| Literature DB >> 30202056 |
Jesse R Dixon1, Jie Xu2, Vishnu Dileep3, Ye Zhan4, Fan Song5, Victoria T Le6, Galip Gürkan Yardımcı7, Abhijit Chakraborty8, Darrin V Bann9, Yanli Wang5, Royden Clark10, Lijun Zhang2, Hongbo Yang2, Tingting Liu2, Sriranga Iyyanki2, Lin An5, Christopher Pool9, Takayo Sasaki3, Juan Carlos Rivera-Mulia3, Hakan Ozadam4, Bryan R Lajoie4, Rajinder Kaul11, Michael Buckley11, Kristen Lee11, Morgan Diegel11, Dubravka Pezic12, Christina Ernst13, Suzana Hadjur12, Duncan T Odom13,14, John A Stamatoyannopoulos11, James R Broach2, Ross C Hardison15, Ferhat Ay16,17, William Stafford Noble18, Job Dekker19,20, David M Gilbert21, Feng Yue22,23.
Abstract
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.Entities:
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Year: 2018 PMID： 30202056 PMCID： PMC6301019 DOI： 10.1038/s41588-018-0195-8
Source DB: PubMed Journal: Nat Genet ISSN： 1061-4036 Impact factor: 38.330