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Real time PCR standard curve

Real time PCR standard curve


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As blunt as possible: when performing real time PCR it is a routine step to run one PCR in order to plot a "standard curve" with several decreasing dilution ratios from your sample. what is the real purpose of this? how should results be used/interpreted?


You can use 3 or 4 dilutions- 1:1, 1:5, 1:25, 1:125

Purpose of doing this is to calculate the primer efficiency. Ideally primer efficiency should be 2 i.e. two molecules of DNA are formed in a round of PCR. So after n-rounds of PCR there should be $2^n$ DNA. However, this may not be the case always. You calculate primer efficiency like this:

  • Plot $Ct$ vs $log_2(Conc)$
  • Get the trendline (in excel) or use a linear regression command for other applications
  • Get the slope ($s$) of the trendline
  • Efficiency in this case would be $2^{-s}$.

Some people use base of 10 in the log instead of 2 (for which you have to do $10^{-s}$ instead.

This, you can directly use to find out how many copies are produced after n cycles i.e instead of $2^n$ it will be $x^n$ where $x$ is the calculated efficiency. This is particularly useful when you are calculating the fold changes using the comparative Ct method. For details see this article.


Because the purpose of the standard curve (which actually results in a standard line) needs to be linear. If it is not linear (because of not enough values which are not linear distributed), then you quantification will be wrong. Ideally the line should look like this:

This picture is taken from this website, which gives a nice introduction into the topic.


Real-Time qRT-PCR standard curves. efficiency is too high! - (Jun/29/2005 )

In my Real-Time qRT-PCR experiments, I employ the standard curve method for quantification of gene expression. However, standard curves seem to be a huge hit-or-miss procedure for me, even with genes that are well-established to work well with Real-Time such as GAPDH.

At times, I am able to produce excellent standard curves with slopes at approximately -3.3 (

100% efficiency) the associated melting curves for each dilution are excellent as well.

However, most of the time I may get excellent melting curves for each dilution, but the slope for my standard curve may fall at around -2.6 (

Can anyone offer some explanations for this strange dilemma? Consequently, can anyone offer some suggestions to solve this problem?

One thing I can think of is that I'm getting disuniform amplification efficiencies at different RNA concentrations. FYI, I typically use 100 ng/uL RNA for "1x" and make serial dilutions up to 100x. I understand I really should be using a larger range of dilutions, but greater than 100x dilutions just don't work out for my genes/primers.

Thanks for any help I can get.

What is the range of the Cts? Did you see any contamination in your negative control?

My Ct values for the standard curves usually range from around 14-20, and the negative controls are showing no DNA contamination.

What instrument are you using?

Dear YuJ,
Are you using SYBR Green as reporter dye and you are using iCycler?
What is your lowest dilution in your standard?

This is what always happen to me. If i run a SYBR Green assay using standard ranging from 10e6 to 1, i will get > 100% efficiency.
So what i did was I unselect the last two dilution (10 and 1) and the efficiency become

3.3.
I think this is due to the primer dimer formation that contribute to the false signal in you reaction. And the effect of the primer dimer is great enough to afact you data especially in the low concentration standard.

I am indeed using SYBR Green chemistry (ABI SYBR Green PCR Mix), but the instrument I use is the Applied Biosystems 7900HT.

I have tried removing certain dilutions in all possible permutations before plotting the trendlines, but the outcomes are inconsistent between experiments. I also don't believe I have any primer-dimers because of the very pronounced product peaks and complete absence of primer-dimer peaks from the dissociation/melting data.

Hi YuJ,
Could you please describe how you preparing your quantitative standard?

My quantitative standards are prepared as such.

1. RNA isolation using TRIZOL reagent following manufacturer instructions plus an additional overnight purification step with ethanol (100%) and sodium acetate (3 M).

2. Spectrophotometric determination of [RNA]. A260/A280 ratio is usually at around 1.8.

3. Serial dilution of RNA at 1x, 10x, 25x, 75x, 100x, and sometimes 1000x (with 1x being 100 ng/uL diluted from stock, 10x being 10 ng/uL, etc.) using DEPC-treated water. I make sure to vortex each tube very well before pipetting for the next dilution.

4. Reagents in RT-PCR reactions include: Multiscribe Reverse Transcriptase (ABI), RNaseOUT RNase Inhibitor (Invitrogen), SYBR Green 2x PCR Mix (ABI). These, plus DEPC-treated water, are combined as a master mix.

5. Primer concentrations have been previously optimized for each primer. In the case of GAPDH, I determined the ideal concentration to use would be 0.06 uM per reaction for both the forward and reverse primer.

6. In each reaction tube, I first add the water and master mix, then the primers, and then finally the appropriate RNA template.

7. Each tube is vortexed and loaded in triplicate into the appropriate optical reaction plate. Plate is centrifuged to get rid of air bubbles and placed into the ABI 7900HT.

8. Thermocycler is set for a 45C RT phase (30min), 95C melting + 60C annealing phase (40 cycles), and then an additional dissociation phase at the end for generating the dissociation curves.

I probably included a lot of irrelevant facts, but hopefully this is what you meant by how I prepare my quantiative standards.

Dear YuJ,
Thanks for your description. I would strongly suggest you to use invitro transcription to prepare your GAPDH mRNA rather than using TRIzol extracted total RNA.

The reason is when you use TRIzol to extraction, you will get total RNA not GAPDH specific mRNA. So when you quantitate using spetrophotometrically, the reading will be out. Thus it would not give you a

You may try to clone the GAPDH gene into a plasmid and invitro trascripted(IVT) into GAPDH mRNA --> treat with DNase I to completly remove DNA conteminant--> stop DNase reaction --> purify the mRNA --> quantitate you mRNA*-->converte xx ug/ul into xx RNA copy/ul--> perform 10 fold serial dilution --> run RT-PCR.

This should give you a batter result.

