rt-qpcr guidelines - uc davis school of veterinary ... · pdf filert-qpcr guidelines: from...
TRANSCRIPT
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RT-qPCR Guidelines:From designing to publishing
your data
Emir Hodzic D.V.M., Ph.D.
Real-Time PCR Molecular & Diagnostic Core Facility
UC Davis, January 31, 2011
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1997
qPCR 2011
Novelty“Free-for-all”
ReflectionExaminationExplanation
Criticalassessment
Reliability? Relevance?
Technology
PCR efficiencyNormalizationRT condition
Primer designRNA integrity
InhibitionSample heterogeneityReporting standards
Biology
Allele specific expressionSplice variants
miRNAmRNA localizationMultiple promotersTemporal variation
Single cell expression
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Many publications using
RT-qPCR report
seriously misleading
results
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incorrectanalysis
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Slope: -1.365Slope: -2.276
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The problemsThe problems
All theories proven with one graph
Insufficient information
sample: quality assessment experimental design: primers, probe, and
much more protocol: reaction condition analysis: normalization interpretation: significance of fold
change methods
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AimsAims
Maximize confidence in technical merit ofpublications using real-time PCR
Reliable and unequivocal interpretation ofresults
Full disclosure of reagents and analyticalmethods
Published results easier to reproduce Focus on their biological relevance
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Nomenclature
qPCR and RT-qPCR
Reference gene(s) not housekeeping genes
Quantification not quantitation
Hydrolysis probes not TaqMan
Quantification cycles (Cq) replaces Ct, Cp, TOP*
*Ct=cycle threshold-AB; Cp=crossing point-Roche; TOP=take of point-Corbett
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RT-qPCR:steps and variables
Tissue sample
RNA cDNAExperimentdesign
Samplepreparation
Nucleic acidextraction
Reversetrancriptase
Scientificmethods
Sampling method:-Biopsy-Stability of DNA/RNA-Tissue storage-Liquid Nitrogen-RNA later
Extraction method:-Total RNA-mRNA-Columns-Robot-OD -Bioanalyzer 2100-Storage
Efficiency of RT:-RT enzyme type-RT temperature-Poly-T primer-Random hexamers-Specific primer-One step-Two step
Experimentalprocedure:-Observation-Define problem-Hypothesis-Experimental and control groups-Experimental replicates
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PCR productQuantification
strategyStatistics
Detection Software Test
Detection method:-Sybr Green I-Probes; TaqMan, Beacons, etc-Background correction-Fit point method-Other models (Log)-Singleplex, multiplex
Quantification strategy:-Absolute quantification * Using calibration curve-Relative quantification * Normalization with RG * Normalization with more (>3) RGs
Test method:-SAS, SPSS, Excel-Normality of data-t-Test-ANOVA-Randomization test
Biologicalmeaningful
results
RT-qPCR:steps and variables
PCR
Real-time PCRamplification
Efficiency andspecificity:-Primer design-Primer specificity-gDNA/cDNA input-Enzyme types &mixture-Cycler
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Guidelines
Experimental designSample handling
Nucleic acid extractionReverse transcription
TargetPrimers & probes
Assay detailsValidation
Data analysis
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E = essential, D = desirable
The MIQE guidelines-Experimental design-
Definition of experimental and control groups E
Number within each group E
Assay carried out by the core or investigator’s laboratory? D
Acknowledgment of authors’ contributions D
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Experimental design
Exp’tprocedure
Controlgroups
Replicates Exp’tconditions
Disease ortreatmentgroups
Targetgenes
Timecourse ofstudy
Normal vs.disease
Referencegenes
Untreatedvs. treated
Technicalsamples
Biologicalsamples
Growthconditions
Days ofdevelopment
Amount ofdrug/mass
Phenotype
Incubationtime
These steps define the: experimental parameters;the goals and the samples based on literature orprevious experimental data.
