Gene Expression Analysis by Real Time PCR

Nowadays, Real Time-PCR analysis has become the method of choice for gene expression studies and validating transcriptomic data.

1. 1 Gene Expression Analysis by Real Time PCR Presented by, Antre Suresh Haribhau Jr. M.Sc. Plant Biotechnology PALB 6272 22/12/2016 Department of Plant Biotechnology Submitted To, Dr. Shyamalamma Techniques in Molecular Biology University of Agricultural Sciences, GKVK Campus, Bangalore

2. 2 O verview 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).

3. 3 P rinciple 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.

4. Endpoint RT-PCR Real Time RT-PCR W hat is endpoint RT-PCR and real time RT-PCR …? 4

5. 5 cDNA From mRNA Step 1 Generating cDNA from RNA population W orking Procedure for real time PCR Instrument

6. 6 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.

7. 7 Step 3 Amplicon Detection in the Real-Time Thermal Cycler i ) Fluorescent dyes for monitoring real-time amplification

8. 8 SYBR Green I Assay Detector

9. 9 TaqMan Assay

10. 10 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’ Q R 5’ Molecular Beacons

11. 11 Components of Real-Time PCR Detection Systems Optical detection system  

12. 12 Nomenclature commonly used in real-time quantitative PCR. Single Amplification Plot

13. 13 Software of Bio system for Real Time PCR

14. 14 ii) Melting point analysis to verify amplification specificity Shows double peaks. (primer- dimer ) ( B) A single peak melting curve, representative of a single species of DNA molecule in the reaction.

15. 15 Step 4 Real-Time RT-PCR Analysis and Quantification i ) Setting the threshold for detection of the amplicon 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.

16. 16 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. C T 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

17. 17 Linear plot Logarithmic plot Standard curve Standard curve analysis

18. 18 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.

19. 19 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

20. 20 Southern blot analysis of the transgenic chickpea plants carrying Transgenic chickpea plants Cry1Aa3 gene (b) Transgenic chickpea plants Cry1Ac gene Cry1Aa3 Cry1Ac

21. 21 Reference gene ( Housekeepng genes) : A bundantly and constantly expressed gene. E xpression level of these genes remains constant. eg 18 S rRNA , GAPDH, β Actin Comparative C T  Method . ( Pfaffl , 2001 ) This involves comparing C T  values of the samples with a control or calibrator such as a non-treated sample. The C T  values of both the calibrator and the samples are normalized to an endogenous housekeeping gene. This  give ∆C T value of control and the sample. The comparative C T  method is also known as 2 -∆∆CT  method , where  ∆∆C T  = ∆ C T,sample  - ∆ C T,reference Fold change = Efficiency -∆∆CT or 2 -∆∆CT (which gives relative gene expression) 2. Relative Quantification

22. 22 For example - Assume the following average C T for your experimental and control treatments: Experimental target C T = 27.1; Experimental housekeeping C T = 26.3; Control target C T = 31.3; control housekeeping C T = 26.2. In addition, assume that the efficiencies for both primer sets are the same at 90% (E P = 1.9). Plugging these into the equations above: Then   ∆∆C T target = ( C T control − C T treatment ) = (31.3 − 27.1) = 4.2 ∆∆C T housekeeping = ( C T control − C T 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 …

23. 23 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.

24. 24 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 TOP10 E.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

25. 25 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

26. 26 2. Multiple sequence alignments of deduced amino acids sequence of ClKTI with sequences of KTI from different plant species.

27. 27 3. Evolution relationships 3 Disulfide bridges 6 Cysteine residues 12 Beta sheets 4. Homology modeling

28. 28 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 .

29. 29 6.Normalized fold expression of ClKTI in methyljasmonate (MJ)-treated and - non-treated (NT) t issues by using Actin as reference gene for normalization.

30. 30 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

31. 31 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 o C. 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).

32. 32 Candidate reference genes and validation genes used for qPCR expression study in Solanum lycopersicum cv.MT-Rg1 during fruit development stages.

33. 33 Data Analysis Data processing workflow for quantitative PCR data. Each program generates an input file needed for next step in the workflow .

34. 34 1. Expression Stability Values (M)of Candidate Reference Genes geNorm Results NormFinder

35. 35 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

36. 36 S ummary 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).

37. 37 R eferences 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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