Quality Control of RNA Samples - For Gene-Expression Results you Can Rely on
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By their very nature RNA molecules, especially mRNA and regulator RNA, are labile and can be highly unstable and sensitive to heat, UV and RNase contamination. The quality, relevance and scientific impact of gene expression results directly depends on the ability to extract RNA without losing any fraction of interest, while preserving the integrity of the biological information it carries. RNA quality control is thus critical to ensure high-quality results and for turning these results into actionable insights with confidence. In this webinar, we will introduce you to the main parameters influencing RNA-based assays and their respective impact on downstream applications, discuss how to monitor them and cover the advantages of automation for quality control along complex workflows.
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Quality Control of RNA Samples - For Gene-Expression Results you Can Rely on
- 1. Sample to Insight 1 Pierre-Henri Ferdinand Global Product Management Pierre-henri.ferdinand@qiagen.com Quality Control of RNA samples — For gene-expression results you can rely on Quality Control of RNA samples
- 2. Sample to Insight Legal Disclaimer 2 ▪ 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. Quality Control of RNA samples
- 3. Sample to Insight Outline Quality Control of RNA samples 3 Why is RNA quality control so important1 Main parameters for RNA QC2 Fast and reliable quality control3 Comparison of RIN and RIS4 Wrap up5
- 4. Sample to Insight 4 http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002165 “Low reproducibility rates within life science research undermine cumulative knowledge production and contribute to both delays and costs of therapeutic drug development. An analysis of past studies indicates that the cumulative (total) prevalence of irreproducible preclinical research exceeds 50%, resulting in approximately US$28 Billion/year spent on preclinical research that is not reproducible—inthe UnitedStatesalone.” Freedman LP, et al. (2015) The Economics of Reproducibility in Preclinical Research. PLoS Biol. Quality Control of RNA samples
- 6. Sample to Insight 6 Non reproducibleReproducible biomedical research 50% • Culture of “publish or perish” • Inefficiencies in designing, conducting, and reporting of studies • Lack of standardization of sample quality for inter-lab reproducibility Some solutions for tackling the issue: • Implementing quality control procedures at key steps of laboratory workflows to help standardizing the parameters of the samples, and thus the quality of the data generated. • Combining lab automation with quality chemistries to enhance reproducibility of experiments, bringing confidence in data interpretation. Quality Control of RNA samples
- 7. Sample to Insight 7 QC emphasizes on gaining insight into a sample quality and assessing its suitability for downstream applications and its potential for generating reliable results. QC plays an important role when it comes to developing routine procedures or troubleshooting an experiment. µg ? Purity? Quantity? Integrity? Size? Are these parameters in the range of my experiment’s requirements for generating high-quality results? RNA Quality? What is RNA sample QC? Quality Control of RNA samples
- 8. Sample to Insight 8 Why is sample QC so important? Risk of failure Molecular biology workflows are complex, error- and failure-prone multi-step procedures A lot of things can potentially go wrong during workflows RNA can be unstable: sensitive to heat, radiations and nucleases Confidence in results At the end, only the quality of the final results matters The quality of the final results is highly influenced by quality of samples Cost aspects Downstreamapplications get more sensitive but not necessarily more robust to variations in samples quality Failure means waste of time and resources Price per sample Time qPCR 1.5 $US 4-5 hrs Sanger Sequencing 5-6 $US 4-6 hrs Next-Gen Sequencing >200 $US(5plex) 2-3 working days Affymetrix GeneChip Analysis 500-800 $US/sample > 2 working days Quality Control of RNA samples
