Single-cell barcoding technologies enable genome sequencing of thousands of individual cells in parallel, but with extremely low sequencing coverage (<0.05×) 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 ~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.

单细胞条形码技术可对数千个单个细胞进行并行基因组测序，但每个细胞的测序覆盖率极低 (<0.05×)。虽然可以从此类数据中得出大型多兆碱基片段的总拷贝数，但遗漏了重要的等位基因特异性突变，例如癌症中的拷贝中性杂合性丢失 (LOH)。我们使用进化链接 (CHISEL) 在单个细胞中引入拷贝数单倍型推断，这是一种通过聚集数百或数千个单个细胞的稀疏信号来推断单个细胞和细胞亚群中等位基因和单倍型特定拷贝数的方法。我们将 CHISEL 应用于来自两名乳腺癌患者的约 2,000 个细胞的十个单细胞测序数据集。我们在这些样本中发现了广泛的等位基因特异性拷贝数畸变 (CNA)，包括拷贝中性 LOH、全基因组重复 (WGD) 和镜像亚克隆 CNA。这些等位基因特异性 CNA 会影响包含众所周知的乳腺癌基因的基因组区域。我们还改进了肿瘤进化的重建，在 WGD 之前和之后计时等位基因特异性 CNA，识别由独特 CNA 区分的低频亚群，并揭示趋同进化的证据。