing. The authors used the same population of CD4+ Th1 cells to generate an ensemble Hi-C library. Sequencing and analysis of 190 million read pairs produced a contact map representing the mean contact enrichments within approximately 10 million nuclei. The probability of observing a contact between two chromosomal elements decays with linear distance following a power law regime for distances larger than 100 kb. They found similar regimes for the ensemble, individual cells, and a pool of 60 single cells. Moreover, after normalizing the matrices given this canonical trend, comparison of intra-chromosomal interaction intensities for the pool and ensemble, by global correlation analysis of contact enrichment values at 1 Mb resolution generates a highly significant correspondence. The authors used the ensemble domains to ask whether the same domain structure can be observed at the single-cell level. Visual inspection of the domain structure overlaid on individual intra-chromosomal contact maps and global statistical analysis of the ratios between intra- and inter-domain contact intensities in individual cells both supportedSingle-cell Hi-C reveals cell-to-cell variability in chromosome structure. This study introduces a method to analyze chromosome structure at the single-cell level, showing that individual chromosomes maintain domain organization at the megabase scale but exhibit variable structures at larger scales. Despite this variability, active gene domains are consistently localized at the boundaries of chromosome territories. Single-cell Hi-C bridges the gap between genomics and microscopy, demonstrating how modular organization underlies dynamic chromosome structure and how this structure is probabilistically linked with genome activity patterns. Chromosome conformation capture methods, including Hi-C, have enabled the detection of chromosome organization in the 3D space of the nucleus. These methods assess millions of cells and are increasingly used to calculate conformations of genomic regions. However, fluorescence in situ hybridization analyses show that genetically and phenotypically identical cells have non-random, but highly variable genome and chromosome conformations, likely due to the dynamic and stochastic nature of chromosomal structures. Therefore, while 3C-based analyses can estimate an average conformation, it cannot be assumed to represent a simple and recurrent chromosomal structure. To move from probabilistic chromosome conformations averaged from millions of cells towards determination of chromosome and genome structure in individual cells, the authors developed single-cell Hi-C, which can detect thousands of simultaneous chromatin contacts in a single cell. They used male, mouse, spleenic CD4+ T cells differentiated into T helper (Th1) cells to produce a population of cells (over 95% CD4+), of which 69% have 2n genome content. Chromatin cross-linking, restriction enzyme digestion, biotin fill-in, and ligation were performed in nuclei. The captured ligation junctions were then digested with a second restriction enzyme and ligated to customized Illumina adapters. Single-cell Hi-C libraries were then PCR amplified, size selected, and characterized by multiplexed, paired-end sequencing. The authors used the same population of CD4+ Th1 cells to generate an ensemble Hi-C library. Sequencing and analysis of 190 million read pairs produced a contact map representing the mean contact enrichments within approximately 10 million nuclei. The probability of observing a contact between two chromosomal elements decays with linear distance following a power law regime for distances larger than 100 kb. They found similar regimes for the ensemble, individual cells, and a pool of 60 single cells. Moreover, after normalizing the matrices given this canonical trend, comparison of intra-chromosomal interaction intensities for the pool and ensemble, by global correlation analysis of contact enrichment values at 1 Mb resolution generates a highly significant correspondence. The authors used the ensemble domains to ask whether the same domain structure can be observed at the single-cell level. Visual inspection of the domain structure overlaid on individual intra-chromosomal contact maps and global statistical analysis of the ratios between intra- and inter-domain contact intensities in individual cells both supported