- 9. Sample to Insight 9 Sample collection/ stabilization RNA purification, cDNA & cRNA synthesis Quantification, Normalization, Fragmentation Array Hybridization and scanning Data analysis & interpretation Gene expression Microarrays QC QC Sample collection/ stabilization RNA purification Amplification Analysis Data analysis & interpretation Gene expression RT-PCR QC Sample collection/ stabilization DNA/RNA purification NGS Library Prep Sequencing Data analysis & interpretation RNA-Seq QC QC RNA Quality Control is recommended in Gene expression workflows RNA Quality Control after purification Quality Control of RNA samples
- 10. Sample to Insight Outline Quality Control of RNA samples 10 Why is RNA quality control so important1 Main parameters for RNA QC2 Fast and reliable quality control3 Comparison of RIN and RIS4 Wrap up5
- 11. Sample to Insight Six parameters of prime relevance for sample Quality Control Quality Control of RNA samples 11 QC Criteria UV spectro. Gels Dye-based spectro. CE / µ- fluidic UV/VIS spectro. Protein contaminants (A260/280) ✓ ✓ Salts & other contaminants (A260/230) ✓ ✓ Quantity of dsDNA vs. other NA ✓ Yield ✓ (✓) ✓ ✓ ✓ Degradation/ Size distribution (✓) ✓ Sizing ✓ ✓ There is no one-for-all solution – 2 technologies cover all sample QC needs purity quantity integrity
- 12. Sample to Insight Main RNA quality parameters Quality Control of RNA samples 12 Purity Quantity Integrity What is the yield of my extraction? How much RNA is in the tube and at what concentration? Will I have enough material? When the concentration of NA is overestimated, the input amount will be too low. This leads to weak amplification and weak signal strength. When the concentration of DNA is underestimated the input amount will be too high and can lead to overuse of precious samples, increased concentration of inhibitors, false priming, unfavorable ratios, etc. What’s really in my tube? Could contamination or impurities interfere with my assay? Phenol, ethanol, salts, etc. can jeopardize sensitivity and efficiency of downstream enzymatic reactions. Large amounts of unwanted ssDNA or dsDNA template lead to overestimation of the molecule of interest and interferes with downstream applications. Does my RNA sample have the correct size distribution? Has RNA been degraded? RNA samples of poor integrity can affect PCR or sequencing reactions and lead to errors in replication and/or lower yields e.g. irrelevant CT values. Degraded samples can produce false negative results.
- 13. Sample to Insight Quality Control of RNA samples 13 • RNA QC requirements vary depending on downstream applications: RT-PCR, qRT-PCR, Microarray or RNA-Seq • Small deviations in key sample parameters can have potential impact on final results Implementation of QC procedures with relevant pass-criteria and ensuring RNA samples quality parameters are within acceptable range are essential to maximize success of experiments, thus saving time, money and peace of mind Highest quality results are only achieved from quality samples Only quality results are worth sharing
- 14. Sample to Insight Key quality indicators Quality Control of RNA samples 14 QC Criteria UV spectro. Gels Dye-based spectro. CE / µ- fluidic UV/VIS spectro. Protein contaminants (A260/280) ✓ ✓ Salts & other contaminants (A260/230) ✓ ✓ Quantity of dsDNA vs. other NA ✓ Yield ✓ (✓) ✓ ✓ ✓ Degradation/ Size distribution (✓) ✓ Sizing ✓ ✓ There is no one-for-all solution purity quantity integrity
- 15. Sample to Insight Key quality indicators Quality Control of RNA samples 15 QC Criteria UV spectro. Gels Dye-based spectro. QIAxcel Advanced QIAxpert Protein contaminants (A260/280) ✓ ✓ Salts & other contaminants (A260/230) ✓ ✓ Quantity of dsDNA vs. other NA ✓ Yield ✓ (✓) ✓ ✓ ✓ Degradation/ Size distribution (✓) ✓ Sizing ✓ ✓ purity quantity integrity There is no one-for-all solution – QIAGEN covers all your needs for sample Quality Control!
