Innovative NGS Library Construction Technology
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Next-generation sequencing (NGS) is a driving force for numerous new and exciting applications, including cancer research, stem cell research, metagenomics, population genetics, medical research and single cell analysis. While NGS technology is continuously improving, library preparation remains one of the biggest bottlenecks in the NGS workflow and includes several time-consuming steps that can result in considerable sample loss and the potential to introduce handling errors. Moreover, conducting single-cell genomic analysis using NGS methods has traditionally been challenging since the amount of genomic DNA present in a single cell is very limited.
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Innovative NGS Library Construction Technology
- 1. Sample to Insight Innovative QIAseq FX technology for construction of NGS libraries for use with Illumina instruments Ioanna Andreou Ph. D. Senior Scientist, NGS Life Sciences Team, QIAGEN Innovative NGS library prep methods 1
- 2. Sample to Insight 2 Overview of NGS technologies and innovative NGS library prep methods Part 1: Introduction to next-generation sequencing (NGS) technology Part 2: Innovative NGS library construction technology Part 3: Advanced NGS library prep for challenging samples Welcome to a 3-part series: NGS technology and applications Intro to NGS, 11.30.2016
- 3. Sample to Insight Legal disclaimer 3 • 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. Innovative NGS library prep methods
- 4. Sample to Insight Agenda Innovative NGS library prep methods 4 1 Introduction FX technology for NGS library construction Single cell analysis Single cell DNA sequencing Single cell RNA sequencing 2 3 4 5
- 5. Sample to Insight Agenda Innovative NGS library prep methods 5 1 Introduction FX technology for NGS library construction Single cell analysis Single cell DNA sequencing Single cell RNA sequencing 2 3 4 5
- 6. Sample to Insight NGS technology overview and applications series: Part 2 6 Overview of NGS technologies and innovative NGS library prep methods Part 1: Introduction to next generation sequencing (NGS) technology Part 2: Innovative NGS library construction technology Part 3: Advanced NGS library prep for challenging samples Innovative NGS library prep methods
- 7. Sample to Insight Typical challenges in whole genome sequencing 7 Faster turnaround Higher library complexity Control per-sample costs Nucleic acid isolation Data analysis and interpretation Library preparation and QC Sequencing Sample collection and stabilization → Permits process scale-up → Maximizes clinical utility of data → To preserve sample information content → To enable high-quality downstream analysis → Time, consumables, first-pass success rate Innovative NGS library prep methods
- 8. Sample to Insight Current options for DNA fragmentation are suboptimal 8 Mechanical shearing Enzymatic shearing Fragment DNA Add adapters Amplify and QC library Typical NGS Library Prep Process High costs (instrumentation lab space, hands-on-time) Harder to scale-up Intermediate cleanup steps Poor data quality, introduction of sequence bias Inflexible protocol Not easy to adapt for different DNA input Innovative NGS library prep methods
- 9. Sample to Insight Agenda 9 1 Introduction FX technology for NGS library construction Single cell analysis Single cell DNA sequencing Single cell RNA sequencing 2 3 4 5 Innovative NGS library prep methods
- 10. Sample to Insight QIAseq FX: Gold-standard quality from an enzymatic workflow Innovative NGS library prep methods 10 Single-use barcoded adapters can be used all at once or in batches of 10–12 Faster and easier to automate without the need for fragmentation instrumentation Outperforms other enzymatic shearing procedures on genomic coverage Flexible fragment size, batch size and input DNA amount Complete kit that includes reagents for fragmentation, ligation, library amplification and 96-plex dual-barcoded adapters Suitable for whole genome sequencing, whole exome / hybrid capture, metagenomics
- 11. Sample to Insight QIAseq FX – the ideal balance of speed and high data quality Innovative NGS library prep methods 11 QIAseq FX uses only a standard thermocyler and 96-well PCR plates for truly scalable library prep 2.5 hour total workflow <20 min hands-on time Single-tube enzymatic reaction workflow Easy manual implementation or adaptation for automated liquid handling QIAGEN high-fidelity library amplification and plate format 96-plex adapters included Adapter ligation Cleanup Library amplification (optional) Fragmenta- tion, end- repair and A-tailing 2.5 h Single tube Purified gDNA 1 ng – 1 µg
- 12. Sample to Insight Innovative NGS library prep methods 12 PCR-free option from as little as 10 ng input DNA QIAseq FX (50 ng PCR-Free) QIAseq FX (100 ng PCR-Free) Mechanical shearing (100 ng) with PCR QIAseq FX (100 ng) with PCR 0 0.5 1 1.5 2 0 20 40 60 80 100 Normalizedcoverage GC% over 100 bp regions Excellent G/C coverage with or without PCR PCR-free library yield (nM) vs. input (ng) Yields as low as 2 nM can typically be sequenced 10 nM PCR-free yield from just 100 ng input
- 13. Sample to Insight Compatible with downstream hybrid capture technologies 13 QIAseq FX Library preparation: - gDNA fragmentation - Barcoded adapter ligation - Library amplification Purified gDNA 1 ng–1 µg Library QC Innovative NGS library prep methods Hybrid capture Target enrichment (IDT xGen, Agilent SureSelect) QIAseq FX library Sequence selected library http://eu.idtdna.com/pages/products/nextgen/target-capture#
- 14. Sample to Insight Mechanical-quality fragmentation from an enzymatic workflow Innovative NGS library prep methods 14 Sample-to-sample fragmentation reproducibility 0 200 400 600 5 min 10 min Averagefragmentsize(bp) Fragmentation time Frag. #1 Frag. #2 Frag. #3 Frag. #4 Customize fragment size by adjusting incubation time 0 200 400 600 5 min 10 minAveragefragmentsize (bp) Fragmentation time Input DNA species Bacterial Mix Human 250 bp 450 bp 1000 bp