*optional:
If you want to make sure that you IVT GAPDH mRNA is free from DNA conteminat, you may run a RT-PCR and a PCR (no RT) simultaneously. Your (no RT) PCR should not give you any band. If it does, treat you standard again with DNase I.

Note:
when you do a cloning please in clude 10-20 bp extra flanking at the both 3' and 5' end of your acture mRNA target. This will provide bater stability against exonuclease and yield prolong shelf life to your standard.

I would like to recommend you to use Ambion produst for IVT purpose.

Thank you for your advice, Hadrian, but I do not believe that method is suitable for me.

Although I've only mentioned GAPDH serial dilution as an example, I am actually conducting a gene expression study for some other genes, merely using GAPDH as an internal control.

Also, when I made the spectrophotometric measurements, I was just interested in the A260/A280 ratio as a measure of RNA purity and a rough estimate of the total RNA concentration in the stock tube. Indeed I am measuring total RNA, but gene-specific primers are used in the RT-PCR for actual quantification.

Sorry, I should have first mentioned what I'm actually doing instead of assuming that others can read my mind.


INTRODUCING UNDERGRADUATE STUDENTS TO REAL TIME PCR

As research in molecular biology increasingly focuses on the regulation of gene expression in eukaryotic cells, techniques such as real time PCR, which enable sensitive measurement of the cellular steady state level of specific mRNA sequences, are becoming common place analyses [ 1 , 2 ]. Courses in molecular biology need to include this technology both at a theoretical and practical level if they are to reflect current directions in the field [ 3 , 4 ]. To this end we present an experiment which, over four 3 h sessions, measures changes in the steady state mRNA levels during differentiation of four sequences in a cultured erythroid cell line.

The RNA source used for the experiment is the murine erythroleukemia cell or MEL cell [ 5 , 6 ], a model previously described for use in teaching microarray analysis [ 7 ]. This continuously cycling immature erythrocyte has been arrested early in the differentiation program but can be induced to progress further through the process by a number of chemicals such as DMSO [ 8 ]. Culturing in 1.8% DMSO for 72 h produces cells which display erythroid characteristics, that is, they now produce significant quantities of haemoglobin although they still retain their nucleus. They are particularly well suited to teaching as they are not nutritionally fastidious, they are nonadherent and can be grown to high concentrations without any ill-effects on the cells. The induction with chemicals such as DMSO or sodium butyrate provides a clear differentiation model with large, well-characterized changes in gene expression. The up-regulation of haemoglobin can also be monitored visually as the cells appear red after treatment.

Unlike microarray analysis, where changes in gene expression are identified by examining the behaviour of thousands of genes, real time PCR takes a candidate gene approach. Certain target sequences, often identified by microarray analysis, are selected and the relative abundance of these sequences is monitored with treatment. In many cases the level of a particular sequence is expressed relative to a reference gene. 18S rRNA was chosen in this experiment as the reference gene as it does not change with DMSO treatment, but commonly-used reference genes are glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and β-actin [ 9 ]. In this model, both β-actin and GAPDH gene expression change with DMSO treatment, according to array results. Three sequences were selected to compare between the control and treated cells. Two were significantly up-regulated with DMSO treatment: β-globin (βHb) and aminolevulinate synthase (ALAS), while one was down-regulated: Carbonic Anhydrase 1 (CA-1).

These sequences were chosen because they showed large reproducible changes (>50-fold) in gene expression and could be linked to the process of erythroid differentiation and function. They were originally selected from the results of a set of spotted arrays performed on samples from similarly-treated cells [ 7 ] in senior Biochemistry laboratory classes. β-globin is one of the most abundant structural proteins in mature erythocytes, comprising two of the subunits of tetrameric adult haemoglobin. ALAS is the rate limiting enzyme in heme synthesis, a pathway which is significantly up-regulated in erythroid differentiation. Carbonic anhydrases catalyse the hydration of CO2, (the by-product of cellular fuel oxidation) to bicarbonate, making the CO2 more soluble in the blood and contributing to the control of blood pH. There are a number of carbonic anhydrases, two of which are expressed in MEL cells, CA-1 and CA-2. While CA-2 expression does not change with DMSO exposure, CA-1 is significantly down-regulated [ 10 ].


How to Perform a qPCR Standard Curve

To perform a qPCR standard curve, you set up qPCR reactions to amplify different amounts of the same DNA sample. Theoretically, efficient primers will result in a proportional dose-response curve.

I usually test 5 concentrations with a dilution factor of 1:5. To obtain precise results, do sequential dilutions and pipet the same volume of DNA in every reaction. Use water instead of DNA as a negative control to detect contaminants in the reaction and to discriminate background amplification. Also, make sure your DNA sample has a good quality (intact DNA, appropriate concentration, and a good 260/280 ratio).

Some qPCR software have an application to analyze your standard curve. It generates the curve and calculates the efficiency of the reaction. Acceptable ranges are between 90 and 110% with a slope of the curve around -3.3 for an efficiency of 100%. The R 2 of the curve should be > 0.99 to provide a good confidence within the correlation.

If you are satisfied with the efficiency of the primers, but it is not of 100%, you might be able to indicate it to the software when you analyze your data, but I never tried it.


Contents

Cells in all organisms regulate gene expression by turnover of gene transcripts (single stranded RNA): The amount of an expressed gene in a cell can be measured by the number of copies of an RNA transcript of that gene present in a sample. In order to robustly detect and quantify gene expression from small amounts of RNA, amplification of the gene transcript is necessary. The polymerase chain reaction (PCR) is a common method for amplifying DNA for RNA-based PCR the RNA sample is first reverse-transcribed to complementary DNA (cDNA) with reverse transcriptase.