- 16. Sample to Insight Outline Quality Control of RNA samples 16 Why is RNA quality control so important1 Main parameters for RNA QC2 Fast and reliable quality control3 Comparison of RIN and RIS4 Wrap up5
- 17. Sample to Insight How does QIAGEN helps you achieving reliable QC? Quality Control of RNA samples 17 Quantity & Purity Integrity & size distribution QIAxpert QIAxcel Advanced Let lab automation work for you and do the job they are excellent at: Delivering reliable and reproducible results Performaccurate measurements, keep track of your sample quality, standardize your experiments and increase reproducibility of your results. Increase your lab productivity: automation frees your hands and your mind!
- 18. Sample to Insight Quality Control of RNA samples 18 Sample collection/ stabilization RNA purification Amplification/ NGS Library Prep Analysis Data analysis & interpretation QCQC Quantity & Purity Integrity & size distribution QIAxpert QIAxcel Advanced
- 19. Sample to Insight QIAxpert uses innovative microfluidic sample carrier 19 Key features: 1 2 3 4 5 1 2 3 4 5 Sample loading well Capillaries Microcuvette Overflow Vent hole for vacuum Only 2 µl of sample required DNA range: 1.5 ng/μl up to 2000 ng/μl dsDNA(A260) Fast analysis, up to 16 samples in less than 2 minutes Algorithm can unmixe sample’s spectra to differentiate contribution of different molecules. QIAxpert is a high-speed spectrophotometer for DNA, RNA and protein analysis. It is fast, accurate and sensitive. Quality Control of RNA samples
- 20. Sample to Insight Quality Control of RNA samples 20 Classic spectrophotometry A230: impurities A280: proteins A260: nucleic acids
- 21. Sample to Insight Quality Control of RNA samples 21 1. Absorbance measurement (and background correction) 2. Content profiling of the measured spectrum by fitting of reference spectra into • Specific DNA or RNA spectrum • Impurities spectrum • Residue spectrum 3. Quality control • Impurities spectrum • Residue spectrum • Backround spectrum • A260/A280 ratio for protein contamination QIAxpert – Unique spectral content profiling protocols Quantity of DNA or RNA you think you have Quantity of DNA or RNA you actually have
- 22. Sample to Insight QIAxpert – Excellent measurement accuracy 22 QIAxpert: lowest %CV value Qubit: high mean variation 250 ng/µl reference RNA (Agilent Technologies) Accuracy qPCR Human Reference Total RNA (Agilent Technologies) was dilutedto 250 ng/µL (dilutionfrom original solution in H2O). A total of 40 replicateswere measured, each on the QIAxpert (RNA260 app), on a Nanodrop 8000, and the Qubit system. Quality Control of RNA samples
- 23. Sample to Insight QIAxpert – Excellent linearity in RNA quantification 23 QIAxpert Nanodrop Qubit Excellent linearity Systematic overquantification Systematic underquantification Comparisonof RNA linearity using different systems Linearity Human Reference RNA (Agilent) was diluted to 1000 ng/µl, 500ng/µl, 100 ng/µl,50 ng/µl, 10 ng/µl, 5 ng/µl, and 1.5 ng/µl. A total of 5 replicatesof each dilution were measured using the QIAxpert system, a Nanodrop 8000, and the Qubit. Data shown for the QIAxpert reflectstotal NA measured with the RNeasy app. Quality Control of RNA samples
- 24. Sample to Insight With QIAxpert – tell RNA from DNA and other contaminantswithout a dye 24 High-speed microfluidics • No drop & clean action required, no cross contamination • Evaporation-safefor 2h • Flexible input & up to 16 samples in <2 min Comprehensive Export • Reports can be viewed on any browser • USB and Network data output • No extra software or computer required Easy interaction • Inbuilt touchscreen • Simple GUI • Variety of pre-installed protocols Spectral contentprofiling • Differentiationbetween molecules • Quantify and subtract identified impurities • Give best insight into samples’ quality Quality Control of RNA samples
