Lecture 3 (RT_qPCR) PDF

1 Gene Expression Analysis  2 Summary of weeks 1-2 labs Sterilization and plating of Arabidopsis wild-type seeds Testing primers with Arabidopsis gDNA Bioinformatics Lab1 (DNA sequence structu...

1 Gene Expression Analysis  2 Summary of weeks 1-2 labs Sterilization and plating of Arabidopsis wild-type seeds Testing primers with Arabidopsis gDNA Bioinformatics Lab1 (DNA sequence structure and alignment, in silico PCR) DNA isolation & analysis (gel electrophoresis) DNA amplification by PCR using gene-specific primers (for test and reference genes)  3 Weeks 3-5 labs Gene expression level of CBF4 in WT seedlings exposed to abiotic stress or to the stress hormone, ABA. Bioinformatics analysis (week 3): In-silico gene expression analysis using Microarray/RNAseq (www.bar.utoronto.ca) Designing optimal qPCR primers with Primer-Blast (https://www.ncbi.nlm.nih.gov/tools/primer-blast/) Predicting amplicon size (Primer-Blast) Setting up your qPCR reaction Calculation of relative gene expression level (-delta delta Ct method) RNA isolation & analysis, cDNA synthesis and qPCR (one-step RT-qPCR) (weeks 4-5)  4 Gene expression analysis To gain insight into the function of a gene, it is important to study its expression pattern and regulation, e.g. by quantifying mRNA/transcript levels and profiles: Spatio-temporal expression pattern (expression profile) o In which organs (where) and at which time during development (when) is a gene expressed Regulation of gene expression (up- and down-regulation) o If mRNA level increases/decreases following exposure to different growth conditions or treatments (stress, hormones, pathogens, drugs, etc.)  5 Techniques to determine gene expression profiles Reverse transcription PCR (RT-PCR) Reverse transcription-quantitative PCR (RT-qPCR) → used in this course Northern blot (or RNA-blot) In-situ hybridization Microarrays RNA sequencing (RNAseq)  6 Techniques to determine gene expression profiles Several techniques can be used to characterize gene expression patterns: RT-PCR, RT-qPCR, Northern blot, in-situ hybridization → the expression pattern of a limited number of genes can be determined at the same time. Microarray and RNAseq. The completion of several genome-sequencing projects, coupled to major technological developments, has allowed investigators to quickly determine the expression patterns of thousand of genes at the same time by microarray and RNAseq technologies. This is known as transcriptomic analysis. The data is usually deposited online in databases and can be used in many gene discovery research projects and for hypothesis generation. In BIOD21 lab, you will use RT-qPCR to determine the expression level of CBF4 in WT exposed to stress or ABA, and survey microarray and RNAseq data to predict CBF4 expression pattern and regulation in Arabidopsis (Bioinformatic lab 2)  7 RT-qPCR: Most sensitive and quantitative: can detect and quantify very low abundant genes Applications: gene expression analysis (mRNA/transcript). Examples: quantifying changes in gene expression levels: during development in response to a treatment in WT vs mutant (confirming knockout/knockdown mutations) validating results obtained from transcriptomic studies (microarray, RNAseq) etc. Thermofisher molecular biology library has good explanations of the most popular molecular biology techniques, including basic principles of RT-qPCR. Check this link (https://www.thermofisher.com/ca/en/home/brands/thermo-scientific/molecular-biology/molecular-biology-learning-center/molecular-biology-resource-library/spotlight- articles/basic-principles-rt-qpcr.html)  8 Overview of RT-qPCR 1. In RT-qPCR, total RNA (messanger RNA, transfer RNA or ribosomal RNA) or small RNA (ncRNA, miRNA, etc) is first 1. RNA isolation isolated. RT 2. RNA is transcribed into complementary DNA (cDNA) by 2. cDNA synthesis reverse transcriptase (RT). fluorescent probe Taq DNA Pol 3. The cDNA is then used as the template in the PCR reaction, together with gene specific primers and a fluorescent probe 3. PCR amplification (such as SYBR Green I, which binds only to double stranded DNA) 4. cDNA is amplified and the fluorescence signal that is 4. Fluorescence generated reflects the amount of PCR product formed (qPCR). quantification  9 Primers for RT-qPCR In mRNA quantification by RT-PCR and RT-qPCR, false positive signals (false amplifications) may arise from amplification of the gene of interest in genomic DNA (gDNA), which may be present in impure cDNA preparations that contain gDNA contamination. Since RNA is converted back into DNA via reverse transcriptase, and RNA then target genes are amplified by PCR, any genomic DNA present could also be amplified. This questions whether the final results of RT-qPCR are due to the cDNA that was generated, or simply the genomic DNA contaminating the cDNA sample. Why is this important? This problem can be avoided by treating the RNA with Dnase I, prior to cDNA synthesis!! Why prior to? However, genomic DNA contamination can be introduced at later steps during cDNA synthesis, or while setting up the RT-qPCR reaction.  