In order to amplify small amounts of DNA, the same methodology is used as in conventional PCR using a DNA template, at least one pair of specific primers, deoxyribonucleotides, a suitable buffer solution and a thermo-stable DNA polymerase. A substance marked with a fluorophore is added to this mixture in a thermal cycler that contains sensors for measuring the fluorescence of the fluorophore after it has been excited at the required wavelength allowing the generation rate to be measured for one or more specific products. This allows the rate of generation of the amplified product to be measured at each PCR cycle. The data thus generated can be analysed by computer software to calculate relative gene expression (or mRNA copy number) in several samples. Quantitative PCR can also be applied to the detection and quantification of DNA in samples to determine the presence and abundance of a particular DNA sequence in these samples. [3] This measurement is made after each amplification cycle, and this is the reason why this method is called real time PCR (that is, immediate or simultaneous PCR). In the case of RNA quantitation, the template is complementary DNA (cDNA), which is obtained by reverse transcription of ribonucleic acid (RNA). In this instance the technique used is quantitative RT-PCR or Q-RT-PCR.

Quantitative PCR and DNA microarray are modern methodologies for studying gene expression. Older methods were used to measure mRNA abundance: Differential display, RNase protection assay and northern blot. Northern blotting is often used to estimate the expression level of a gene by visualizing the abundance of its mRNA transcript in a sample. In this method, purified RNA is separated by agarose gel electrophoresis, transferred to a solid matrix (such as a nylon membrane), and probed with a specific DNA or RNA probe that is complementary to the gene of interest. Although this technique is still used to assess gene expression, it requires relatively large amounts of RNA and provides only qualitative or semi quantitative information of mRNA levels. [4] Estimation errors arising from variations in the quantification method can be the result of DNA integrity, enzyme efficiency and many other factors. For this reason a number of standardization systems (often called normalization methods) have been developed. Some have been developed for quantifying total gene expression, but the most common are aimed at quantifying the specific gene being studied in relation to another gene called a normalizing gene, which is selected for its almost constant level of expression. These genes are often selected from housekeeping genes as their functions related to basic cellular survival normally imply constitutive gene expression. [5] [6] This enables researchers to report a ratio for the expression of the genes of interest divided by the expression of the selected normalizer, thereby allowing comparison of the former without actually knowing its absolute level of expression.

The most commonly used normalizing genes are those that code for the following molecules: tubulin, glyceraldehyde-3-phosphate dehydrogenase, albumin, cyclophilin, and ribosomal RNAs. [4]

Real-time PCR is carried out in a thermal cycler with the capacity to illuminate each sample with a beam of light of at least one specified wavelength and detect the fluorescence emitted by the excited fluorophore. The thermal cycler is also able to rapidly heat and chill samples, thereby taking advantage of the physicochemical properties of the nucleic acids and DNA polymerase.

The PCR process generally consists of a series of temperature changes that are repeated 25–50 times. These cycles normally consist of three stages: the first, at around 95 °C, allows the separation of the nucleic acid's double chain the second, at a temperature of around 50–60 °C, allows the binding of the primers with the DNA template [7] the third, at between 68–72 °C, facilitates the polymerization carried out by the DNA polymerase. Due to the small size of the fragments the last step is usually omitted in this type of PCR as the enzyme is able to replicate the DNA amplicon during the change between the alignment stage and the denaturing stage. In addition, in four-step PCR the fluorescence is measured during short temperature phases lasting only a few seconds in each cycle, with a temperature of, for example, 80 °C, in order to reduce the signal caused by the presence of primer dimers when a non-specific dye is used. [8] The temperatures and the timings used for each cycle depend on a wide variety of parameters, such as: the enzyme used to synthesize the DNA, the concentration of divalent ions and deoxyribonucleotides (dNTPs) in the reaction and the bonding temperature of the primers. [9]

Real-time PCR technique can be classified by the chemistry used to detect the PCR product, specific or non-specific fluorochromes.

Non-specific detection: real-time PCR with double-stranded DNA-binding dyes as reporters Edit

A DNA-binding dye binds to all double-stranded (ds) DNA in PCR, increasing the fluorescence quantum yield of the dye. An increase in DNA product during PCR therefore leads to an increase in fluorescence intensity measured at each cycle. However, dsDNA dyes such as SYBR Green will bind to all dsDNA PCR products, including nonspecific PCR products (such as Primer dimer). This can potentially interfere with, or prevent, accurate monitoring of the intended target sequence.

In real-time PCR with dsDNA dyes the reaction is prepared as usual, with the addition of fluorescent dsDNA dye. Then the reaction is run in a real-time PCR instrument, and after each cycle, the intensity of fluorescence is measured with a detector the dye only fluoresces when bound to the dsDNA (i.e., the PCR product). This method has the advantage of only needing a pair of primers to carry out the amplification, which keeps costs down multiple target sequences can be monitored in a tube by using different types of dyes.

Specific detection: fluorescent reporter probe method Edit

Fluorescent reporter probes detect only the DNA containing the sequence complementary to the probe therefore, use of the reporter probe significantly increases specificity, and enables performing the technique even in the presence of other dsDNA. Using different-coloured labels, fluorescent probes can be used in multiplex assays for monitoring several target sequences in the same tube. The specificity of fluorescent reporter probes also prevents interference of measurements caused by primer dimers, which are undesirable potential by-products in PCR. However, fluorescent reporter probes do not prevent the inhibitory effect of the primer dimers, which may depress accumulation of the desired products in the reaction.

The method relies on a DNA-based probe with a fluorescent reporter at one end and a quencher of fluorescence at the opposite end of the probe. The close proximity of the reporter to the quencher prevents detection of its fluorescence breakdown of the probe by the 5' to 3' exonuclease activity of the Taq polymerase breaks the reporter-quencher proximity and thus allows unquenched emission of fluorescence, which can be detected after excitation with a laser. An increase in the product targeted by the reporter probe at each PCR cycle therefore causes a proportional increase in fluorescence due to the breakdown of the probe and release of the reporter.

