FAQs

For high-throughput analyses of many samples or precise detection of rare transcripts, a one-step RT-qPCR protocol is recommended. An additional advantage of one-step RT-PCR is the existence of single-tube workflows, avoiding the need to add additional reagents halfway through the procedure and thus lowering the risk of contamination.

For more information, view our BioView blog post "One-step vs. two-step RT-qPCR—tips for choosing the right protocol".

Calibration curves for RT-qPCR may be prepared by either of the following methods:

1. Serial dilution of RNA, followed by reverse transcription and real-time PCR
2. Serial dilution of cDNA (obtained by reverse transcription reaction), followed by real-time PCR

Since the two methods evaluate different parameters, it is important to choose a method appropriate for the experimental system being used. Calibration curves prepared from diluted RNA samples reflect differences in not only PCR amplification efficiency, but also differences in reverse transcription efficiency, which is dependent on the amount of RNA. PCR amplification efficiencies determined from such calibration curves may potentially differ from the actual efficiency.

For Absolute Quantification, the reverse transcription efficiency is critical. Therefore, use serially diluted RNA to prepare calibration curves (cDNA dilution is unsuitable).

For Relative Quantification, differences in reverse transcription efficiency can be corrected by assaying a reference gene, such as a housekeeping gene. The use of serially diluted cDNA is recommended for preparing calibration curves.

To avoid amplification of genomic DNA in total RNA samples:

• Design primers that avoid genomic amplification: select a large intron region and design forward and reverse primers in exons upstream and downstream of the intron. With this strategy, genomic amplifications cannot occur for large introns. When introns are small, genomic amplification can be differentiated based on differences in melting temperature as the result of different amplification sizes (melt curve).
• For genes that lack introns or when the genomic structure is unknown, treat the total RNA with DNase I to remove genomic DNA.
• Use the PrimeScript RT Reagent Kit with gDNA Eraser (Perfect Real Time) (Cat.# RR047A). The gDNA Eraser in this kit removes genomic DNA in just 2 minutes, followed by a 15-minute reverse transcription reaction. The resulting cDNA can be amplified using a Takara Bio qPCR premix.

There is no single, universally appropriate housekeeping gene suitable for accurate normalization in every experimental condition, as it is important to select housekeeping genes that do not vary in expression levels in the experimental system used. Common housekeeping genes that have been used in the past include GAPDH and β-actin; however, reports in recent years indicate that expression of these genes may also vary, depending on the sample type and/or experimental conditions.

Using multiple housekeeping genes for normalization is currently the most reliable approach. In this strategy, the expression of multiple housekeeping genes is assayed, and the genes that show the lowest level of variation are selected for use. Software has been developed for selecting the optimum genes for correction (e.g., geNorm and BestKeeper). Inferences may also be made from microarray or RNA-seq expression profiling data, if available.

For additional information refer to: J. Vandesompele, et al. (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3(7):RESEARCH0034.1–11.

Suitable standard samples are those that approximate the actual sample as closely as possible. For gene expression analysis studies, use cDNA prepared from samples collected under conditions in which the target gene is known to be expressed. For genomic analysis studies, use genomic DNA.

Artificial standard samples (e.g., plasmid DNA) are not recommended. Even when the sequence of the amplicon is identical, any substantial difference in the template composition may result in variable PCR amplification efficiencies (e.g., genomic DNA vs. plasmid DNA).

When using a validated primer, previous melt curve analysis (Tm values) can serve as a reference. If the Tm value is the same as observed in the past, it is reasonable to assume that the PCR product is the same as that obtained in the past.

Keep in mind, however, that although identical PCR products will show the same Tm value, obtaining identical Tm values alone does not necessarily confirm that the PCR products are identical. An independent confirmation method should be used; when using a primer for the first time, please perform electrophoresis to confirm that the amplification product of the real-time PCR is the intended size.

The necessary number of sample replicates (n) varies depending on the experimental system. In principle, when the experimental error is expected to be relatively large, use a larger number of samples.

• When profiling gene expression by RT-qPCR, it is useful to prepare multiple biological replicates and perform multiple RNA extractions in order to ascertain the degree of biological variability.
• With respect to qPCR, greater variability is expected when using a low level of template because the number of cycles required for detection will be high. In such cases, use a larger number of replicates.

The sensitivity of qPCR varies depending on experimental conditions such as the reagents and primers used. Appropriately designed systems have demonstrated the ability to detect as few as ~10 copies of template.

The Ct value can be determined by two different methods:

1. The crossing point method defines the Ct value as the crossing point between the amplification curve and the threshold line.
2. The second derivative maximum method defines the Ct value as the point of the maximum of the second derivative of amplification curve (second differential curve).

The latter method allows highly precise analyses, since the Ct value is fixed by setting a threshold and is not subject to the effect of instrument-specific detection variability.

Please note that some instrument systems do not allow one to choose between the crossing point method and the second derivative maximum method.

• Absolute quantification determines the absolute number (i.e., number of copies) of a target using a standard sample that has a known number of copies.
• Relative quantifications allow a relative comparison between samples.

Typically, using relative quantification, a target gene to be quantified and a reference gene (e.g., a housekeeping gene) are simultaneously assayed for the purpose of correction (normalization). Relative quantification provides the difference in expression level in the unknown sample compared with the control sample.