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. 2012 Nov;58(3):268-76.
doi: 10.1016/j.ymeth.2012.05.001. Epub 2012 May 29.

Hi-C: a comprehensive technique to capture the conformation of genomes

Affiliations

Hi-C: a comprehensive technique to capture the conformation of genomes

Jon-Matthew Belton et al. Methods. 2012 Nov.

Abstract

We describe a method, Hi-C, to comprehensively detect chromatin interactions in the mammalian nucleus. This method is based on Chromosome Conformation Capture, in which chromatin is crosslinked with formaldehyde, then digested, and re-ligated in such a way that only DNA fragments that are covalently linked together form ligation products. The ligation products contain the information of not only where they originated from in the genomic sequence but also where they reside, physically, in the 3D organization of the genome. In Hi-C, a biotin-labeled nucleotide is incorporated at the ligation junction, enabling selective purification of chimeric DNA ligation junctions followed by deep sequencing. The compatibility of Hi-C with next generation sequencing platforms makes it possible to detect chromatin interactions on an unprecedented scale. This advance gives Hi-C the power to both explore the biophysical properties of chromatin as well as the implications of chromatin structure for the biological functions of the nucleus. A massively parallel survey of chromatin interaction provides the previously missing dimension of spatial context to other genomic studies. This spatial context will provide a new perspective to studies of chromatin and its role in genome regulation in normal conditions and in disease.

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Figures

Figure 1
Figure 1. Overview of Hi-C technology
A) Hi-C detects chromatin interaction both within and between chromosomes by covalently crosslinking protein/DNA complexes with formaldehyde. B) The chromatin is digested with a restriction enzyme and the ends are marked with a biotinylated nucleotide. C) The DNA in the crosslinked complexes are ligated to form chimeric DNA molecules. D) Biotin is removed from the ends of linear fragments and the molecules are fragmented to reduce their overall size. E) Molecules with internal biotin incorporation are pulled down with streptavidin coated magnetic beads and modified for deep sequencing. Quantitation of chromatin interactions is achieved through massively parallel deep sequencing.
Figure 2
Figure 2. Relative ligation efficiency of Hi-C library
A) Digestion of a PCR amplicon generated from a neighboring pair of restriction fragments in both the 3C sample and the Hi-C sample. The amplicon was digested with HindIII (H), NheI (N), Both HindIII and NheI (B), or not digested (0). The amplicon when digested yields 2 products of different molecular weight. The molecular weight ladder is the Low Molecular Weight Ladder from NEB. B) The Hi-C library is fragmented using the Covaris 8700. A titration of fragmentation time is shown, starting with un-fragmented Hi-C library (lane 1) and increasing in the number of minutes of fragmentation (lanes 2-5). At 4 minutes (lane 5) the distribution of fragment sizes is ~50bp – 600bp. C) AMpure XP is used to fractionate the library. The 0.9x AMpure XP fraction includes molecules that are larger then ~150bp and the 1.1x fraction includes molecules that are between ~150bp – 300bp. D) The Illumina Paired-end graft sequences are added to the Illumina adapter modified Hi-C libraries using PCR with primers PE 1.0 and PE 2.0. These primers are partially homologous to the PE adapter, which was ligated to the Hi-C library. The gel shows a titration of the number of cycles. At higher numbers of PCR cycles, higher molecular weight artifacts are produced (arrow). Sufficient amounts of DNA are produced at 12 cycles for this library. E) Three completed Hi-C libraries were digested with NheI. The shift of the size distribution of the library following digestion with NheI estimates the proportion of the library that consists of real Hi-C ligation products. A range of performances are shown, with library 1 showing poor performance, library 2 showing medium performance and library 3 showing good performance. The percentages below the each library are the percentages of dangling-ends that were tabulated after sequencing these libraries and mapping the reads to the genome.
Fig 3
Fig 3. Hi-C sequence mapping and binning considerations
A) Different types of molecules in the Hi-C library (left) lead to different orientations of mapped reads relative to restriction sites (right). Mapped reads (colored arrows) facing outward in the same fragment come from self-circles (top); Reads facing inward in the same fragment arise from dangling ends (middle); Reads from different restriction fragments and facing toward a restriction site arise from valid interaction pairs (bottom). B) Relationship between sequencing depth and choice of bin size. Each graph shows the percentage of cis (top) or trans (bottom) bins that contain at least one mapped read from a valid interaction pair (y-axis) for each different bin size (x-axis). Colored dotted lines indicate the bin size at which 90% of bins contain at least one valid pair read for a Hi-C library with a high (blue) or low (red) number of total unique valid pairs after sequencing.
Fig 4
Fig 4. Hi-C data visualization and analysis
A) A heatmap of interactions between all 1 Mb bins along chr1 for GM06990 cells. The intensity of red color corresponds to the number of Hi-C interactions. B) A “4C profile” derived from one row of the Hi-C heatmap (blue box in A) showing all interactions between a fixed 1 Mb location at 190 Mb on chr1 and the rest of chr1. CTCF and H3K4me3 tracks from a similar cell line are displayed below as examples of other genomic datasets that can be compared with such an interaction profile. C) The log10 of the Hi-C interaction counts of each pair of bins along chr1 is plotted versus the log of the genomic distance between each pair of bins. The median value of datapoints in the graph is indicated by a blue line while the 5% and 95% confidence intervals are shown as thin black lines. The slope of the median line from 500 kb to 10 Mb is -1, following the relationship expected for a fractal globule polymer structure of the chromatin. D) Red and blue “plaid” patterns show the compartmentalization of chr1 in two types of chromosomal domains. The data from A were transformed by first finding the observed interactions over the expected average pattern of decay away from the diagonal and then calculating a Pearson correlation coefficient between each pair of rows and columns. Regions highly correlated with one another in interaction are colored red and are likely to be classified by principle components analysis into the same compartment as shown above (black bands = open chromatin compartment; light grey bands = closed chromatin compartment). The compartment assignments correlate with the gene density profile, shown above the compartment profile (high gene density = black; low gene density = white). E) Whole chromosome interaction patterns show that longer chromosomes (chr1-10, chrX) are more likely to interact with one another and not with shorter chromosomes (chr14-22). The observed number of interactions between any pair of chromosomes is divided by the expected number of interactions between those chromosomes given the total number of reads for either chromosome in the whole experiment. Red indicates an enrichment of interaction as compared to expected values while blue indicates a depletion of interactions between two chromosomes.

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