A Brief Introduction to Quantitative PCR and Applications basics and...Avoids amplification of genomic DNA T m of Primers should be at 60°C Reduces risk of primer dimers and enables

A Brief Introduction to Quantitative PCR and Applications

Cathy CutlerField Application Scientist

Stratagene Products Division

Our measure is your success.

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Quantitative Real Time PCR

Definition: Assay that monitors the accumulation of a DNA product from a PCR reaction in real time

Uses fluorescence-based chemistriesData collection during the early exponential phase of PCR Benefits over traditional PCR assays

Sensitivity (as little a single copy)Enhanced dynamic range of detection (7-8 magnitudes)Increased reproducibilityIncreased throughputCost efficiency

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Introduction to PCR

[DN

A]

Cycle #lag phase

exponential phase

limiting phase

plateau phase

Endpoint measurement!

Limited dynamic range!

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Real-time PCR

detection limit

[DN

A]

Cycle #

Ct

CtCt

threshold

Continuous measurement,wide dynamic range!

Ct=Fractional PCR cycle # at which the fluorescence intensity crosses the established threshold fluorescence value; in the exponential region

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Quantitative PCR vs Endpoint PCR

96 technical replicates

Variability using Variability using QPCR endpoint PCR

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MX Real-time PCR Threshold

NormGOI

Threshold *

Threshold Cycle (Ct)

• ′ Fluor method or• Background method

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Polymerase Chain Reaction

MeltAnneal primers

MeltAnneal

+

Extension/Measure

Gene of interest (Amplicon)

DNA(genomic/cDNA)

Forward and Reverse Primers + dNTPs

DNAPolymerase

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Exponential amplification of the original DNAQuantitation using the Pfaffl Efficiency corrected method, NAR 2001, V29, 9

Xn=X0 (1+E)n

X = DNA concentrationX0= Starting DNA concentrationXn= DNA concentration at cycle n

E = Efficiency of PCR reaction, 0-1

Real-time PCR Quantitation

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Influence of Reaction Efficiency

5-fold 24-fold 131-fold

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QPCR Standard Curve

QPCR Efficiency (E)= 99.5%(E) = 10[-1/slope] -1

Coeff. of Det. (R2)=0.995

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The Mx as Open PlatformChemistries

SYBR Green I™

EVA Green

TaqMan®

Molecular BeaconsScorpions™

Plexor™

Others...

dsDNA detection

Target-specific detection

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Fluorescent Wavelength Range

Quartz-tungsten halogen lamp excitation range (350-750nm)TAMTET TxRedJOE

FAM HEX ROX Cy5Alx350 Cy3

350nm 700nm

- Many other fluorescent dyes can be detected using a given filter sets

- Be aware of potential for cross-talk between selected dyes

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1.Experimental Design

2.Sample preparationand purification

cDNATotal RNA

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4.Reverse Transcription5.Real time QPCR6.Post-run Analysis

Steps towards successfulSteps towards successfulRealReal--time QPCR experimentstime QPCR experiments

3. RNA/DNA quantification and quality

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Step 1: Experimental DesignStep 1: Experimental DesignUnderstanding experimental varianceexperimental variance

Sources of variance in QPCR experiments:

Biology of experimental systemUse of biological replicates

Technical varianceUse of technical replicates

Pipetting errorAvoid pipetting small volumes and use of calibrated pipettesVarying template quality and/or quantityUse of sample QC and proper normalizationRun-to-run variabiltyUse of inter-run calibrating samples

Number of biological replicates depends on system variability.Usually 3 technical replicates are sufficient.

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Step 2: Sample PreparationInfluence of Sampling and Sample Preparation

Sample preparation influences QPCR results

Quality of template Amount of Inhibitors Amount of co-purifiedsalts

Quantification assumescomparable quality

Low quality can leadto failure of detection

Inhibitors can lead todelayed or failure ofdetection

Affects primer and probebinding affinity

Sample preparation affects QPCR assay performanceresulting in lower assay sensitivity if not optimized!