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Experimental replicates
Biological replicates
RT-qPCR samplesTechnical replicates
Experiment
Control
A
CBA
CB
A A
A
A
AA
A
A
A
A
A
A BBB
BBB
BBB
BBB
C
CC
CC
CCC
CCC
C
Target
Target
RG
RG
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E = essential, D = desirable, FFPE = formalin-fixed paraffin embedded
Description E
Volume/mass of sample processed D
Microdissection or macrodissection E
Processing procedure E
If frozen, how and how quickly? E
If fixed, with what and how quickly? E
Sample storage conditions and duration (especially
for FFPE samples) E
The MIQE guidelines-Sample handling-
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- Source- Method of preservation
Snap freezeRNAlater®
- Storage time RNAlater®: at 370C 24 h, at 250C 1-2 week, at 40C for months
- Handling Tissue grinding, freeze/thaw
- Disruption
Sample handling
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Freeze/thaw effect
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mRNA recovery
0.00E+00
1.00E+05
2.00E+05
3.00E+05
4.00E+05
5.00E+05
Frozen Carnoy's Formalin 8h Formalin 24h
Tota
l R
NA
recovery
(pg)
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Procedure and/or instrumentation EName of kit and details of any modifications ESource of additional reagents used D
Details of DNase or RNase treatment EContamination assessment (DNA or RNA) ENucleic acid quantification E
Instrument and method EPurity (A260/A280) DYield D
RNA integrity: method/instrument ERIN/RQI or Cq of 3 and 5 transcripts EElectrophoresis traces D
Inhibition testing (Cq dilutions, spike, or other) EE = essential, D = desirable
The MIQE guidelines-Nucleic acid extraction-
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Nucleic acid extraction
Total RNA
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Extraction method
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Should be free of protein (absorbance260nm/280nm - >1.8)
Undegraded (28S/18S - 1.8 to 2.0) Free of gDNA Free of any substance which complex with
reaction co-factors, like Mg2+ or Mn2+ Free of nucleases Free of PCR inhibitors
Purification methods Clean-up methods
Total RNA quality
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Total RNA analysis
RIN classification:High: RIN ≥ 7Medium: 2.5 ≥ RIN < 7Low: RIN < 2.5
RNA degradation
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Analysis of RNA purity and integrity
Accepted ratios for good quality RNA are >1.8
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Cq
va
lue
s
RIN
r2mean=0.837P<0.001Mean slope of theregression line=1.578
Threshold for reliable qPCR results: RIN > 6
Becker C et al. Methods 2010
Influence of RIN on Cq
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Input material:fecal samplecartilage, liver, cornea, etcenvironmental sample: soil, water, air, stones, wood, swabs:humic acidplants: …whole blood: hemeanticoagulant: heparin
Caused by extraction system / wrong protocol: total RNA or gDNAinsufficient centrifugation with second wash: ethanol in eluteinhibits RT step and PCR stepRNA precipitation with isopropanol; ethanol wash steps:
ethanol leftovercDNA or gDNA too concentrated:
more than 10% of cDNA into PCR: inhibitiontoo much gDNA in PCR; inhibition
PCR inhibition: in what samples?
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Can be relieved by heat-denaturation
PCR inhibition
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1:10 1:5 1:1
E-No 0.5 1 ul 5 ul oCT @15 23.17 22.72 30.22 22.72 1:516 21.85 22.35 - 21.85 1:1017 27.08 31.24 - 27.08 1:1018 20.71 20.8 - 20.71 1:1019 20.01 20.02 30.02 20.01 1:1020 21.3 24.7 - 21.3 1:1021 19.35 19.04 34.58 19.04 1:522 33.88 22.99 - 22.99 1:523 22.04 30.79 - 22.04 1:1024 - - - 19.99 -25 19.99 21.43 - 17.62 1:1026 17.62 18.3 - 17.62 1:1027 35 - - 35 1:10
Dilution of NA
Volume used for PCR
Stool sample
Removal of PCR inhibition
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Complete reaction conditions E
Amount of RNA and reaction volume E
Priming oligonucleotide (if using GSP) and concentration E
Reverse transcriptase and concentration E
Temperature and time E
Manufacturer of reagents and catalogue numbers D
Cqs with and without RT D
Storage conditions of cDNA D
The MIQE guidelines-Reverse transcription-
E = essential, D = desirable
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Reverse transcription
The conversion of mRNA tocDNA is a major obstacle andarguably is the single mostvariable step in the wholequantification procedure.
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One step vs. two step
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One step vs. two step
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•random primer•oligo dT•specific primers (more sensitive?)
•control
Efficiency of RT primers
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Time (minutes)
Le
vels
of
rela
tive
exp
ress
ion
cDNA synthesis: 250C vs. 420C
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Gene symbol ESequence accession number ELocation of amplicon DAmplicon length EIn silico specificity screen (BLAST, and so on) EPseudogenes, retropseudogenes, or other homologs? DSequence alignment DSecondary structure analysis of amplicon DLocation of each primer by exon or intron (if applicable) EWhat splice variants are targeted? E
The MIQE guidelines-qPCR target information-
E = essential, D = desirable
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Amplicon secondary structure
600C 650C
http://mfold.rna.albany.edu/?q=mfold/DNA-Folding-Form
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Primer sequences ERTPrimerDB identification number DProbe sequences DLocation and identity of any modifications EManufacturer of oligonucleotides DPurification method D
The MIQE guidelines-qPCR oligonucleotides-
E = essential, D = desirable
“Disclosure of the probe sequence is highly desirable andstrongly encouraged; however, because not all vendors ofcommercial predesigned assays provide this information, itcan not be an essential requirement. Use of such assays isdiscouraged.”(Bustin SA et al.Clin Chem, 2009)
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qPCR oligonucleotides
Primer-BLAST your sequence (NCBI) to findunique primers and amplicon sequences.