- 15. Sample to Insight QIAseq FX exhibits less G/C bias than comparable methods Innovative NGS library prep methods 15 QIAGEN QIAseq FX Supplier N – Enzymatic shearing Mechanical shearing + Standard LP (Tagmentation not possible at 100 ng input) QIAGEN QIAseq FX Supplier N - Enzymatic Mechanical shearing + Standard LP Supplier I - Tagmentation
- 16. Sample to Insight 0 10 20 30 40 50 0 50 100 150 %individualnucleotide read position (nt) Supplier N - 100 ng A T C G 0 10 20 30 40 50 0 50 100 150 %individualnucleotide read position (nt) Supplier I - 1 ng A T C G 0 10 20 30 40 50 0 50 100 150 %individualnucleotide read position (nt) QIAseq FX 100 ng A T C G 0 10 20 30 40 50 0 50 100 150 %individualnucleotide read position (nt) QIAseq FX 1 ng A T C G QIAseq FX generates a purer random base composition Innovative NGS library prep methods 16
- 17. Sample to Insight Superior genomic coverage and duplication rate Innovative NGS library prep methods 17 0 0.02 0.04 0.06 0.08 0.1 0.12 0 50 100 Fractionoftargetgenome Coverage depth (X) Coverage distribution QIAseq FX (100 ng) Supplier N – Enzymatic (100 ng) Mechanical shearing + Standard LP (100 ng) Supplier I – Tagmentation (1 ng) QIAseq FX (1 ng and 100 ng*) Supplier N – Enzymatic (1ng) Mechanical shearing + Standard LP (1 ng) Supplier I – Tagmentation (1 ng) Duplication rate, 1 ng input Gold- standard % duplication
- 18. Sample to Insight Agenda Innovative NGS library prep methods 18 1 Introduction FX technology for NGS library construction Single cell analysis Single cell DNA sequencing Single cell RNA sequencing 2 3 4 5
- 19. Sample to Insight Cells differ on the genome level 19 Genome variations occur in health and disease (1) Iourov, I.Y. et al. (2010) Somatic Genome Variations in Health and Disease, Curr Genomics 11(6) Somatic genome variations consist of : Aneuploidy Structural rearrangements Copy number variations Gene mutations Somatic genome variations Occur during normal development/aging Contribute to pathogenesis Are the cause of diseases such as cancer, autoimmune, brain and other diseases Examples (1) Aneuploidy in pre-implantation embryos occurs in 15–91% of samples Aneuploidy in skin fibroblasts occurs in adults Middle age: in 2.2% of cells Aged: in 4.4% of cells Almost all cancers are caused by different types of genome variations including aneuploidy/polyploidy, structural rearrangements, gene amplifications, gene mutations Innovative NGS library prep methods
- 20. Sample to Insight Seemingly identical cells – unique transcriptional patterns Innovative NGS library prep methods 20 Cells change their transcription pattern: (1) Kumar L.M. et al. (2014) Deconstructing transcriptional heterogeneity in pluripotent stem cells. Nature 4;516 The transcriptome of a cell is not fixed but dynamic The transcriptome reflects the Function of the cell Type of the cell Cell stage Gene expression is influenced by intrinsic or extrinsic factors (signaling response, stress response) Only on single cell level you obtain: Real (not average) transcriptome gene expression data Allelic expression data A deeper understanding of the transcription dynamics within a cell Heat map of single cell RNA-seq data for selected pluripotency regulators (1)
- 21. Sample to Insight Single cell analysis enables new insights 21 CTC = Circulating tumor cells, PGD = Pre-implantation genetic diagnosis Cellular heterogeneity Detection and analysis of rare cells (example: CTC from liquid biopsy) Identification of cell subpopulations based on genomic structure or gene expression (tumors, tissues, immune cells, cell cultures) Limited availability of cells Analysis of limited sample material (example: embryo biopsy for PGD, fine-needle aspirates) ApplicationReason Biological insights instead of data from an aggregate No data Bulk result Single cell data Innovative NGS library prep methods
- 22. Sample to Insight Agenda Innovative NGS library prep methods 22 1 Introduction FX technology for NGS library construction Single cell analysis Single cell DNA sequencing Single cell RNA sequencing 2 3 4 5
- 23. Sample to Insight Discover the QIAseq FX Single Cell DNA Library Kit 23 Maximize coverage Superior and more uniform genome coverage compared to other kits High sequence fidelity MDA-based amplification technology, proven for higher fidelity compared to PCR-based methods Enables biobanking Excess amplified DNA can be stored for follow-up use, perfect for confirming novel mutations or structural variants. Higher diversity libraries PCR-free workflow, better library diversity by eliminating PCR-duplicates Less GC-bias Superior presentation of GC-rich regions, perfect for bacteria with high GC- content genomes Robust and streamlined workflow Everything in one package, single-use adapters cut down on contamination possibilities, no need for extensive QC Minimize hands-on-time Under 4 h workflow from single cell to library, without any additional kits Superior sensitivity The only kit sensitive enough for single bacterial genomes QIAseq FX Single Cell DNA Library Kit Innovative NGS library prep methods
- 24. Sample to Insight For single-cell DNA sequencing Innovative NGS library prep methods 24 Ideally suited for The analysis of inter-cellular genome heterogeneity The analysis of aneuploidy and sub-chromosomal copy number variations Sequence variation analysis (SNV, structural variants) in single cells Whole genome sequencing from rare samples Resequencing or de-novo sequencing of unculturable microorganisms For new type of experiments such as low-pass sequencing, consensus-based variant calling QIAseq FX Single Cell DNA Library Kit
