Abstract
The nature and pace of genome mutation is largely unknown. Because standard methods sequence DNA from populations of cells, the genetic composition of individual cells is lost, de novo mutations in cells are concealed within the bulk signal and per cell cycle mutation rates and mechanisms remain elusive. Although single-cell genome analyses could resolve these problems, such analyses are error-prone because of whole-genome amplification (WGA) artefacts and are limited in the types of DNA mutation that can be discerned. We developed methods for paired-end sequence analysis of single-cell WGA products that enable (i) detecting multiple classes of DNA mutation, (ii) distinguishing DNA copy number changes from allelic WGA-amplification artefacts by the discovery of matching aberrantly mapping read pairs among the surfeit of paired-end WGA and mapping artefacts and (iii) delineating the break points and architecture of structural variants. By applying the methods, we capture DNA copy number changes acquired over one cell cycle in breast cancer cells and in blastomeres derived from a human zygote after in vitro fertilization. Furthermore, we were able to discover and fine-map a heritable inter-chromosomal rearrangement t(1;16)(p36;p12) by sequencing a single blastomere. The methods will expedite applications in basic genome research and provide a stepping stone to novel approaches for clinical genetic diagnosis.
Highlights
Large-scale sequencing of whole-cancer genomes is revealing an unexpectedly diverse array of mutational profiles, hinting at considerable underlying complexity in somatic mutation processes [1,2,3,4,5,6,7]
In comparison, $77% of the genome was covered by $12.7 Gb of paired-end sequence of non-whole-genome amplification (WGA) DNA of four different HCC38 subclones (Figure 1A, Supplementary Table S1 and Supplementary Figure S1A and B). These data suggest that single-cell WGA results in amplification products that represent only a fraction of a cell’s genome following sequencing, with multiple displacement amplification (MDA)-based single-cell sequencing attaining a breadth of genomic coverage that is significantly broader than following PicoPlex-based single-cell sequencing (Table 1)
All methods for single-cell genomics face the difficulty to detect with confidence DNA copy number and/or single-nucleotide variants in a cell, and far, none of the methods has proven the ability to unravel the genomic structure of detected DNA copy number variants [8,9,10,12,13,16,17,18,23,24,25,26,27,28,42,43,44]
Summary
Large-scale sequencing of whole-cancer genomes is revealing an unexpectedly diverse array of mutational profiles, hinting at considerable underlying complexity in somatic mutation processes [1,2,3,4,5,6,7]. Such studies are necessarily limited by the fact that somatic mutations can only be detected when they have occurred in a lineage of cells that subsequently undergoes significant clonal expansion and is, already progressing towards malignancy. Current methods for single-cell analysis have important limitations regarding the accuracy, resolution and the various classes of DNA mutation that can be detected in a cell
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