10 A) Intron flanking primers To determine if the cDNA prepared contains genomic DNA contamination, PCR can be run using intron flanking primers, which anneal to different exons, having at least one intron in between. Do both primers need to flank an intron to detect gDNA contamination? Why?  11 A) B) 1. 2. 1. PCR amplicon generated using Primers A+B and cDNA made by student X 1500 bp- 1000 bp- 2. PCR amplicons generated using Primers A+B and cDNA made by student Z 500 bp- Which student has generated a cDNA sample with genomic DNA contamination and why?  12 B) Intron spanning primers If the cDNA is contaminated with genomic DNA, you can still detect the presence or absence of your gene’s transcript, WITHOUT amplifying the genomic DNA, by using primers spanning an intron. This AVOIDS amplification of genomic DNA (contamination) in cDNA samples 3’ 5’ 5’ 3’ The Forward primer can amplify this gene ONLY from cDNA, and NOT from genomic DNA, because the primer spans an intron and the 3’ end of the primer would not be able to bind the DNA (too far). Do both primers need to span an intron to avoid gDNA contamination? Why?  13 Normalization and Reference Genes Comparing samples requires normalization to compensate for differences in the amount of starting biological material in the tested samples. ❖Although we try to use the same amount of starting RNA for each sample, PCR is very sensitive and any small difference in the starting RNA material will show a difference in the final expression level of your gene. You can normalize the total RNA amount to ribosomal RNA or internal reference genes, such as housekeeping genes. ❖Housekeeping genes are those whose expression levels remain roughly constant in all cells and tissues. The gene whose expression levels you wish to analyze is amplified from the cDNA mixture together with the housekeeping gene. The reference gene is subject to the same errors in cDNA preparation as the gene of interest, so it makes an excellent normalizing control. In the lab you will use ACTIN 7 (ACT7) as the reference gene.  14 The fluorescent reporter (probe or dye) In Real-time PCR, the reaction products for each sample are quantified in every cycle and monitored by the increase in fluorescent signal. The fluorescent signal is proportional to the amount of DNA amplified  15 SYBR Green I A number of fluorescent reporters are available; the most common are TaqMan probes and SYBR Green I dye. In D21 labs we will use SYBR Green I. SYBR Green I binds only double stranded DNA. The reporter generates a fluorescence signal that reflects the amount of PCR product formed. The resulting DNA-dye-complex absorbs blue light (λmax = 497 nm) and emits green light (λmax = 520 nm). Question: Why can’t we use classical DNA intercalators, such as EtBr? EtBr interferes with the polymerase reaction, while cyanine dyes (such as SYBR Green I) become fluorescent upon binding to double stranded DNA and do not interfere. Also, SYBR green I is much more fluorescent than EtBr →more sensitive  SYBR green I 16 from Qiagen The fluorescence signal is measured by the fluorimeter at the end of each PCR extension step (every cycle). Fluorescence intensity correlates with amount of amplicon. All double stranded DNA will bind SYBR green, including primer-dimers and non-specific reaction products, hence high primer specificity is required. A well-optimized reaction is essential for accurate results.  17 qPCR response curves Plateau phase Ct(1) Ct(2) Linear phase Exponential phase Figure 1. The plot is sigmoidal, flat at the baseline level for the first 10 cycles (in this example) while the amount of template initially accumulates to the point where the fluorescence signal becomes detectable, and then enter the exponential phase. Then the plot rises linearly for several cycles and finally begins to "roll over" and then becomes almost flat (plateau). A threshold level is set sufficiently above background and the number of cycles required to reach threshold, Ct, or Quantification cycle (Qc), are registered. The EXPONENTIAL phase is used for quantification because it produces a fluorescence signal measurable over background.  