SNES: single nucleus exome sequencing.

Marco L Leung,Nicholas E Navin,Yong Wang,Jill Waters

doi:10.1186/s13059-015-0616-2

Abstract

Single-cell genome sequencing methods are challenged by poor physical coverage and high error rates, making it difficult to distinguish real biological variants from technical artifacts. To address this problem, we developed a method called SNES that combines flow-sorting of single G1/0 or G2/M nuclei, time-limited multiple-displacement-amplification, exome capture, and next-generation sequencing to generate high coverage (96%) data from single human cells. We validated our method in a fibroblast cell line, and show low allelic dropout and false-positive error rates, resulting in high detection efficiencies for single nucleotide variants (92%) and indels (85%) in single cells.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0616-2) contains supplementary material, which is available to authorized users.

Highlights

Single-cell sequencing methods have the potential to provide great insight into the genomes of rare subpopulations and complex admixtures of cells, but are currently challenged by extensive technical errors and poor physical coverage data
The 6 picograms (2 N) or 12 picograms (4 N) of gDNA from each nucleus is incubated with the Φ29 polymerase (New England Biolabs) and modified random hexamer primers to perform timelimited MDA
We investigated the spectrum of the false positive (FP) errors and found that 82.3% were C > T and G > A transitions (Figure 3c), showing a significant bias relative to the normal transition and transversion spectrum in the population of fibroblast cells (Figure 3d)

Summary

Introduction

Single-cell sequencing methods have the potential to provide great insight into the genomes of rare subpopulations and complex admixtures of cells, but are currently challenged by extensive technical errors and poor physical coverage data. In our previous work we developed the first single-cell genome sequencing method, Single-NucleusSequencing (SNS), which utilized DOP-PCR to generate about 10% coverage breadth of an individual cell [7,8]. Two subsequent methods were developed that use multiple-displacementamplification (MDA) [9] and multiple-annealing-loopingbased-amplification-cycles (MALBAC) [10] to increase coverage breadth during WGA. While pioneering, these studies increased coverage breadth at the cost of introducing high false positive and false negative error rates, due to excessive over-amplification (1:1e6) of the DNA from a single cell from 6 picograms to microgram concentrations. It was necessary to call variants across most of the single cells to reduce the high false positive (FP) technical errors, which is equivalent to sequencing the bulk tissue en masse

Methods

Results

Conclusion