SummaryChromosome conformation capture technologies have revealed important insights into genome folding. Yet, how spatial genome architecture is related to gene expression and cell fate remains unclear. We comprehensively mapped 3D chromatin organization during mouse neural differentiation in vitro and in vivo, generating the highest-resolution Hi-C maps available to date. We found that transcription is correlated with chromatin insulation and long-range interactions, but dCas9-mediated activation is insufficient for creating TAD boundaries de novo. Additionally, we discovered long-range contacts between gene bodies of exon-rich, active genes in all cell types. During neural differentiation, contacts between active TADs become less pronounced while inactive TADs interact more strongly. An extensive Polycomb network in stem cells is disrupted, while dynamic interactions between neural transcription factors appear in vivo. Finally, cell type-specific enhancer-promoter contacts are established concomitant to gene expression. This work shows that multiple factors influence the dynamics of chromatin interactions in development.

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...

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor–binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor–binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

No abstract

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.