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Stratagene’s Absolutely RNA® kits

Spin columsOrganic Liquids

guanidinium thiocyanate/phenol:chloroform

Pro: higher yieldworks with larger amounts of cellsworks better with troublesome tissues(like adipose tissue, bone, cartilage etc)

Con:higher DNA contaminationseparate DNase I digestion withadditional purification neededresidual phenol inhibits PCR

Pro: less contaminating DNAon column DNase digest

Less loss of RNAhigher qualityEase of use

Con: limited loading capacityloss of small RNA

miRACLE™ miRNA kits

Step 2: Sample PreparationRNA Preparation

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Several Methods exist: Always use the same, considerablevariation exists between methods!

UV (photometer or Nanodrop [>2 ng]):easy to use, high amount of starting material (photometer), not specificfor DNA or RNA, highly variable, don’t trust absorptions <0.1

Ribogreen [>0.5 ng] and Picogreen :Very sensitive (0.5 ng -1 µg), can use Mx as plate reader, expensivesupposedly specific for RNA (Ribogreen) or dsDNA (Picogreen)

Quantity/quality assessment using Agilent Bioanalyzer [>50 pg/µl]

Accurate quantification of external standards is key for absolute quantification!

Step 3: RNA/DNA Quantification

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Step 4: Reverse TranscriptionAAAAAAAAAAAA

Reverse transcription is the main source of error in qRT-PCR

Therefore optimizing the RT step improves your PCR results

High quality RNA gives the most reproducible and robust resultsEssential for detection of low abundant transcripts or 5’ biasedamplicons

MMLV based enzymes (AffinityScript™ RT) usually work at higher temperaturesEnables full-length cDNA from RNA with high secondary structureRNaseH activity can improve PCR sensitivity from GC rich messengers

RT is a non-linear process: Standardize your input amountUse of same amount of RNA (or same number of cells) for all samples

RT reagents are inhibitory to PCR dilute the reaction

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Step 5: Real-time PCRInstrumentation

Over 6 years of experience in Real-timeQPCR instrumentation

Freedom of choice: Use all available chemistries

Halogen lamp based excitation (350-750 nm)

Scanning optical design: Avoids positional effectsNo reference dye needed

4 colors (Mx3000P™) or 5 colors (Mx3005P™)

Photomultiplier tube allows sensitive measurement

Internal computer saves data: Recovery of datain case of external computer failure

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Sensitive sequencedetection andquantification

Gene expressionanalysis

Detection ofsequence variants

Fluorescencedetection

Pathogen detection

GMO analysis

Quality control

Forensics

Validation ofmicroarrays

Comparativequantification

ChIP

Copy number analysis

SNP detection/allelic discrimination

Methylation studies

Immuno-PCRDetect proteins withQPCR

DNA/RNA quantification

Protein stability testing

Versatile technology:

and many more …..

5: Real Time PCR Applications

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Step 5: Real-time PCRAssay Design

Amplicons Amplicon length affects assay performance:QPCR uses small amplicons between 70-200 bp

Primers

Avoid long primers:Primers should be in the range of 17-25 bpDesign cDNA specific primers over exon junctions:Avoids amplification of genomic DNATm of Primers should be at 60°CReduces risk of primer dimers and enables runningmultiple assays on the same plate or using primersin a probe based assay

ProbesAvoid long probes:Probes should be in the range of 17-30 bpProbes should have a Tm that is 10°C higher than primersProbes should bind before primers do

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Step 5: Real-time PCRAssay Validation

Validating an assay generates useful assay performance data:

- The specificity of your primers and probesMelting curves, Negative controls

- The working range and sensitivity of your assayStandard curves

- The reproducibility of your experimentsReplicates, Statistics

Assay validation makes it easy to avoid or understandunexpected results in future experiments

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Step 5: Real-time PCRAssay Optimization

