RT2 qPCR Primer Assays
For accurate and reliable gene expression analysis using laboratory-verified assays
For accurate and reliable gene expression analysis using laboratory-verified assays
RT² qPCR Primer Assays are specifically designed and experimentally verified for real-time PCR analysis. The rigorous assay verification criteria ensure PCR specificity and efficiency for reliable and accurate gene expression analysis results.
RT² qPCR Primer Assays use SYBR® Green-based quantitative real-time PCR technology to provide a sensitive and reliable tool for gene expression analysis.
Each assay utilizes a proprietary and experimentally verified algorithm for the design of gene-specific qPCR primers with uniform PCR efficiency and amplification conditions. Each lot of every assay is further wet-bench tested for real-time PCR performance for specificity and amplification efficiency. Amplification of a single product of the correct size with high PCR efficiency (>90%) is guaranteed when the assays are used with RT² SYBR® Green qPCR Mastermixes. The uniform PCR efficiencies and PCR conditions of the RT² qPCR Primer Assays provide an accurate and scalable solution for multiple gene expression analyses.
For gene expression analysis by real-time RT‑PCR
There are several reasons for not seeing a PCR product.
1. The corresponding gene may not be expressed above the limit of detection of the qRT-PCR assay method.
2. There may have been experimental error, in which case, use a template known to contain the gene of interest as a positive control to troubleshoot the PCR reagents and experimental procedure.
3. The RNA may have been of poor quality, in which case, be sure to perform all of the recommended quality control checks on the RNA sample (see Sample Preparation FAQs, above).
4. There may not have been enough template, in which case, use more input total RNA, or use the template at a lower dilution factor (higher concentration), or use a larger volume of template.
5. Another possible explanation pertains to when one is trying to detect cellular expression from an exogenous vector that has been introduced into a cell. If the vector expresses only the open reading frame (ORF) of the gene of interest, and the qPCR primers being used amplify a target within the 5' or 3' UTR (untranslated region) of the gene, the transcript will not be detected.
Prepare five (5) 2-fold, 5-fold, or 10-fold serial dilutions of cDNA template known to express the gene of interest in high abundance. Use each serial dilution in separate real-time reactions, and determine their threshold cycle values. In a base-10 semi-logarithmic graph, plot the threshold cycle versus the dilution factor and fit the data to a straight line. Confirm that the correlation coefficient (R2) is 0.99 or greater. The closer the slope of this straight line is to -3.32, the closer the amplification efficiency is to 100 percent.
The amplification efficiency = [10(-1/slope)] - 1
Alternatively, a number of data analysis models have been developed that enable the calculation of PCR amplification efficiencies from individual amplification plots, without the use of standard curves. These include the Data Analysis for Real-time PCR (DART-PCR), LinReg, and the Real-time PCR Miner algorithms. Because these methods do not require the generation of standard curves, they are well suited for large scale experiments
When using the standard curve method, the quantity of each experimental sample is first determined using a standard curve, and is then expressed relative to a calibrator sample.
In order to use this quantification method, prepare five (5) 2-fold, 5-fold, or 10-fold serial dilutions of cDNA template known to express the gene of interest in high abundance. Use each serial dilution in separate real-time reactions, and determine their threshold cycle values.
In a base-10 semi-logarithmic graph, plot the threshold cycle versus the dilution factor and fit the data to a straight line. Confirm that the correlation coefficient (R2) for the line is 0.99 or greater.
This plot is then used as a standard or calibration curve for extrapolating relative expression level information for the same gene of interest in unknown experimental samples. The relative quantification calibration curve result for the gene of interest is normalized to that of a housekeeping gene in the same sample, and then the normalized numbers are compared between samples to get a fold change in expression.
A standard or calibration curve must be generated separately for each gene of interest and each housekeeping gene.
See Critical Factors for Successful Real-Time PCR for additional details.
The most important prerequisite for any gene expression analysis experiment is the preparation of consistently high-quality RNA from every experimental sample. Contamination by DNA, protein, polysaccharide, or organic solvents can jeopardize the success of an experiment.
Genomic DNA contamination in an RNA sample compromises the quality of gene expression analysis results. The contaminating DNA inflates the OD reading of the RNA concentration. It is also a source of false positive signals in RT-PCR experiments.
