Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 18 (1), 125

Hi-C as a Tool for Precise Detection and Characterisation of Chromosomal Rearrangements and Copy Number Variation in Human Tumours

Affiliations

Hi-C as a Tool for Precise Detection and Characterisation of Chromosomal Rearrangements and Copy Number Variation in Human Tumours

Louise Harewood et al. Genome Biol.

Abstract

Chromosomal rearrangements occur constitutionally in the general population and somatically in the majority of cancers. Detection of balanced rearrangements, such as reciprocal translocations and inversions, is troublesome, which is particularly detrimental in oncology where rearrangements play diagnostic and prognostic roles. Here we describe the use of Hi-C as a tool for detection of both balanced and unbalanced chromosomal rearrangements in primary human tumour samples, with the potential to define chromosome breakpoints to bp resolution. In addition, we show copy number profiles can also be obtained from the same data, all at a significantly lower cost than standard sequencing approaches.

Keywords: Anaplastic astrocytoma; Cancer; Chromosome conformation capture; Chromosome rearrangement; Copy number variation; Glioblastoma; Hi-C; Tumour.

Figures

Fig. 1
Fig. 1
Hi-C detects chromosomal rearrangements. a Overview of the Hi-C method. b Cartoon representation of cross-linked DNA in a normal nucleus (top) and both unbalanced and balanced translocation carrying nuclei, with derivative chromosomes (der) demarked. Representative paired end reads and theoretical heatmaps are also shown. c Partial heatmaps for chromosomes 11 and 22 generated from two sets of Hi-C data performed on human cell lines from an Emanuel syndrome patient and balanced translocation carrier. The red box outlines interactions observed from the derivative chromosome 22 and the green box outlines those from the derivative chromosome 11 (up to the centromere). Ideograms for chromosomes 11 and 22 are provided alongside for reference. d Hi-C interaction heatmap of a mouse cell line showing unsuspected chromosomal rearrangements. Chromosomes are listed along the x and y axes in numerical order. All three suspected translocations are enlarged and were confirmed by fluorescence in-situ hybridisation (FISH), as can be seen by the co-localisation of probes from different chromosomes (one red and one green) on a single metaphase chromosome (inset)
Fig. 2
Fig. 2
Tumour GB180. a Heatmap and partial heatmap of tumour GB180 showing a balanced translocation between chromosomes 3 and 13 (t(3;13)(p24.1;q33.3)). Heatmaps were coloured by the number of interactions with the colour gradient scaled linearly from ten (blue) to 50 (red). Bins containing less than ten interactions are not represented. The small red arrows indicate amplified regions. b Read counts for amplified regions on chromosomes 7 (top) and 12 (bottom). The high peaks show a significantly higher number of reads than in the surrounding regions. EGFR, CDK4 and MDM2 oncogenes are labelled
Fig. 3
Fig. 3
Tumour GB176. a Heatmap and partial heatmaps of tumour GB176 showing some of the rearrangements present in this tumour. b Hi-C ‘other ends’ from regions distal and proximal to the suspected breakpoint on chromosome 1 (top) and chromosome 20 (bottom) showing the breakpoint regions. A sudden drop-off in the number of reads can be seen where the remaining chromosome is not involved in the translocation and is therefore not in cis. c Left: Polymerase chain reaction (PCR) on tumour and blood DNA from GB176 showing amplification products from both derivative chromosomes, indicating a balanced translocation. Right: BLAT results from sequenced tumour specific PCR amplicons showing the breakpoint regions on chromosome 1 (top) and 20 (bottom). The gaps in the BLAT results show deletions at the translocation breakpoints
Fig. 4
Fig. 4
Hi-C and normalised linkage density heatmaps for tumour GB176. a Hi-C interaction heatmap generated using 500 kb probe size. b Heatmap of normalised linkage densities at 500 kb resolution. c Examples of enlarged regions of both heatmaps showing the rearrangements involving chromosomes 2 and 7 (left) and chromosomes 2 and 13 (right)

Comment in

Similar articles

See all similar articles

Cited by 22 PubMed Central articles

See all "Cited by" articles

References

    1. Hakim O, Resch W, Yamane A, Klein I, Kieffer-Kwon KR, Jankovic M, et al. DNA damage defines sites of recurrent chromosomal translocations in B lymphocytes. Nature. 2012;484:69–74. - PMC - PubMed
    1. Zhang Y, McCord RP, Ho YJ, Lajoie BR, Hildebrand DG, Simon AC, et al. Spatial organization of the mouse genome and its role in recurrent chromosomal translocations. Cell. 2012;148:908–921. doi: 10.1016/j.cell.2012.02.002. - DOI - PMC - PubMed
    1. Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS, et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods. 2009;6:677–681. doi: 10.1038/nmeth.1363. - DOI - PMC - PubMed
    1. Zeitouni B, Boeva V, Janoueix-Lerosey I, Loeillet S, Legoix-ne P, Nicolas A, et al. SVDetect: a tool to identify genomic structural variations from paired-end and mate-pair sequencing data. Bioinformatics. 2010;26:1895–1896. doi: 10.1093/bioinformatics/btq293. - DOI - PMC - PubMed
    1. Yang R, Chen L, Newman S, Gandhi K, Doho G, Moreno CS, et al. Integrated analysis of whole-genome paired-end and mate-pair sequencing data for identifying genomic structural variations in multiple myeloma. Cancer Inform. 2014;13:49–53. - PMC - PubMed

Publication types

LinkOut - more resources

Feedback