What can you do from a single cell? Actually, quite a lot! Beginning with the genome, you can discover new biomarkers by identifying new genetic variances and their association with specific diseases, including cancers. Moving on to RNA, the recent advances in RNA sequencing technology have made single-cell transcriptomics a possibility. Along with these possibilities, come challenges that start from the moment you get the sample to the final step of gaining insights into the cell. This slidedeck will provide an overview on the multiple steps involved as you move from sample acquisition to analysis and data interpretation in different sample types.
Single-Cell Analysis - Powered by REPLI-g: Single Cell Analysis Series Part 1
1. Sample to Insight
Single-Cell Analysis – From Sample to Insight
Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015 1
Courtney Nadeau
Sr. Global Product Manager, NGS Life Sciences, QIAGEN Hilden, Germany
2. Sample to Insight
2Single Cell Analysis - From Sample to Insight,Hilden,Oct. 2015
Legal disclaimers
The QIAGEN products shown here are intended for molecular
biology applications. These products are not intended for the
diagnosis, prevention, or treatment of a disease.
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.
3. Sample to Insight
Overview
3Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Overview
• Why study single cells
o Scarce sample
o Genome heterogeneity
o Transcriptome heterogeneity
o Statistical power
• Basic parts of a single-cell workflow
o Cell isolation
o WGA or WTA
o Analytical techniques
o Data analysis
• QIAGEN products for single cell analysis
4. Sample to Insight
Studying limited amounts of material
4Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Scarce Sample Material
• Allows the analysis of cells
from small and precious
starting materials:
o Circulating tumor cells
(CTCs)
o Cells from small biopsies
o Cells from in vitro
fertilized embryos
o Microorganisms from
environmental samples
Standard NGS
Library Prep
Input:
100-1000ng
Bacterium Mammalian
cell
200 µl Blood
1 µg
1 ng
1 pg
1 fg
Average DNA content
5. Sample to Insight
Genome heterogeneity
5Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Genome Heterogeneity
• Allows investigation into genomic
heterogeneity between individual
cells:
o Copy number alterations
o Structural alterations and
rearrangements
o Single nucleotide mutations
o Variability in transposable
element or viral genome
integration
Zhengwen Jiang et al. Nucl. Acids Res. 2005;33:e91
6. Sample to Insight
Transcriptome heterogeneity
6Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Transcriptome Heterogeneity
• Investigate differences in
transcript expression and gene
regulation in individual cells:
o Differences in transcript
abundance
o Usage of alternate
transcription initiation and
polyadenylation sites
o Alternative splicing and
differential expression of
transcript isoforms
Zeisel A. et al. (2014) Brain Structure. Cell types of the cortex
and hippocampus revealed by single-cell RNA-seq, Science
347(6226):1138-42
7. Sample to Insight
Averaging averages
7Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
The basic unit of research we are often interested in is the cell. But we usually analyze
populations of cells and this can:
• Lead to false positives from underestimating biological variability
• Miss important biological divisions
0 0
0 3
0 0
0 0
0 0
0 6
0 6
0 0
0,938
Biological Sample 1
Biological Sample 2
Population
Mean 2
1
Single Cell
Analysis
Population
Mean 1
Mean=0,969
Stdev=1,470
Sample Size=32
SEM=0,260
1 1
1
1 1
1 1
1 1
1 1
1 1
1 1
1
Mean=0,969
Stdev=0,048
Sample Size=2
SEM=0,031
Bulk
Approach
8. Sample to Insight
Wide array of applications for single-cell analysis
Title, Location,Date 8
WGA
or
WTA
Whole Genome Sequencing
• Detect variability in genome sequence (SNV, microsatellites, etc.)