Enter sequence in “M-fold” to assure minimalsecondary structure.
Choose at least two sets of primer pairs andvalidate with thermal gradient and standard curve.
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Gene accession number Amplicon size Primers/probe sequence Specificity Efficiency
No primer-dimers Ideally should not give a DNA signal
cross exon/exon boundary
qPCR oligonucleotides
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Intron spanning/flanking primers
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Detection Systems
TaqMan®
Quantiprobe® Amplifluor™
Q
Q
LUX™
SYBR Green I®
Probe systems
Primer systems
Intercalating dye
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Complete reaction conditions EReaction volume and amount of cDNA/DNA EPrimer, (probe), Mg2 , and dNTP concentrations EPolymerase identity and concentration EBuffer/kit identity and manufacturer EExact chemical composition of the buffer DAdditives (SYBR Green I, DMSO, and so forth) EManufacturer of plates/tubes and catalog number DComplete thermocycling parameters EReaction setup (manual/robotic) DManufacturer of qPCR instrument E
E = essential, D = desirable
The MIQE guidelines-qPCR protocol-
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Analytical Sensitivity: reproducible threshold at 5
molecules
Precision: CV
RNA transcripts: 50 500 5000
Within run 9.29 11.72 6.43
Between runs 13.56 11.63 10.22
RT-qPCRRT-qPCR assay characteristics
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Core kits or MasterMixes?
Taq Polymeraseantibody-blocked Taqchemically-blocked Taq
dNTPs / dUTPsdNTPs increases the sensitivitydUTPs brings security to the assay
UNG (Uracil-N-Glycosylase)hydrolyses all single-stranded and double-strandedDNA containing dUTPs
ROXMgCl2Inert colored dye
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40 Cycle
Thermal profile
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Evidence of optimization (from gradients) DSpecificity (gel, sequence, melt, or digest) EFor SYBR Green I, Cq of the NTC ECalibration curves with slope and y intercept EPCR efficiency calculated from slope ECIs for PCR efficiency or SE Dr2 of calibration curve ELinear dynamic range ECq variation at LOD ECIs throughout range DEvidence for LOD EIf multiplex, efficiency and LOD of each assay E
LOD = Limit of detectedE = essential, D = desirable,
The MIQE guidelines-qPCR validation-
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Reaction validation
Start with a gradient RT-qPCR to optimizeannealing temperature.
Create standard curve from a serial dilutionof template to test primers/probe acrossbroad dynamic range.
Evaluate:- Specificity- Efficiency- Reproducibility- Dynamic range- Intra assay variation
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Conceptual considerations
Analytical sensitivity, clinical sensitivity, limit
of detection
Analytical specificity
Accuracy
Repeatability
Reproducibility
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Linear standard curve (R2 > 0.985)
High amplification efficiency
Consistency across replicate reactions
The hallmarks of anoptimized RT-qPCR
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Standard curve
y = -3.4155x + 38.904
R2 = 0.9988
0
5
10
15
20
25
30
35
40
0 1 2 3 4 5 6 7 8 9
Log copy number
Ct
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Difference in PCR efficiency generate falselycalculated differences in gene expression
The efficiency of the PCR should be 95-100% (idealslope = -3.32)
Several methods are described to calculatereal-time PCR efficiency
Amplification efficiency
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Amplification efficiency
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1
10
100
1,000
10,000
100,000
1,000,000
10,000,000
100,000,000
1,000,000,000
10,000,000,000
0 10 20 30
PCR CYCLE NUMBERA
MO
UN
T O
F D
NA
100% EFF
90% EFF
80% EFF
70% EFF
Amplification efficiency
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RT-qPCRRT-qPCREfficiencyEfficiency
PCR InhibitorsHemoglobin, Urea, Heparin
Organic or Phenol CompoundsGlycogen, Fats, Ca2
+
Laboratory items, Powder
PCR EnhancersDMSO, BSA, Glycerol
Formamid, PEG, TMANO, TMACGene 32 protein, Taq ExtenderAccuPrime, E. coli ss DNA bind
NA degradation
Tissue degradation
DNA dyes
Nonspecific PCR products
Lab management Cycle conditions
PCR platform
NA concentration
PCR components
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qPCR analysis program (source, version) EMethod of Cq determination EOutlier identification and disposition EResults for NTCs EJustification of number and choice of reference genes EDescription of normalization method ENumber and concordance of biological replicates DNumber and stage (reverse transcription or qPCR) of technical replicates ERepeatability (intraassay variation) EReproducibility (interassay variation, CV) DPower analysis DStatistical methods for results significance ESoftware (source, version) ECq or raw data submission with RDML D