- 25. Sample to Insight Quantity & Purity ! QIAxpert – Unique spectral content profiling protocols 25 Classic spectrophotometry Quantity Spectral Content Profiling For internal use only • DNA or RNA spectrum • Impurities spectrum • Residue spectrum Quality Control of RNA samples
- 26. Sample to Insight Quality Control of RNA samples 26 Sample collection/ stabilization RNA purification Amplification/ NGS Library Prep Analysis Data analysis & interpretation QCQC Quantity & Purity Integrity & size distribution QIAxpert QIAxcel Advanced
- 27. Sample to Insight QIAxcel Advanced allows separation, detection and analysis of NA 27 QIAxcel Advanced ▪ Fully automated DNA and RNA analysis ▪ Fast processing: 12 samples in 8 – 13 min ▪ Up to 96 samples per run ▪ Up to twenty 96-well plates with QIAxcel HT ▪ High resolution down to 3 – 5 bp up to 500 bp ▪ Safety and convenience with ready-to-use gel cartridges ▪ Digital data output QIAxcel Advanced is an automated capillary electrophoresis systemfor DNA and RNA analysis. QIAxcel Advanced allows analysis of gDNA, RNAand NGS libraries Quality Control of RNA samples
- 28. Sample to Insight QIAxcel Advanced capillary electrophoresis principle 28Quality Control of RNA samples • Reusable 12-capillary cartridges • Fast processing: 12 samples in 8-13 min • Detection limit of 0.1 ng/µl • Sample consumption < 0.1µl
- 29. Sample to Insight How does it work? Place the gel cartridge into the instrument Load samples (tube strips or 96-well plates), buffers, and markers Select the Process Profile of your choice... and GO! Look at the results in real-time on the screen and report data just a few minutes later Operating the QIAxcel Advanced system: Quality Control of RNA samples 29
- 30. Sample to Insight Total RNA quality is assessed by analysing the migration pattern 30 28S 18S 5S 18S/28S ratio Smears Objectivity of the visual ratio estimation? Ratio is not always correlated to integrity! Quality Control of RNA samples
- 31. Sample to Insight RNA Quality Control - RNA Integrity Score (RIS) 31 A1 RIS: 9.5 A7 RIS: 5.8 A11 RIS: 3.6 Superimposed view Lane Name RIS A1 rat_liver _1 9.5 A7 rat_liver _4 5.8 A11 rat_liver _6 3.6 Quality Control of RNA samples RIS 10 1 RNA Integrity
- 32. Sample to Insight 32 The gel images of QIAxcel and Agilent 2100 are comparable QIAxcelBioanalyzer Quality Control of RNA samples
- 33. Sample to Insight RIS and RIN can objectively assess RNA integrity 33 RIS : RNA Integrity Score, by QIAGEN RIN : RNA Integrity Number, by Agilent • Indicators reflecting RNA integrity • Intended to predict the validity of downstream qPCR Frame of reference of RIS and RIN: • Values range from 1 (highly degraded) to 10 (mostly intact) • Analyse several different electropherogram’s parameters, including 28S and 18S peaks analysis • Values between 7 and 10 (depending of what is achievable with samples) are indicators of RNA quality suitable for downstream applications • Allow comparison of sample, standardization and repeatability of experiments Quality Control of RNA samples
- 34. Sample to Insight Outline Quality Control of RNA samples 34 Why is RNA quality control so important1 Main parameters for RNA QC2 Fast and reliable quality control3 Comparison of RIN and RIS4 Wrap up5
- 35. Sample to Insight RIS is more robust than RIN for assessing RNA integrity 35 • Depending on the degradation mechanism(heat, nuclease or UV), total RNA samples have different electrophoreticbehavior • Different RNAdegradation methods result in different ranges ofΔΔCt values for identical RIS/RIN values • “Overall, RIS was more robust than RIN for assessingRNAintegrity” Unger, C et al., 2015 http://www.ncbi.nlm.nih.gov/pubmed/25998866 www.researchgate.net/publication/277080839_Ultraviolet_C_radiation_influences_the_robustness_of_RNA_integrity_measurement Quality Control of RNA samples
