Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

Abstract

The presence of somatic mutations, including copy number variants (CNVs), in the brain is well recognized. Comprehensive study requires single-cell whole genome amplification, with several methods available, prior to sequencing. Here we compare PicoPLEX with two recent adaptations of multiple displacement amplification (MDA): primary template-directed amplification (PTA) and droplet MDA, across 93 human brain cortical nuclei. We demonstrate different properties for each, with PTA providing the broadest amplification, PicoPLEX the most even, and distinct chimeric profiles. Furthermore, we perform CNV calling on two brains with multiple system atrophy and one control brain using different reference genomes. We find that 20.6% of brain cells have at least one Mb-scale CNV, with some supported by bulk sequencing or single-cells from other brain regions. Our study highlights the importance of selecting whole genome amplification method and reference genome for CNV calling, while supporting the existence of somatic CNVs in healthy and diseased human brain.

Fig. 1. Experimental overview and scWGS preliminary analysis from human post-mortem brain samples.

a Methodology overview created with BioRender (RRID:SCR_018361; BioRender.com; agreement KB25LPBTEK). b Mean depth of coverage for each WGA method. PicoPLEX vs PTA ns (adj. p > 0.99), PicoPLEX vs dMDA ** (adj. p = 0.008) and PTA vs dMDA * (adj. p = 0.04). Kruskal–Wallis test with Dunn’s multiple comparisons correction. c Bases potentially covered if sequenced deeper. P value for all pairwise comparisons <0.001. Brown-Forsythe and Welch ANOVA tests with Dunnett’s T3 multiple comparisons correction. d Median Absolute Pairwise Deviation (MAPD) scores at 500 kb bin size. P value for all pairwise comparisons <0.001 (adj. p < 0.001). Kruskal–Wallis test with Dunn’s multiple comparisons correction. For (b–d) PicoPLEX (n = 33), PTA (n = 21), dMDA (n = 39); Mean ± SD shown.

Fig. 2. scWGA method comparison from brain analyzed by Ginkgo at 500 kb bin size.

a Visual view of copy number profiles of single-nuclei amplified by PicoPLEX, PTA, and dMDA from the control (top) and MSA1 (bottom) brains. b Lorenz curves. The black lines with slope 1 represent perfect coverage uniformity. Increasing divergence of the curve of each cell from this indicates lower overage uniformity. c Effect of GC content in scWGA. For b-c PicoPLEX n = 33, PTA n = 21, dMDA n = 40.

Fig. 3. Comparison of discordant read pairs of brain nuclei amplified with each method.

a Outward pairs. Differences analyzed using Brown-Forsythe and Welch ANOVA test with Dunnett’s T2 multiple comparisons test. PicoPLEX vs PTA *** (adj. p < 0.001), PicoPLEX vs dMDA *** (adj. p < 0.001), PTA vs dMDA * (adj. p = 0.02). b Pairs on different chromosomes indicating translocations. Differences analyzed by Kruskal-Wallis test with Dunn’s multiple comparisons test. PicoPLEX vs PTA ns (adj. p > 0.99), PicoPLEX vs dMDA ** (adj. p = 0.002), PTA vs dMDA *** (adj. p = 0.02). c Pairs in other orientations. Differences analyzed by Kruskal-Wallis test with Dunn’s multiple comparisons test. PicoPLEX vs PTA *** (adj. p < 0.001), PicoPLEX vs dMDA *** (adj. p < 0.001), PTA vs dMDA ns (adj. p = 0.18. a-c PicoPLEX (n = 33), PTA (n = 10). dMDA (n = 38).

Fig. 4. Integrative Genomics Viewer (IGV) views demonstrating tentative support for a single cell deletion in MSA1 cingulate cortex bulk short read WGS.

The 9.5 Mb single cell deletion (chromosome 6: 161,264,702–170,805,979; cell L21, PTA) is supported by one read pair (in red) in correct orientation, but spaced 9.8 Mb apart. Read mapping quality 60 and 6 respectively. Both reads are within LINE1 elements, as shown in blue in the bottom track.