• Variability in genome structure (CNV, structural rearrangements,aneuploidy)
• De novo sequencing of new, unidentified and unculturable organisms
TargetedResequencing
• Detect variability in a target set of genes or region of the genome
Microarrays
• Use SNP-chips to genotype thousands of loci
mRNA-seq
• Detect variability in transcript abundance for all expressed genes
• Detect variability in isoform structure and abundance
qRT-PCR profiling
• Profile gene expression for a targeted set of transcripts
• Accurately quantify specific splice-junctions, isoforms or other structural
features
9. Sample to Insight
Single cell workflow overview
9Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
In general, single cell molecular biology
experiments follow a general workflow:
• Obtain primary sample
• Detect and isolate cell of interest
• Lyse cell (often integrated with WGA or
WTA)
• Whole genome or whole transcriptome
amplification (for DNA/RNA studies)
• Analytical technique of choice (NGS
library prep and sequencing, gene panels,
real-time PCR, microarrays, sanger
sequencing)
• Data analysis and interpretation
10. Sample to Insight
Single cell workflow overview
10Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
In general, single cell molecular biology
experiments follow a general workflow
• Obtain primary sample
• Detect and isolate cell of interest
• Lyse cell (often integrated with WGA or
WTA)
• Whole genome or whole transcriptome
amplification (for DNA/RNA studies)
• Analytical technique of choice (NGS
library prep and sequencing, gene panels,
real-time PCR, microarrays, sanger
sequencing)
• Data analysis and interpretation
11. Sample to Insight
Single cell isolation: cell suspensions
11Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Isolating single cells:
• Cells in suspension?
Dilution (cell suspension)
• Cheap, but labor intensive
• Negative wells
• Mild conditions, easy on cells
Micromanipulation (cell culture)
• Transfer pipet required
• Mild conditions, easy on cells
• Labor intensive
• Obtain specific cell of interest
FACS (Fluorescence-activated cell sorting)
• Efficient for isolating large numbers of cells,
needs high number of input cells
• Expensive instrumentation required
• Sorting alters RNA expression profiles
Microfluidics
• Efficient for isolating large numbers of
cells, needs high number of input cells
• Expensive instrumentation required
Image adapted from: Genome Biology. 2014 : 15(452): . doi:10.1186/s13059-014-0452-9
12. Sample to Insight
Single cell isolation: tissue
12Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Isolating single cells:
• Cells in suspension?
• Solid Sample
Laser-capturemicrodissection (tissue)
• Direct isolation of single (or multiple) cells
• Loss of genomic information – slicing of nuclei
• Mounting and LCM both disturb gene expression
Tissue dissociation
• Mechanical, detergent and enzymatic disruption
• Produce a suspension from a solid tissue
• Potential for drastic alterations in gene expression
Image adapted from: Genome Biology. 2014 : 15(452): . doi:10.1186/s13059-014-0452-9
13. Sample to Insight
Single cell isolation: required throughput
13Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Type of Primary sample?
• Solid or Suspension?
• Viability and Cell Stress
• Scope and throughput:
• Depends on application
• Depends on cells
• Depends on budget
Cell-to-cell
variation
Biological
variation
Technical
variation
14. Sample to Insight
Single cell isolation: considerations
14Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Type of Primary sample?
• Solid or Suspension?
• Viability and Cell Stress
• Scope and throughput
• Cell Storage and Transport
o Uninterrupted cold chain
o Minimize storage time
when possible
o Keep in mind small
volumes
15. Sample to Insight
Single cell isolation: contamination
15Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Type of Primary sample?
• Solid or Suspension?
• Viability and Cell Stress
• Scope and throughput
• Cell Storage and Transport
• Contamination
o With intact cells
o With DNA
Figure is taken from: FEMS Microbiol Rev. 2013 May ; 37(3): .
doi:10.1111/1574-6976.12015.
