3D genome of multiple myeloma reveals spatial genome disorganization associated with copy number variations. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Wu, Pengze; Li, Tingting; Li, Ruifeng; Jia, Lumeng; Zhu, Ping; Liu, Yifang; Chen, Qing; Tang, Daiwei; Yu, Yuezhou; Li, Cheng
• Is Part Of: Nature communications. Volume 8:Issue 1(2017)
• Page Start: 1
• Page End: 11
• Publication Date: 2017-12
• Subjects: Biology -- Periodicals; Physical sciences -- Periodicals; 505
• DOI: 10.1038/s41467-017-01793-w
• Languages: English
• ISSNs: 2041-1723

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. Chromosome conformation capture techniques enable the study of genome organization in cancer cells. Here, the authors use Hi-C, WGS, and RNA-seq to study the 3D genome of multiple myeloma and find that genome disorganization is associated with copy number variations and changes in gene expression.