A quantitative comparison of single-cell whole genome amplification methods.

Charles F A De Bourcy,Jianbin Wang,Stephen R Quake,Iwijn De Vlaminck,Jad N Kanbar,Charles Gawad,Kai Wang

doi:10.1371/journal.pone.0105585

Charles F A De Bourcy, Jianbin Wang + Show 5 more

Open Access

https://doi.org/10.1371/journal.pone.0105585

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Journal: PloS one	Publication Date: Aug 19, 2014
Citations: 294	License type: CC BY 4.0

Affiliation: Stanford University, Howard Hughes Medical Institute

Abstract

Single-cell sequencing is emerging as an important tool for studies of genomic heterogeneity. Whole genome amplification (WGA) is a key step in single-cell sequencing workflows and a multitude of methods have been introduced. Here, we compare three state-of-the-art methods on both bulk and single-cell samples of E. coli DNA: Multiple Displacement Amplification (MDA), Multiple Annealing and Looping Based Amplification Cycles (MALBAC), and the PicoPLEX single-cell WGA kit (NEB-WGA). We considered the effects of reaction gain on coverage uniformity, error rates and the level of background contamination. We compared the suitability of the different WGA methods for the detection of copy-number variations, for the detection of single-nucleotide polymorphisms and for de-novo genome assembly. No single method performed best across all criteria and significant differences in characteristics were observed; the choice of which amplifier to use will depend strongly on the details of the type of question being asked in any given experiment.

Highlights

The recent development of techniques to perform single-cell genome analysis enables direct interrogation of the genetic heterogeneity of cellular populations
Specificity We investigated specificity by computing the fraction of mapped, unmapped and discordantly mapped read pairs resulting from the different Whole genome amplification (WGA) reactions (Fig. 2A)
We analyzed the fractional genome coverage achieved given a fixed total sequencing depth (Fig. 3D, 20x sequencing depth), thereby both taking into account reads that mapped and reads that did not map to the reference genome. (The dependence of genome coverage on total sequencing depth is illustrated by the rarefaction curves in Fig. S3.) Remarkably, when considering the fractional coverage at a fixed sequencing depth, we found that the different chemistries perform over the range of reaction gains investigated: the greater inherent uniformity achieved by MALBAC and NEB-WGA was offset by the larger proportion of unmappable sequences that resulted from these chemistries (Fig. 2A)

Summary

Introduction

The recent development of techniques to perform single-cell genome analysis enables direct interrogation of the genetic heterogeneity of cellular populations. Whole genome amplification (WGA) is used in order to obtain sufficient material for genetic analyses of DNA isolated from single cells: Illumina and PacBio-based sequencing workflows typically require 1 ng and 500 ng of input material respectively, and a single bacterial or human cell contains on the order of 1 fg or 1 pg of genomic material only. Best-in-class performance for PCR-based methods is achieved with protocols that include a limited MDA pre-amplification phase preceding PCR. The PicoPLEX singlecell WGA kit (NEB-WGA) and the recently described Multiple Annealing and Looping Based Amplification Cycles chemistry (MALBAC) are in this category. It is unclear to what extent cycling of MDA or loop formation contributes to potential reduction of amplification bias and the performance of MALBAC and NEB-WGA has not been compared systematically

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