Recent advances in whole genome amplification (WGA), whole transcriptome amplification (WTA) technologies and next-generation sequencing (NGS) have enabled whole genome or transcriptome sequencing at the single-cell level. Single-cell sequencing studies have yielded new insights into the heterogeneity of the genome and transcriptome in individual cells. Such heterogeneity at the single-cell level has been shown to be closely related to cellular function, differentiation, development, and diseases. A critical element of the single-cell sequencing workflow is sequencing library construction following WGA or WTA. An efficient library construction method is required to convert a high percentage of the DNA fragments to an adaptor-ligated sequencing library and to ensure high sequence complexity of the library. Furthermore, uniform representation of all genomic regions in a sequencing library is essential for retaining all important sequence information. Here we compared 2 library construction methods following a REPLI-g MDA-mediated WGA or WTA: • A ligation-based library construction method using a GeneRead Library Prep Kit (QIAGEN) • A ‘tagmentation’-based method using Nextera DNA Sample Prep Kit (Illumina), which simultaneously fragments and tags DNA. Our results demonstrated that the Nextera library construction method can be directly used with the REPLI-g-amplified DNA following MDA reaction, without the need for DNA purification. This could be beneficial if working with a high number of samples or if the complete workflow of single WGA/WTA and library construction should be automated. However, compared with the tagmentation method, the ligation-based library construction method is more flexible with regard to the input DNA amount and delivers sequencing libraries with higher complexity and less bias. This is critical for sensitive applications, such as identification of genomic variants or comprehensive profiling of transcriptomes.

1. Rumeysa Akinci-Tolun, Isabell Haupt, Ioanna Andreou, Peter Hahn, Christian Korfhage and Nan Fang
QIAGEN GmbH, QIAGEN Strasse 1, 40724 Hilden, Germany
109638708/2015
Comparison of Different NGS Library Construction
Methods for Single-Cell Sequencing
Sample to Insight
Abstract
Recent advances in whole genome amplification (WGA), whole transcriptome amplification (WTA) technologies and next-
generation sequencing (NGS) have enabled whole genome or transcriptome sequencing at the single-cell level. Single-cell
sequencing studies have yielded new insights into the heterogeneity of the genome and transcriptome in individual cells. Such
heterogeneity at the single-cell level has been shown to be closely related to cellular function, differentiation, development,
and diseases.
A critical element of the single-cell sequencing workflow is sequencing library construction following WGA or WTA. An
efficient library construction method is required to convert a high percentage of the DNA fragments to an adaptor-ligated
sequencing library and to ensure high sequence complexity of the library. Furthermore, uniform representation of all genomic
regions in a sequencing library is essential for retaining all important sequence information.
Here we compared 2 library construction methods following a REPLI-g MDA-mediated WGA or WTA:
• A ligation-based library construction method using a GeneRead™
Library Prep Kit (QIAGEN)
• A ‘tagmentation’-based method using Nextera DNA Sample Prep Kit (Illumina), which simultaneously fragments and tags
DNA.
Our results demonstrated that the Nextera library construction method can be directly used with the REPLI-g-amplified DNA
following MDA reaction, without the need for DNA purification. This could be beneficial if working with a high number of
samples or if the complete workflow of single WGA/WTA and library construction should be automated. However, compared
with the tagmentation method, the ligation-based library construction method is more flexible with regard to the input DNA
amount and delivers sequencing libraries with higher complexity and less bias. This is critical for sensitive applications, such
as identification of genomic variants or comprehensive profiling of transcriptomes.
Following MDA-based WGA or WTA from 1–1000 cells, the amplified genomic DNA or cDNA, respectively, can be
subject to library construction using either a PCR-free, adaptor-ligation–based library prep method (GeneRead) or
tagmentation-based library prep method (Nextera). The workflows show the steps involved in sequencing library
construction. Both GeneRead and Nextera protocols can be completed in under 2 hours. The GeneRead library construction
protocol combines all enzymatic reactions (end-repair, A-addition, and ligation) in one reaction tube and does not require
PCR-based library amplification. The Nextera method requires an intermediate cleanup step between tagmentation and
PCR-amplification, but does not require DNA fragmentation.
GeneRead and Nextera Library Prep Workflow for
Single-Cell Sequencing
Single-Cell Sequencing Library Qualification
The genome from Bacillus subtilis cells and transcriptome from HeLa S3 cells were amplified using the REPLI-g Single Cell
WGA Kit or REPLI-g Single Cell WTA Kit (both QIAGEN), respectively. The amplified genomic DNA (gDNA) or cDNA
was constructed into sequencing libraries for Illumina sequencing platforms using either the GeneRead Library Prep Kit
(QIAGEN) or Nextera DNA Library Prep Kit (Illumina). The size distribution of the sequencing libraries was analyzed on an
Agilent BioAnalyzer. GeneRead libraries from A REPLI-g–amplified gDNA and B REPLI-g-amplified cDNA. Nextera libraries
from C REPLI-g-amplified gDNA and D REPLI-g-amplified cDNA.