- 36. Sample to Insight Methods 36 RNA extraction RNA degradation x3 independent experiments RNA integrity assessment measured in duplicate SYBR Green qRT-PCR RT2 RNA QC PCR Array, selective degraded RNA samples applied in triplicate Goal of the study: compare RIS and RIN to the mRNA integrity observed by qRT-PCR in order to evaluate their respective ability to assess RNA integrity Jurkat & HeLa S3 cells RNase III 0-7 min, 37°C Heat 0-120 min, 70°C UV light 0-220 min, 254 nm Agilent 2100 Bioanalyzer RIN QIAxcel Advanced RIS Jurkat ΔΔCt of actb and hprt1 Quality Control of RNA samples
- 37. Sample to Insight 37 Figure : Decreasing RIS and RIN valueswere obtained by increasing time of heat degradation of total RNA. RIS and RIN were determined of duplicates from partially degradedRNA. In three independent experiments. The mean of RIS and RIN obtained for each cell type is presented over time of heat degradation (A). The correlation of RIS and RIN calculated with a regressionanalysis using Minitab 16 presented for degraded RNA from Jurkat (B) and HeLa S3 cells (C). RIN and RIS have a high correlation for heat-degraded RNA Quality Control of RNA samples
- 38. Sample to Insight 38 Figure : Increasing degradation level of total RNA by RNase digestion resulted in decreasing RIS and RIN. RIS and RIN were determined for duplicates of degraded RNA samples from three independent experiments; the mean was plotted as function of time of incubation with RNase(A). A linear regression analysis was performed with Minitab 16 to determine correlation of RIS and RIN for degraded RNA from Jurkat (B) and HeLa S3 cells (C). RIN and RIS have a high correlation for RNase-digested RNA Quality Control of RNA samples
- 39. Sample to Insight 39 RIS and RIN values are dissimilar after 100 minutes of UV exposure Figure: RNA exposure to UV-irradiation resulted in decreasing RIS and RIN over time with high variancesin lowerRIN values. RIS and RIN were determined of duplicates for each samplefrom three independent experiments. The mean values were plotted as function of exposure time (A), the correlation between RIS and RIN was analyzed by a linear regressionanalysis with Minitab 16 for Jurkat (B) and HeLa S3 cells (C). Presented are also screenshots of the 2100 Expert software showing the electropherogram from duplicates of Jurkat RNA degraded for 185 min, resulting in RIN 2.6 (D) and 4.7 (E). Quality Control of RNA samples
- 40. Sample to Insight RIN algorithm struggles defining 28S peaks of highly UV-damaged RNA 40 Electropherograms of these duplicates look similar but 28S peaks are defined differently (Jurkat RNA degraded for 185 min) resulting in RIN 2.6 (D) and 4.7 (E). Quality Control of RNA samples
- 41. Sample to Insight 41 RIS>RIN RIS>RIN RIS>RIN RNase digestion Heat degradation UV-light exposure Correlation ΔΔCt and RIS values R²= 89,7% R²= 89,6% R²= 97,4% Correlation ΔΔCt and RIN values R²= 89,6% R²= 87,6% R²= 93,1% Figure: the correlation of ΔΔCt-values with RIS and RIN values Calculated by a linear regression analysis with Minitab 16, to study whether RIS and RIN could predict the outcome of a qPCR. Fitted line plots with regression line and adjusted R2 values of RIS and RIN against ΔΔCt-values of ACTB Quality Control of RNA samples
- 42. Sample to Insight Heat 42 RNase UV light 1) RNase, heat and UV light have differentdegradation mechanisms on RNA 2) Different RNAdegradationmethods result in different ranges ofΔΔCt values at similar RNA integrity values (1-log difference) 3) RIS is more robust than RIN to determine RNAintegrity of RNA degraded by different methods and to evaluate suitability of RNA sample for qRT-PCR ▪ High correlation between RIS and RIN values for heat- and RNase III-degraded RNA ▪ Lower correlation between RIN and RIS values for UV-degraded RNA, due to high variation in RIN values, but similar at a decision level of RIN/RIS 7 Quality Control of RNA samples
