3D genome of multiple myeloma reveals spatial genome disorganization associated with copy number variations

Pengze Wu, Tingting Li, Ruifeng Li, Lumeng Jia, Ping Zhu, Yifang Liu, Qing Chen, Daiwei Tang, Yuezhou Yu and Cheng Li ()
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Pengze Wu: Peking University
Tingting Li: Peking University
Ruifeng Li: Peking University
Lumeng Jia: Peking University
Ping Zhu: Peking University
Yifang Liu: Tsinghua University
Qing Chen: Peking University
Daiwei Tang: Tsinghua University
Yuezhou Yu: Peking University
Cheng Li: Peking University

Nature Communications, 2017, vol. 8, issue 1, 1-11

Abstract: Abstract The Hi-C method is widely used to study the functional roles of the three-dimensional (3D) architecture of genomes. Here, we integrate Hi-C, whole-genome sequencing (WGS) and RNA-seq to study the 3D genome architecture of multiple myeloma (MM) and how it associates with genomic variation and gene expression. Our results show that Hi-C interaction matrices are biased by copy number variations (CNVs) and can be used to detect CNVs. Also, combining Hi-C and WGS data can improve the detection of translocations. We find that CNV breakpoints significantly overlap with topologically associating domain (TAD) boundaries. Compared to normal B cells, the numbers of TADs increases by 25% in MM, the average size of TADs is smaller, and about 20% of genomic regions switch their chromatin A/B compartment types. In summary, we report a 3D genome interaction map of aneuploid MM cells and reveal the relationship among CNVs, translocations, 3D genome reorganization, and gene expression regulation.

Date: 2017
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DOI: 10.1038/s41467-017-01793-w

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