Optimizing your assay can help you to

- Increase specificity: Get rid of unspecific amplificationeg. primer dimers

- Increase sensitivity: Get earlier Ct values, detect lowerconcentrations

- Increase reproducibility: Low replicate variability,high amplification efficiency

Multiple levels of assay optimization available

Assay optimization will improve assay robustnessand minimize assay variability

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Step 5: Real-time PCRTroubleshooting – Primer Dimers

NTC

Detection of primer dimers is onlypossible with SYBR melt curves.They tend to have a Tm between 72-78°Cdepending on sequence

Primer dimers tend to occur in lowconcentrated samples or NTCs at late Cts

In SYBR they contribute to the overallsignal and may make accurate quantificationimpossible.

Moving to a probe based chemistry:allows specific detection BUT doesn’t remove competitionresulting in higher variability and loss of sensitivity

Try to get rid of them by primer titration, decreasing annealing time,or redesign

Low conc.High conc.

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Step 5: Real-time PCRTroubleshooting - Efficiency

Properties of a good standard curve:high efficiency (80%<85%<90%-105%<110%<115%)good R2 (>0.98)low replicate variability for individual standards (SDrep/meanrep*100 = %CV < 1%)

Low efficiencies:Inhibition of amplification

Primer and/or probe don’t bind efficiently

High variability/loss of linearity at highconcentrations

High efficiencies:High variability/loss of linearity at lowconcentrations

Amplification/detection of more thanone product

Template independent probe degradation

Loss of linearityat lower conc.

E = 154%E = 105%

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Step 5: Real-time PCRQuantification –Absolute Quantification

Absolute quantification:Relative to a standard set of known concentration (purified virus, cloned targets, etc.). Assumes equal efficiency of amplification between unknowns and standards.Must run a standard in every plate.Results readily comparable to other techniques or sources.

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∆Ct

normalizer (Correction factor)

GOI

Step 5: Real-time PCRQuantification – Comparative Quantification

*Applied Biosystems. User Bulletin #2 Relative Quantitation of Gene Expression. Dec. 11, 1997

The The ∆∆Ct Method*Ct Method*

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∆Ct

Untreated Drug Treated



∆Ct

∆Ct∆Ct


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∆Ct ∆Ct

Calibrator Unknown

RQ to calibrator = 2-∆∆Ct

Where ∆∆Ct = ∆Ct(calibrator) - ∆Ct(unknown)*Applied Biosystems. User Bulletin #2 Relative Quantitation of Gene Expression. Dec. 11, 1997



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∆Ct

normalizer

GOI

Enorm = EGOI




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Requirements for ∆∆Ct analysis method•Efficiencies of GOI assay and normalizer assay must be similarValidation is performed by comparing slopes of standard curves

slope < 0.1



The The ∆∆Ct Method*Ct Method*∆C

t

Log relative quantity

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∆Ct norm ∆Ct GOI

normalizer

GOI

calibrator unknown


*Pfaffl MW. 2001. A New Mathmatical Model for Relative Quantification in Real-time RT-PCR. Nucleic Acids Res. May 1;29(9): E45

Efficiency Corrected Method*

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Example:

IL-1 expression in cells following stimulation.

GAPDH used as normalizer.

E(IL-1) = .9 (90%)

E(GAPDH) = 1 (100%)

19treated2(18-19) = 0.5

18controlGAPDH(Normalizer)

19treated(3.61/0.5) = 7.22

1.9(21-19) = 3.6121control

IL-1(GOI)

Corrected Relative QuantityRelative QuantityCtCellsGene


Efficiency Corrected Method*

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Step 5: RealStep 5: Real--time PCRtime PCRComparative Quantification using Comparative Quantification using MxProMxPro™™

MxPro™ our data acquisition and analysissoftware allows analysis of absolute andcomparative quantification.

It also offers the ability to analyze multipleexperiments at once.

