Department of Plant Biotechnology 1

Gene Expression Analysis by Real

Time PCR

Presented by,Antre Suresh Haribhau

Jr. M.Sc. Plant BiotechnologyPALB 6272

22/12/2016

Submitted To,Dr. ShyamalammaTechniques in Molecular Biology

University of Agricultural Sciences, GKVK Campus, Bangalore

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Overview It was first introduced in 1992 by Higuchi and coworkers and has seen a rapid increase in its use since (Higuchi et al., 1992, 1993).

Over the past decade, real-time PCR applications have become broadly used tools for the quantification of specific sequences in complex mixtures.

For example Genotyping (Alker et al., 2004; Cheng et al., 2004; Gibson, 2006) Assessing gene copy number in cancer tissue (Bieche et al., 1998;

K¨onigshoff et al., 2003; Kindich et al., 2005) Quantifying viral load in patients (Ward et al., 2004)

However, the most common use for this technology has been to study gene expression levels by coupling it with a procedure called reverse transcription (Gibson et al., 1996; Bi´eche et al., 1999; Leutenegger et al., 1999; Livak and Schmittgen, 2001; Liss, 2002).

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Principle

Real-time PCR allows precise quantification of specific nucleic acids in a complex mixture even if the starting amount of material is at a very low concentration.

This is accomplished by monitoring the amplification of a target sequence in real-time using fluorescent technology.

How quickly the amplified target reaches a threshold detection level correlates with the amount of starting material present.

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Endpoint RT-PCR Real Time RT-PCR

What is endpoint RT-PCR and real time RT-PCR …?

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cDNA From mRNA

Step 1 Generating cDNA from RNA population

Working Procedure for real time PCR Instrument

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Step 2 Optimizing the PCR Reaction for Real –Time Analysis

i) Primer design

PCR primers for the qPCR step of RT-qPCR should ideally be designed to span an exon-exon junction.

Primers pairs should not significantly complement each other or themselves.

Primer pairs should have approximately equal GC content (between 40% to 70%) and have similar annealing temperatures.

ii) Annealing temperature

Using a temperature gradient analysis to determine the optimal annealing temperature.

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Step 3 Amplicon Detection in the Real-Time Thermal Cycler

i) Fluorescent dyes for monitoring real-time amplification

Fluorescent dyes

Non specific OR DNA-binding agents

SYBR Green I

Strand specific OR Hydrolyzation based Assays

TaqMan

Molecular Beacons

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SYBR Green I Assay

Detector

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TaqMan Assay

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Molecular Beacons are hairpin structures composed of a (25–40 nt) nucleotide base paired stem and a target specific nucleotide loop.

Denaturation

Primer molecular Beacon annealing

Extension

5’3’ Q

3’5’5’

5’3’

3’5’

5’3’

3’5’

5’

3’5’

5’3’5’

5’

5’

QR

5’

Molecular Beacons

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Components of Real-Time PCR Detection Systems

Optical detection system

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Nomenclature commonly used in real-time quantitative PCR.

Single Amplification Plot

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Software of Bio system for Real Time PCR

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ii) Melting point analysis to verify amplification specificity

(A) Shows double peaks. (primer-dimer)

(B) A single peak melting curve, representative of a single species of DNA molecule in the reaction.

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Step 4 Real-Time RT-PCR Analysis and Quantification

i) Setting the threshold for detection of the amplicon

(A) Linear plot (Cycle no. Vs Amount of DNA)

(B) Logarithmic plot (Cycle no. Vs Amount of DNA)

The threshold line is used to quantify the amount of DNA and is set at the exponential phase of the amplification.

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1. Absolute Quantification

Requires the construction of an absolute standard curve for each target.

The standard curve is based on a serial dilution of a sample with known copy number.

CT of each standard sample is plotted against the logarithm of the known concentration.

The standard curve is then used to estimate concentrations of unknown samples and gene copy number

ii) Amplicon quantification

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Linear plot Logarithmic plot

Standard curve

Standard curve analysis

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Five independent chickpea lines two carrying Cry1Aa3 (462 bp) and three expressing Cry1Ac (533 bp) were used for real time PCR based analysis and southern hybridization.

Real time PCR analysis carried out by using Maxima SYBR Green.

The transgene copy number in transgenic plant sample was calculated by interpolation from a standard curve Ct values generated using known amount of starting DNA concentrations.

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The cry1Ac/cry1Aa3 gene PCR product detection in real-time PCR.

(a) Amplification plots generated using known amounts of the pBinAR plasmid.

(b)Standard curve for data present in (a) (c)Melting curve derivative profile

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Southern blot analysis of the transgenic chickpea plants carrying

(a) Transgenic chickpea plants Cry1Aa3 gene

(b) Transgenic chickpea plants Cry1Ac gene

Cry1Aa3

Cry1Ac

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Reference gene (Housekeepng genes): Abundantly and constantly expressed gene. Expression level of these genes remains constant. eg 18 S rRNA, GAPDH, β Actin

Comparative CT Method. (Pfaffl, 2001)

This involves comparing CT values of the samples with a control or calibrator such as a non-treated sample.

The CT values of both the calibrator and the samples are normalized to an endogenous housekeeping gene.

This give ∆CT value of control and the sample.

The comparative CT method is also known as 2-∆∆CT method, where ∆∆CT = ∆CT,sample - ∆CT,reference

Fold change = Efficiency-∆∆CT or 2-∆∆CT

(which gives relative gene expression)

2. Relative Quantification

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For example - Assume the following average CT for your experimental and control treatments:

Experimental target CT = 27.1; Experimental housekeeping CT = 26.3; Control target CT = 31.3; control housekeeping CT = 26.2.

