Single-Cell Analysis - Powered by REPLI-g: Single Cell Analysis Series Part 1
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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.
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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
- 36. Sample to Insight Questions 36 Q&A Single-Cell Analysis – From Sample to Insight Single Cell Analysis- From Sample to Insight, Hilden, Oct. 2015
Notes de l'éditeur
- Amplified single sperm (haploid genome) with REPLI-g, ran microsatellite (C)and SNP assays (A and B)