  1. The PCR is prepared as usual (see PCR), and the reporter probe is added.
  2. As the reaction commences, during the annealing stage of the PCR both probe and primers anneal to the DNA target.
  3. Polymerisation of a new DNA strand is initiated from the primers, and once the polymerase reaches the probe, its 5'-3'-exonuclease degrades the probe, physically separating the fluorescent reporter from the quencher, resulting in an increase in fluorescence.
  4. Fluorescence is detected and measured in a real-time PCR machine, and its geometric increase corresponding to exponential increase of the product is used to determine the quantification cycle (Cq) in each reaction.

Real-time PCR permits the identification of specific, amplified DNA fragments using analysis of their melting temperature (also called Tm value, from melting temperature). The method used is usually PCR with double-stranded DNA-binding dyes as reporters and the dye used is usually SYBR Green. The DNA melting temperature is specific to the amplified fragment. The results of this technique are obtained by comparing the dissociation curves of the analysed DNA samples. [11]

Unlike conventional PCR, this method avoids the previous use of electrophoresis techniques to demonstrate the results of all the samples. This is because, despite being a kinetic technique, quantitative PCR is usually evaluated at a distinct end point. The technique therefore usually provides more rapid results and/or uses fewer reactants than electrophoresis. If subsequent electrophoresis is required it is only necessary to test those samples that real time PCR has shown to be doubtful and/or to ratify the results for samples that have tested positive for a specific determinant.

Modeling Edit

Unlike end point PCR (conventional PCR), real time PCR allows monitoring of the desired product at any point in the amplification process by measuring fluorescence (in real time frame, measurement is made of its level over a given threshold). A commonly employed method of DNA quantification by real-time PCR relies on plotting fluorescence against the number of cycles on a logarithmic scale. A threshold for detection of DNA-based fluorescence is set 3–5 times of the standard deviation of the signal noise above background. The number of cycles at which the fluorescence exceeds the threshold is called the threshold cycle (Ct) or, according to the MIQE guidelines, quantification cycle (Cq). [12]

During the exponential amplification phase, the quantity of the target DNA template (amplicon) doubles every cycle. For example, a DNA sample whose Cq precedes that of another sample by 3 cycles contained 2 3 = 8 times more template. However, the efficiency of amplification is often variable among primers and templates. Therefore, the efficiency of a primer-template combination is assessed in a titration experiment with serial dilutions of DNA template to create a standard curve of the change in (Cq) with each dilution. The slope of the linear regression is then used to determine the efficiency of amplification, which is 100% if a dilution of 1:2 results in a (Cq) difference of 1. The cycle threshold method makes several assumptions of reaction mechanism and has a reliance on data from low signal-to-noise regions of the amplification profile that can introduce substantial variance during the data analysis. [13]

To quantify gene expression, the (Cq) for an RNA or DNA from the gene of interest is subtracted from the (Cq) of RNA/DNA from a housekeeping gene in the same sample to normalize for variation in the amount and quality of RNA between different samples. This normalization procedure is commonly called the ΔCt-method [14] and permits comparison of expression of a gene of interest among different samples. However, for such comparison, expression of the normalizing reference gene needs to be very similar across all the samples. Choosing a reference gene fulfilling this criterion is therefore of high importance, and often challenging, because only very few genes show equal levels of expression across a range of different conditions or tissues. [15] [16] Although cycle threshold analysis is integrated with many commercial software systems, there are more accurate and reliable methods of analysing amplification profile data that should be considered in cases where reproducibility is a concern. [13]

Mechanism-based qPCR quantification methods have also been suggested, and have the advantage that they do not require a standard curve for quantification. Methods such as MAK2 [17] have been shown to have equal or better quantitative performance to standard curve methods. These mechanism-based methods use knowledge about the polymerase amplification process to generate estimates of the original sample concentration. An extension of this approach includes an accurate model of the entire PCR reaction profile, which allows for the use of high signal-to-noise data and the ability to validate data quality prior to analysis. [13]

According to research of Ruijter et al. [18] MAK2 assumes constant amplification efficiency during the PCR reaction. However, theoretical analysis of polymerase chain reaction, from which MAK2 was derived, has revealed that amplification efficiency is not constant throughout PCR. While MAK2 quantification provides reliable estimates of target DNA concentration in a sample under normal qPCR conditions, MAK2 does not reliably quantify target concentration for qPCR assays with competimeters.

There are numerous applications for quantitative polymerase chain reaction in the laboratory. It is commonly used for both diagnostic and basic research. Uses of the technique in industry include the quantification of microbial load in foods or on vegetable matter, the detection of GMOs (Genetically modified organisms) and the quantification and genotyping of human viral pathogens.

Quantification of gene expression Edit

Quantifying gene expression by traditional DNA detection methods is unreliable. Detection of mRNA on a northern blot or PCR products on a gel or Southern blot does not allow precise quantification. [19] For example, over the 20–40 cycles of a typical PCR, the amount of DNA product reaches a plateau that is not directly correlated with the amount of target DNA in the initial PCR. [20]

Real-time PCR can be used to quantify nucleic acids by two common methods: relative quantification and absolute quantification. [21] Absolute quantification gives the exact number of target DNA molecules by comparison with DNA standards using a calibration curve. It is therefore essential that the PCR of the sample and the standard have the same amplification efficiency. [22] Relative quantification is based on internal reference genes to determine fold-differences in expression of the target gene. The quantification is expressed as the change in expression levels of mRNA interpreted as complementary DNA (cDNA, generated by reverse transcription of mRNA). Relative quantification is easier to carry out as it does not require a calibration curve as the amount of the studied gene is compared to the amount of a control reference gene.

