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Introduction to quantitative realtime PCR Veryan Codd [email protected] Overview • • • • • What is real-time PCR and what is it used for? Real time platforms available in CVS Basic Principles Experimental design, Controls and QC Quantification methods What is real time PCR • Ability to monitor PCR reaction in real time • Accurate quantification of the amount of starting material (template) added to a reaction • Increase dynamic range of detection over end point methods Why do we use real-time PCR • Quantification of gene expression levels • Quantification of DNA (Telomere assays, mtDNA content, copy number) • Virus titre • Can be used as a quantitative step as part of another technique e.g. ChIP and DNA Methylation Our facilities – ViiA7 • • • • Life Tech (Applied Biosystems) 96, 384 well plates and Taqman array cards Upgraded 7900 Advanced optics – 6 excitation and 6 emission wavelengths – 21 dye combinations • Value ~75K Our facilities – Rotorgene-Q • Qiagen • Unique rotary system – no well-to-well thermal variation – improved accuracy • 0.2ml tubes (36), 0.1ml strip tube (72), rotordisc (72 or 100) • Robotic set-up required but available for 100 well disc • Additional quant methods in software • 2-plex – Green (SYBR green, FAM) and Yellow (VIC, JOE)channels Our facilities – Rotorgene-Q • Value ~20K Basic Principles • PCR with a fluorescent dye that can be detected • PCR is theoretically exponential – product doubles with each cycle • The more starting material the faster the reaction will occur (lower cycle number) Experimental design - reagents • Primers – – – – Specific to target 18 – 24bp Produce product 50 – 150 bp in length (200bp does work) Product ~50% GC and avoid GC stretches and repetitive sequences – Check for primer dimers especially for SYBR green assays – F and R primers annealing temp within 5˚C – In separate exons or spanning exon boundaries • Pre-designed assay available (taqman probes, sybr based assays) • Array cards / expression sets Experimental design – probe or SYBR? SYBR green • Dye binds minor groove of all DNA • Fluorescence much stronger when bound • More product more dye bound • Cheap • Not specific • At early stage check product on gel and perform dissociation analysis (melt curve) Probe • Dye and quencher either end of probe • Nuclease activity of polymerase removes dye and quencher during PCR • More product produced, more fluorescence • No melt curve • Allows multiplexing Experimental design- singleplex or multiplex Singleplex (simplex) • One gene per PCR • SYBR green or Probe – more flexible • More variation • Usually simpler to set up • Uses more enzyme mix but can SYBR green with cheap primers instead of expensive probes • More template? Multiplex • Multiple genes per PCR • Probe based – 2 dyes (VIC FAM) • Minimises pipetting error • Competition between reactions can be problematic • Cheaper? • Higher throughput – 2 measurements in one • Less template? Experimental design - reagents • Enzyme or enzyme master mix governed by primer probe choice and by choice of platform (e.g. ViiA7 or rotorgene) • 2x mastermixes widely available – Consistent – Pre-optimized (MgCl2 etc) Experimental design - Template • For gene expression analysis need to reverse transcribe mRNA into cDNA • Good quality RNA • Accurately quantified • Variety of RT enzymes commercially available Reverse transcription - Priming • Three (or four) basic choices Oligo-dT priming • Favourite choice of many as specific to mRNA • Total RNA – 80% rRNA – 15% tRNA – 5% mRNA • Sensitive to secondary structure – incomplete reverse transcription • Design primers at 3’ end of transcript • Don’t use 18s as a control (it’s rRNA!) Random Priming • Uses random hexamer primers • Bind throughout RNA molecule – Secondary structure less of a concern – Less sensitive to RNA degradation – Increase yield of cDNA • Amplify ALL RNA – mRNA, tRNA and rRNA Sequence specific priming • Only gene of interest is reverse transcribed • Limits use of cDNA, used up RNA stocks • Only used in one-step reverse transcriptionqPCR (one step qRT-PCR) Option no 4 • Mix of oligo-dT and random primers • Best of both worlds Good laboratory practice • qPCR can be a sensitive technique if performed correctly and with care • Keep everything clean • Aliquot reagents to prevent freeze/thaw • Accurate pipetting – – – – – – Make master mix of everything except template then aliquot Mix everything gently but thoroughly 2x master mixes are viscous Small volume pipetting less accurate 22ul + 3ul or 23ul + 2ul works well (MM + Template) Don’t use second stop on pipette to avoid “spraying” • Perform triplicate PCRs for sample Contamination • Big problem for qPCR • Most common cause of contamination comes from product of previous PCRs • Don’t leave PCRs in machine indefinitely after completion • If running product on get use separate pipettes to those you use for PCR set-up • Use PCR dedicated Hood (genomics lab) to set up PCR MM’s – Keep primers and other reagents free from contamination – DNA/cDNA MUST NOT BE ADDED IN THE HOOD – pipette contamination Getting started • For pre-designed assays have a test run to check for good amplification • If designing own assay – Test to check product of correct size is formed – Optimise annealing temp (gradient PCR) – Test in real-time PCR that amplification looks reasonable – Titrate primer concs if/as necessary Normalisation • Housekeeping gene(s) – Accounts for pipetting error and differences in RT efficiencies between samples – Constantly expressed at a stable level – Put the same starting RNA in all RT-reactions when samples are to be compared – IT IS NOT THERE TO ACCOUNT FOR MASSIVE DIFFERENCES IN STARTING MATERIAL! • Calibrator sample – Sample run on every assay • T0 / Untreated – Compare everything to this sample Controls • NTC (No template control) – PCR contamination detection – Primer dimers • no-RT control – Detection of genomic contamination and/or nonspecific product – Especially important in transient over-expression experiments to check for carry over of plasmid DNA Dissociation or Melt curve analysis • To check for single specific product in SYBR green based assays • Compare to product on gel in early stages of set-up • Detection of primer dimers and non-specific products Melt curve Example 1 Melt curve example 2 NTC Primer dimers Specific product Melt curve example 3 Specific product Non-specific product In this case NTC’s showed no product, so no primer dimers, large nonspecific product observed on gel Standard curves • Do I need a standard curve??? – YES! • “My assay is predesigned and guaranteed to be efficient therefore I don’t need to waste my time doing a Standard curve” – Not true! But very common!! What is a standard curve and why is it necessary? • Real time PCR conducted across a series of serially diluted template/samples • Tell you what the dynamic (linear) range of the assay is • Allows calculation of efficiency Cycle number Ct or take-off Log10 template concentration Cycle number Ct or take-off Log10 template concentration Cycle number Ct or take-off 25 20 y = -3.2241x + 25.595 R² = 0.9813 15 10 5 0 0 0.5 1 1.5 2 Log10 template concentration 2.5 14 12 10 8 6 4 2 0 0 0.5 1 1.5 2 2.5 3 Linear range 7 -10 cycles Therefore experimental samples with Ct’s outside of this should not be used for quantification Set the concentration of template in middle of linear range If input concentrations are highly variable then more likely to get samples falling outside of LR that cannot be accurately quantified Efficiency • • • • Efficiency = 10(-1/gradient)-1 Gradient of -3.32 = 100% efficient 90-110% considered ok (-3.1 to -3.6) For some, most commonly used, quantification methods it is important to have similar efficiencies between GOI and housekeeping genes Quantification methods- Absolute Quantification • Samples calculated against a standard curve of known concentration • Allows quantification as copy number – Can be used when one condition contains no expression • Takes some variability into account • Requires more reagents • Needs a known standard – Plasmid DNA containing product – no RT step so efficiencies may be different – In-vitro transcription to generate specific mRNA – RT, costly Quantification methods- ΔCt, ΔΔCt • • • • • • • • • • Comparative quantification Threshold cycle number – Ct Slightly subjective Calibrator – i.e T0 or untreated Normalized to housekeeper (HK) ΔCt = CtGOI-CtHK Δ ΔCt = ΔCtsample- Δctcalibrator Fold change = 2- Δ ΔCt Assumes efficiency 100% for both GOI and HK Can substitute 2 for your calc efficiency but must be the same for GOI and HK Example Efficiency is 88% GOI (red) Efficiency is 1.07% Housekeeper Calculate average DeltaCt for each dilution: 200 -4.8 100 -4.65 50 -4.5 25 -4.35 12.5 -4.2 6.25 -4.05 3.125 -3.9 1.56 -3.75 One end of range 1.05 cycles different to other end – equivalent to a two fold difference when it should be the same 26 24 y = -3.1552x + 25.061 R² = 1 22 20 18 16 14 y = -3.6534x + 21.407 R² = 1 12 10 0 0.5 1 1.5 2 2.5 Comparative quantification - Qiagen • Method on rotorgene software • Calculates efficiency for each individual sample based on rate of fluorescence change and mean efficiency across run • Calculates a “take off” value – start of exponential phase, less subjective than setting threshold for Ct • Set calibrator sample, T0 or untreated etc • Relative amount calculated against calibrator • Relative conc = MAE(calibrator takeoff-sample takeoff) • Effectively a ΔCt but with real efficiency • Then need to manually normalise to HK or a Δ ΔCt and fold change calculation Example GOI efficiency = 96% HK efficiency = 104% Comparative quant each dilution for GOI and HK separately using one concentration as calibrator 24 y = -3.2241x + 25.595 R² = 0.9813 22 20 18 16 14 y = -3.4327x + 21.765 R² = 0.9906 12 10 0 200 100 50 25 12.5 GOI/HK 0.999 1.002 1.006 1.021 0.968 Δ ΔRc 0.996 1.000 1.001 1.003 0.997 0.5 1 1.5 Δ Δ Ct (using Ct rather than TO) 1.000 0.749 0.620 0.488 0.357 2 2.5 Accuracy • Singleplex reaction more prone to variation in pipetting accuracy • Replica error – How consistent is Ct/take off value between triplicate measurements? – A 1 cycle difference across the triplicate is a 2-fold difference within the same sample! – Rotorgene 0.2 or 0.3 cycles easily achievable – ViiA7 and other block based ~0.5 • Rotorgenes better at accurate quantification of small differences – No thermal variation – Take off calculation less prone to subjectivity Further resources • Real-time PCR handbook • LifeTech • Molecular Cloning, Green and Sambrook • MIQE guidlines