BGI-Shenzhen, Shenzhen, 518083, PR China.
MGI, BGI-Shenzhen, Shenzhen, 518083, China.
Prenat Diagn. 2017 Dec;37(13):1311-1321. doi: 10.1002/pd.5186.
The purpose of this study were to develop a methodology of isolating fetal cells from maternal blood and use deep sequence demonstrating the promise for complete and accurate genetic screening compared to other non-invasive prenatal testing.
Here in this study, we developed a double negative selection (DNS) procedure to unbiasedly enrich fetal cells. After validated by short tandem repeat (STR), the isolated circulating fetal cells (CFCs) were subjected to deep whole genome sequencing analysis.
Our DNS protocol significantly increasing the purity of the mimic fetal cells from 1 in 1 million nucleated cells in whole blood to 1:8 to 1:30 (12.5%-3.33%) after 2 steps of enrichment. Isolated single fetal cell obtained a coverage rate (86.8%) and allelic dropout rate (24.90%) comparative to the reported results of human cell line. Several disease-associated variants were identified in the whole genome sequencing data of isolated CFCs and further confirmed in the sequencing data of unamplified gDNA.
In conclusion, the robustness of DNS and STR to collect CFCs from peripheral maternal blood for the first time coupled with deep sequencing technique demonstrates the possibility of comprehensive non-invasive prenatal testing of genetic disorders using isolated CFCs.
本研究旨在开发一种从母体血液中分离胎儿细胞的方法，并利用深度测序技术与其他非侵入性产前检测方法相比，展示其在完全和准确的遗传筛查方面的潜力。
在本研究中，我们开发了一种双重阴性选择 (DNS) 程序，以无偏地富集胎儿细胞。在通过短串联重复序列 (STR) 验证后，对分离出的循环胎儿细胞 (CFC) 进行深度全基因组测序分析。
我们的 DNS 方案显著提高了模拟胎儿细胞的纯度，从全血中每 100 万个有核细胞中的 1 个增加到富集 2 步后的 1:8 至 1:30（12.5%-3.33%）。分离得到的单个胎儿细胞的覆盖率（86.8%）和等位基因缺失率（24.90%）与已报道的人细胞系结果相当。在分离的 CFC 的全基因组测序数据中鉴定出了几个与疾病相关的变异体，并在未扩增 gDNA 的测序数据中进一步得到了证实。
总之，DNS 和 STR 从外周母体血液中首次收集 CFC 的稳健性与深度测序技术相结合，证明了使用分离的 CFC 进行全面的非侵入性产前遗传疾病检测的可能性。