As the units used to express the results of relative quantification are unimportant the results can be compared across a number of different RTqPCR. The reason for using one or more housekeeping genes is to correct non-specific variation, such as the differences in the quantity and quality of RNA used, which can affect the efficiency of reverse transcription and therefore that of the whole PCR process. However, the most crucial aspect of the process is that the reference gene must be stable. [23]

The selection of these reference genes was traditionally carried out in molecular biology using qualitative or semi-quantitative studies such as the visual examination of RNA gels, northern blot densitometry or semi-quantitative PCR (PCR mimics). Now, in the genome era, it is possible to carry out a more detailed estimate for many organisms using transcriptomic technologies. [24] However, research has shown that amplification of the majority of reference genes used in quantifying the expression of mRNA varies according to experimental conditions. [25] [26] [27] It is therefore necessary to carry out an initial statistically sound methodological study in order to select the most suitable reference gene.

A number of statistical algorithms have been developed that can detect which gene or genes are most suitable for use under given conditions. Those like geNORM or BestKeeper can compare pairs or geometric means for a matrix of different reference genes and tissues. [28] [29]

Diagnostic uses Edit

Diagnostic qualitative PCR is applied to rapidly detect nucleic acids that are diagnostic of, for example, infectious diseases, cancer and genetic abnormalities. The introduction of qualitative PCR assays to the clinical microbiology laboratory has significantly improved the diagnosis of infectious diseases, [30] and is deployed as a tool to detect newly emerging diseases, such as new strains of flu and coronavirus, [31] in diagnostic tests. [32] [33]

Microbiological uses Edit

Quantitative PCR is also used by microbiologists working in the fields of food safety, food spoilage and fermentation and for the microbial risk assessment of water quality (drinking and recreational waters) and in public health protection. [34]

qPCR may also be used to amplify taxonomic or functional markers of genes in DNA taken from environmental samples. [35] Markers are represented by genetic fragments of DNA or complementary DNA. [35] By amplifying a certain gentic element, one can quantify the amount of the element in the sample prior to amplification. [35] Using taxonomic markers (ribosomal genes) and qPCR can help determine the amount of microorganisms in a sample, and can identify different families, genera, or species based on the specificity of the marker. [35] Using functional markers (protein-coding genes) can show gene expression within a community, which may reveal information about the environment. [35]

Detection of phytopathogens Edit

The agricultural industry is constantly striving to produce plant propagules or seedlings that are free of pathogens in order to prevent economic losses and safeguard health. Systems have been developed that allow detection of small amounts of the DNA of Phytophthora ramorum, an oomycete that kills Oaks and other species, mixed in with the DNA of the host plant. Discrimination between the DNA of the pathogen and the plant is based on the amplification of ITS sequences, spacers located in ribosomal RNA gene's coding area, which are characteristic for each taxon. [36] Field-based versions of this technique have also been developed for identifying the same pathogen. [37]

Detection of genetically modified organisms Edit

qPCR using reverse transcription (RT-qPCR) can be used to detect GMOs given its sensitivity and dynamic range in detecting DNA. Alternatives such as DNA or protein analysis are usually less sensitive. Specific primers are used that amplify not the transgene but the promoter, terminator or even intermediate sequences used during the process of engineering the vector. As the process of creating a transgenic plant normally leads to the insertion of more than one copy of the transgene its quantity is also commonly assessed. This is often carried out by relative quantification using a control gene from the treated species that is only present as a single copy. [38] [39]

Clinical quantification and genotyping Edit

Viruses can be present in humans due to direct infection or co-infections which makes diagnosis difficult using classical techniques and can result in an incorrect prognosis and treatment. The use of qPCR allows both the quantification and genotyping (characterization of the strain, carried out using melting curves) of a virus such as the Hepatitis B virus. [40] The degree of infection, quantified as the copies of the viral genome per unit of the patient's tissue, is relevant in many cases for example, the probability that the type 1 herpes simplex virus reactivates is related to the number of infected neurons in the ganglia. [41] This quantification is carried out either with reverse transcription or without it, as occurs if the virus becomes integrated in the human genome at any point in its cycle, such as happens in the case of HPV (human papillomavirus), where some of its variants are associated with the appearance of cervical cancer. [42] Real-time PCR has also brought the quantization of human cytomegalovirus (CMV) which is seen in patients who are immunosuppressed following solid organ or bone marrow transplantation. [43]


Real time PCR standard curve - Biology

Real-time PCR technology is an established powerful research tool used in many scientific disciplines and is also utilised for mainstream testing in the regulated markets such as food, veterinary and human in-vitro diagnostics.

This essential manual provides both the novice and experienced user with an invaluable reference to a wide-range of real-time PCR technologies and applications and provides an overview of the theory of this increasingly important technique. Renowned international authors present detailed technical insights into the underlying principles, methods and practice of real-time PCR. The initial chapters cover the important aspects of real-time PCR including choosing an instrument and probe system, set-up, nucleic acid synthesis, sample extraction controls, and validation and data analysis. Further chapters provide a comprehensive overview of important real-time PCR methodologies such as quantification, expression analysis and mutation detection. This is complemented by the final chapters, which address the application of real-time PCR to diagnosis of infectious diseases, biodefence, veterinary science, food authenticity and molecular haplotyping. This timely and authoritative volume serves both as a basic introduction to real-time PCR and as a source of current trends and applications for those already familiar with the technology. The editors also aim to stimulate readers of all levels to develop their own innovative approaches to real-time PCR.

An essential book for all laboratories using PCR.

"an excellent reference for a wide range of real-time PCR technologies and applications . an invaluable reference . an extremely useful book for both novice and experienced users that serves to stimulate readers at all levels to develop their own innovative approaches to real-time PCR." from Doodys

"Both beginners and experienced users should find helpful information" from Res. Ref. Book News (August 2013) p.196.

"a wide range of real time PCR technologies and applications" from Food Sci. Technol. Abs. (2013) 45 (9)

"This book provides a well thought out overview of real time PCR, providing the foundational knowledge to become competent in the design, validation and routine practise of this methodology . This book is well written . the content is up-to-date . I was impressed by this text, and expect to refer to it regularly in the course of my work in the future. I would similarly recommend it to researchers and diagnostic scientists alike who either currently use, or wish to improve their understanding of real time PCR" from Australian Journal of Medical Science (August 2014).

