Single-cell Hi-C reveals cell-to-cell variability in chromosome structure

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 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...

Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell

“…Although coverage was low, it was uniform, suggesting that it was unlikely to be due to biased retrieval from the genome. Chromosome structure modeling confirmed this, as combining individual cell data sets led to compact ball-shaped structures with increased violations, rather than a refinement of the models from the initial data sets 13 .…”

“…Therefore, the data provide the opportunity to analyze snapshots of chromosome conformations from individual cells capturing cellular heterogeneity, which may reflect their dynamic behavior. For example, we showed in our singlecell Hi-C study on mouse T H 1 cells that individual chromosomes maintain topological domain organization at the megabase scale, but that chromosome structures vary from cell to cell at larger scales 13 . An important point to note is that single-cell Hi-C data are sparse, and a potential concern is that the variability in interactome maps derived from individual cells could be because of nonuniform sampling of the interactome from each cell.…”

“…To develop single-cell Hi-C, we modified the original Hi-C protocol 12 to perform the ligation in the nucleus 13 , allowing us to isolate single cells in which the Hi-C procedure was nearly complete. Cells were then transferred to individual tubes for cross-link reversal, DNA fragmentation, capture of ligation junctions and Hi-C library construction (Fig.…”

“…Although coverage was low, it was uniform, suggesting that it was unlikely to be due to biased retrieval from the genome. Chromosome structure modeling confirmed this, as combining individual cell data sets led to compact ball-shaped structures with increased violations, rather than a refinement of the models from the initial data sets 13 .The sparsity of genome coverage leads to concerns over the success rate of the experimental protocol. We showed that the richest data sets-i.e., those with the highest number of restraints (unique read pairs)-generated the most accurate and precise 3D models.…”

“…For example, the interaction data from the single-copy male X chromosome was used to derive distance restraints to calculate 3D models of chromosomes, upon which genomic and epigenomic information can be projected for the study of spatial patterns of such features 13 .…”