Department of Hematology, Aarhus University Hospital, Aarhus, Denmark.
AAGAARD Skejby Fertility Clinic, Aarhus, Denmark.
BMC Genomics. 2018 Sep 17;19(1):681. doi: 10.1186/s12864-018-5063-5.
The current literature on single cell genomic analyses on the DNA level is conflicting regarding requirements for cell quality, amplification success rates, allelic dropouts and resolution, lacking a systematic comparison of multiple cell input down to the single cell. We hypothesized that such a correlation assay would provide an approach to address the latter issues, utilizing the leukemic cell line OCI-AML3 with a known set of genetic aberrations.
By analyzing single and multiple cell replicates (2 to 50 cells) purified by micromanipulation and serial dilution we stringently assessed the signal-to-noise ratio (SNR) from single as well as a discrete number of cells based on a multiple displacement amplification method, with whole exome sequencing as signal readout. In this setting, known OCI-AML3 mutations as well as large copy number alterations could be identified, adding to the current knowledge of cytogenetic status. The presence of DNMT3A R882C, NPM1 W288 fs and NRAS Q61L was consistent, in spite of uneven allelic read depths. In contrast, at the level of single cells, we observed that one-third to half of all variants were not reproduced in the replicate sample, and this allelic mismatch displayed an exponential function of cell input. Large signature duplications were discernible from 5 cells, whereas deletions were visible down to the single cell. Thus, even under highly optimized conditions, single cell whole genome amplification and interpretation must be taken with considerable caution, given that allelic change is frequent and displays low SNR. Allelic noise is rapidly alleviated with increased cell input, and the SNR is doubled from 2 to 50 cells.
In conclusion, we demonstrate noisy allele distributions, when analyzing genetic aberrations within single cells relative to multiple cells. Based on the presented data we recommend that single cell analyses should include replicate cell dilution assays for a given setup for relative assessment of procedure-specific SNR to ensure that the resolution supports the specific hypotheses.
目前关于单细胞基因组 DNA 水平的研究文献在细胞质量要求、扩增成功率、等位基因缺失和分辨率方面存在冲突，缺乏对单细胞水平以下的多个细胞输入的系统比较。我们假设这种相关分析方法将提供一种解决后一问题的方法，利用具有已知遗传异常的白血病细胞系 OCI-AML3。
通过分析通过微操作和连续稀释纯化的单个和多个细胞的重复（2 到 50 个细胞），我们基于多次置换扩增方法严格评估了来自单个细胞和离散数量细胞的信噪比（SNR），以全外显子测序作为信号读出。在这种情况下，可以识别已知的 OCI-AML3 突变以及大的拷贝数改变，增加了对细胞遗传学状态的现有认识。DNMT3A R882C、NPM1 W288fs 和 NRAS Q61L 的存在是一致的，尽管等位基因读取深度不均匀。相比之下，在单细胞水平上，我们观察到三分之一到一半的变体在重复样本中没有重现，并且这种等位基因不匹配显示出细胞输入的指数函数。从 5 个细胞中可以识别出大的特征重复，而缺失则可以在单细胞中看到。因此，即使在高度优化的条件下，单细胞全基因组扩增和解释也必须非常谨慎，因为等位基因变化很常见，并且 SNR 较低。随着细胞输入的增加，等位基因噪声迅速减轻，信噪比从 2 个细胞增加到 50 个细胞。
总之，我们证明了在分析单细胞内遗传异常时，等位基因分布存在噪声。基于所提供的数据，我们建议单细胞分析应包括用于给定设置的重复细胞稀释分析，以相对评估特定于程序的 SNR，以确保分辨率支持特定的假设。