(EAN: 9781908230225 9781908230874 Subjects: [molecular microbiology] [pcr] [molecular biology] )


And what about RT-PCR and Real-Time PCR?

qPCR and Real-time PCR are the same techniques, and are explained in the paragraph above. But RT-PCR means something different. A RT-PCR is short for Reverse Transcriptase PCR. This method allows the use of RNA as a template. With the use of an enzyme called reverse transcriptase, RNA is translated into complementary DNA (cDNA). Most commonly, RT-PCR serves as a first step in qPCR, which quantifies RNA transcripts in a biological sample. It is then called RT-qPCR.

To make this even more complex, the abbreviation frequently used for Real-Time PCR is RT-PCR.


Quantification Analysis in qPCR

The quantity of DNA at the start of the PCR can then be determined by interpolation of the resulting CT or Cp value in a linear standard curve of values obtained from serially diluted known-amount standards (Figure 12).

This standard curve correlates the emitted fluorescence (CT or Cp value) with the initial concentration of the standards used and the final result is achieved by interpolation of the produced fluorescence (CT or Cp value) during the amplification of the sample in this standard curve. In practice, such curves are linear over more than five orders of magnitude Rodriguez-Lazaro and Hernandez, 2013.


Materials and Methods

Ethics statement

All animal work has been conducted according to the relevant national and international guidelines.

Insect sample preparation

A N. lugens colony was maintained on rice (Oryza sativa) variety Taichung Native 1 (TN1, a hopper susceptible variety) in a greenhouse of the China National Rice Research Institute under the conditions of 28 ± 1 °C, 80 ± 10% relative humidity and a 16 L/8D photoperiod 34,46 . Eggs, first- to fifth-instar nymphs (I1, I2, I3, I4 and I5), and newly emerged adults (female and male) (<24 h after molting) were collected and frozen at −80 °C until RNA extraction. Furthermore, a pooled sample including eggs, nymphs (I1-I5) and adults (male and female) was collected for PCR efficiency testing. For the insect samples of amino acid deprivation, newly formed third-instar nymphs were transferred to the standard artificial diet D-97 or modified artificial diets without one of the 20 amino acids 46 . For each diet type, 250 individuals were prepared in groups of 25 (a total of 10 groups). After four days on the diet, five individuals of each group were collected and pooled as one sample (a total of 50 individuals) and frozen at −80 °C until RNA extraction. This experiment was repeated three times as independent biological replicates.

To evaluate the effect of temperature, 180 newly emerged female adults (<24 h after molting) were placed into 18 glass tubes in a group of 10. Three of the tubes (replications) were exposed under one of the 6 temperature regimes (0 °C, 8 °C, 18 °C, 28 °C, 38 °C, 48 °C) for 2 h in an incubator (DC-3010, Jiangnan Equipment, Hangzhou, China). The nymphs then were recovered at 28 ± 1 °C for 2 h. The surviving individuals were frozen in liquid nitrogen and stored at −80 °C.

RNAi samples were prepared according to a previously reported protocol 36 as the following: four dsRNAs were synthesized from EdePRTase (dsEdePRTase), ylsArg4 (dsylsArg4-1 and dsylsArg4-2), and the green fluorescent protein (dsGFP) as dsEdePRTase and dsylsArg4 had previous successes of knocking down the targeted genes evaluated using N. lugens reference genes NlRPS11 and NlRPS15 36 . A total of 90 fourth-instar nymphs (1-day old) in three groups of 30 individuals each (as three replicates) were injected with the four dsRNAs (in 50 nL) (dsEdePRTase, 0.5 μg/μL dsylsArg4, 1.5 μg/μL and dsGFP, 1.5 μg/μL as negative controls, respectively) at the thorax between the mesocoxa and the hind coxa. Insects without dsRNA injection were used as blank control. Three days after the injection, the surviving individuals were collected and pooled for RT-qPCR analysis using the primers listed in Table 1. The experiment was repeated three times as independent biological replicates.

RNA extraction and cDNA synthesis

Total RNA was extracted from the collected samples using the Trizol Reagent (Invitrogen, Shanghai, China) and the RNeasy Mini Kit (Qiagen, Valencia, CA) according to the manufacturer’s instructions. The RNA purity was measured with a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Rockford, USA) and the integrity was checked by agarose gel electrophoresis. One microgram total RNA was reverse-transcribed to cDNA by using TransScript One-Step gDNA Removal and cDNA Synthesis SuperMix kit (TransGen Biotech, Beijing, China).

Reference gene candidates from YLS and cloning

A total of eight housekeeping genes was selected from YLS draft genome sequences (Genbank accession numbers: JRMI00000000.1) as candidates of the most consistently expressed reference gene(s) to be used in RT-qPCR studies. They are γ-actin (ylsACT), α-tubulin (ylsTUB), ribosomal protein S11 (ylsRPS11), ribosomal protein S19A/S15e (ylsRPS15e), ribosomal protein S15P/S13E (ylsRPS15p), elongation factor 1α (ylsEF1α), glyceraldehyde-3-phosphate dehydrogenase (ylsGAPDH) and ubiquitin (ylsUBQ). These gene types have been used widely as reference genes in studies of insects and fungi. Primers were designed based on the sequences selected by the PrimerQuest software (Integrated DNA Technologies, Inc, Coralville, IA, USA) (Table 1). Additionally, BLAST analyses were performed to verify their specificity (Fig. 1). The PCR products of the female adults were sequenced by an ABI 3730 automated sequencer (Applied Biosystems, Foster City, CA, USA) in both directions. The obtained sequences were submitted to GenBank database (AB914563-AB914566).