The MIQE guidelines- Data analysis-
E = essential, D = desirable,
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Importance ofcontrols
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Frequency of use of controls
N=148
From Nucleic Acid Research Group, NARG survey 2007,http://www.abrf.org/NARG/
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Normalization ofRT-qPCR
•Real-time PCR can be very accurate over a large
dynamic range
•Measuring RNA by RT-qPCR can be affected by error:
- Inherent variability of RNA
- Multi-step process
•Normalization required to control for error
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Using a reference gene is a simple and
effective method
Must be validated for the specific experiment
using the actual samples being measured
Failure to do so may generate incorrect results
Reference genes
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•Valid reference gene should correct differences in RNA sampling.•Reference gene should have:
- constant RNA transcription- transcribed at different experimental conditions- sufficiently abundant across different tissues and cell types
•The "perfect" RG does NOT exist.
Reference genes
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Reference genes
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Reference genes
Genes that show little variation from the calibrator should be chosen as reliable reference genes.
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There is a lot of published datathat has used invalidated
reference gene(s) for normalization
Software: geNormBestKeeperGeneral pattern recognition
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Intra-assay variationCV=18.7%
Inter-assay variationCV=28.6%
Input RNA Input RNA
Intra/inter-assayvariation
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Quantification strategies inRT-qPCR
Pfaffl, M.W., BioSpectrum 2004
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Relative quantification
The mRNA expression is relative to:- non treated control- time point zero- another gene of interest- mean expression of a target gene- universal calibration curve- constant expressed RG- RG index of more RGs (>3)- etc ?????
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Relative quantification
Three general procedures of calculation:1. ΔCq (R = 2[Cq sample – Cq control], R = 2ΔCq ), ΔΔCq
method (R = 2–[ΔCq sample – ΔCq control] , R = 2–ΔΔCq)without efficiency correction.
2. Calculation models, based on ONE sample and MULTIPLE samples
3. Calculation models, based on MULTIPLE sample and on MULTIPLE reference genes, consisting at least of three reference genes
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Data analysis methods
Standard curve ΔΔCt REST software (free) RealTime Statminer® software (AB, $3,000/1 year) GenEx software LinRegPCR software qBase software DART-PCR software Q-Gene software CAamER software Gene expression Macro software (Bio-Rad) qPCR-DAMS software LinRegPCR software Other
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Sample procurement which requires following strictexperimental protocols for acquisition, processing, andstorage to assure biological reproducibility and minimizeSD between replicates.
Appropriate number of biological (n≥3) and technical (n≥2)replicates with SD between technical replicates of less than0.3 Cq.
Use an RNA isolation procedure that produces high-qualitytotal RNA and high yield.
Digest purified RNA with DNase I. Perform RT reactions with a robust reverse transcriptase. Test cDNA yield and quality.
The key steps for most RT-qPCRexperiments include:
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Design gene-specific PCR primers. Reduce technical errors in PCR reaction setup. For relative quantification test gene-specific primers for at
least four potential reference genes. Perform real-time PCR on test and reference genes in
parallel for each sample (≤0.5 Cq between all experimentalconditions or time points).
Determine which reference gene(s) is best for normalization. Calculate relative transcript abundance for each gene in
each sample. RT-qPCR experiments with appropriate positive and no
template controls.
The key steps for most RT-qPCRexperiments include:
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RDMLReal-Time PCR Data Markup Language
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RDMLhttp://www.rdml.org
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RT-qPCRassay
NA QC
Assayoptimization
Samplehandling
Analysis
MIQE
RT-qPCRlanguage
Components for publishing a reliable RT-qPCR assay
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Acknowledgments
qPCR Core Facility
Alicja OmanskaCara WademanCathy IntaGreg SimonekTammi Olineka
Dr. Nicola PusterelaSamantha Mapes
Dr. Adib RowhaniDr. Fatima Osman
Dr. Stephen W. BartholdDr. Sunlian FengEdlin EscobarKimberly Olsen
Dr. Jane Sykes