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MxProMxPro 4.014.01General functionality changesGeneral functionality changes

New wizard with added experimenttypes:

EvaGreen™ (with Dissociation curve)

Start project for multiple experimentanalysis

MxPro 3.x wizard

MxPro 4.0 wizard

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PlatePlate Setup:Setup:

No well names in standard viewin previous versions. Only infullscreen plate view

Show Well Names button

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ThermoThermo Profile Setup:Profile Setup:

Custom setup as in oldMx software

Predefined one click setupusing Standard Design:

Add RT step, normal or fast2 or 3-step cycling protocol,dissociation curve

Estimated run time shown

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New Default Sets options:

Apply to new experiments

Apply to opened experiments

MxPro 3.x preferencesMxPro 4.01 preferences

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Analysis Analysis sectionsection::

Lock thresholds: Thresholdis fixed to current value.Selection of different part of platedoesn‘t change threshold whenlocked.

Customizable Toolbar

Label graph according toreplicate/well ID or well name

MxPro 3.x: Amplification plotsMxPro 4.0: Amplification plots

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Projects

In the MxPro Software, a Project is the architecture used for analyzing the data from multiple different experiments together.A single experiment file is saved in a file with a .mxp format. A project is stored as a .mxprj file.A project will allow unknowns from one plate to be compared to standard curves run on a separate plate, or for comparative quantitation a gene of interest (GOI) on one plate can be normalized to normalizer wells run on a separate plate. Currently, the software will not allow for relative quantities of Unknown samples to be calculated relative to Calibrator samples run on a separate plate. That functionality will probably be incorporated in the next version of the software.

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Setting up a new Project

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Adding Experiments to Project

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Restrictions on a ProjectA maximum of 12 experiments can be imported into a Project.Can only import experiments with the same experiment type and that have the same thermal profile.Can only open a project if the software is running in Standalone mode (not instrument connected). If on an instrument connected computer, this can be done just by opening a second copy of the application.Not available if the MxPro software is running in the optional ET (electronic tracking) mode.

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The Project View

A new section button called Project will be visibleSeparate button listing each imported experiment

Scroll bars if all experiment buttons won’t fit

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Control Panel in Project View

Different Areas to Analyze correspond to the views that would be available under the Analysis Results tab in a single experiment.

Data can be grouped together for display on separate plots discriminated according to the original experiment files, by Assay (by dye is Assays not assigned), or all together on a single consolidated plot.

Areas per page can be set to 1, 2, or 4. If the total number of plots exceeds the areas per page, a scroll bar will appear to the right side of the plots.

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Adjusting Individual Plate Settings in a Project

If you select the Setup, Run, or analysis buttons in the Project view, the experiment buttons at the top of the screen can be used to select which experiment is displayed.

In this way, the wells selected and analysis parameters can be adjusted for each experiment independently.

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Absolute Quantification

If you are comparing unknowns on one plate to a Standard curve run on a separate plate, the software will calculate quantities for your Unknowns based on that curve as long as both sets of wells have the same assay name.

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Setting Assay Names

Assignment of Assay Names is accessed under the Setup Screen for each experiment, just as this would be set in single experiment mode.

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Comparative Quantification

In a normal single plate analysis, the software associates normalizer wells to the corresponding GOI wells from the same sample using Association Symbols.

In a Project these are associated together differently across experiments, instead using Well Names.

Plate 1 Plate 2

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Setting Well Names

Well names are accessed under the Setup Screen for each experiment, just as this would be set in a single experiment.

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A Note on Multiple Experiment Analysis

When performing Multiple Experiment analysis, it is essential that all experiments are run under identical conditions, otherwise a direct comparison of Cts across plates is be invalid.Anything that would alter the efficiency of amplification across plates, such as a change in polymerase activity or the manner in which the plates are set up has the potential to invalidate the results.This is the reason the software can only import experiments into a Project if they were all amplified using the same thermal profile.

Documents

A Brief Introduction to Quantitative PCR and Applications basics and...Avoids amplification of genomic DNA T m of Primers should be at 60°C Reduces risk of primer dimers and enables