Optimizing Real Time PCR: A Focused Approach for Exceptional Real-Time qpcr Results Michael Wakem M.Sc Bio-Rad Laboratories Canada Ltd (800) 268-0213 Ext 3360 michael_wakem@bio-rad.com
Overview Fundamentals of real-time qpcr Real-time qpcr theory Chemistries Quantification methods Achieving exceptional results Experimental design Optimization and validation
Traditional PCR Template Cycle 1 5 Taq Taq 5 End-point analysis of amplification product 2X Template Cycle 2 5 5 Taq Taq Taq Taq 5 5 4X Template 30-40 cycles
What is Real-Time qpcr? Fluorescence-based detection of amplification products during the PCR reaction Measures input quantity of a nucleic acid by determining the number of cycles required to reach a set level of product In contrast, traditional PCR is used to amplify DNA using end point analysis to distinguish products
Real-Time qpcr Template Cycle 1 5 Taq Taq 5 Fluorescence detection of amplification product 2X Template Cycle 2 5 5 Taq Taq Taq Taq 5 5 4X Template 30-40 cycles
PCR: Theory vs. Reality Log Target DNA Theoretical increase Reality Exponential increase in product is limited, eventually reaching a plateau PCR end-point analysis is not appropriate for quantification Real-time qpcr enables quantification during the exponential phase Cycle #
96 Replicates of identical reactions have very different individual efficiencies by the end of the reaction
Data Analysis: Setting the Threshold The threshold line is a fluorescence value at which curves are compared Set empirically or by a statistical calculation above background Threshold line
Data Analysis: Determining C(t) Value C(t) value equals the number of cycles required for a reaction s fluorescence to reach the threshold C(t) value C(t) values 13.45 +/- 0.008
Data Analysis: C(t) Value Inverse, linear relationship between the logarithm of the initial template amount and the C(t) Increasing input DNA results in a lower C(t) because fewer cycles are required for the fluorescence to reach the threshold 10 6 10 5 10 4
Data Analysis: C(t) Value A 50% decrease in input nucleic acid target equals 1 unit increase in C(t) value Product T = (Template 0 )2 n (n = # of cycles) C(t) values 1024 = 25.78 +/- 0.02 512 = 26.88 +/- 0.11 256 = 27.97 +/- 0.03 128 = 28.92 +/- 0.09
Advantages of Real-Time qpcr Over Other Quantification Methods Sensitive Detects fewer copies of target Detects small fold differences Large dynamic range of detection Samples can be analyzed without normalizing input amounts Time efficient Cost effective Flexible assay design
Real-Time qpcr Applications Gene expression GMO testing Viral load SNP detection CGATAGGCCATCGCAATTC CGATAGGCCGTCGCAATTC Gene therapy
Real-Time qpcr Chemistries Fluorescence-based After absorbance of certain wavelengths of light (excitation) the fluorophore emits light at a longer wavelength (emission) Fluorescence proportional to amplified product Two commonly used chemistries: SYBR Green I TaqMan probes
SYBR Green I Chemistry Advantages Experiment only requires primers Post-amplification melting curve analysis Disadvantages Potential contribution to fluorescence from nonspecific products (primer-dimers) No multiplexing
Real-Time Chemistries: SYBR Green I λ λ λ λ λ λ λ λ λ PCR Reaction Progression λ λ λ λ λ λ λ λ λ λ λ λ λ λ λ SYBR Green I (SGI) fluorescence increases upon binding dsdna As dsdna accumulates during the reaction, more SGI binds the DNA and fluorescence increase λ λ
Melting Curve Analysis Using SGI Used to analyze reaction specificity after amplification Complementary to running an agarose gel except Tm is used to distinguish products As temperature increases dsdna melts, SGI is released and fluorescence decreases Melting temperature (Tm) of dsdna Temperature at which half the DNA is double stranded and half is single stranded Depends on nucleotide content and length
Melting Curve Analysis Using SGI Decreasing fluorescence Due to increasing temperature Due to denaturation and release of SGI Tm is the point of inflection on the melting curve Tm
Melting Curve Analysis Using SGI Plot the negative of the rate of change of fluorescence vs. temperature (-di/dt) For new amplicons, run melting curve followed by gel analysis (and sequencing) for validation -di dt
