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 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 modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of 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 organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns.Chromosome conformation capture 1 (3C) and derivative methods (4C, 5C and Hi-C) [2][3][4][5][6] have enabled the detection of chromosome organisation in the 3D space of the nucleus. These methods assess millions of cells and are increasingly used to calculate conformations of a range of genomic regions, from individual loci to whole genomes 3,[7][8][9][10][11] . However, fluorescence in situ hybridisation (FISH) analyses show that genotypically and phenotypically identical cells have non-random, but highly variable genome and chromosome conformations 4,12,13 probably due to the dynamic and stochastic nature of chromosomal structures [14][15][16] . Therefore, whilst 3C-based analyses can be used to estimateCorrespondence and requests for materials should be addressed to PF (peter.fraser@babraham.ac.uk) for the single cell Hi-C method, AT (amos.tanay@weizmann.ac.il) for the statistical analysis, or EDL (e.d.laue@bioc.cam.ac.uk) for the structural modelling.. Author Contributions TN and PF devised the single cell Hi-C method. TN performed single cell Hi-C and DNA FISH experiments. SS carried out ensemble Hi-C experiments. WD microscopically isolated single cells. YL, EY and AT processed and statistically analyzed the sequence data. TJS and EDL developed the approach to structural modelling and analysed X chromosome structures. TJS wrote the software for 3D modeling, analysis and visualisation of chromosome structures. TN, YL, TJS, EDL, AT and PF contributed to writing the manuscript, with inputs from all other authors.Data deposited in NCBI's Gene Expression Omnibus (Nagano et al., 2013) and are accessible through GEO Series accession number GSE48262 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48262).The authors declare that they have no competing financial interests. an average conformation, it cannot be assumed to represent one simple and recurrent chromosomal structure. To move from probabilistic chromosome conformations averaged from millions of cells towards determinati...

Recent investigations have implicated long antisense noncoding RNAs in the epigenetic regulation of chromosomal domains. Here we show that Kcnq1ot1 is an RNA polymerase II-encoded, 91 kb-long, moderately stable nuclear transcript and that its stability is important for bidirectional silencing of genes in the Kcnq1 domain. Kcnq1ot1 interacts with chromatin and with the H3K9- and H3K27-specific histone methyltransferases G9a and the PRC2 complex in a lineage-specific manner. This interaction correlates with the presence of extended regions of chromatin enriched with H3K9me3 and H3K27me3 in the Kcnq1 domain in placenta, whereas fetal liver lacks both chromatin interactions and heterochromatin structures. In addition, the Kcnq1 domain is more often found in contact with the nucleolar compartment in placenta than in liver. Taken together, our data describe a mechanism whereby Kcnq1ot1 establishes lineage-specific transcriptional silencing patterns through recruitment of chromatin remodeling complexes and maintenance of these patterns through subsequent cell divisions occurs via targeting the associated regions to the perinucleolar compartment.

Summary Chromosomes in proliferating metazoan cells undergo dramatic structural metamorphoses every cell cycle, alternating between highly condensed mitotic structures facilitating chromosome segregation, and decondensed interphase structures accommodating transcription, gene silencing and DNA replication. Here we use single-cell Hi-C to study chromosome conformations in thousands of individual cells, and discover a continuum of cis-interaction profiles that finely position individual cells along the cell cycle. We show that chromosomal compartments, topological associated domains (TADs), contact insulation and long-range loops, all defined by bulk Hi-C maps, are governed by distinct cell-cycle dynamics. In particular, DNA replication correlates with build-up of compartments and reduction in TAD insulation, while loops are generally stable from G1 through S and G2. Whole-genome 3D structural models reveal a radial architecture of chromosomal compartments with distinct epigenomic signatures. Our single-cell data thereby allow for re-interpretation of chromosome conformation maps through the prism of the cell cycle.