Sequencing libraries constructed using GeneRead had a peak size ~500 bp; Nextera libraries had a peak size above
700 bp.
Sequencing Data Quality
All 4 sequencing libraries were sequenced on an Illumina MiSeq®
instrument with a MiSeq Reagent Kits v2 (300-cycle,
paired end-sequencing, 2X151). FastQC software (Babraham Bioinformatics) was used to analyze the sequencing data
quality. As shown in the per-base-GC-content (1A-1D) and per-base-sequence-content (2A–2D), the Nextera Libraries had
characteristic GC bias in the first 20 nucleotides (C and D). This is likely caused by the bias of the Nextera transposase
in recognizing genome sequences for tagmentation. GeneRead libraries from A REPLI-g-amplified gDNA and B REPLI-g-
amplified cDNA. Nextera libraries from C REPLI-g-amplified gDNA and D REPLI-g-amplified cDNA. The reverse reads of
the same libraries showed same patterns in per-base-GC content as the forward reads.
GeneRead library construction workflow.
Nextera library construction workflow.
Comparison of Library Quality Metrics
To further evaluate the quality of the GeneRead and Nextera
sequencing libraries, we analyzed the following metrics:
percentages of the WGA-gDNA reads mapped to the
B. subtilis reference genome, and WGA-gDNA reads with
PHRED score of ≥30; GC bias metrics, plotted as normalized
sequence coverage on genome regions with different GC
contents; and distribution of reads for different RNA species
for the in the WTA-cDNA libraries.
Summary
Both GeneRead and Nextera library prep methods:
• Are compatible with REPLI-g WGA and WTA for single cell sequencing
• Provide streamlined protocols to construct libraries in under 2 hours
• Deliver high library quality for sequencing MDA-amplified gDNA and cDNA
GeneRead library prep:
• PCR-free library prep for minimal bias
• High coverage uniformity
• Requires additional DNA fragmentation
Nextera library prep:
• Combined fragmentation and adaptor ligation suitable for automation
• Requires PCR amplification
• GC bias with low coverage of AT-rich region
• Bias at the ends of sequencing reads
For up-to-date licensing information and product-specific disclaimers, see the respective QIAGEN kit handbook or user
manual. QIAGEN kit handbooks and user manuals are available at www.qiagen.com or can be requested from QIAGEN
Technical Services or your local distributor.
Trademarks: QIAGEN®
, Sample to Insight®
, GeneRead™
, REPLI-g®
(QIAGEN Group); Illumina®
, MiSeq®
(Illumina, Inc.). Registered names, trademarks, etc.
used in this document, even when not specifically marked as such, are not to be considered unprotected by law. © 2015 QIAGEN, all rights reserved.
2
Normalized coverage
1.6
1.2
0.8
0.4
0 10 20 30 40 50 60 70 80
0
Nextera
GeneRead
GC Contents, %
100
80
60
40
20
Pecentage of
mapped ready
Pecentage of mapped ready
with PHRED score ≥30
0
% GeneRead Nextera
100
80
60
40
20
GeneRead Nextera
0
%
snRNA_pseudogene
snoRNA
snRNA
scRNA_pseudogene
rRNA_pseudogene
pseudogene
misc_RNA
miRNA
lincRNA
Mt_tRNA_pseudogene
1–1000
cells
WGA
or WTA
Tag-
mentation
Cleanup
PCR
amplification
Cleanup/
Adaptor
removal
Sequencing
library
1–1000
cells
WGA
or WTA
DNA
fragmenta-
tion
End-repair A-addition
Adapter
ligation
Cleanup/
Adaptor
removal
Sequencing
library
One tube
Tube 1 Tube 2
RNA-seq libraries made with WTA-cDNA in combination with either
GeneRead or Nextera kits, showed a high percentage of reads mapped to
the protein-coding genes.
Normalized coverage across genomic regions with different GC contents
with WGA-gDNA libraries generated with either GeneRead or Nextera
library prep kits.
Sequencing libraries constructed with both GeneRead and Nextera methods
had almost 100% reads successfully mapped to the reference genome, as
well as a high percentage of bases with a PHRED score of ≥30.
C D
1A
2A 2B 2C 2D
1B 1C 1D
C