RT-qPCR

Prior to the RT-qPCR amplification, a portion of cDNA was used to construct standard curves for PCR condition optimization and calculation of PCR efficiency of the eight selected reference gene candidates. For this purpose, five cDNA quantities (0.2, 2, 10, 50, 200 ng) were tested. PCR amplification efficiencies were calculated using the formula E = (10 [−1/slope] − 1) × 100.

The RT-qPCR experiments were performed using the TransStart Top Green qPCR SuperMix- -UDG (TransGen Biotech) according to the manufacturer’s instructions on an ABI 7500 Real Time PCR System. Amplification reaction volume was 20 μL with 3 μL cDNA as template and a final concentration of 200 nM primers. The following thermal cycling condition was used: initial denaturation at 95 °C for 2 min, followed by 40 cycles of 95 °C for 20 s and 60 °C for 1 min. After all reactions, a melting curve analysis from 65 °C to 95 °C was applied to ensure consistency and specificity of the amplified product, and the most adequate annealing temperature was determined and used for PCR reaction. Each primer pair was checked for size specificity of the amplicon using 1.5% agarose gel electrophoresis and ethidium bromide staining. A reaction mix without template (no template control) was used to detect possible reagent contamination. The average of the Ct values was determined using manual quantification settings. The values of Ct for the control wells were excluded from further analysis, as these values were greater than 35 or not detectable.

Determination of expression stability

Stabilities of the reference gene candidates were evaluated by BestKeeper 38 , geNorm 10 , NormFinder 47 and the ΔCt method 11 . BestKeeper analysis uses Ct values directly, while geNorm, NormFinder and ΔCt method use transformed Ct values of (1 + E) −ΔCt . In addition, RefFinder 48 , a web-based comprehensive platform that integrates the four above mentioned algorithms, was used for the overall ranking of the stability of these reference gene candidates. All data were analyzed according to the perspective instructions of the software used.

Validation of selected reference genes

Three YLS originated genes that are involved in amino acids biosynthetic pathways including NlylsSDH 34 , EdePRTase 36 and ylsArg4 (unpublished data) were used as target genes to validate the selected YLS reference gene candidates using the 2 −ΔΔCt method. Developmental stage and sex samples, samples of methionine- or histidine-free artificial diets, and RNAi samples were used.


Quantitative Real-Time PCR (qRT-PCR)

Experimental Gene(s) Selection
In order to perform qRT-PCR, one needs to both identify experimental and housekeeping genes and design primers for them. Start by looking up your plant under the stress condition you want to test. For example, I want to do a drought stress experiment with potatoes so I internet searched for drought tolerant genes in potato and found a paper that used STANN1.
You will want to find multiple genes for the given scenario. You can not rule out the possibility of working with an unknown gene or a lesser known gene. Maybe a lot of work has not been done with your plant or you cannot find the gene sequence you want to evaluate. Start by looking at closely related relatives and see if you can find the gene sequence there.

Research housekeeping genes to use
Next, you will need to find endogenous genes, also called reference, control genes or housekeeping genes, that will not be affected by your experiment. Housekeeping genes will not work with all experiments! Sometimes your housekeeping gene is upregulated by your experiment or by the age of your plant material.

For example, I internet searched housekeeping genes potato and found these housekeeping genes were used.

  • Beta-tubulin
  • Actin
  • Ubiquitin gene is useful in some hosts
  • Cyclophilin
  • Elongation factor 1-alpha (ef1alpha)
  • 18S rRNA
  • Adenine phosphoribosyl transferase (aprt)
  • Cytoplasmic ribosomal protein L2

Most common genes used are actin, beta tubulin, and ubiquitin. Many papers use glyceraldehyde 3 phosphatase dehydrogenase (GADPH) but it all depends on the host you are working with.

You should run your own test of the endogenous genes you are planning to use to first determine whether or not your housekeeping/control gene will serve the purpose you are looking for (that it doesn’t vary between samples or treatments). When you test the amplification of this gene, all your samples from different treatments should have results that are roughly the same.

Other resources
A good review paper on housekeeping genes

Look at some of the pitfalls of qRT-PCR and may provide some insight on how to design your experiment (or keep you up late with worry).

The Applied Biosystems Manual on StepOnePlus Systems.

Applied Biosystems Guide to Relative Quantification using real-time PCR.

Once you have settled on your primer sequences, order your primers through Rutgers market place under Thermofisher scientific, direct ordering, custom primers (oligonucleotides), DNA Value Oligos, Basic and Bulk upload. They are around $5 each and arrive after a few days. A more economical and quicker way to get your primers is through Integrated DNA Technologies at RWJMS (Busch Campus, Piscataway). They sell primers around $2.70-3.00 and you can pick up your order around 24 hours after ordering the primers in person at the RWJ Medical School Building or they deliver to you. Saves on shipping and avoiding on waiting for shipments.

Now is a good time to extract some genomic DNA (gDNA) from your plant while you wait for your primers to arrive. Test your primers to make sure they are really going to work for you by running a basic PCR.

After extracting DNA dilute to about 5 ng/ul before running PCR. You can also dilute 10 ul of DNA into 990 ul for 100 fold dilution then serial dilute to -6 then run PCR with each dilution and see if the primers amp your gene. Even though there are introns in the DNA (meaning the size might vary), this validation step works in most situations. Every once in a while you may have to do this with the converted DNA (cDNA) if you fail to amplify with repeated attempts using gDNA.

  • DNeasy Powerplant Pro kit by Qiagen catalog number: 13400-50
  • Items needed that are not provided in the kit:
    • Ethanol
    • Liquid Nitrogen
    • Sterile mortar and pestle
    • PCR Super Mix from supply center catalog number: 10572014

    Extracting RNA
    Remember RNA is not stable like DNA. You need to be extra careful. Sterilize tools, work in a hood, wear a lab coat and always wear gloves (if you touch your skin or clothing with your gloves – change them to avoid contaminating your extract with RNase).