- 25. Sample to Insight QIAseq FX Single Cell DNA Library Kit Complete cell-to-library solution 25 Primary sample isolation Single cell isolation NGS library construction NGS run Data analysis InterpretationSample Insight Single eukaryotic cell Single bacterial cell Picogram levels of purified DNA Whole genome NGS Library Illumina-compatible Sequence variants Structural variants Aneuploidy Bacterial genomes Innovative NGS library prep methods
- 26. Sample to Insight QIAseq FX Single Cell DNA Library Kit: kit contents Innovative NGS library prep methods 26 Both kits contain: Cell lysis reagents Enzymes and buffers for whole genome amplification Enzymatic DNA fragmentation Single-step NGS library preparation Single-use, disposable Illumina Adapters in 96-well format Multiple reagent aliquots to reduce contamination risk and freeze-thaw cycles What is not included: AMPure XP beads for library purification PCR reagents for library amplification: not needed as the entire workflow is PCR-free qPCR reagents for library quantification: recommended for accurate flow-cell loading Cat No./ID: 180713 QIAseq FX Single Cell DNA Library Kit (24) Cat No./ID: 180715 QIAseq FX Single Cell DNA Library Kit (96)
- 27. Sample to Insight Innovative NGS library prep methods 27 QIAseq FX Single Cell DNA Library Kit: the workflow Cell lysis From single eukaryotic or bacterial cells, or small amounts (pg–ng) of intact gDNA Starting with 4 µl cell material in PBS (included) Prepare lysis buffer, mix with cells, incubate for 10 minutes at 65°C. If using purified DNA as input, incubate for 3 minutes at room temperature Hold at 4°C
- 28. Sample to Insight Innovative NGS library prep methods 28 QIAseq FX Single Cell DNA Library Kit: the workflow Whole genome amplification Prepare WGA master mix, mix with lysed cells, incubate for 2 h Amplified gDNA can be used directly or frozen until needed There will be an excess of amplified gDNA, this can be stored for later use or follow-up studies (i.e. confirming deletions detected with NGS via PCR or Sanger sequencing) Library preparation accepts a wide range of inputs, so quantification of the amplified DNA is not needed
- 29. Sample to Insight Innovative NGS library prep methods 29 QIAseq FX Single Cell DNA Library Kit: the workflow NGS library preparation Prepare FX master mix, add to diluted WGA 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 master mix, add to samples and incubate for 15 min to produce library Cell lysis 15 min WGA 2 h FX library preparation 70 min Purification 20 min ILLUMINA sequencing 3h 45 min with ~40 min hands-on time
- 30. Sample to Insight Innovative NGS library prep methods 30 QIAseq FX Single Cell DNA Library Kit: the workflow Library purification Remove excess adapters with double-sided Agencourt 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 lysis 15 min WGA 2 h FX library preparation 70 min Purification 20 min ILLUMINA sequencing 3h 45 min with ~40 min hands-on time
- 31. Sample to Insight Discover complete genome coverage 31 Perfect for low-pass sequencing Don’t miss out on variants or structural features due to low coverage or locus drop-outs See more of the genome with the same sequencing depth Innovative NGS library prep methods Libraries generated from single PBMC using the QIAseq FX DNA Library Kit or kits from two other suppliers and sequenced at low depth using MiSeq. Data were analyzed according to Zhang C.Z. et. al “Calibrating genomic and allelic coverage bias in single cell sequencing“, (2015) Nat. Commun. 6, 6822. Comprehensive genome coverage Genome coverage of various kits
- 32. Sample to Insight More uniform coverage, even with GC-rich regions 32 Perfect for bacteria with high GC- content genomes Coverage of traditionally difficult-to-sequence regions Innovative NGS library prep methods Coverage versus GC content Libraries were generated from single PBMC using the QIAseq FX DNA Library Kit or kits from two other suppliers and sequenced at low depth on the MiSeq. Data was analyzed using the CLC Genomic workbench 8.5.1. Sequence GC-rich regions
- 33. Sample to Insight Highest fidelity sequence data: Have confidence in your results 33 Perfect for low-pass consensus variant calling Lower background when analyzing sequence variants or mutations and small indels Fewer spurious sequence errors in your dataset Fewer false positives Innovative NGS library prep methods Single cell libraries from isolated PBMCs were sequenced with an Illumina MiSeq. Reads were mapped to the human genome (hg19) and sequence mismatches between NGS data and the reference were computed using the CLC Genomic workbench 8.5.1. Data plotted are the mean proportion of sequence differences +/– standard deviation for 3 replicates. Combined error-rate of several single cell NGS methods Highest sequence fidelity
- 34. Sample to Insight Analyze copy number variants and aneuploidy 34 Biobanking allows follow-up experiments: confirm structural variations with PCR or Sanger sequencing With comprehensive coverage, detect structural variants regardless of where they are in the genome Innovative NGS library prep methods QIAseq FX Single Cell DNA libraries from PBMCs and Jurkat cells were sequenced to 0.1x depth on a MiSeq. Reads were mapped to human genome (GRCh38) and the copy number variation of Jurkat vs PBMCs (control diploid cells) was assessed using the methods published in: Chao Xie, Martti T Tammi, “CNV-seq, a new method to detect copy number variation using high-throughput sequencing”, BMC Bioinformatics, 2009,10:80. The plot is the Log2 ratio (Jurkat/PBMC) of coverage using a window size of 500 Kb for chromosome 2 from a cell with an approx. 25 Mbp deletion. Detection of a 25 Mbp deletion in a single cell Analyze CNVs and aneuploidy
