Download - RNA Sequencing from Single Cell
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RNA sequencing from single cell
Find out how to go from a single to NGS ready library in ~5 hrs
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Complete cell-to-library solution
PCR-free workflow
Primary sample isolation
Single cell isolation
NGS library constructionSample
• Single eukaryotic cell• Picogram leves of purified RNA
• Whole genome NGS library◦ Illumina-compatible◦ Transcript discovery◦ Gene expression ◦ Differential expression
InsightNGS run Data analysis Interpretation
QIAseq FX Single Cell RNA Library Kit
Single cell genomics by QIAGEN, 2016
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For single cell RNA sequencing
Ideally suited for• Sensitive transcript discovery and differential gene
expression analysis from single eukaryotic cells• High frequency detection of sequence polymorphisms• Analyzing both mRNA and long non-coding RNAs in a
single dataset• Studying intercellular heterogeneity• RNA-seq from limited amounts of difficult-to-obtain samples• Researching infectious diseases
QIAseq FX Single Cell
RNA Library Kit
Single cell genomics by QIAGEN, 2016
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QIAseq FX Single Cell RNA Library Kit: the contents
Both kits contain:• Cell lysis and gDNA degradation reagents
• Reverse transcription buffers, primers and enzymes
• Enzymes and buffers for cDNA amplification and fragmentation
• Single step NGS library prep
• Single-use, disposable Illumina adapters in 96-well format
• Multiple reagent aliquots to reduce contamination risk and freeze-thaw cycles
What’s not included:• AMPure XP beads for library purification
• PCR reagents for library amplification are not needed as the entire workflow is PCR-free
• qPCR reagents for library quantification: recommended for accurate flow-cell loading
Cat No./ID: 180733QIAseq FX Single Cell RNA Library Kit (24)
Cat No./ID: 180735QIAseq FX Single Cell RNA Library Kit (96)
Single cell genomics by QIAGEN, 2016
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Discover QIAseq FX Single Cell RNA Library Kit
• More diverse libraries◦ WTA technology with fewer dropouts and less length-bias ◦ Highly efficient library preparation◦ PCR-free workflow eliminates PCR duplicates
• Highest sequence fidelity◦ High-fidelity WTA minimizes spurious sequence errors; ideal for viral RNA sequencing
• Maximized transcript discovery◦ More transcripts with the same sequencing depth ◦ Sequence both mRNAs and lncRNAs using the same protocol
• Robust & streamlined workflow◦ Everything needed in one package, single use adaptors cut down on contamination possibilities◦ 5.5 hours workflow from single cell to library without any additional kits
• Enables bio-banking◦ Amplified cDNA can be stored for follow-up studies or confirmatory testing.
MDA* instead of
PCR
Innovative QIAseq FX technology
Complete cell-to-library
solution
*MDA = multiple displacement amplification
Single cell genomics by QIAGEN, 2016
Sample to Insight
QIAseq FX Single Cell RNA Library Kit
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NGS library preparation for single cell RNA sequencing of eukaryotic cells. Ideally suited for differential gene expression, sequence polymorphism analysis.
• Cell-to-Library PCR-free workflow, robust & streamlined workflow. In 5.5 hours hours from single cell to library, no additional kits
• Sensitive transcript discovery - WTA technology with high accuracy
• No PCR duplicates - Highly diverse libraries
Maximized transcript discovery
mRNA & lncRNA in same datasetHigh diversity libraries
Reads / cell
100 pg RNA
Single cellsSingle cells
Single cell genomics by QIAGEN, 2016
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QIAseq FX Single Cell RNA Library Kit: streamlined workflow
Cell Lysis• Start with single eukaryotic cells or small amounts
(pg or ng) of high quality, purified RNA
• Starting with 7 µl cell material in PBS (included)
• Prepare lysis buffer, mix with cells, incubate for 8 minutes
• Cool to 4°C
• Add gDNA degradation reagent, incubate for 10 min
Cell lysis15 min
WTA3 h 45 min
FX library preparation
70 min
Purification20 min
ILLUMINA sequencing
5h 30 min with ~1 h hands-on time
Single cell genomics by QIAGEN, 2016
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QIAseq FX Single Cell RNA Library Kit: streamlined workflow
Whole Transcriptome Amplification• Prepare RT mastermix, mix with lysed cells, incubate 1 h
• Prepare cDNA ligation mix, incubate for 30 min
• Prepare cDNA amplification mix, mix with unamplified cDNA, incubate for 2 h
◦ Amplified cDNA can be used directly or frozen until needed
◦ There will be an excess of amplified cDNA, which can be stored for later use or follow-up studies (e.g. confirming deletions detected with NGS via PCR or sanger sequencing).
◦ Library preparation accepts a wide range of inputs. So quantification of the amplified cDNA is generally not necessary.