TaqMan Chemistry Advantages Fluorescence is target specific Multiplexing Disadvantages High initial cost Assay design not trivial
Real-Time Chemistries: TaqMan Target specific hybridization probe 5 reporter and 3 quencher Utilizes FRET quenching Light Light* R Q Reporter Quencher R Energy Q * heat for BHQs
λ TaqMan Chemistry R 1. During PCR, probe hybridizes to target sequence Taq R Taq Q 2. Probe is partially displaced during extension 3. Probe cleaved by 5-3 nuclease activity of polymerase 4. Illuminated free reporter exhibits unquenched fluorescence
Quantification Methods Absolute Determines input quantity of a nucleic acid target Requires a standard curve Relative Determines fold differences in input target quantities between samples Performed with or without a standard curve Typically used for gene expression analysis
Absolute Quantification of an Unknown Sample Generate a standard curve using sample templates of known concentration (copies, ng, etc.) Plot log starting quantity vs. C(t) 10 6 10 5 10 4 10 3 10 2
Absolute Quantification of an Unknown Sample Determine C(t) value for unknown Interpolate unknown quantity using the standard curve 27,500 copies 5,350 copies
Absolute Quantification Considerations Reaction efficiencies of standards and samples must be equivalent Must use appropriate template to generate standard curve Generating a standard curve can be a source of error for analysis
Relative Quantification Using standard curves Quantities used to measure fold differences in target nucleic acid between samples Ratio of target gene to reference gene used for normalization Using the Livak comparative Ct method (2 -ΔΔCt ) Ct values used to measure fold differences in target nucleic acid between samples
Livak 2 -ΔΔC(t) Method 1. Normalize C(t): ΔC(t) = C(t)target -C(t)hskpg 2. Calculate ΔC(t)Average: ΔC(t)Average = Average ΔC(t) of replicates 3. Normalize to calibrator: ΔΔC(t) = ΔC(t)Avg-Sample - ΔC(t)Avg-calibrator (For calibrator, ΔΔC(t) = 0) 4. Fold difference: 2 -ΔΔC(t) = Normalized fold difference (For calibrator, 2 -ΔΔC(t) = 1)
Relative Quantification Results 7 6 5 Normalized Expression 4 3 2 1 0 Calibrator Sample #1 Sample #2
Relative Quantification Considerations Housekeeping (reference) gene expression must be consistent between samples Reaction efficiencies of target and housekeeping genes should be equivalent Method requires validation
Overview Fundamentals of real-time qpcr Real-time qpcr theory Chemistries Quantification methods Achieving exceptional results Experimental design Optimization and validation Multiplexing
Parameters to Optimize Reaction Specificity and Efficiency Assay design Amplicon Primers Experimental approaches Cycling conditions Reaction temperatures Reaction validation Reagents for template preparation and real-time qpcr experiment Lab technique
Plan Ahead When Designing Primers If starting with SYBR Green I, design assays with the potential to use probes and/or to multiplex later Amplicons will have been tested Reaction will have been validated TaqMan PCR requires optimization Fluorescence should be target specific, but a TaqMan assay does not monitor PCR specificity
Amplicon Design Length of 75 to 300 bp Limited secondary structure Model secondary structure using mfold http://bioinfo.math.rpi.edu/mfold/applications Elaborate on salt and temperature for mfold Avoid primer locations at stem loop structures Design assays using Beacon Designer Software
Amplicon Secondary Structures http://bioinfo.math.rpi.edu/mfold/applications Sequence folded at 55 o C, 50 mm Na+ and 3 mm Mg++ Same sequence folded at 58 o C, 50 mm Na+ and 3 mm Mg++
Optimizing Primer Location Reverse primer A η = 66.3 % Forward Primer 1 110 Reverse Primer A
Optimizing Primer location Reverse primer B η = 95.8 % Reverse Primer B Forward Primer 1 110
Primer Design Limit secondary structure 50 to 60% overall GC content Limit stretches of G or C s longer than 3 bases No Gs on the 5 end Place C s and G s on ends of primers, but no more than 2 in the last 5 bases on 3 end
Achieving Specificity By Design Avoid non-specific amplification and stable interactions between primers (primer-dimers) BLAST searches Sequence of interest (avoid homology) Primers and probe Design compatible primers Beacon Designer Software Performs integrated BLAST
