To address data management and data exchange problems in the nuclear magnetic resonance (NMR) community, the Collaborative Computing Project for the NMR community (CCPN) created a "Data Model" that describes all the different types of information needed in an NMR structural study, from molecular structure and NMR parameters to coordinates. This paper describes the development of a set of software applications that use the Data Model and its associated libraries, thus validating the approach. These applications are freely available and provide a pipeline for high-throughput analysis of NMR data. Three programs work directly with the Data Model: CcpNmr Analysis, an entirely new analysis and interactive display program, the CcpNmr FormatConverter, which allows transfer of data from programs commonly used in NMR to and from the Data Model, and the CLOUDS software for automated structure calculation and assignment (Carnegie Mellon University), which was rewritten to interact directly with the Data Model. The ARIA 2.0 software for structure calculation (Institut Pasteur) and the QUEEN program for validation of restraints (University of Nijmegen) were extended to provide conversion of their data to the Data Model. During these developments the Data Model has been thoroughly tested and used, demonstrating that applications can successfully exchange data via the Data Model. The software architecture developed by CCPN is now ready for new developments, such as integration with additional software applications and extensions of the Data Model into other areas of research.

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...

The folding of genomic DNA from the beads-on-a-string like structure of nucleosomes into higher order assemblies is critically linked to nuclear processes. We have calculated the first 3D structures of entire mammalian genomes using data from a new chromosome conformation capture procedure that allows us to first image and then process single cells. This has allowed us to study genome folding down to a scale of <100 kb and to validate the structures. We show that the structures of individual topological-associated domains and loops vary very substantially from cell-to-cell. By contrast, A/B compartments, lamin-associated domains and active enhancers/promoters are organized in a consistent way on a genome-wide basis in every cell, suggesting that they could drive chromosome and genome folding. Through studying pluripotency factor- and NuRD-regulated genes, we illustrate how single cell genome structure determination provides a novel approach for investigating biological processes.

Specific modifications to histones are essential epigenetic markers---heritable changes in gene expression that do not affect the DNA sequence. Methylation of lysine 9 in histone H3 is recognized by heterochromatin protein 1 (HP1), which directs the binding of other proteins to control chromatin structure and gene expression. Here we show that HP1 uses an induced-fit mechanism for recognition of this modification, as revealed by the structure of its chromodomain bound to a histone H3 peptide dimethylated at Nzeta of lysine 9. The binding pocket for the N-methyl groups is provided by three aromatic side chains, Tyr21, Trp42 and Phe45, which reside in two regions that become ordered on binding of the peptide. The side chain of Lys9 is almost fully extended and surrounded by residues that are conserved in many other chromodomains. The QTAR peptide sequence preceding Lys9 makes most of the additional interactions with the chromodomain, with HP1 residues Val23, Leu40, Trp42, Leu58 and Cys60 appearing to be a major determinant of specificity by binding the key buried Ala7. These findings predict which other chromodomains will bind methylated proteins and suggest a motif that they recognize.

HP1 family proteins are adaptor molecules, containing two related chromo domains that are required for chromatin packaging and gene silencing. Here we present the structure of the chromo shadow domain from mouse HP1b bound to a peptide containing a consensus PXVXL motif found in many HP1 binding partners. The shadow domain exhibits a novel mode of peptide recognition, where the peptide binds across the dimer interface, sandwiched in a b-sheet between strands from each monomer. The structure allows us to predict which other shadow domains bind similar PXVXL motif-containing peptides and provides a framework for predicting the sequence specificity of the others. We show that targeting of HP1b to heterochromatin requires shadow domain interactions with PXVXL-containing proteins in addition to chromo domain recognition of Lys-9-methylated histone H3. Interestingly, it also appears to require the simultaneous recognition of two Lys-9-methylated histone H3 molecules. This finding implies a further complexity to the histone code for regulation of chromatin structure and suggests how binding of HP1 family proteins may lead to its condensation.