- 35. Sample to Insight High-yield WGA enables biobanking and confirmatory testing 35 Follow-up tests to confirm structural variants or sequence variants or novel discoveries Store unused amplified gDNA at –20 for later use Innovative NGS library prep methods Data from 4 individual PBMCs for each kit, with the kit from Supplier R, no extra DNA was available for storage. Yields of amplified gDNA of various kits Biobanking enables follow-up testing
- 36. Sample to Insight Robust FX accepts a wide range of inputs: Save time on QC 36 PCR-free libraries from a wide range of amplified gDNA inputs Go directly from amplified gDNA to library prep: simple dilution for all samples No need to quantitate amplified gDNA: save time on QC Innovative NGS library prep methods In this experiment, libraries were prepared from different amounts of the same pool of amplified gDNA.The library yield after the final purification is shown. Any libraries over 2 nM concentration can be sequenced directly and do not need PCR amplification. Consistent results with less QC Yields of generated library vs DNA input
- 37. Sample to Insight Highly tunable fragmentation: Determine insert size 37 Adjust insert size with longer or shorter FX incubation Insert size consistent with varying amounts of amplified gDNA Innovative NGS library prep methods Libraries with a varying amount of amplified gDNA were prepared and subjected to a gradient of FX fragmentation times. The plots show that the longer the incubation times, the shorter the inserts, and that this approximately follows the same trend regardless of the amount of input used. Mean insert size per incubation time Insert size determined by fragmentation incubation time
- 38. Sample to Insight Agenda Innovative NGS library prep methods 38 1 Introduction FX technology for NGS library construction Single cell analysis Single cell DNA sequencing Single cell RNA sequencing 2 3 4 5
- 39. Sample to Insight Discover the QIAseq FX Single Cell DNA Library Kit 39 Maximize transcript discovery Discover a greater number of transcripts with the same sequencing depth High sequence fidelity High-fidelity WTA minimizes spurious sequence errors. Ideal for viral RNA sequencing. Enables biobanking Excess amplified DNA can be stored for follow-up use, perfect for confirming novel mutations or structural variants Higher diversity libraries WTA technology with less dropouts and less length-bias against long transcripts and highly efficient library preparation with maximized conversion rate No PCR duplicates PCR-free workflow eliminating PCR duplicates Robust and streamlined workflow Everything needed in one package. Single-use adaptors cut down on contamination possibilities, no need for extensive QC. Minimize hands-on-time 5.5 h workflow from single cell to library, without any additional kits Uncover mRNA and lincRNA Sequence lincRNA and mRNA with a single protocol QIAseq FX Single Cell RNA Library Kit Innovative NGS library prep methods
- 40. Sample to Insight For single cell RNA sequencing Innovative NGS library prep methods 40 Ideally suited for Sensitive transcript discovery and differential gene expression analysis from single eukaryotic cells Transcriptome analysis with best-in-class transcript detection The analysis of both mRNA and long non-coding RNAs in a single dataset Studies in inter-cellular heterogeneity RNA-seq from limited amounts of difficult-to-obtain samples Studies in infectious disease research QIAseq FX Single Cell RNA Library Kit
- 41. Sample to Insight QIAseq FX Single Cell RNA Library Kit 41 Complete cell-to-library solution Primary sample isolation Single cell isolation NGS Library construction NGS run Data analysis InterpretationSample Insight Single eukaryotic cell Picogram levels of purified RNA from different species Whole genome NGS Library Illumina-compatible Transcript discovery Gene expression Differential expression Viral RNA Innovative NGS library prep methods
- 42. Sample to Insight QIAseq FX Single Cell RNA Library Kit: the contents Innovative NGS library prep methods 42 Both kits contain: Cell lysis and gDNA degradation reagents Reverse transcription primers, buffers and enzyme Enzymes and buffers for cDNA amplification Enzymatic cDNA fragmentation Single-step NGS library preparation Single-use, disposable Illumina adapters in 96-well format Multiple reagent aliquots to reduce contamination risk and freeze-thaw cycles What is not included: Agencourt AMPure XP beads for library purification PCR reagents for library amplification: not needed as the entire workflow is PCR-free qPCR reagents for library quantification: recommended for accurate flow-cell loading Cat No./ID: 180733 QIAseq FX Single Cell RNA Library Kit (24) Cat No./ID: 180735 QIAseq FX Single Cell RNA Library Kit (96)
- 43. Sample to Insight Innovative NGS library prep methods 43 QIAseq FX Single Cell RNA Library Kit: the workflow Cell lysis From single eukaryotic or small amounts (pg – 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 lysis 15 min WTA 3 h 45 min FX library preparation 70 min Purification 20 min Illumina sequencing 5.5h with ~1h hands-on-time
- 44. Sample to Insight Innovative NGS library prep methods 44 QIAseq FX Single Cell RNA Library Kit: the workflow Whole transcriptome amplification Prepare RT master mix, 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, this can be stored for later use or follow-up studies (i.e. 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 lysis 15 min WTA 3 h 45 min FX library preparation 70 min Purification 20 min Illumina sequencing 5.5h with ~1h hands-on-time
- 45. Sample to Insight Innovative NGS library prep methods 45 QIAseq FX Single Cell RNA Library Kit: the workflow Cell lysis 15 min WTA 3 h 45 min FX library preparation 70 min Purification 20 min Illumina sequencing 5.5h with ~1h hands-on-time NGS library preparation Prepare FX master mix, 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 master mix, add to samples and incubate for 15 min to produce library.
