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Structural variants can contribute to oncogenesis through a variety of mechanisms. Despite their importance, the identification of structural variants 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 structural variants 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 non-coding sequences, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel 3D chromatin structural domains. Our results indicate that non-coding structural variations may be underappreciated mutational drivers in cancer genomes.

SUMMARY Although aneuploidy is found in the majority of tumors, the degree of aneuploidy varies widely. It is unclear how cancer cells become aneuploid or how highly aneuploid tumors are different from those of more normal ploidy. We developed a simple computational method that measures the degree of aneuploidy or structural rearrangements of large chromosome regions of 522 human breast tumors from The Cancer Genome Atlas (TCGA). Highly aneuploid tumors overexpress activators of mitotic transcription and the genes encoding proteins that segregate chromosomes. Overexpression of three mitotic transcriptional regulators, E2F1, MYBL2, and FOXM1, is sufficient to increase the rate of lagging anaphase chromosomes in a non-transformed vertebrate tissue, demonstrating that this event can initiate aneuploidy. Highly aneuploid human breast tumors are also enriched in TP53 mutations. TP53 mutations co-associate with the overexpression of mitotic transcriptional activators, suggesting that these events work together to provide fitness to breast tumors., In Brief Pfister et al. analyzed TCGA sequence data to identify drivers of aneuploidy in breast tumors. TP53 is mutated in most aneuploid tumors, and a large number of genes that control mitosis are overexpressed. The oncogenes E2F1, MYBL2, and FOXM1 that regulate mitotic transcription drive the overexpression of mitotic proteins to lower the fidelity of chromosome segregation.

Somatic mutation in neurons is linked to neurologic disease and implicated in cell type diversification. However, the origin, extent and patterns of genomic mutation in neurons remain unknown. We established a nuclear transfer method to clonally amplify the genomes of neurons from adult mice for whole genome sequencing. Comprehensive mutation detection and independent validation revealed that individual neurons harbor ~100 unique mutations from all classes, but lack recurrent rearrangements. Most neurons contain at least one gene disrupting mutation and rare (0-2) mobile element insertions. The frequency and gene bias of neuronal mutations differs from other lineages, potentially due to novel mechanisms governing post-mitotic mutation. Fertile mice were cloned from several neurons, establishing the compatibility of mutated adult neuronal genomes with reprogramming to pluripotency and development.

Structural variants can contribute to oncogenesis through a variety of mechanisms, yet, despite their importance, the identification of structural variants in cancer genomes remains challenging. Here, we present an integrative framework for comprehensively identifying structural variation in cancer genomes. For the first time, we apply next-generation optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole genome sequencing to systematically detect SVs in a variety of cancer cells.Using this approach, we identify and characterize structural variants in up to 29 commonly used normal and cancer cell lines. We find that each method has unique strengths in identifying different classes of structural variants and at different scales, suggesting that integrative approaches are likely the only way to comprehensively identify structural variants in the genome. Studying the impact of the structural variants in cancer cell lines, we identify widespread structural variation events affecting the functions of non-coding sequences in the genome, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel 3D chromatin structural domains.These results underscore the importance of comprehensive structural variant identification and indicate that non-coding structural variation may be an underappreciated mutational process in cancer genomes.