Temperature Optimization-Thermal Gradient icycler dynamic thermal gradient C A, B C A, B
Reaction Validation with SGI Use a serial dilution of template to test primers across a broad dynamic range Include representative unknown samples Evaluate Specificity Efficiency Reproducibility Dynamic range
Reaction Validation with SGI
Analyzing Specificity Using Melting Curves Two amplification products
Primer Interactions (Primer Dimers) 5 3 3 5 Stable Interaction Amplification 5 3 3 5 Primer Dimers For traditional PCR, primer-dimers are usually tolerated Product Primer-dimers NTC A B C
Primer-Dimers in Real-Time qpcr Can contribute to reaction fluorescence when using SYBR Green I Miscalculated Ct values Amplifying primer-dimers affects reaction efficiency Lose sensitivity of detection Poor reproducibility
Analyzing Specificity Using Melting Curves Amplicon 10,000 copies of input nucleic acid Amplicon 10 copies of input nucleic acid Non-specific product
Results From a Poorly Designed Assay No resolution below 2000 copies r = 0.957 η = 153%
Results From a Poorly Designed Assay 10,000 copies 2,000 400 Primerdimers 0 (NTC)
Assay Redesigned with New Primers Redesigned primer set with Texas Red probe Good Resolution r = 0.999 η = 91.3%
Testing PCR Variables Specificity Melting curve analysis and gel analysis PCR Efficiency Slope of standard curve Reproducibility Standard deviations between replicates Sensitivity and dynamic range Experimental validation
Reaction Efficiency If the product amount is doubling at every cycle of a reaction, the PCR efficiency is 100% Determined using a serial dilution of template Designate the reactions as standards Exact starting quantity of template does not have to be known, use 1.0, 0.1, 0.01, etc. in software
Calculating Reaction Efficiency Efficiency (η) = [10 (-1/slope) ] - 1
Design and Optimization A real-time qpcr assay should be optimized for reliable quantification Hallmarks of a good assay: One specific product Good reaction efficiency Good reproducibility High sensitivity Broad dynamic range
Improving Reproducibility Laboratory Techniques Use clean bench (hood) Use screw cap tubes Use aerosol resistant tips Use calibrated micropipettors Use large volumes (5µL and up) Pipette into each reaction vessel once
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Sample Preparation Use purified template to minimize PCR inhibition For RT-qPCR, the RNA should not be degraded
Reverse Transcription Should be optimized and validated Test the dynamic range of the RT kit Optimize primers Oligo dt Random oligomers iscript is preblended and optimized Validate 1μg to 1 pg of input RNA
Reverse Transcription Efficiency iscript 1μg 100ng 10ng 1ng 100pg 10pg 1pg Kit I No discrimination at low concentration No detection at 1 pg
Reliable Results Across a Range of cdna Input Concentrations with iscript iscript qrt-pcr Standard Curve Comparison: cdna serial dilution vs. total RNA serial dilution 40 HeLa, β-actin T 35 30 cdna Standard Total RNA Standard 25 20 y e 15 10 cdna total Slope -3.394-3.382 Corr. Coef. 0.999 0.999 Intercept 38.91 38.09 PCR efficiency 97.1% 97.6% d u 5 1 2 3 4 5 6 7 8 9 Log Starting Quantity (femtograms of input RNA) Note: 1/10th of cdna reaction used for PCR
iscript One-Step SYBR Green Kit 100ng to 100fg Total HeLa cell RNA, GAPDH Target r = 1.000 η = 95% r =0.932 η = 216.3%
iscript One-Step Probes Kit 1μg- 100fg Total HeLa cell RNA r = 1.000 efficiency = 97.2%
Evaluate RNA Quality and Quantity Before Performing Real Time PCR Experion-Automated Electrophoresis System
Multiplexing Performing two or more PCR amplifications in the same well Reactions are specific to different reporters Reactions must be optimized for efficient amplification and to eliminate interference Bio-Rad Laboratories standard recommendations are 300 nm primers and 200 nm probe concentrations Standard recommendations of 200 µm each dntp and from 3 mm to 5 mm of MgCl 2 Additional Taq DNA polymerase may be required The polymerase chain reaction (PCR) is a process covered by patents owned by Hoffman- LaRoche, Inc. & F. Hoffmann-LaRoche Ltd. Users should obtain proper license to perform the reaction. Additional licensing information is presented at the end of this presentation.
