PT - JOURNAL ARTICLE AU - Sergey Aganezov AU - Sara Goodwin AU - Rachel Sherman AU - Fritz J. Sedlazeck AU - Gayatri Arun AU - Sonam Bhatia AU - Isac Lee AU - Melanie Kirsche AU - Robert Wappel AU - Melissa Kramer AU - Karen Kostroff AU - David L. Spector AU - Winston Timp AU - W. Richard McCombie AU - Michael C. Schatz TI - Comprehensive analysis of structural variants in breast cancer genomes using single molecule sequencing AID - 10.1101/847855 DP - 2019 Jan 01 TA - bioRxiv PG - 847855 4099 - http://biorxiv.org/content/early/2019/11/19/847855.short 4100 - http://biorxiv.org/content/early/2019/11/19/847855.full AB - Improved identification of structural variants (SVs) in cancer can lead to more targeted and effective treatment options as well as advance our basic understanding of disease progression. We performed whole genome sequencing of the SKBR3 breast cancer cell-line and patient-derived tumor and normal organoids from two breast cancer patients using 10X/Illumina, PacBio, and Oxford Nanopore sequencing. We then inferred SVs and large-scale allele-specific copy number variants (CNVs) using an ensemble of methods. Our findings demonstrate that long-read sequencing allows for substantially more accurate and sensitive SV detection, with between 90% and 95% of variants supported by each long-read technology also supported by the other. We also report high accuracy for long-reads even at relatively low coverage (25x-30x). Furthermore, we inferred karyotypes from these data using our enhanced RCK algorithm to present a more accurate representation of the mutated cancer genomes, and find hundreds of variants affecting known cancer-related genes detectable only through long-read sequencing. These findings highlight the need for long-read sequencing of cancer genomes for the precise analysis of their genetic instability.