qRT-PCR and Application
Transcript of qRT-PCR and Application
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Course Outline
• Definition of qRT-PCR
• Experimental Design for qRT-PCR
• Analysis and Calculation
• Application
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You have learned
• Session 1:
– Definition of Functional Genomics and Proteomics
– Various instrumentation that can access Functional Genomics and Proteomics
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You have learned
• Session 2, 3, 4
– Targetting gene or region of interest using PCR
– Discovering functions of genes/protein:
• Multiple sequence Alignment
• BLAST: DNA and protein
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This session
• Session 5
– You know the gene functions
– How to measure it quantitatively?
– What is the effect of certain genes if treatments: drugs, knock-out, mutations occur?
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Introduction
• PCR: Amplifying DNA into millions/billions of copies.
• In normal PCR, we can just see the endpoints or final result.– In many occasions, varying
amounts of starting materials will eventually reach same amount of copy numbers
Endpoint
Are there any difference in the endpoint? NO!!
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Looking at the Amplification Graph
Then how are we quantify the DNA samples?
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Looking at the Threshold can differentiate and relate to the quantity!
Threshold
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Real-Time PCR
• Real-Time PCR is the technique where amplification process of DNA template is monitored real-time.
• Detection of DNA Amplification: Fluorophores
• There are 2 types of Fluorophores:
– Sybr Green
– Taqman Probes
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Sybr Green
• Principle: Form DNA Intercalation, similar with Ethidium Bromide.
• Non-specific fluorophores.
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Taqman Probes
• Specific Fluorophores.• Only bind to target
amplicons, non-specific ones will not give signals.
• Consists of fluorophores and quenchers.
• Quenchers will suppress fluorescences and dissociates when amplification occurs, hence releasing the signal from fluorescences.
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Experimental Design for qRT-PCR
• qRT-PCR can be used for 2 purposes:
– Detection
– Quantification
• DNA (for the purpose such as detecting genome copy numbers) and RNA (for the purpose such as mRNA transcripts, miRNAs, viral RNA etc) samples can be used.
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Experimental Design for qRT-PCR
1. Sample Preparation
2. Primer (and Taqman Probe Design)
3. Reaction Setting
4. Analysis and Calculation
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Sample Preparation
• Sample must be purified• Nowadays, Extraction Kits are available.• For DNA samples, more straightforward. No
treatment generally required upon harvesting.• For RNA samples, due to its instability, additional
steps must be done, because RNase easily degrades RNA and reduce RNA quality.– Harvesting in cold temperature (4 oC)– Using RNA stabilization agent with denaturant such
as ammonium sulfate. (Commercially available: RNAlater, RNAshield etc)
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Primer Design• The rule: Primer Design from Session 2.• BUT with additional rule:
– Fragment of the desired genes is created instead, approximately 50 – 400 base pairs, usually termed as amplicons.
– For Taqman Probes, third primer is required (Taq Probe).
– Nearer to 3’ is preferable.
Full Length Gene Forward
Amplicon
Reverse
Taq Probe
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There is already available Program
• Google: Primer Design Software for QPCR.
• One of the easiest and user friendly software: Universal Probe Library from Roche.
• Software will recommend multiple primer sets, hence further optimization is required.
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Reaction Setting The Thermal Cycler
• Rules, same with PCR Session 2.
• With additional Rules:
– Detection step: Usually done in Elongation.
– Since Amplicon is shorter, in some application, anneal and elongation can be done in one temperature.
Denaturation 95oC, 2 min
Denaturation 95oC, 30 sec
Annealing 65oC, 15 sec
Elongation 68oC, 30 sec (Fluorescence Detection)
Cooling 4oC, indefinite
Repeated 40-50 cycles
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Analysis
• The graph produced will be S-curved shape.
• In higher amount of sample, the fluorescence peaks earlier.
• The cycle required to reach fluorescence threshold = Ct value.
• Each number of Ct value represent one-time amplification with 2-fold magnitude.
• We can use this to estimate the amount of the sample, which can be done in relative and absolute methods.
Threshold
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Relative Methods
• In relative methods, the amount of a sample will be compared with another sample (example control or mock).