18 During the initial cycles the fluorescence is low and cannot be distinguished from the background. As the amount of product accumulates fluorescence increases and generate a detectable signal. The signal initially increases exponentially, since the reagents are not limited. The linear phase is characterized by a linear increase in product as PCR reagents become limited. Thereafter it levels off and saturates (Figure 1). The signal saturation is due to the reaction running out of some critical component (the primers, the reporter, or the dNTPs). In a typical real-time PCR experiment all response curves saturate at the same level. Hence, conventional (end-point) PCR measurements tell us nothing about the initial amounts of target molecules that were present in the samples; they only distinguish a positive from a negative sample. On the other hand, the response curves in real-time PCR are separated in the growth phase of the reaction. This reflects the difference in their initial amounts of template molecules. The difference is quantified by comparing the number of amplification cycles required for the samples’ response curves to reach a particular threshold fluorescence signal level. The number of cycles required to reach threshold is called the Cycle threshold (Ct) or Quantification cycle (Qc). Ct (or Qc) inversely correlates with initial template concentrations (amounts). Question: In the previous graph, Ct(1) is 11, while Ct(2) is 15. which sample has lower amounts of transcripts for the gene being amplified? See video from NEB: https://international.neb.com/tools-and-resources/video-library/overview-of-qpcr?autoplay=1  19 Conventional PCR is based on end-point analysis -> you look at a band on a gel, you look at your data at one point in your reaction which happens to be when it’s all finished. Real time, quantitative PCR enables you to watch the kinetics of the reaction. The amount of product formed can be seen during the course of the reaction by monitoring the fluorescence of dyes or probes introduced into the reaction that is proportional to the amount of product formed.  20 Quantification of gene expression level: the ΔΔCt method 1. Normalization. To normalize gene expression for any differences in starting material, the ΔΔCt method (Livak and Schmittgen, 2001; Methods) can be used. To use this method, the target and reference genes must amplify with high efficiency, close to 100% (amplicon amount doubles at every cycle) and the efficiencies differ from each other by less than 5%. The efficiency of amplification is measured using serial dilution of cDNA. 2. Amplification efficiency. Parameters that affect amplification efficiency: Your samples may contain PCR inhibitors (proteins, polysaccharides, residual RNA prep contaminants) → Question: How can you check if your samples have contaminants? Your PCR primers may not be optimal Inaccurate sample and reagent pipetting If reaction efficiencies are low, optimize the reactions and/or select different primers pairs. If the efficiencies are ~100%, then calculate the expression ratio or fold difference using the 2-ΔΔCt. 2. Accuracy and Reproducibility. Pipetting must be very accurate Use 3 technical repeats (same RNA isolation) and 3 biological repeats (3 separate RNA isolations from 3 different experiments)  21 Relative quantification of gene expression STEPS to calculate the expression ratio or fold difference. Example: PYL1 expression level in WT compared to pyl1 mutant 1) Normalize Ct target gene (PYL1) to Ct reference gene (ACT7) in control samples (WT cDNA) → ΔCt1 2) Normalize Ct target gene (PYL1) to Ct reference gene (ACT7) in test sample (pyl1 ko mutant cDNA) → ΔCt2 3) Normalize ΔCt2 test sample (pyl1 mutant) to ΔCt1 control sample (WT) → ΔΔCt 4) Calculate the expression ratio or fold difference 2-ΔΔCt  22 Relative quantification of gene expression STEPS to calculate the expression ratio or fold difference 1) Normalize Ct target gene (PYL1) to Ct reference gene (ACT7) in control samples (WT cDNA) → ΔCt1 2) Normalize Ct target gene (PYL1) to Ct reference gene (ACT7) in test sample (pyl1 ko mutant cDNA) → ΔCt2 3) Normalize ΔCt2 test sample (pyl1 mutant) to ΔCt1 control sample (WT) → ΔΔCt 4) Calculate the expression ratio or fold difference 2-ΔΔCt Example: Ct Ct 1. ΔCt1 control sample (WT) = 25.85 - 24.47 = 1.38 (PYL1) (ACT7) 2. ΔCt2 test sample (pyl1 mutant) = 29.05 - 24.21 = 4.84 WT cDNA 25.85 24.47 3. ΔΔCt = 4.84-1.38 = 3.46 Pyl1 cDNA 29.05 24.21 4. Fold change = 2-ΔΔCt = 2-3.46 = 0.09 PYL1 expression level in the pyl1 mutant is 0.09-fold lower than in WT (9% of WT) → this is likely a knockout mutant  23 ACT7 PYL1 PYL4 template Ct template Ct template Ct WT 24.47 WT 25.85 WT 25.21 pyl1 24.21 pyl1 29.05 pyl1 25.03 pyl4 24.48 pyl4 25.77 pyl4 26.01 dCt1(mutant)=Ct(PYL1)-Ct(ACT7) = 29.05-24.21=4.84 dCt2(Wt)= Ct(PYL1)-Ct(ACTt7)=25.85-24.47=1.38 WT=1 ddCt PYL1(WT-mutant)=1.38-4.84=-3.46 pyl1 =0.09 → Normalized gene expression level of PYL1 vs WT: 2-3.46=0.091 dCt1(mutant)=Ct(PYL4)-Ct(ACT7)=26.01-24.48= 1.53 dCt2(Wt)= Ct(PYL4)-Ct(ACTt7)=25.21-24.47=0.74 WT=1 ddCt PYL4 (WT-mutant)=0.74-1.53= -0.79 pyl4 =0.58 → Normalized gene expression level of PYL4 vs WT: 2-0.79=0.58 Is pyl4 a knockout mutant?  