PRJNA273682
Quantitative assessment of two single-cell whole genome amplification methods for detecting copy number variations using hippocampal neurons
Single-cell genomic analysis has grown rapidly in recent years and will find widespread applications in various fields of biology, including cancer biology, development, immunology, pre-implantation genetic diagnosis, and neurobiology. To date, the amplification bias, amplification uniformity, reproducibility of two major single cell whole genome amplification methods (GenomePlex WGA4 and MALBAC) have not been systematically investigated using mammalian cells. In this study, we amplified genomic DNA from individual hippocampal neurons using one of two single-cell DNA amplification methods (MALBAC and WGA4), and sequenced them at shallow depth. We then systematically evaluated the GC-bias, reproducibility, and copy number variations among individual neurons. Our results showed that single-cell genome sequencing results obtained from the MALBAC and WGA4 methods are highly reproducible and have a high success rate. The MALBAC display significant biases towards high GC content. We developed a bioinformatics pipeline to correct the GC biases and call CNVs in single cell sequencing data. We also proposed a metric to determine the CNV detection limits. By carefully correcting the biases generated during sample preparation, chromosome-level and subchromosomal-level CNVs among individual neurons can be detected.