• Every +1 Ct value in relative to control = the sample is 2x less than the control
• For example: If the control shows Ct value of 20 and the sample shows 16, it means that the sample have (24) = 16 times more DNA copies.
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A B C D E F
Ct A = 12.8
Ct B = 16.2
It means that A has more sample than B by 2(16.2-12.8) = 23.4 = 10.6x
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Housekeeping Genes in Relative Quantification
• In Experiment, there are many cases that we need to normalize experiments to make unbiased comparison.– Amount of cells variations
– Replicates variations
• For more correct comparisons, housekeeping genes are used.
• Housekeeping Genes: Genes that are expressed consistently and relatively unchanged in application.
• Recommended to use multiple housekeeping genes.
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List of Housekeeping Genes
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Using Housekeeping Genes for Normalization
• With the Ct value rules, we can normalize all samples with the basis of housekeeping genes.
Example:
– If sample A has Ct value of 17 and sample B has Ct value of 18. It means that the amount of sample A is 2x more than sample B.
– Hence, to make unbiased comparison between sample A and sample B. All result of sample B must be multiplied by 2 to match with the amount of sample A.
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Formula used in qRT-PCR calculation
• Most commonly used formula: 2-∆∆Ct by Livak and Schmittgen (2001).
• Always ∆Ct = Ct of treatment or target – Ct of control
• Consist of 3 steps:– Normalize against housekeeping genes (first
delta)
– Calculate against target gene(s) (second delta)
– Calculate based on Ct value with 2-∆∆Ct
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Example:
Sample Gene Ct value
Control BRCA1 19.11
ACTB 21.25
GAPDH 26.24
Drug X BRCA1 22.25
ACTB 22.51
GAPDH 28.23
How many fold changes of BRCA1 in the sample?
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Step 1: Normalization against Housekeeping Genes
• For multiple housekeeping genes, average is the the most common practice of normalization.
• Control: (21.25 + 26.24)/2 = 23.745• Drug X: (22.51 + 28.23)/2 = 25.37• First Delta: 2-∆Ct = 2-(Ct drug – Ct control) = 2 –(25.37-23.745) = 2 -1.625 = 0.324 fold• Meaning = Drug X is still 0.324 x Control (Not comparable)• To normalize Drug X and Control, we need to increase value of Drug X by
(1/0.324) = 3.084 x
Sample Gene Ct value
Control BRCA1 19.11
ACTB 21.25
GAPDH 26.24
Drug X BRCA1 22.25
ACTB 22.51
GAPDH 28.23
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Step 2: Calculation against Genes
• BRCA1 expression in Drug X = 2-∆Ct = 2-(Ct drug – Ct
control) = 2-(22.25-19.11) = 0.113 x Control (Second Delta)
Sample Gene Ct value
Control BRCA1 19.11
ACTB 21.25
GAPDH 26.24
Drug X BRCA1 22.25
ACTB 22.51
GAPDH 28.23
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Step 3: Calculate the 2-∆∆Ct
• The value from Step 1 = Control have 3.084x more than Drug X
• The value from Step 2 = BRCA1 in DrugX change is 0.113x than Drug X
BRCA1 fold-change in Drug X is changed by = Step 1 x Step 2 = 3.084 (from Step 1) x 0.113 (from Step 2) = 0.348 x Control
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Easy Step of Calculation
http://bitesizebio.com/24894/4-easy-steps-to-analyze-your-qpcr-data-using-double-delta-ct-analysis/
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Practice QuestionA student conduct investigation of toxicity of a his developed drug to a kidney. He picked 3 genes to monitor kidney toxicity (KIM, NGAL, HGF). He diluted the drug into 4 concentrations and tested to the kidney cell culture. The result is as follows
Gene Tested
Control 125 pM 250 pM 500 pM 1000pM
KIM 21.25 20.98 21.22 23.55 30.77
NGAL 26.22 26.63 27.44 27.65 28.66
HGF 24.43 25.64 26.33 26.66 27.23
GAPDH 22.61 22.14 23.15 22.16 22.95
EEF1A1 19.16 19.66 19.99 18.95 19.23
a. Determine the fold-change of each category: KIM, NGAL, HGF
b. What is your analysis of the result?
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Next Session:Microarray and Application
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THANK YOU!