Cell lysis15 min
WTA3 h 45 min
FX library preparation
70 min
Purification20 min
ILLUMINA sequencing
5h 30 min with ~1 h hands-on time
Single cell genomics by QIAGEN, 2016
Sample to Insight
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QIAseq FX Single Cell RNA Library Kit: streamlined workflow
NGS Library Preparation• Prepare FX mastermix, add to diluted WTA
product and incubate for ~15 min. Insert size can be set by user
• Hold at 4°C
• Add adapters from single-use adapter plate
• Prepare ligation mastermix, add to samples and incubate for 15 min to produce library
Cell lysis15 min
WTA3 h 45 min
FX library preparation
70 min
Purification20 min
ILLUMINA sequencing
5h 30 min with ~1 h hands-on time
Single cell genomics by QIAGEN, 2016
Sample to Insight
10
QIAseq FX Single Cell RNA Library Kit: streamlined workflow
Library Purification• Remove excess adapters with double-sided
Ampure XP cutoff
◦ No PCR amplification necessary; protocol generates sufficient library without enrichment
◦ Library quantification via qPCR (i.e. QIAseq Library Quant) is highly recommended to ensure accurate clustering on sequencer
Cell lysis15 min
WTA3 h 45 min
FX library preparation
70 min
Purification20 min
ILLUMINA sequencing
5h 30 min with ~1 h hands-on time
Single cell genomics by QIAGEN, 2016
Sample to Insight
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Discover more: libraries with higher diversity
The QIAseq FX Single Cell RNA Library Kit detects a greater number of transcripts than competitor C/I at the same sequencing depth. To account for cell-to-cell differences in transcript abundance, libraries were produced from 100 pg of reference RNA from PBMCs. After sequencing, quality control and mapping, annotated transcripts with >1 TPM were quantified from either the full dataset or rarified sub-fractions. Saturation curves are from different sample preparation methods. Each point on the curve was generated by randomly selecting a number of raw reads from each sample library and then using the same alignment pipeline to call genes with mean TPM>1.
Discovery plot
Single cell genomics by QIAGEN, 2016
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Discover more: highly diverse libraries from single cells
Libraries were generated from single isolated PBMCs with the QIAseq FX Single Cell RNA Library Kit. After QC and mapping, the number of annotated transcripts with >1 TPM was computed. Data were then rarified repeatedly, where a subset of reads was selected at random, and the number of annotated transcripts with >1 TPM was computed for each sub-sampled set of reads. This was repeated at multiple read depths.
Discovery plot
Reads/cell
Single cell genomics by QIAGEN, 2016
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Discover more: detect high numbers of transcripts
Libraries were generated from three individually isolated HeLa cells or from 100 pg of bulk RNA isolated from HeLa cells using the QIAseq FX Single Cell RNA Library Kit. After QC and mapping, the number of annotated transcripts with >1 FPKM was computed.
Number of transcripts
Single cell genomics by QIAGEN, 2016
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PCR-free library preparation yields highly diverse datasets
Single cell RNA libraries from PBMCs were generated using the QIAseq FX Single Cell RNA Library Kit or a kit from supplier C/I. Libraries were sequenced on Illumina NextSeq. Plotted are the percentage of duplicates that were obtained from the FastQC report of the sequenced libraries.
Note: While true PCR duplicates cannot be produced with the PCR-free QIAseq protocol, some duplicates will still be counted using this calculation method. This is completely due to the high abundance of transcripts and probability, which dictates that at higher transcript abundance the chance of two reads being counted as a duplicate increases (using this calculation method).
Level of duplicates
Single cell genomics by QIAGEN, 2016
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Uncover lncRNAs and mRNAs with a single protocol
Single cell RNA libraries from PBMCs and HeLa Cells were generated using QIAseq FX Single Cell RNA Library kit or a kit from supplier C/I. Plotted are the percentage of reads that map to lncRNAs detected in PBMC and HeLa preparations. QIAseq detects a significantly higher percentage of lncRNAs compared to supplier C/I.
Percentage of mapped reads that are lncRNAs
Single cell genomics by QIAGEN, 2016
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High proportion of reads map to protein-coding genes
Single cell libraries were prepared from PBMCs or total RNA from PBMCs using the QIAseq FX Single Cell RNA Library Kit and sequenced on NextSeq. Plotted is the percentage of reads that map to different RNA biotypes.
RNA biotypes
Single cell genomics by QIAGEN, 2016
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Consistent, robust cDNA amplification enables bio-banking
Whole transcriptome amplification yield from single cells using the QIAseq FX Single Cell RNA Library Kit or a competing, PCR-based method (Supplier C). Eight replicates from different single cells are shown.
Reproducible cDNA yield
Single cell genomics by QIAGEN, 2016
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High reproducibility
Four individual HeLa cells were isolated from the same cell culture and libraries were prepared with either the QIAseq FX Single Cell RNA Library Kit or a competing workflow. After sequencing to equal depth, quality control, alignment and TPKM calculation, pairwise comparisons of the number of common transcripts detected with >1 FPKM divided by sum of all transcripts in both preps were made between all tested cells. The data shown represent mean of 6 pairwise comparisons with SD. This graph demonstrates that the more sensitive transcript detection and the capturing of both lncRNAs and mRNAs does not come at the cost of reproducibility, and that this method is at least as reproducible as other workflows.
Single cell genomics by QIAGEN, 2016
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Single cell genomics by QIAGEN
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For in-depth, molecular analysis of single cells
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Single cell genomics by QIAGEN, 2016
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