qPCR standard curve

The Obligate qPCR Standard Curve

At first sight, real-time PCR looks like a very simple technique—very straightforward. Also, when it’s optimized, real-time PCR leads to interesting results. However, to obtain consistent and accurate results reflecting the reality, good controls are crucial for SYBR qPCR.  One of these controls is the qPCR standard curve to check for the efficiency of your primers.

Efficient Primers Are Important for qPCR

Testing the primers using a standard curve is an absolute requisite before doing any qPCR experiments! Making sure that the obtained Ct values are valuable and reflect the reality is important. I saw lot of students skipping this step, which is risky. After you receive your new primers, you’re often impatient to run your qPCR to obtain new results. But if you avoid testing the primers first, then you might obtain false results and lose a lot of time.

Whether you design the primers with bioinformatics software or you choose a sequence already published in a great article, it does not mean your primers are good. Even if the melt curve results in a nice, clean single peak, it does not indicate that the oligos are usable. They still may not amplify the target efficiently during a dose-dependent DNA amplification.

Therefore, you should always test your primers with a qPCR standard curve. The standard curve ensures that your primers detect efficiently and precisely their target, which is critical.

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 R2 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.

What If Your Primers Are Not Efficient?

It happens surprisingly often that the standard curve results in an unproportioned curve; each DNA concentration results in approximately the same Ct value. This means that the primers do not recognize the target efficiently.

If this happens to you, first, make sure your DNA sample is clean and does not contain contaminants. If your primers still do not amplify efficiently, then design and order a new pair of primers. In the past, I have tried to troubleshoot inefficient primers to find the appropriate parameters (primers concentration, annealing temperature, etc.). In my opinion, it rarely leads to good results.

A Bad Standard Curve May Reflect Low DNA Expression

A poor standard curve may not be caused by inefficient primers. Your standard curve might be incorrect if your target is expressed poorly in your sample. You should verify whether this target is expressed in the cell type that you’re studying. If your target is poorly expressed, increase the quantity of DNA used for the amplification.

Alternatively, you could do a pre-amplification step to increase the expression of your target, for which commercial kits are available.1 You can also do your qPCR on crude cell lysates instead of purified RNA samples to avoid losing material.2

Another Advantage of a Standard Curve

Besides knowing if your primers are efficient, a standard curve tells you the detection limit. This can help you determine the appropriate amount of DNA to use in your next experiments. Why use 10 ng per reaction when you can use only 1 ng? You can spare your precious DNA samples for more qPCR reactions.

In summary, it might be tempting to skip the qPCR standard curve step. I hope I convinced you how important it is to take the time to evaluate the efficiency of your new primers. It can save a lot of time and lead to better results!

References

  1. Korenkova V, et al. (2015) Pre-amplification in the context of high-throughput qPCR gene expression experiment. BMC Mol Biol. 16:5.
  2. Van Peer G, Mestdagh P, Vandesompele J. (2012) Accurate RT-qPCR gene expression analysis on cell culture lysates. Sci Rep. 2:222.

 

4 Comments

  1. Jolene on April 12, 2017 at 7:34 pm

    I have Ct values from my standard curve experiment, but I am not sure how to do the analysis and calculate efficiency. The lightcycler I used belongs to another lab and they advised against using the software on it so I am wondering if there is any good, user friendly, free software I can use to do the calculation. Or is there a way to manually plot and calculate efficiency if I have the Ct values?
    Thanks,
    Jolene

  2. Tatpong on December 21, 2016 at 6:13 am

    I also perform the qPCR like this.
    This article is very helpful to my experiment.
    Thank you
    Best Regards,
    Tatpong

  3. Feli on November 17, 2016 at 6:18 pm

    Hi,
    Thanks for the article, qPCR really does have it’s difficulties for beginnners. In our lab, we are using Taqman primers, and I was wondering whether the standard curve is also necessary for these primers?
    Cheers, Feli

    • Stéphanie Bilodeau on November 18, 2016 at 8:51 pm

      Hi Feli,
      Thanks for your comments!
      For Taqman primers, you can do a standard curve, but it is not as necessary as for SYBR green. The probe makes the qPCR reaction more specific and effective.
      Best regards, Stéphanie

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