- 46. Sample to Insight Innovative NGS library prep methods 46 QIAseq FX Single Cell RNA Library Kit: the workflow Library purification Remove excess adapters with double-sided Agencourt AMPure XP cut-off 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 lysis 15 min WTA 3 h 45 min FX library preparation 70 min Purification 20 min Illumina sequencing 5.5h with ~1h hands-on-time
- 47. Sample to Insight Discover more: higher library diversity than competing workflows 47 See more of the transcriptome Discover a greater number of transcripts with the same sequencing depth Spend reads sequencing RNA molecules, not PCR duplicates Innovative NGS library prep methods Libraries were generated from 100 pg of input from the same pool of RNA isolated from PBMCs with either the QIAseq FX Single Cell RNA Library Kit or a commonly used workflow employing separate kits for whole transcriptome amplification and library preparation from Suppliers C/I. Libraries were multiplexed and sequenced on the same MiSeq to approximately the same sequencing depth. After QC and mapping, the number of annotated transcripts with TPM >1 was computed. Data were then rarified repeatedly, where a subset of reads was selected at random, and the number of annotated transcripts with TPM >1 was computed for each sub-sampled set of reads. This was repeated at multiple read depths. Discovery plot High library diversity
- 48. Sample to Insight Discover more: high library diversity from single cells 48 Usually, single cell libraries are easily saturated Sequence more, discover more Innovative NGS library prep methods Libraries were generated from single isolated PBMCs the QIAseq FX Single Cell RNA Library Kit. After QC and mapping, the number of annotated transcripts with TPM >1 was computed. Data were then rarified repeatedly, where a subset of reads was selected at random, and the number of annotated transcripts with TPM >1 was computed for each sub-sampled set of reads. This was repeated at multiple read depths. High library diversity: even from single cells Discovery plot
- 49. Sample to Insight Discover more: high number of transcripts detected 49 High diversity libraries maximize transcript detection in each single cell Innovative NGS library prep methods Libraries were generated from 3 single isolated HeLa cells or from 100 pg of bulk RNA isolated from the same cells using the QIAseq FX Single Cell RNA Library Kit. After QC and mapping, the number of annotated transcripts with FPKM>1 was computed. Maximize transcript detection Number of transcripts
- 50. Sample to Insight High dataset diversity provided by PCR-free library preparation 50 PCR-free workflow eliminates PCR duplicates Frees read-depth for discovering new transcripts Innovative NGS library prep methods Libraries were generated from single isolated PBMCs using the QIAseq FX Single Cell RNA Library Kit and a kit from Supplier C. Libraries were multiplexed and sequenced on the same run of a MiSeq instrument to equal sequencing depth. Duplicates were calculated using FastQC. PCR duplicates represent reads that provide no additional insight into the sample, and detract from the sensitivity of the experiment by consuming valuable sequencing depth. Duplicate level Sequence new transcripts not PCR duplicates
- 51. Sample to Insight Uncover linc and mRNA with a single technique 51 Sequence mRNA and lincRNA in a single experiment Examine protein- coding gene expression and regulatory RNAs simultaneously Innovative NGS library prep methods Libraries were prepared from single PBMCs or HeLa cells using the QIAseq FX Single Cell RNA Library Kit or a commonly used workflow employing separate kits for whole transcriptome amplification and library preparation from Suppliers C/I. Libraries were multiplexed and sequenced on the same MiSeq to approximately the same sequencing depth. After QC and mapping, the proportion of reads mapping to annotated lincRNA for each library was calculated. Sequence lincRNA and mRNA with a single protocol % of detected lincRNA
- 52. Sample to Insight High proportion of mRNA reads 52 Discover the insights only a combined mRNA and lncRNA dataset can bring Use single cell sensitivity to analyze mRNA expression Innovative NGS library prep methods Libraries were prepared from single isolated PBMCs. The QIAseq FX Single Cell RNA Libraries were multiplexed and sequenced on an Illumina NextSeq. After QC and mapping via STAR, the proportion of reads mapping to each GO annotation was calculated with HTSeq. Maintains a high proportion of protein-coding reads RNA biotypes
- 53. Sample to Insight Consistent, robust cDNA amplification enables biobanking 53 Protocol consistently generates excess cDNA Consistent WTA produces consistent libraries Freeze excess amplified cDNA for follow-up studies or confirmatory testing Innovative NGS library prep methods Whole transcriptome amplification yield from single cells from the QIAseq FX Single Cell RNA Library Kit and a competing, PCR-based method (Supplier C). 8 Replicates from different single cells are shown. Yield of amplified cDNA in ng Robust WTA enables biobanking
- 54. Sample to Insight Summary Innovative NGS library prep methods 54 QIASeq FX Kits for NGS library construction use an innovative technology that: Uses a fast and streamlined workflow, without the need of additional kits and highly specialized instrumentation Delivers high yields of high-quality libraries ready for sequencing on Illumina platforms Addresses different applications DNA libraries from a wide range of input DNA PCR-free DNA libraries from single eukaryotic and bacterial cells and very limited purified DNA material PCR-free RNA libraries from single eukaryotic cells, limited purified RNA material and viral RNA
- 55. Sample to Insight 55 Upcoming webinars “Overview of NGS technologies and innovative NGS library prep methods” Part 1: Introduction to next-generation sequencing (NGS) technology Part 2: Innovative NGS library construction technology Part 3: Advanced NGS library prep for challenging samples Innovative NGS library prep methods