16. Sample to Insight
Single cell workflow overview
16Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
In general, single cell molecular biology
experiments follow a general workflow:
• Obtain primary sample
• Detect and isolate cell of interest
• Lyse cell (often integrated with WGA or
WTA)
• Whole genome or whole transcriptome
amplification (for DNA/RNA studies)
• Analytical technique of choice (NGS
library prep and sequencing, gene panels,
real-time PCR, microarrays, Sanger
sequencing)
• Data analysis and interpretation
17. Sample to Insight
Whole genome or transcriptome amplification
17Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Whole Genome (WGA) and Whole
Transcriptome (WTA) Amplification
• Uses one of several techniques to amplify
the DNA or RNA from a single cell to a level
amenable to downstream protocols
PCR-Based
-Degenerative oligo-primer
PCR (DOP-PCR)
-Multiple annealing and
looping based amplification
cycles (MALBAC)
PCR-Free
-Multiple Displacement
Amplification (MDA)
-Single Primer Isothermal
Amplification (SPIA)
Whole Genome/Transcriptome Amplification Technologies
18. Sample to Insight
Single cell workflow overview
18Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
In general, single cell molecular biology
experiments follow a general workflow:
• Obtain primary sample
• Detect and isolate cell of interest
• Lyse cell (often integrated with WGA or
WTA)
• Whole genome or whole transcriptome
amplification (for DNA/RNA studies)
• Analytical technique of choice (NGS
library prep and sequencing, gene panels,
real-time PCR, microarrays, Sanger
sequencing)
• Data analysis and interpretation
19. Sample to Insight
Analytical techniques
19Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Depends on the research topic:
• PCR and Sanger sequencing for:
o Genes or regions of interest
• qPCR (real-time or digital) single or
multiplex assays for:
o Specific point mutations
o Aneuploidy or structural rearrangements
o Quantification of specific transcripts or
transcript variants
• Microarrays for:
o RNA quantification
o SNP-chips
• NGS for:
o Point mutations, aneuploidy and
structural rearrangements
o Copy number variation
o RNA quantification, splicing analysis
20. Sample to Insight
Single cell workflow overview
20Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
In general, single cell molecular biology
experiments follow a general workflow:
• Obtain primary sample
• Detect and isolate cell of interest
• Lyse cell (often integrated with WGA or
WTA)
• Whole genome or whole transcriptome
amplification (for DNA/RNA studies)
• Analytical technique of choice (NGS
library prep and sequencing, gene panels,
real-time PCR, microarrays, Sanger
sequencing)
• Data analysis and interpretation
21. Sample to Insight
Data analysis and interpretation
21Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Depends on the research topic:
• CLC:
o Sequence Viewer
o Genomics Workbench
o Biomedical Workbench
• Ingenuity:
o Variant Analysis
o Pathway Analysis
22. Sample to Insight
Single cell workflow overview
22Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
In general, single cell molecular biology
experiments follow a general workflow:
• Obtain primary sample
• Detect and isolate cell of interest
• Lyse cell (often integrated with WGA or
WTA)
• Whole genome or whole transcriptome
amplification (for DNA/RNA studies)
• Analytical technique of choice (NGS
library prep and sequencing, gene panels,
real-time PCR, microarrays, Sanger
sequencing)
• Data analysis and interpretation
23. Sample to Insight
QIAGEN products for single-cell analysis
23Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Complete Sample to Insight Solutions for Single Cell Applications
WGA, WTA or both
• REPLI-g portfolio
Cell isolation
• Coming soon
Analytical techniques
• REPLI-g NGS Library Prep kits
• GeneRead Panels
• RT2 Profiler PCR arrays
• Wide variety of available tools
Data Analysis and Interpretation
• CLC bioinformatics software
• Ingenuity variant and pathway analysis
24. Sample to Insight
The PCR-free REPLI-g protocol
24Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
REPLI-g is QIAGEN’s MDA technology, and is
incorporated into both WGA and WTA products:
• Highly specific phi29 Polymerase
• PCR-free isothermal amplification (30°C)
• 1000-fold higher fidelity than Taq
• Generates long fragments (2–70 kb)
• Minimal sequence bias
25. Sample to Insight
REPLI-g for WGA, WTA or both
25Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
26. Sample to Insight
Single Cell
Multiple Cells
Tissue
Blood
gDNA
RNA
Single-cell DNA
Sequencing
Single-cell RNA
sequencing
REPLI-g Single
Cell DNA
Library Kit
REPLI-g Single
Cell RNA
Library Kit
NGS
Library
NGS
Single-cell DNA
analysis
Single-cell RNA
analysis
Comparative
analysis of DNA
and RNA
(25+ cells)
REPLI-g
Single Cell
Kit
REPLI-g
WTA Single
Cell Kit
REPLI-g Cell
WGA & WTA
Kit
Amplified
WTA- DNA or
WGA-DNA
NGS
Microarray
qPCR
26
Choosing a REPLI-g Single Cell Kit for your application
Starting material Application Q solution Kit output Analysis
Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
27. Sample to Insight
Lower background with REPLI-g
27Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Bacterial DNA (2000 copies) was spiked into
REPLI-g sc Reaction Buffer, which was then
decontaminated using the standard procedure for
all buffers and reagents provided with the REPLI-
g Single Cell Kit. In subsequent real-time PCR, no
bacterial DNA was detectable.
