Comprehensive analysis of structural variants in breast cancer genomes using single molecule sequencing
Sergey Aganezov, Sara Goodwin, Rachel Sherman, Fritz J. Sedlazeck, Gayatri Arun, Sonam Bhatia, Isac Lee, Melanie Kirsche, Robert Wappel, Melissa Kramer, Karen Kostroff, David L. Spector, Winston Timp, W. Richard McCombie, Michael C. Schatz
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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. |
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Analysis Manuscripts
Method Availability
SV inference and comparison workflow is implemented with Snakemake v5.5.4 and is available at github.com/aganezov/EnsembleSV.
RCK v1.1 utilized for cancer genome karyotype inference is available at github.com/aganezov/RCK
Data Availability
Raw sequencing data for SKBR3 are available within the SRA under BioProject PRJNA476239.
Patient data are available within dbGaP under accession phs038843.v1
SKBR3 Merged Analysis
SKBR3 PacBio-based Analysis
SKBR3 Oxford Nanopore-based Analysis
SKBR3 10X Genomics-based Analysis
SKBR3 Illumina PE-based Analysis
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