- 56. Sample to Insight 56 Questions? Thank you for attending! All our solutions from Sample to Insight on: QIAGEN.com Contact QIAGEN Technical Service Call: 1-800-426-8157 for US Call: +49 2103-29-12400 EU Email: techservice-na@QIAGEN.com techservice-eu@QIAGEN.com QIASeq.NGS@QIAGEN.com QIAwebinars@QIAGEN.com Innovative NGS library prep methods
Notes de l'éditeur
- This slide describes some of the main challenges in whole genome and whole exome sequencing that we think this technology can help our customers solve. First is the need to generate libraries, sequence those libraries, and return a dataset or result as quickly as possible. For some customers, extra speed means the ability to increase their scale of operations, or to operate with lower labor costs. For others, the narrow window of opportunity for making clinical decisions based on NGS data mandates a maximally accelerated process. Second, large region-of-interest applications like whole genome and whole exome sequencing depend on the ability to preserve the genomic complexity of a sample from the point of collection all the way to analysis. Current options for DNA fragmentation often force researchers to choose between either speed or high library complexity. With the novel enzymatic fragmentation solution in QIAseq FX, we think we can bring together the best elements of both. Finally, every NGS lab must carefully manage their costs. By providing a streamlined technology that is easy to automate and eliminates the high costs associated with mechanical shearing and tagmentation, we think labs will find QIAseq FX a valuable addition to their NGS toolbox.
- All short read sequencing technologies including Illumina and Ion Torrent require high molecular weight genomic DNA to be fragmented into short, typically 200-600bp pieces prior to library prep. This step is show in the middle of the workflow scheme at the bottom of this slide. As I mentioned, the two market-leading solutions to this fragmentation problem are: First, Covaris: an acoustic shearing technology that requires the purchase of (and lab space for) highly specialized equipment and expensive single-use glass tubes, and Second, Nextera: an all-enzymatic method in which DNA is fragmented and adapters are added at the same time using a transposase or “tagmentation” reaction.
- For all of these reasons, we are excited to launch the new QIAseq FX DNA Library Kit for Illumina-based sequencing applications. This kit brings together customizable DNA fragmentation, compatibility with a wide range of DNA inputs, the speed of an all-enzymatic workflow, and gold-standard quality that outperforms other enzymatic methods.
- Finally, while Qiagen’s High Fidelity library amplification reagents are included in the QIAseq FX kit, we do want to highlight the potential to use the QIAseq FX fragmentation and adapter ligation chemistries in PCR-free workflows. Shown here are two PCR-free reaction conditions (blue and green) compared with Covaris + Library Amplification (black) and QIAseq FX + Library Amplification (red), showing no significant differences between genomic coverage with or without PCR. Library yields from this kit are also highly linear, with the amount of total library generated directly proportional to the amount of input DNA (the figure in the lower right). Our data suggest this kit can generate the 2nM library concentration needed for sequencing without library amplification by starting from as little as 50ng input DNA.
- QIAseq FX also offers one of the simplest workflows on the market – just three reactions – for easy manual implementation or straightforward automation on liquid handling platforms. Starting with as little as 1ng or as much as 1 microgram of input DNA, the FX reaction fragments, end repairs, and A-tails the DNA in a little under an hour. This is followed by adapter ligation and a high fidelity amplification step using Qiagen’s proprietary HiFi Master mix. 96 uniquely dual-barcoded adapters compatible with all Illumina sequencers are included in the kit, in a foil-sealed 96-well plate format for ease of use, easy automation, and reduced risk of cross-contamination. The foil seal means you pierce exactly as many adapter well as your batch size demands – the unused adapters just go back in the freezer for later use.
- In our hands, fragmentation profiles generated using Qiagen’s FX technology are highly comparable to Covaris in both reproducibility and fragment size tunability. In the top two figures, you can see that fragmentation of multiple samples using the same FX reaction condition is highly reproducible as reported by both Bioanalyzer and also insert size calculated by downstream analysis. Likewise, in the bottom left figure, we target three different fragment sizes with each of two input amounts, demonstrating both the tunability of the kit and also the flexibility to accommodate a range of DNA inputs. Finally, in the lower right, we’ve treated human genomic DNA and a bacterial DNA mixture designed to have broad G/C content with either a 5 minute or 10 minute reaction to demonstrate consistent results regardless of sample origin.
- Due to its highly sequence-independent fragmentation, QIAseq FX exhibits excellent G/C bias similar to mechanical shearing. At 100ng input (the figure on the left), QIAseq FX (in blue) overlays closely with data generated from Covaris-sheared libraries (in black). An all-enzymatic protocol using NEB Fragmentase and NEB Ultra library prep (in green) demonstrates much higher bias. On the right, QIAseq FX also outperforms competitors at 1ng input – here in addition to QIAseq FX (in blue), Covaris (in black), and NEB (in green), we’ve included Nextera Tagmentation (red), again showing the transposase’s preference for sequences around approximately 30% G/C.