Fourplex Optimization: Taq DNA Polymerase 3.5 mm MgCl 2 β-actin ODC AZI Cycle OAZ Cycle Cycle Singleplex: 1x Taq DNA polymerase (1.25 U) Fourplex: 1x Taq DNA Pol (1.25 U) Fourplex: 3x Taq DNA Pol (3.75 U) Fourplex: 2x Taq DNA Pol (2.5 U) Fourplex: 4x Taq DNA Pol (5 U) Cycle
Fourplex Optimization: dntps and MgCl 3.75 U Taq DNA polymerase 2 β Actin ODC Cycle Cycle AZI OAZ Cycle Cycle 3.5 mm MgCl2 200 μm dntp 5.0 mm MgCl2 200 μm dntp 3.5 mm MgCl2 400 μm dntp 5.0 mm MgCl2 400 μm dntp
Validating Multiplex Assay For each primer/probe set, compare singleplex results with multiplex results Logarithmic phase of singleplex and multiplex fluorescence curves should be identical Example: Human prostate cdna with an input of 50 ng/ml total RNA.
Verifying Multiplex Reactions: Singleplex vs. Fourplex β-actin 17.0 ± 0.0 OAZ 20.8 ± 0.1 17.3 ± 0.1 20.8 ± 0.2 Cycle ODC 23.0 ± 0.2 AZI 22.2 ± 0.1 23.1 ± 0.2 22.2 ± 0.1
Sensitivity and Reproducibility of Singleplex and Multiplex Reactions Input total RNA 50 ng/μl ACT ODC OAZ AZI 17.3 ± 0.1 23.1 ± 0.2 20.7 ± 0.1 22.0 ± 0.1 17.7 ± 0.1 23.2 ± 0.2 20.7 ± 0.2 22.1 ± 0.1 Cycle 1/1000 dilution of input template ACT ODC OAZ AZI 27.2 ± 0.1 33.6 ± 0.1 31.1 ± 0.2 32.1 ± 0.2 27.3 ± 0.1 33.0 ± 0.1 31.1 ± 0.2 32.1 ± 0.2
Summary Real-time qpcr is a specific, sensitive, and reproducible method for quantification of nucleic acids Multiple detection methods are available Assay design and optimization are the keys for reliable quantification Bio-Rad real-time qpcr systems support multiplexing and a variety of applications
Livak 2 -ΔΔC(t) Method 1. Normalize C(t): ΔC(t) = C(t)target -C(t)hskpg 2. Calculate ΔC(t)Average: ΔC(t)Average = Average ΔC(t) of replicates 3. Normalize to calibrator: ΔΔC(t) = ΔC(t)Avg-Sample - ΔC(t)Avg-calibrator (For calibrator, ΔΔC(t) = 0) 4. Fold difference: 2 -ΔΔC(t) = Normalized fold difference (For calibrator, 2 -ΔΔC(t) = 1)
Temperature Optimization-Thermal Gradient DNA Engine dynamic gradient Up to 24 o C range across block
Other Target Specific Chemistries Internal Oligos Molecular beacons Scorpions TM Primer Based Amplifluor TM LUX TM C C A A T T G C C T T C A A R G C A C G C G G T C Q 3 5
Reaction Efficiency Analysis Optimized assay η = 101% r = 0.997 Non optimized assay η = 131% r = 0.982
Same Reagents, Different Hands Cycle Good Technique Cycle Poor Technique
Plan Ahead When Designing Primers Bad primer set with a target specific Texas Red probe Poor resolution below 2000 copies Poor Replicates η = 71%
Annealing Temperature Gradient Annealing gradient from 45 o C to 65 o C 45 o C 55 o C 65 o C
Contributors to Poor Reproducibility Laboratory technique Specificity issues Cross homology of primers Primer-dimer Reaction efficiency Secondary structure of amplicon Primer-dimers
Reverse Transcription Efficiency Reproducible Data RNA Reality Ideal? cdna Not Reproducible
Calculating Reaction Efficiency Efficiency (η) = 10 (-slope) -1 PCR efficiency 94.9%
Data Analysis: C(t) Value A 10 fold decrease in input nucleic acid target equals 3.322 unit increase of CT value Product T = (Template 0 )2 3.33 Product T = (Template 0 )10 10 6 10 5 10 4 C(t) values 1 X 10 6 = 13.45 +/- 0.01 1 X 10 5 = 16.76 +/- 0.05 1 X 10 4 = 19.88 +/- 0.01