24 Assay specificity: Tm and Melt Curve Tm and Melt Curve analysis are important features of SYBR I‐based assay to monitor the purity and specificity of the PCR product amplified. When SYBR I is present, as a DNA fragment is heated, a sudden decrease of fluorescence signal is observed at Tm when 50% of molecules become single‐stranded thus the loss of binding of SYBR I. Tm depends on length, sequence, and GC content. Melt curve analysis is important to assess whether the intercalating dye assays have produced single, specific PCR products. A Tm value and single melt curve peak indicates your primers are specific and amplify only one gene in the mixture of cDNA: 1 peak = 1 amplicon.  25 Melt Curve analysis Normalized Fluorescence (Rn) Temperature (°C) Rn (Normalized reporter) : The fluorescence emission intensity of the reporter dye (SYBR green) divided by the fluorescence emission intensity of the reference dye (ROX). The reference dye (such as ROX) normalizes non-PCR-related fluctuations in fluorescence. ROX is an inert fluorescent dye that can be added in a qPCR master mix. Unlike SYBR Green, the fluorescence of ROX is not affected by amplification of the PCR product. However, ROX fluorescence is affected by anything else that would alter overall fluorescence readings, such as bubbles in wells, evaporation, condensation or droplets, instrument issues, such as electrical surges.  26 Melt Curve analysis Fluorescence (-dRFU/dT ) Temperature (°C) Plot showing the change in fluorescence (delta relative fluorescence unit) with change in temperature (–dRFU/dT) and calculating the temperature at which the biggest change in fluorescence occurs (melt peak).  27 WT pyl4 ACT7 Relative fluorescence units pyl1 Ct Tm Amplification curve WT 24.47 81 pyl1 24.21 81 pyl4 24.48 81 What do these melt curves tell us? Melt curve Are the primers specific for ACT7  28 pyl4 WT PYL1 Ct Tm WT 25.85 80 pyl1 pyl1 29.05 80 pyl4 25.77 80 What do these melt curves tell us? Are the primers specific for PYL1  29 WT pyl1 PYL4 PYL4 0 Ct Tm pyl4 WT 25.21 82.5 pyl1 25.03 82.5 pyl4 26.01 82.5 What do these melt curves tell us? Are the primers specific for PYL4  30 Melt curves showing problematic melt peaks: primer-dimers Problems arise when the melt curve show that there are 2 or more peaks with one set of primers: o Primer-dimers (or primer hairpin formation) appear as a broader peak, usually with lower fluorescence and lower Tm (because of smaller amplicon size). This will shift the Ct and give false results. Primer dimers are more of a problem in one-step qPCR, because they are present during reverse transcription, which occurs at lower Temp. Solution: use higher Ta, lower [primer] and Hot-start Taq Pol. o Agarose gel analysis is gold standard for analyzing the products of qPCR. Validate all primer pairs the first time they are used, by running the final PCR product on an agarose gel to ensure that an observed melt peak corresponds to the expected target product size.  31 Examples of problematic melt peaks: tailing and leading peaks indicate primer dimers. At the end of the qPCR reaction, two bands would show on an agarose gel. Primer dimers or hairpins will usually appear at lower temperatures than full length products, although this is not always the case.  32 Melt curves showing problematic melt peaks: non-specific products o Amplicon from genomic DNA or non-specific products can manifest as a second peak, with different Tm (higher Tm for gDNA, why?). o Some targets with a similar length and sequence can have the same melt curves. Solution: use intron-spanning primers, if possible. Always blast your primers Check this video from’BIOC3001 students at the University of Western Australia, School of Molecular Sciences’ (https://www.youtube.com/watch?v=FvJnXKzejSQ) Additional info: https://www.youtube.com/watch?v=FvJnXKzejSQ  33 Examples of problematic melt peaks: shifted or double peaks indicate non-specific product amplification Shifted or multiple peaks are all strong indications of non-specific products accumulating in the reaction and require further investigation prior to conducting analysis for template quantification. Genomic DNA contamination may result in the amplification of larger fragments with higher Tm.  34 Overview of RT-qPCR 1. In RT-qPCR, total RNA or messenger RNA (mRNA) is first isolated 1. RNA isolation 2. RNA is transcribed into complementary DNA (cDNA) by reverse RT transcriptase (RT). 2. cDNA synthesis 3. The cDNA is then used as the template in the qPCR reaction, fluorescent together with gene specific primers. Taq DNA Pol probe RT-qPCR is used in a variety of applications including gene 3. PCR amplification expression analysis, RNAi validation, microarray/RNAseq validation, pathogen detection, genetic testing, and disease 4. Fluorescence research. quantification