Performance of four modern whole genome amplification methods for copy number variant detection in single cells

Whole genome amplification (WGA) has become an invaluable tool to perform copy number variation (CNV) detection in single, or a limited number of cells. Unfortunately, all current WGA methods introduce representation bias that limits the detection of CNVs smaller than 3 Mb. New WGA methods have been introduced that might have the potential to reduce this bias. We compared the performance of PicoPLEX DNA-Seq (Picoseq), DOPlify, REPLI-g and Ampli-1 WGA for aneuploidy screening and copy number analysis using shallow whole genome massively parallel sequencing (MPS), starting from single or a limited number of cells. Although the four WGA methods perform differently, they are all suited for this application.

全基因组扩增（Whole Genome Amplification, WGA）已成为在单个或少量细胞中开展拷贝数变异（Copy Number Variation, CNV）检测的关键工具。遗憾的是，当前所有WGA方法均会引入扩增偏倚，这极大限制了对小于3 Mb的CNV的检测效能。近期已有新型WGA方法问世，其有望降低此类偏倚。本研究以单细胞或少量细胞为起始样本，采用浅层全基因组大规模并行测序（Massively Parallel Sequencing, MPS）技术，对比评估了PicoPLEX DNA-Seq（Picoseq）、DOPlify、REPLI-g及Ampli-1 WGA四种方法在非整倍体筛查与拷贝数分析中的应用性能。尽管四种WGA方法的检测表现存在差异，但均适用于该类应用场景。