Top FAQs in qPCR

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Since the development of high-throughput techniques such as next-generation sequencing and RNA-seq, “omics” type data has really taken off. Proven methods, like qPCR, are routinely used in combination with these high-throughput methods in labs across the world. Real-time PCR (quantitative PCR, qPCR) is a well-established method for gene expression analysis due to its superior sensitivity, dynamic range and precision, while eliminating the need for post-PCR sample processing. Although qPCR is a relatively straightforward technique, some factors still need to be considered if you want to achieve successful qPCR results and get meaningful data every time.

Recently, we held some dedicated qPCR webinars to cover the basics of real-time PCR, which included how to conduct a real-time PCR assay and the different challenges and possible solutions associated with qPCR analysis. We have compiled a list of the most frequently asked questions from the audience with their answers to help you with your gene expression research.

Why and what negative controls are typically included in qPCR and/or qRT-PCR experiments?

It is critical to include appropriate positive controls in a qPCR experiment to detect false negatives and check that that the PCR reaction mix and cycling conditions are working. If the positive control does not amplify, then it’s unlikely that your target will be amplified. There are two options for positive controls:

1. Exogenous positive controls refer to the use of external DNA or RNA, which do not interfere with the target of interest. They serve as a control to determine whether or not the reverse transcription and/or PCR reaction mix and conditions are working, and to detect the presence of inhibitors that might prevent optimal amplification. Positive controls can either be performed in separate reactions or as spike-in controls in the same reaction if using a multiplex procedure. If these positive controls are assayed in separate wells/tubes from the experimental sample, they serve as a control to determine whether or not the reverse transcription and/or PCR reaction conditions are optimal. Additionally, exogenous DNA or RNA positive controls may be spiked into the experimental sample(s) and assayed in parallel or in a multiplex format with the target of interest. These control reactions assess whether the samples contain any components that could inhibit reverse transcription and/or PCR.

2. A no reverse transcriptase control (NRT) or minus reverse transcriptase control (MRT) involves carrying out the reverse transcription step of a qRT-PCR experiment in the absence of a reverse transcriptase. This control assesses the amount of DNA contamination present in the RNA sample.

3. A no amplification control (NAC) omits the DNA polymerase from the PCR reaction. This is a control for background fluorescence that is not a function of the PCR. Such fluorescence is typically attributable to the use of a degraded, dual-labelled probe. This control is unnecessary when utilizing SYBR-Green probe chemistries.

What positive controls are typically included in qPCR and/or qRT-PCR experiments?

It is critical to include appropriate positive controls in a qPCR experiment to determine if false negatives are being detected in the experiment. Positive controls fall into one of 2 classes.

1. Exogenous positive controls refer to the use of external DNA or RNA carrying a target of interest. If these positive controls are assayed in separate wells/tubes from the experimental sample, they serve as a control to determine whether or not the reverse transcription and/or PCR reaction conditions are optimal. Additionally, exogenous DNA or RNA positive controls may be spiked into the experimental sample(s) and assayed in parallel or in a multiplex format with the target of interest. These control reactions assess whether the samples contain any components that inhibit reverse transcription and/or PCR.

2. Endogenous positive controls refer to the use of a native target that is present in the experimental sample(s) of interest, but is different from the target under study. These types of controls are often referred to as normalizers and are typically used to correct for quantity and quality differences between samples. This includes reference gene or housekeepers.

3. Within the RT² Profiler PCR Arrays, the Positive PCR Control (PPC) wells contain a plasmid with a primer assay that detects a sequence it produces. This allows quick confirmation of the performance of the PCR steps.

The RTC wells include assays that detect the artificial RNA that is spiked in to each sample during the cDNA synthesis step. This allows you to check whether the reverse transcription step proceeded correctly.

What do I need to complete a RT² qPCR Primer Assay?

You need:

1. A RT² SYBR Green Mastermix with or without ROX, depending on the qPCR instrument in your laboratory
2. RT² qPCR Primer Assays for your target genes
3. A housekeeping gene RT² qPCR Primer Assay

We also recommend using our RT² First Strand Kit for reverse transcription.

Which qPCR instrument should I use with RT² qPCR Primer Assays?

