Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates

Abstract

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.

Keywords: microdroplet; multiple displacement amplification; nanoliter volume; single-cell sequencing; whole genome amplification.

Fig. 1.

Droplet MDA system. (A) Schematic of single-cell droplet MDA protocol. (B) Substrate with 100-nL droplets of food dye covered by light mineral oil.

Fig. 2.

Scatterplots and boxplots of SD of reads per 1-Mb bin comparing other published methods with all 184-hTERT single-cell droplet MDA samples sequenced to low depth. Unamplified bulk 184-hTERT gDNA is also included for comparison. Shown for the 184-hTERT single-cell droplet MDA samples are unsorted single cells (with three extreme outliers omitted), single cells FACS-sorted by cell phase (G1, S, and G2), and the 10 samples with the lowest SDs of all sorted and unsorted single cells.

Fig. 3.

Normalized read depth plots using 1-Mb bins for the sample from each method with the lowest SD in reads per bin.

Fig. 4.

Analysis of amplification bias from high-depth WGS. (A) Lorenz curves depicting uniformity of coverage for the two samples with the lowest SD in reads per 1-Mb bin from each amplification method. (B) Coverage breadth as a function of sequencing depth for the sample with the lowest SD in reads per 1-kb bin from each method. (C) Mean power spectra of 1-kb binned read depth for all samples analyzed from each amplification method. (D) Power spectra of 1-kb binned read depth for the sample with the lowest SD in reads per bin from each method.

Fig. 5.

Normalized read depth plots using 1-Mb bins for TOV2295 bulk DNA and four single-cell samples. Horizontal green lines indicate segments of contiguous bins inferred to have the same copy number, where the read depth of each segment is equal to the median read depth of the bins in that segment. Inferred copy numbers are indicated by the color of the data point for each bin.