The PCR-free REPLI-g kits offer:
• Minimal background:
o Kits are produced to exceptionally
high standards and reagents
undergo a unique manufacturing
process which virtually eliminates
any chance of contamination
28. Sample to Insight
High yield: wide range of applications including archival
28Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield:
o Kits produce 10 µg or more of
amplified cDNA or gDNA from a
single cell
o Library prep kits produce 2-4 nM
of PCR-free sequencer-ready
whole genome or RNAseq library
Starting Material Typical Yield
REPLI-g Single Cell RNA
Library Prep
Single cell or purified total RNA (50 pg-100 ng) 2-4 nM PCR-free NGS Library
REPLI-g Single Cell DNA
Library Prep
Single cell or purified gDNA(10 pg-10 ng)
2-4 nM PCR-free NGS Library
REPLI-g Single Cell Single cell or purified gDNA(1-10 ng) 40 µg amplified gDNA
REPLI-g WTASingle Cell Single cell or purified total RNA (10 pg-100 ng) 40 µg amplified poly(A+) cDNA
REPLI-g Cell WGA &
WTA
25+ cells
WTA: 10-20 µg, depending on
protocol
WGA: 20 µg
29. Sample to Insight
Completely PCR-free NGS workflows
29Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS library prep:
o REPLI-g single cell DNA and RNA library kits produce NGS-
ready libraries from a single cell in as little as 5.5 hours
REPLI-g Single Cell DNA Library Kit
Cell lysis
15 min
WGA
3 h
Shearing and
purification
30-60 min
End-repair
50 min
A-addition
40 min
Adapter
ligation
10 min
Cleanup and
size selection
15 min
REPLI-g Single Cell RNA Library Kit
Cell lysis
15 min
Sequencing
Data Analysis
Interpretation
gDNA
Removal
10 min
Reverse
Transciption
1 h
Ligation
35 min
WTA
2 h
One-tube
One-tube
One-tube
30. Sample to Insight
Even coverage in whole genome sequencing
30Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS library prep
• Even Coverage:
o Superior genome coverage due to even
amplification: fewer drop-outs, missed
loci and more accurate quantification
o Important for NGS as well as traditional
applications
1 pg DH10B DNA, amplified with either REPLI-g Single Cell Kit
or by MALBAC, sequenced on MiSeq Illumina (V2, 2x150nt.)
31. Sample to Insight
Fewer dropped loci
31Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS library prep
• Even Coverage
Repli-g coverage Max 3,000
MALBAC coverage Max 3,000
REPLI-g
Max 153
MALBAC
Max 4284
32. Sample to Insight
Higher transcript discovery rates
32Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS library prep
• Even Coverage
33. Sample to Insight
Higher fidelity: fewer sequencing errors
33Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS
library prep
• Even Coverage
• Fewer sequence errors:
o Polymerase has ~1000x better
proofreading activity than Taq
o Lack of PCR means errors
introduced aren’t propagated
34. Sample to Insight
Key for evaluating SNV
34Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS
library prep
• Even Coverage
• Fewer sequence errors
o Polymerase has ~1000x better
proofreading activity than Taq
o Lack of PCR means errors
introduced aren’t propagated
o ~10x better error rate than
MALBAC(1); essential for SNV
analysis
REPLI-g SC MALBAC
Total Reads 3 187 060 3 327 084
Mapped reads 3 176 341
(99,66%)
3 276 090
(98,47%)
Not mapped 10 719 (0,34%) 50 994 (1,53%)
Broken read pairs 284 017 (8,91% of
total reads)
314 550 (9,45% of
total reads)
Covered bases in
Reference
98,69% 95,82%
Insertions 6 3
Deletions 0 6
Single-nucleotide
variation
0 222
(1) Bourcy et al. (2014) PLoS ONE 9(8): e105585. doi:10.1371/journal.pone.0105585
35. Sample to Insight
Summary
35
Advantages of single-cell analysis over bulk data:
• Analyze scarce materials
• Account for genomic and transcriptomic heterogeneity
Parts of a single-cell workflow:
• Obtaining primary sample, detecting and isolating cells of interest
• Lysis, WGA or WTA, and variety of molecular biology methods
• Data analysis and interpretation
QIAGEN products for single-cell analysis
REPLI-g enables single-cell applications via:
• Minimal background
• High yield
• Integration with PCR-free NGS library prep
• Even coverage (manifests as better assembly, fewer drop-outs,
better transcript detection)
• Fewer sequence errors
Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015