In addition, assume that the efficiencies for both primer sets are the same at 90% (EP = 1.9). Plugging these into the equations above:

Then ∆∆CT target = (CT control − CT treatment) = (31.3 − 27.1) = 4.2

∆∆CT housekeeping = (CT control − CT treatment) = (26.3 − 26.2) = 0.1

Fold change normalized = (1.9)4.2/(1.9)0.1 = 14.81/1.07 = 13.8. This corresponds to a 13.8 fold increase in gene expression in the treated samples compared to the control samples.

Cntd…

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Case Study 1

In this study, a novel Kunitz trypsin inhibitor gene, ClKTI, was isolated from a medicinal herb plant, turmeric, Curcuma longa.

Using real-time quantitative PCR, the ClKTI gene expression pattern in five different tissues (flower, basal stem, stem, rhizome and root) treated with methyl-jasmonate(MeJA) was studied where MeJA was suggested to regulate expression of PI genes in plants.

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Procedure

1. RNA extraction from 60 days old C. longa leaves treated with 10% MeJA (24 Hrs.)

2. Primer design for ClKTI gene – Multiple sequence alignment between different plant species to find out highly conserved region. (Amplification target gene around 380bp)

3. cDNA Synthesis & PCR

4. Sequencing - Purified PCR product ligated into cloning vector (pGEM-T) & cloned into TOP10E.coli

5. Determination of gene identity – BLASt at NCBI

6. Full length of ClKTI gene synthesis- By developing new set of primer based on sequencing.

7. Phylogenetic tree construction- Amino acid sequences of KTIs from other plant species with ClKTI .

8. Homology modeling- To predict protein structure

9. Real-time quantitative polymerase chain reaction analysis

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Results

1. A full-length sequence of ClKTI with deduced amino acid sequence (754bp).

ClKTI protein - consisting of 213 amino acids with a calculated molecular mass of 22.8 kDa

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2. Multiple sequence alignments of deduced amino acids sequence of ClKTI with sequences of KTI from different plant species.

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3. Evolution relationships

3 Disulfide bridges6 Cysteine residues

12 Beta sheets

4. Homology modeling

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Actin, alpha-tubulin and ubiquitin (ubox) genes were selected for the expression stability validation in five different tissues of C. longa.

5. RT-qPCR analysis

Expression stability of the reference gene candidates and their stability ranking generated by RefFinder.

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6.Normalized fold expression of ClKTI in methyljasmonate (MJ)-treated and - non-treated (NT) tissues by using Actin as reference gene for normalization.

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The expression stability of four tomato reference genes, namely CAC, SAND, Expressed and ACTIN2 was evaluated.

The expression profiles of the transcription factors FRUITFULL1 and APETALA2c during fruit development was compared with validated the reference genes

Case Study 2

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Procedure

1. Plant Growth Conditions Tomato (S. lycopersicum) MT-Rg1 genotype plants were grown in a greenhouse under local conditions in the summer (around 16h light/8h dark)at an average mean temperature of 30 oC.

2. Tissue Collection Tomato fruits were sampled at eight different developmental stages, based on the fruit stage division .

3. RNA Extraction and cDNA Synthesis Total RNA extraction was performed using the TRIzolR (Ambion) protocol.

4. Quantitative Real-Time PCR

ABI7500 Fast Real Time –PCR System using SYBRR Green I (Life Technologies).

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Candidate reference genes and validation genes used for qPCR expression study in Solanum lycopersicum cv.MT-Rg1 during fruit development stages.

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Data Analysis

Data processing workflow for quantitative PCR data. Each program generates an input file needed for next step in the workflow .

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1. Expression Stability Values (M)of Candidate Reference Genes

geNorm

Results

NormFinder

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2. AP2c and FUL1 Expression Profiles in MT-Rg1 fruits.

(A) AP2c

Dataset was normalized using the two best reference genes(CAC and Exp) & poorly ranked reference gene (SAND).

(B) FUL1

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Summary

The measurement of PCR products as they accumulate (i.e., real-time quantitative PCR) removes the variability associated with conventional PCR.

Amplification detection using fluorescent dyes (SYBR green l ) and also by using sequences specific probes (TaqMan, Molecular Beacons).

Two different methods are commonly used to quantify the results obtained by real-time PCR –

Standard curve or absolute quantitation method (Gene copy number).

Relative quantitation also known as the comparative threshold method (Gene expression).

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References

Basic principles of real-time quantitative PCR . Manit Arya†, Iqbal S Shergill, M Williamson, L Gommersall, N Arya and Hitendra RH Patel . Expert Rev. Mol. Diagn. 5(2), (2005)

Real-Time PCR . Dean Fraga, Tea Meulia, and Steven Fenster . Current Protocols Essential Laboratory Techniques, 2008 John Wiley & Sons, Inc.

Real time PCR based detection of transgene copy number in transgenic chickpea lines expressing Cry1Aa3 and Cry1Ac . Surender Khatodia et al., Int. J. Pure App. Biosci. 2 (4): 100-105 (2014)

Identification and expression profiling of a novel Kunitz trypsin inhibitor (KTI) gene from turmeric, Curcuma longa, by real-time quantitative PCR (RT-qPCR). Seow-Neng Chan et al., Acta Physiol Plant (2017) 39:12

Selection of Reference Genes for Quantitative Real-Time RT-PCR Studies in Tomato Fruit of the Genotype MT-Rg1. Karla L. González-Aguilera et al., Frontiers in Plant Science, September 2016 | Volume 7 | Article 1386.

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