RNase contamination degrades RNA samples whichcauses low signal and false-negative results in PCR.
Residual polysaccharides, collagen, other macromolecules, and organic solvents in an RNA sample can inhibit the activity of DNase, which may interfere with DNase treatment for genomic DNA removal. These contaminants may also inhibit reverse transcriptase and DNA polymerase, leading to lower reverse transcription efficiency and reduced PCR sensitivity.
Absolute Quantification determines expression levels in absolute numbers of copies. Relative Quantification determines fold changes in expression between two samples. In absolute quantification, the precise amount of the message or template used for the curve is known. In relative quantification, the template is simply known to contain the message of interest in high abundance, but its absolute amount is not necessarily known. Unknowns are compared to either standard curve and a value is extrapolated. The absolute quantification standard curve provides the final answer. The relative quantification calibration curve result for the gene of interest is normalized to that of a housekeeping gene in the same sample, and then the normalized numbers are compared between samples to obtain a fold change.
See Critical Factors for Sucessful Real-Time PCR for more information.
Instrument-specific protocols are available for selected instruments, and can be accessed at the following link: http://www.sabiosciences.com/pcrarrayprotocolfiles.php
Assuming 100% amplification efficiency, each step increase in Ct value represents a doubling in the amount of qPCR template. Therefore, evaluating the difference in Ct values between the qPCR assay, and its matching NRT control, leads to the following predictions:
|CtNRT - Ct+RT||Fraction of gene expression signal due to contaminating DNA||Percentage of gene expression signal due to contaminating DNA|
|1||(1/21) = 1/2||50%|
|2||(1/22) = 1/4||25%|
|3||(1/23) = 1/8||13%|
|4||(1/24) = 1/16||6%|
|5||(1/25) = 1/32||3%|
In the comparative or ΔΔCt method of qPCR data analysis, the Ct values obtained from two different experimental RNA samples are directly normalized to a housekeeping gene and then compared. This method assumes that the amplification efficiencies of the gene of interest and the housekeeping genes are close to 100 percent (meaning a standard or calibration curve slope of -3.32) First, the difference between the Ct values (ΔCt) of the gene of interest and the housekeeping gene is calculated for each experimental sample. Then, the difference in the ΔCt values between the experimental and control samples ΔΔCt is calculated. The fold-change in expression of the gene of interest between the two samples is then equal to 2^(-ΔΔCt).
See Critical Factors for Successful Real-Time PCR for more information.
Dissociation curves are carried out at the end of a PCR experiment by following a 3-step procedure.
First, all the components are denatured at 95°C, followed by complete annealing at a set temperature (based on the primer Tm values), followed by a gradual increase in temperature up to 95°C. Fluorescence intensity is monitored during this final temperature increase, resulting in the generation of a melting curve or dissociation curve.
By analyzing the first derivative of such a curve, you can readily assess the homogeneity of the PCR products, including the presence of primer–dimers, thereby determining the specificity of the PCR reaction. It is important to carry out such post-PCR analyses when using SYBR Green probe chemistry due to this reagent's lack of sequence specificity.
On the product information sheet, we include the reference position for the gene-specific amplicon relative to the RT² qPCR Primer Assay's corresponding RefSeq number. Journals accept the catalog number and the reference position for publication purposes.
Customers may also use the reference position, the RefSeq number, and the NCBI database to insure that the amplicons are indeed gene-specific and even determine the approximate region amplified by the primers. For extra assurance, you can TA-clone the PCR product and then sequence it.
If the extra peaks seem irregular or noisy, do not occur in all samples, and occur at temperatures less than 70 ºC, then these peaks may not represent real PCR products and instead may represent artifacts caused by instrument settings.
Usually extra peaks caused by secondary products are smooth and regular, occur reproducibly in most samples, and occur at temperatures greater than 70 ºC. Characterization of the product by agarose gel electrophoresis is the best way to distinguish between these cases. If only one band appears by agarose gel then the extra peaks in the dissociation curve are instrument artifacts and not real products. If this is the case, refer to the thermal cycler user manual, and confirm that all instrument settings (smooth factor, etc.) are set to their optimal values.