- Compared to other currently available enzymatic library prep methods, QIAseq FX generates sequencing data with a more nearly random 25% per base (A, C, G, T) per cycle sequence content – even at the sensitive read start position. In the figures above, we compare the per-cycle base composition of 150bp sequencing data generated using 100ng DNA input prepared using NEB Fragmentase (top left) versus QIAseq FX, as well as data from 1ng DNA input prepared using Nextera (bottom left) versus QIAseq FX. At either 1ng or 100ng of input, QIAseq FX produces a more nearly random base composition that is most similar to mechanical shearing methods. This bias-free base composition performs better on Illumina sequencers, leading to a lower fraction of low-quality reads and higher sequencing data yields for the same cost.
- Low sequence bias also generates more even, predictable genomic coverage. The single, narrow peak for QIAseq FX in the plot on the left shows that the majority of genomic targets have very similar total coverage depth, meaning you don’t need to do a lot of additional sequencing to bring low-coverage targets up into an interpretable range. In contrast, the peak for Nextera (in red) tends to be broader, with a lower average coverage depth generated by the same amount of sequencing. Likewise, the bimodal distribution for NEB Fragmentase (in green) shows that while about half of targets are well-covered, a significant peak near zero contains sequences that are poorly covered or not covered at all. On the right, we show duplication rate, or the rate at which sequence reads are discarded during analysis because they are exact matches for a previous read. Duplication rate tells you what fraction of a dataset was derived from PCR copies created during sample processing rather than new genomic diversity present in the original sample DNA. Libraries with low complexity will have a higher duplication rate, while high quality libraries have sufficient genomic diversity to cluster the flowcell with nearly 100% unique sequences. At 1 nanogram of input, QIAseq FX (in blue, second from the right) performs comparably to Covaris, with sub-1% duplication. This is in contrast to the NEB and Nextera methods tested, which each show significant fractions of the data generated coming from PCR duplicate molecules. At 100ng input (blue, far right), QIAseq FX duplication rates are even lower, approaching the level typically seen from PCR-free workflows.
- Computed maximum genome coverage is plotted. This is the maximum achievable coverage of the genome, above which additional sequencing depth does not increase the proportion of the genome covered due to limited library complexity. The higher this number, the higher the proportion of the genome can be detected. This holds true regardless of sequencing depths, so regardless of the number of reads available, a library made with QIAseq FX SC DNA will cover more of the genome than a library prepared with competing methods.
- PCR based kits from supplier R and Y introduce GC bias and lead to underrepresentation of GC-rich regions. This can be extremely important since features of interest may be located in GC-rich stretches, or researchers may be working with bacterial samples with GC-rich genomes.
- Higher numbers mean a greater number of positions where the sequence in the dataset does not match the reference genome. Of course some of these sites will be normal polymorphisms or mutations, but many of these mismatches with either of the competing kits will represent false positives introduced during library preparation. These mismatches can increase background when calling variants, and can be identified as false positives in some cases.
- Single cell libraries from PBMCs and Jurkat cells were prepared using the QIAseq FX Single Cell DNA Library Kit and were sequenced to 0.1x depth on a MiSeq. Reads were mapped to human genome (GRCh38) and the copy number variation of Jurkat vs PBMCs (control diploid cells) was assessed using the methods published in: Chao Xie, Martti T Tammi, “CNV-seq, a new method to detect copy number variation using high-throughput sequencing”, BMC Bioinformatics, 2009,10:80, DOI: 10.1186/1471-2105-10-80.Plotted is the Log2 ratio(Jurkat/PBMC) of coverage using a window size of 500Kb for chromosome 2 from a cell with an approximately 2.5 Mbp deletion CNV detection with similar bioinformatics methods is essential for researchers in oncology and PGD.
- Other kits use either the entire amplified gDNA sample or almost all of the gDNA for library prep, meaning that if something particularly novel or interesting is found, there is no way to confirm this, since the original cell was destroyed and the amplified gDNA is gone. At most, the NGS libraries can be sequenced to greater depth, or a few ng of material remains. With our kit, we produce huge amounts of gDNA that isn‘t needed for the PCR-free library preparation, and this can be stored for later use. This is pseudo-destructive testing: the original cell is gone, but with a high-fidelity, complete copy of the gDNA stored in the freezer, we can go back for follow-up experiments, for example to sanger sequence the junctions of a novel structural rearrangement or virus integration site. This chart shows data from 4 individual PBMCs for each kit, with the kit from supplier R, no extra DNA was available for storage.
- This demonstrates the robustness of the workflow: since we get sufficient library from a wide range of amplified gDNA inputs, and the WGA typically generates these amounts of input if cells are in good condition, we are able to skip the quantification of amplified gDNA prior to library preparation. This robustness delivers direct improvements to the workflow in the lab: it could take around 2 hours to quantify 96 samples with a qubit, and at least another 1-1.5 h to set up a table in excel and dilute each sample to the correct concentration for a downstream library prep. That many dilutions will also likely contain some errors so some libraries could fail, and there is a strong chance for cross-contamination. So by pairing a whole-genome amplification that generates a consistent amount of data with a library prep that accepts a wide range of inputs, we‘re able to skip a time-intensive normalization step between amplification and library preparation. With other WGA methods (ie. supplier Y) the yield can be extremely variable, and with other library preps the range of inputs is extremely narrow and quantification must be exact. Our customers should note that when sequencing PCR-free libraries qPCR (such as the QIAseq Library Quant Kit) is highly recommended for library quantification.
