Integrative detection and analysis of structural variation in cancer genomes

Jesse R. Dixon, Jie Xu, Vishnu Dileep, Ye Zhan, Fan Song, Victoria T. Le, Galip Gürkan Yardımcı, Abhijit Chakraborty, Darrin V. Bann, Yanli Wang, Royden Clark, Lijun Zhang, Hongbo Yang, Tingting Liu, Sriranga Iyyanki, Lin An, Christopher Pool, Takayo Sasaki, Juan Carlos Rivera-Mulia, Hakan OzadamBryan R. Lajoie, Rajinder Kaul, Michael Buckley, Kristen Lee, Morgan Diegel, Dubravka Pezic, Christina Ernst, Suzana Hadjur, Duncan T. Odom, John A. Stamatoyannopoulos, James R. Broach, Ross C. Hardison, Ferhat Ay, William Stafford Noble, Job Dekker, David M. Gilbert, Feng Yue

Research output: Contribution to journalArticlepeer-review

176 Scopus citations


Structural variants (SVs) can contribute to oncogenesis through a variety of mechanisms. Despite their importance, the identification of SVs in cancer genomes remains challenging. Here, we present a framework that integrates optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole-genome sequencing to systematically detect SVs in a variety of normal or cancer samples and cell lines. We identify the unique strengths of each method and demonstrate that only integrative approaches can comprehensively identify SVs in the genome. By combining Hi-C and optical mapping, we resolve complex SVs and phase multiple SV events to a single haplotype. Furthermore, we observe widespread structural variation events affecting the functions of noncoding sequences, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel three-dimensional chromatin structural domains. Our results indicate that noncoding SVs may be underappreciated mutational drivers in cancer genomes.
Original languageEnglish (US)
Pages (from-to)1388-1398
Number of pages11
JournalNature Genetics
Issue number10
StatePublished - Oct 1 2018

PubMed: MeSH publication types

  • Journal Article


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