Journal
NATURE BIOTECHNOLOGY
Volume 39, Issue 2, Pages -Publisher
NATURE RESEARCH
DOI: 10.1038/s41587-020-0661-6
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Funding
- US National Institutes of Health (NIH) [R01HG007069, U24CA211000]
- US National Science Foundation (NSF) CAREER Award [CCF-1053753]
- Chan Zuckerberg Initiative DAF grants [2018-182608]
- NIH [2P30CA072720-20]
- O'Brien Family Fund for Health Research
- Wilke Family Fund for Innovation
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Single-cell barcoding technologies enable simultaneous genome sequencing of thousands of individual cells, but with low sequencing coverage per cell. A method called CHISEL was introduced to infer allele- and haplotype-specific copy numbers in single cells and subpopulations by aggregating sparse signal across hundreds or thousands of individual cells. Application of CHISEL to single-cell sequencing datasets from breast cancer patients identified extensive allele-specific copy-number aberrations affecting genomic regions containing well-known breast cancer genes.
Single-cell barcoding technologies enable genome sequencing of thousands of individual cells in parallel, but with extremely low sequencing coverage (<0.05x) per cell. While the total copy number of large multi-megabase segments can be derived from such data, important allele-specific mutations-such as copy-neutral loss of heterozygosity (LOH) in cancer-are missed. We introduce copy-number haplotype inference in single cells using evolutionary links (CHISEL), a method to infer allele- and haplotype-specific copy numbers in single cells and subpopulations of cells by aggregating sparse signal across hundreds or thousands of individual cells. We applied CHISEL to ten single-cell sequencing datasets of similar to 2,000 cells from two patients with breast cancer. We identified extensive allele-specific copy-number aberrations (CNAs) in these samples, including copy-neutral LOHs, whole-genome duplications (WGDs) and mirrored-subclonal CNAs. These allele-specific CNAs affect genomic regions containing well-known breast-cancer genes. We also refined the reconstruction of tumor evolution, timing allele-specific CNAs before and after WGDs, identifying low-frequency subpopulations distinguished by unique CNAs and uncovering evidence of convergent evolution.
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