A number of large noncoding RNAs (ncRNAs) epigenetically silence genes through unknown mechanisms. The Air ncRNA is imprinted--monoallelically expressed from the paternal allele. Air is required for allele-specific silencing of the cis-linked Slc22a3, Slc22a2, and Igf2r genes in mouse placenta. We show that Air interacts with the Slc22a3 promoter chromatin and the H3K9 histone methyltransferase G9a in placenta. Air accumulates at the Slc22a3 promoter in correlation with localized H3K9 methylation and transcriptional repression. Genetic ablation of G9a results in nonimprinted, biallelic transcription of Slc22a3. Truncated Air fails to accumulate at the Slc22a3 promoter, which results in reduced G9a recruitment and biallelic transcription. Our results suggest that Air, and potentially other large ncRNAs, target repressive histone-modifying activities through molecular interaction with specific chromatin domains to epigenetically silence transcription.

The mysterious secrets of long noncoding RNAs, often referred to as the Dark Matter of the genome, are gradually coming to light. Several recent papers dig deep to reveal surprisingly complex and diverse functions of these enigmatic molecules.

The mammalian genome harbors up to one million regulatory elements often located at great distances from their target genes. Long-range elements control genes through physical contact with promoters and can be recognized by the presence of specific histone modifications and transcription factor binding. Linking regulatory elements to specific promoters genome-wide is currently impeded by the limited resolution of high-throughput chromatin interaction assays. Here we apply a sequence capture approach to enrich Hi-C libraries for >22,000 annotated mouse promoters to identify statistically significant, long-range interactions at restriction fragment resolution, assigning long-range interacting elements to their target genes genome-wide in embryonic stem cells and fetal liver cells. The distal sites contacting active genes are enriched in active histone modifications and transcription factor occupancy, whereas inactive genes contact distal sites with repressive histone marks, demonstrating the regulatory potential of the distal elements identified. Furthermore, we find that coregulated genes cluster nonrandomly in spatial interaction networks correlated with their biological function and expression level. Interestingly, we find the strongest gene clustering in ES cells between transcription factor genes that control key developmental processes in embryogenesis. The results provide the first genome-wide catalog linking gene promoters to their longrange interacting elements and highlight the complex spatial regulatory circuitry controlling mammalian gene expression.

HiCUP is a pipeline for processing sequence data generated by Hi-C and Capture Hi-C (CHi-C) experiments, which are techniques used to investigate three-dimensional genomic organisation. The pipeline maps data to a specified reference genome and removes artefacts that would otherwise hinder subsequent analysis. HiCUP also produces an easy-to-interpret yet detailed quality control (QC) report that assists in refining experimental protocols for future studies. The software is freely available and has already been used for processing Hi-C and CHi-C data in several recently published peer-reviewed studies.

Genome-wide association studies have identified more than 70 common variants that are associated with breast cancer risk. Most of these variants map to non-protein-coding regions and several map to gene deserts, regions of several hundred kilobases lacking protein-coding genes. We hypothesized that gene deserts harbor long-range regulatory elements that can physically interact with target genes to influence their expression. To test this, we developed Capture Hi-C (CHi-C), which, by incorporating a sequence capture step into a Hi-C protocol, allows high-resolution analysis of targeted regions of the genome. We used CHi-C to investigate long-range interactions at three breast cancer gene deserts mapping to 2q35, 8q24.21, and 9q31.2. We identified interaction peaks between putative regulatory elements (''bait fragments'') within the captured regions and ''targets'' that included both protein-coding genes and long noncoding (lnc) RNAs over distances of 6.6 kb to 2.6 Mb. Target protein-coding genes were IGFBP5, KLF4, NSMCE2, and MYC; and target lncRNAs included DIRC3, PVT1, and CCDC26. For one gene desert, we were able to define two SNPs (rs12613955 and rs4442975) that were highly correlated with the published risk variant and that mapped within the bait end of an interaction peak. In vivo ChIP-qPCR data show that one of these, rs4442975, affects the binding of FOXA1 and implicate this SNP as a putative functional variant.