Leung Kaston, Klaus Anders, Lin Bill K, Laks Emma, Biele Justina, Lai Daniel, Bashashati Ali, Huang Yi-Fei, Aniba Radhouane, Moksa Michelle, Steif Adi, Mes-Masson Anne-Marie, Hirst Martin, Shah Sohrab P, Aparicio Samuel, Hansen Carl L
Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada V6T 1Z4;
Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada V5Z 1L3; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada V6T 1Z4;
Proc Natl Acad Sci U S A. 2016 Jul 26;113(30):8484-9. doi: 10.1073/pnas.1520964113. Epub 2016 Jul 13.
The genomes of large numbers of single cells must be sequenced to further understanding of the biological significance of genomic heterogeneity in complex systems. Whole genome amplification (WGA) of single cells is generally the first step in such studies, but is prone to nonuniformity that can compromise genomic measurement accuracy. Despite recent advances, robust performance in high-throughput single-cell WGA remains elusive. Here, we introduce droplet multiple displacement amplification (MDA), a method that uses commercially available liquid dispensing to perform high-throughput single-cell MDA in nanoliter volumes. The performance of droplet MDA is characterized using a large dataset of 129 normal diploid cells, and is shown to exceed previously reported single-cell WGA methods in amplification uniformity, genome coverage, and/or robustness. We achieve up to 80% coverage of a single-cell genome at 5× sequencing depth, and demonstrate excellent single-nucleotide variant (SNV) detection using targeted sequencing of droplet MDA product to achieve a median allelic dropout of 15%, and using whole genome sequencing to achieve false and true positive rates of 9.66 × 10(-6) and 68.8%, respectively, in a G1-phase cell. We further show that droplet MDA allows for the detection of copy number variants (CNVs) as small as 30 kb in single cells of an ovarian cancer cell line and as small as 9 Mb in two high-grade serous ovarian cancer samples using only 0.02× depth. Droplet MDA provides an accessible and scalable method for performing robust and accurate CNV and SNV measurements on large numbers of single cells.
为了进一步理解复杂系统中基因组异质性的生物学意义，必须对大量单细胞的基因组进行测序。单细胞全基因组扩增（WGA）通常是此类研究的第一步，但容易出现不均匀性，这可能会影响基因组测量的准确性。尽管最近取得了进展，但高通量单细胞WGA的稳健性能仍然难以实现。在这里，我们介绍了液滴多重置换扩增（MDA），一种使用商用液体分配器在纳升体积中进行高通量单细胞MDA的方法。使用129个正常二倍体细胞的大型数据集对液滴MDA的性能进行了表征，结果表明，在扩增均匀性、基因组覆盖范围和/或稳健性方面，液滴MDA超过了先前报道的单细胞WGA方法。我们在5倍测序深度下实现了单细胞基因组高达80%的覆盖，并通过对液滴MDA产物进行靶向测序以实现15%的中位等位基因缺失，以及使用全基因组测序在一个G1期细胞中分别实现9.66×10^(-6)和68.8%的假阳性率和真阳性率，证明了出色的单核苷酸变异（SNV）检测能力。我们进一步表明，液滴MDA能够在仅0.02倍深度的情况下，在卵巢癌细胞系的单细胞中检测到小至30 kb的拷贝数变异（CNV），在两个高级别浆液性卵巢癌样本中检测到小至9 Mb的CNV。液滴MDA为对大量单细胞进行稳健且准确的CNV和SNV测量提供了一种易于使用且可扩展的方法。