Our RT² qPCR Primer Assays may be used on any real-time instrument. qPCR solutions are available for the most popular qPCR instrumentation, including those from QIAGEN, ABI, BioRad and Stratagene.Instrument-specific protocols are available for selected instruments, and can be accessed at the following link: http://www.sabiosciences.com/pcrarrayprotocolfiles.php

What RT² qPCR Primer Assays are available?

RT² qPCR Primer Assays are available for any gene in the human, mouse, or rat genome. In addition, we also offer custom primers for other species. Call our Technical Support Team at 1- 888-503-3187, in order to receive a quote for the design and manufacture of custom primers.

What are the guidelines for choosing a housekeeping gene for normalizing qPCR results?

If you are unsure of the correct housekeeping gene(s), review the literature and technical information in your field to determine which gene(s) other researchers commonly use. It is recommended that multiple housekeeping genes are utilized for each gene expression experiment, to account for any impact that an experimental condition may have on the expression of an individual housekeeping gene. For a systematic assessment of which housekeeping genes are appropriate for your specific experimental conditions, we recommend using the housekeeping genes of the RT² Profiler PCR Arrays for human (330231 PAHS-000), mouse (330231 PAMM-000) or rat (330231 PARN-000). These arrays consist of 8 sets of 12 common housekeeping genes. They are a valuable tool for easily identifying genes with a constant level of expression among your different experimental conditions.

How do I determine the amplification efficiency of my qPCR assay?

Prepare five (5) 2-fold, 5-fold or 10-fold serial dilutions of the 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.

What is the recommended amount of input template for each RT² qPCR Primer Assay?

The optimal range of input total RNA for the first strand cDNA template synthesis (reverse transcription) reaction is between 100 ng and 5 µg. For initial experiments, we recommend using between 0.5 to 1 µg of input total RNA, and using 1 µl of either undiluted template or template pre-diluted 1:10 for each 25 µl RT² qPCR Assay reaction.

How do I determine the linear dynamic range of my qPCR or qRT-PCR assay?

Prepare five 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. The linear range of this plot is the linear dynamic range of the qPCR assay.

What is a dissociation curve and why is it important to run a dissociation curve following qPCR using SYBR Green chemistry?

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 amplification 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.

Why do I see multiple high-intensity peaks in my qPCR dissociation curve at temperatures less than 70ºC?

If the extra peaks seem irregular or noisy, do not occur in all samples and occur at temperatures less than 70ºC, 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.

Why is qRT-PCR reproducibility so critical when detecting gene expression knock down in an RNAi experiment?

A 70% drop in gene expression translates into an expected difference in threshold cycles values of 1.75 between gene-specific and negative control shRNAtransfectedcells. The standard deviation in the threshold cycle values must be less than 0.33 in order to reliably detect this difference. If the reproducibility is poor, then the expected difference can be buried in the noise of the variation in the threshold cycle values. For guidance in designing and executing effective qRT-PCR experiments, we recommend reviewing the qPCR section of the QIAGEN FAQ collection.

What are the advantages of qBiomarker somatic mutation PCR arrays and assays compared to other platforms?

The main advantages are superior detection sensitivity and a straightforward data analysis procedure. Additional major advantages over other currently available mutation detection platforms/methods are:

1. The workflow is very simple, involving only one setup step. No multi- step handling is involved, and hands-on time is less than any other method available.
2. All reactions involved are closed-tube reactions, which prevents sample contamination.
3. The DNA sample input is low.
4. The hardware involved in analysis using the mutation detection arrays and assays is highly accessible, enabling analysis for any laboratory with access to a real-time PCR instruments.

For more information about qPCR, application data and how to customize and modify your arrays, download the new guide!

Vishwadeepak Tripathi

Vishwadeepak Tripathi, PhD is a Global Market Manager at QIAGEN. He received his PhD in biochemistry at the Faculty of Medicine from Ruhr-University Bochum, Germany. Dr. Tripathi studied the role of chaperones and co-chaperones in protein folding and quality control and authored a number of scientific publications. He was also at RIKEN Institute in Japan where he studied the pathogenesis of Huntington's disease in cellular and mice models. He is currently interested in biomarker research, NGS and neurodegeneration.

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