- 43. Sample to Insight Outline Quality Control of RNA samples 43 Why is RNA quality control so important1 Main parameters for RNA QC2 Fast and reliable quality control3 Comparison of RIN and RIS4 Wrap up5
- 44. Sample to Insight Sample Insight Sample collection/ stabilization DNA/RNA purification Amplification/ NGS Library Prep Analysis Data analysis & interpretation Sample QC must be part of molecular biology workflows, not optional steps on top. QC brings value to workflow and can save cost, time and peace of mind QC QC Quality Control of RNA samples
- 45. Sample to Insight Key quality indicators Quality Control of RNA samples 45 QC Criteria UV spectro. Gels Dye-based spectro CE / µ- fluidic UV/VIS spectro. Protein contaminants (A260/280) ✓ ✓ Salts & other contaminants (A260/230) ✓ ✓ Quantity of dsDNA vs. other NA ✓ Yield ✓ (✓) ✓ ✓ ✓ Degradation/ Size distribution (✓) ✓ Sizing ✓ ✓ There is no one-for-all solution purity quantity integrity
- 46. Sample to Insight Key quality indicators Quality Control of RNA samples 46 QC Criteria UV spectro. Gels Dye-based spectro. QIAxcel Advanced QIAxpert Protein contaminants (A260/280) ✓ ✓ Salts & other contaminants (A260/230) ✓ ✓ Quantity of dsDNA vs. other NA ✓ Yield ✓ (✓) ✓ ✓ ✓ Degradation/ Size distribution (✓) ✓ Sizing ✓ ✓ purity quantity integrity There is no one-for-all solution – QIAGEN covers all your needs for sample Quality Control!
- 47. Sample to Insight Size distribution analysis Quantity & Purity QIAGEN covers all your needs for sample Quality Control 47 Spectral Content Profiling For internal use only Integrity QIAxpert QIAxcel Advanced Quality Control of RNA samples
- 48. Sample to Insight Sample QC can save you time, money, and peace of mind Quality Control of RNA samples 48 Application Price per sample Time Downstream application qPCR 1.5 $US 4-5 hrs Sanger Sequencing 5-6 $US 4-6 hrs Next-Gen Sequencing >200 $US(5plex) 2-3 working days Affymetrix GeneChip Analysis 500-800 $US/sample > 2 working days Sample Quality Control QIAxpert <1$US 90 seconds (16 samples in parallel) QIAxcel Advanced <1$US 3-10 minutes (12 samples in parallel) Purity & quantity Integrity QC gives insights into sample suitability for downstream application • Brings confidence in data analysis and interpretation, troubleshooting • Saves time, money, and peace of mind by excluding samples of poor quality “Save time, money, and peace of mind only dealing with the samples you deserve: the ones of highest quality”
- 49. Sample to Insight How does QIAGEN helps you achieving reliable QC? Quality Control of RNA samples 49 Quantity & Purity Integrity & size distribution QIAxpert QIAxcel Advanced Let lab automation work for you and do the job they are excellent at: Delivering reliable and reproducible results Performaccurate measurements, keep track of your sample quality, standardize your experiments and increase reproducibility of your results. Increase your lab productivity: automation frees your hands and your mind!
- 50. Sample to Insight Quality Control of RNA samples 50 Quantity & Purity Integrity & size distribution QIAxpert QIAxcel Advanced More info on: QIAGEN.com Discover how these instruments can help you improve the reproducibility of your experiments and achieve higher quality results with our interactive online demo tools and request a free demo in your lab!
- 51. Sample to Insight 51 Questions? Thank you for your attention! Pierre-Henri Ferdinand Global Product Management Pierre-henri.ferdinand@qiagen.com Learn more about nucleic acids QC on: qiagen.com/QCSolutions Quality Control of RNA samples