    Note: The tissue required for RNA extraction is 0.03 g or less.

      • RNeasy mini kit from Qiagen catalog number: 74104 (50) or 74106 (250)
      • UltraPure DNAse/RNAse-free distilled water from the freezer program catalog number: 10977015
        • 10 ul beta-mercaptoethanol, or 20 ul 2 M dithiothreitol (DTT)
        • Ethanol
        • Several Eppendorf tubes
        • Liquid Nitrogen
        • Sterile mortar and pestle

        You may want to consider purchasing a DNA removal kit which may remove any DNA from your RNA extraction. The main concept is to use a DNAse. For example, you could use the following kit or similar kits to remove DNA.

        Assessing RNA quality
        Assess the quality of your RNA using the NanoDrop Spectrophotometer (2nd floor facility). You need keycard access. Make sure you change the settings of the NanoDrop software to measure RNA instead of DNA. First load a blank. Then load 1-2 ul samples into the NanoDrop. For RNA you are looking for a ratio of

        2.00 for 260/280. You must start with good quality RNA otherwise you may compromise the results of the qRT-PCR.

        You may want to consider starting with RNA samples from different treatments that have the same concentration of RNA prior to doing the reverse transcription.

        Decide whether you want to do a 1-step or a 2-step qRT-PCR. The Applied Biosystems manual has a good explanation of the difference between both.

        Convert RNA to cDNA
        High capacity cDNA reverse transcription kit from Thermofisher Scientific catalog number: 4368814

        What is the time range for converting RNA to cDNA?
        If you can not convert RNA to cDNA right away, you can store overnight in -20 C. It is risky to delay this step so plan ahead if you can to convert your RNA the same day (start early). Once you convert RNA to cDNA, the cDNA can be stored for longer periods of time compared to RNA samples.

        How to set your PCR machine to run 1 cycle
        The minimum number of cycles our PCR machine can do is two so this is how you need to set up your machine to complete the one cycle into two cycles.

        85 C for 5 mins, then Cool 4 C

        qRT-PCR setup
        Talk with Mike about your experiment, what genes you are using for reference and experiment. He will design the layout of your well plate (or collection of strip tubes) and print you out a map so you know what to pipet into each well. If you have a windows PC you can download StepOne Software and prepare the layout of your plate/strip tube prior to actually doing the assay. If you do this ahead of time you can save the layout on a USB and take it to the Core Facility where it can be easily loaded onto the software there. You should also have an idea when you want to setup and run the qRT-PCR so you can reserve the time on the machine. You want to run each sample in triplicate.

        Some things you will be asked by Mike.

        If you have room on the plate it may be in your best interest do try different dilutions of your template cDNA. Mike may suggest you dilute a small amount of cDNA 50x = 5 ul of cDNA template into 245 ul of DNAse/RNAse-free distilled water.

        Setting up standard curve
        Whatever dilution you are using in the rest of the experiment will be your starting point for this part too. So if you are diluting 50x you would make sure you dilute enough cDNA for your curve. Read about more about setting up a standard curve.

        Supplies for qRT-PCR
        Power SYBR green from (supply center catalog number: 4367659)
        Well plate vs. strip tubes

          • Well plates (supply center several options)
              • Expensive
              • Self-supporting
              • Requires plate sealer and sealer tool
              • Less chance for contamination while sealing the tubes
              • Plate is well labeled
              • Less expensive
              • Requires a tube holder
              • Requires optical strip caps (supply center: 4323032)
              • Easy to replace a strip if you make an error loading your sample
              • Must label strip caps 1-12 to keep tubes in order (tab at end of cap strip) Do not write the names of the samples on the tubes or on the caps.
              • Increased chance of contamination

              In either case, it is good to use some color to help remind you where specific treatments go as we did when working with strip tubes.

              qRT-PCR master mix protocol 1x

              • 10 ul Power SYBR
              • 1 ul Forward primer (200 to 250 nM final concentration)
              • 1 ul Reverse primer (200 to 250 nM final concentration)
              • 3 ul DNase and RNase free water

              Add 15 ul of master mix and 5 ul of template to each tube for a total of 20 ul per tube. For the No Template Control (NTC) add 15 ul master mix and 5 ul of water. Remember that you want to run each sample in triplicate.

              The Power SYBR will be frozen when it comes out of the freezer, you need to make sure it completely melted and invert several times to mix before you make your master mix.

              Give yourself ample time so you can pipet consistently, start at least 2.5 hours before your scheduled time on the machine. Only use really good pipettes. If possible arrive 5 mins early because your plate/tubes will need to be spun by Mike.

              Mike will help you through the setup process. Do not be afraid to ask him questions. Schedule time to speak with him in case he is busy.

              Why melt curves are important
              The melt curve is run by the qPCR machine after all of the cycles have been completed. The importance of the melt curve analysis is to determine that only a single PCR product has been generated. A melt curve analysis can increase the run-time of your entire experiment. You can change the melt curve portion of the run to 1.0C instead of 0.3C which may be the default that the machine runs it at. 1 clean peak typically indicates the presence of a single amplicon which is what you are looking for.

              I have my data, now what?
              Explanation and quantification of CT and deltaCT, deltadeltaCT values between reference and experimental samples
              Close


              Value

              group The unique entries in group_var

              gene The column names of df

              normalized The normalized expression of target genes relative to a reference_gene

              calibrated The calibrated expression of target genes relative to a reference_group

              error The standard deviation of normalized relative expression

              lower The lower interval of the normalized relative expression

              upper The upper interval of the normalized relative expression

              When plot is TRUE, returns a bar graph of the calibrated expression of the genes in the column and the groups in the column group. Error bars are drawn using the columns lower and upper. When more one gene are plotted the default in dodge bars. When the argument facet is TRUE a separate panel is drawn for each gene.



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