- Here we made libraries with a varying amount of amplified gDNA and ran a gradient of FX fragmentation times. The plots show that the longer you incubate, the shorter the inserts get, and that more or less this follows the same trend regardless of the amount of input used (500-1500ng will be standard if the cells are in good condition and the instructions in the kit are followed, but this doesn‘t need to be quantified since the protocol is so robust).
- Libraries were generated from 100 pg of input from the same pool of RNA isolated from PBMCs with either the QIAseq FX Single Cell RNA Library Kit or a commonly used workflow employing separate kits for whole transcriptome amplification and library preparation from Suppliers C/I. Libraries were multiplexed and sequencing on the same MiSeq to approximately the same sequencing depth. 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. Plots indicate the number of transcripts that can be detected at a given sequencing depth, broadly used as a measurement of library diversity. Higher numbers indicate that, for a given sequencing level, a greater number of transcripts are detected. The number of transcripts detected using the competing kit is lower regardless of the sequencing depth, meaning that a much more limited view of the transcriptome is available. Greater transcript detection is important as it is related to both the sensitivity (or limit of detection) and dynamic range of the assay. The greater transcript discovery is due to a number of factors that maximize library diversity, including avoiding PCR during WTA (causes dropouts due to stochastic effects, also introduces length-bias against long transcripts), having a highly efficient library preparation with maximized conversion rate (based on QIAseq FX, data available there), and avoiding the production of PCR duplicates during libary amplification by having a completely PCR-free workflow.
- Libraries were generated from single isolated PBMCs 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. Plots indicate the number of transcripts that can be detected at a given sequencing depth, broadly used as a measurement of library diversity. The positive slope, even at high (500k reads per cell) read depth indicates highly diverse libraries, where additional sequencing depth will continue to deliver expression data for additional transcripts. The numbers of transcripts detected with each single cell is slightly different since each cell has a different expression profile, which is also why direct comparisons with competitors are only possible with the same input material (purified RNA in the previous slide).
- Libraries were generated from 3 single isolated HeLa cells or from 100 pg of bulk RNA isolated from the same cells using the QIAseq FX Single Cell RNA Library Kit. After QC and mapping, the number of annotated transcripts with >1 TPM was computed. While each individual cell expresses a set of common as well as a set of unique genes, absolute numbers of transcripts detected in each cell are high, and at an equal sequencing depth, the number of transcripts detected in each cell was only slightly lower than the number detected in the bulk control, indicating high-diversity libraries. Absolute number of transcripts detected will differ depending on cell type. The relationship between transcripts detected in single cells and bulk samples will differ depending on the heterogeneity of the cell population.
- Libraries were generated from single isolated PBMCs the QIAseq FX Single Cell RNA Library Kit. Libraries were multiplexed and sequenced on the same run of a MiSeq to equal sequencing depth. Duplicates were calculated using FastQC. PCR duplicates represent reads that provide no additional insight into the sample, and detract from the sensitivity of the experiment by consuming valuable sequencing depth. Note that 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 transcripts high abundance and probability, which dictates that at higher transcript abundance the chance of two reads being counted as a duplicate increases (using this calculation method). Our customers should note that when sequencing PCR-free libraries qPCR (such as the QIAseq Library Quant Kit) is highly recommended for library quantification.
- Libraries were prepared from single PBMCs or HeLa cells using the QIAseq FX Single Cell RNA Library Kit or a commonly used workflow employing separate kits for whole transcriptome amplification and library preparation from Suppliers C/I. Libraries were multiplexed and sequencing on the same MiSeq to approximately the same sequencing depth. After QC and mapping, the proportion of reads mapping to annotated lincRNA for each library was calculated. lncRNAs are often not detected with other methods due to their length (PCR-bias against long transcripts), but represent important regulatory molecules that can add another layer of insight to a dataset.
- Libraries were prepared from single isolated PBMCs or from 100 pg or 1 ng aliquots of RNA extracted from PBMCs. The QIAseq FX Single Cell RNA Libraries were multiplexed and sequenced on an Illumina NextSeq. After QC and mapping via STAR, the proportion of reads mapping to each GO annotation was calculated with HTSeq. Since this kit is capturing polyadenylated RNAs regardless of the source, we see a fairly high proportion of reads mapping to known lncRNAs. Generally lncRNAs are expressed at low abundance, and most other workflows fail to capture these in part due to their rarity and in part due to their length: PCR-based methods of cDNA amplification are inherently biased against long transcripts, including lncRNAs and long mRNAs. Note that while a significant proportion of reads mapped to known lncRNAs, we still have good coverage of mRNAs. This is important since very few users will be interested only in regulatory RNAs: good coverage of lncRNA and mRNA allows us to analyze regulatory transcripts as well as the expression of the genes they are regulating.
- Whole transcriptome amplification yield from single cells from the QIAseq FX Single Cell RNA Library Kit and a competing, PCR-based method (Supplier C). 8 Replicates from different single cells are shown. Amplification yield from the QIAseq FX Single Cell RNA Library kit is high (~20 µg) and consistent, ensuring enough cDNA is available for library preparation. Low and variable cDNA yields may not be sufficient for downstream NGS library preparation and may require additional QC steps after WTA, which can be difficult and inaccurate at such low levels. Additionally, library quality from sample to sample may be inconsistent due to variable input, introducing additional technical noise into the dataset. The extra cDNA not used in library preparation with the QIAseq method can be frozen and stored for follow-up experiments, something that is not possible with other kits. This means that with competitors there is absolutely no possibility to confirm or re-analyze important findings, since the cell is destroyed and the cDNA is gone.