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, 42 (7), 512-522

Characterization of Structural Variations in the Context of 3D Chromatin Structure

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Characterization of Structural Variations in the Context of 3D Chromatin Structure

Kyukwang Kim et al. Mol Cells.

Abstract

Chromosomes located in the nucleus form discrete units of genetic material composed of DNA and protein complexes. The genetic information is encoded in linear DNA sequences, but its interpretation requires an understanding of threedimensional (3D) structure of the chromosome, in which distant DNA sequences can be juxtaposed by highly condensed chromatin packing in the space of nucleus to precisely control gene expression. Recent technological innovations in exploring higher-order chromatin structure have uncovered organizational principles of the 3D genome and its various biological implications. Very recently, it has been reported that large-scale genomic variations may disrupt higher-order chromatin organization and as a consequence, greatly contribute to disease-specific gene regulation for a range of human diseases. Here, we review recent developments in studying the effect of structural variation in gene regulation, and the detection and the interpretation of structural variations in the context of 3D chromatin structure.

Keywords: 3D chromatin structure; Hi-C; gene regulation; structural variation; topologically associating domain.

Conflict of interest statement

Disclosure

The authors have no potential conflicts of interest to disclose.

Figures

Fig. 1
Fig. 1. Principles of topologically associating domains
(A) A correlation matrix of Hi-C chromatin contact map of chromosome 17 showing plaid compartment A/B pattern (Pearson correlation coefficient, red: positive, blue: negative) with its first eigenvector (PC1 values) obtained from principal component analysis (PCA) analysis (bottom track, red: compartment A, blue: compartment B). (B) 500 kb resolution chromatin contact map of the same chromosome (left), along with a zoomed-in 40 kb resolution contact map showing structures of topologically associating domains (right, red boxes). Dark red color in contact maps indicates higher raw ligation frequency. (C) A schematic showing chromatin loops in the corresponding TAD regions (blue dotted boxes in Fig. 1B). Red boxes: enhancers, Blue boxes: promoters, Green circles: CTCF, Yellow rings: cohesin. (D) Conservation of TAD boundaries during cellular differentiation. ES: embryonic stem cells, ME: mesendoderm cells, MSC: mesenchymal stem cells, NPC: neural progenitor cells, TB: trophoblast-like cells. The blue triangles represent TADs. Red color in contact maps indicates higher normalized ligation frequency. (E) Conservation of TAD boundaries between human and mouse genomes. Red color in contact maps indicates higher normalized ligation frequency. (F) TAD-wise interaction changes observed between ES and MSC. Red color indicates higher normalized ligation frequency in the ES than the MSC and blue color indicates higher frequency in the MSC than ES. (G) A schematic showing enhancer-promoter interactions constricted by TAD boundaries (red squares). Red boxes: enhancers, Blue boxes: promoters, Green arrow arc: enhancer-promoter interactions, Red arrow arc: no enhancer-promoter interactions.
Fig. 2
Fig. 2. Structural variations induce TAD alteration
(A) A schematic of TAD fusion caused by boundary deletion (red dotted line) and the resulting effect of enhancer hijacking. (B) A schematic of TAD shuffling between two TADs in chromosomes 1 and 2 as shown in one-dimensional linear genomic sequence (top left) and 3D chromatin structure (top right), and the effect of enhancer hijacking after the inter-chromosomal translocation in perspective of the one-dimensional linear genomic sequence (bottom left) and 3D chromatin structure (bottom right). Red dotted lines: translocation breakpoints, Black arrow: results of shuffled sub-regions of TADs and 3D chromatin structure, Red boxes: enhancers, Blue boxes: promoters.
Fig. 3
Fig. 3. Precise interpretation of structural variations in the context of 3D genome
(A) A schematic showing large scale deletion (red dotted lines) changing the distance between two genomic regions A and B from d1 to d2 (left). WGS read coverage in original and deletion-harboring genome and the resulting plot of read coverage against genomic distance (top). A schematic showing regions A (red line) and B (blue line) in 3D genome space for original and deletion-harboring chromatin and the resulting plot of ligation frequency against genomic distance (bottom). (B–E) Categorization of expected gradient patterns in chromatin contact maps (top), normal TAD structure (middle), and the changes in TAD structure (bottom) for deletion (B), inversion (C), translocation (D), and duplications (E).
Fig. 4
Fig. 4. Detection of complex structural variations with chromatin contact maps
(A) Schematics showing the three possible cases generating paired-end reads spanning A and B regions in WGS: ring-shaped chromosome formation, very large deletion, and WGS mapping error (left). Shown are the corresponding DNA alteration patterns based on WGS data (middle) and gradient patterns in Hi-C chromatin interaction matrix that can distinguish the three cases (right). (B) Schematics showing the mechanism (left), WGS-based genomic rearrangement patterns (middle), and Hi-C chromatin interaction matrix with distinct gradient patterns that can be used to deduce rearranged genomic order (right) in chromothripsis. Color of the genomic rearrangement patterns (middle) indicates the types of the called SVs. (C) Schematics showing the mechanism (blue/red dotted lines are breakpoints) and circos plot showing the closed chain translocation pattern (red arc lines) of the chromoplexy event (left). Der: derivative chromosomes. A circos plot of all chromosomes shows both chromoplexy (red arc lines) and unrelated translocations (black arc lines) produced from WGS data (middle). Shown is Hi-C chromatin interaction matrix with gradient patterns aligned in breakpoint coordinate lines that can easily distinguish translocations involved in chromoplexy (highlighted in yellow) from unrelated translocations (black arrows) (left).

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References

    1. Alkan C., Coe B.P., Eichler E.E. Genome structural variation discovery and genotyping. Nat Rev Genet. 2011;12:363–376. doi: 10.1038/nrg2958. - DOI - PMC - PubMed
    1. Baca S.C., Prandi D., Lawrence M.S., Mosquera J.M., Romanel A., Drier Y., Park K., Kitabayashi N., MacDonald T.Y., Ghandi M., et al. Punctuated evolution of prostate cancer genomes. Cell. 2013;153:666–677. doi: 10.1016/j.cell.2013.03.021. - DOI - PMC - PubMed
    1. Burton J.N., Adey A., Patwardhan R.P., Qiu R., Kitzman J.O., Shendure J. Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nat Biotechnol. 2013;31:1119–1125. doi: 10.1038/nbt.2727. - DOI - PMC - PubMed
    1. Campbell P.J., Stephens P.J., Pleasance E.D., O’Meara S., Li H., Santarius T., Stebbings L.A., Leroy C., Edkins S., Hardy C., et al. Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing. Nat Genet. 2008;40:722–729. doi: 10.1038/ng.128. - DOI - PMC - PubMed
    1. Chaisson M.J.P., Sanders A.D., Zhao X., Malhotra A., Porubsky D., Rausch T., Gardner E.J., Rodriguez O.L., Guo L., Collins R.L., et al. Multi-platform discovery of haplotype-resolved structural variation in human genomes. Nat Commun. 2019;10:1784. doi: 10.1038/s41467-018-08148-z. - DOI - PMC - PubMed
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