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  • lorendarith
    • Oct 2026

    #1

    KAPA qPCR troubleshooting

    Hi,

    I'm having difficulties with using qPCR to quantify my PCR-free libraries. There is just too much inconsistency in the end concentrations I obtain.

    First of, does anybody do the two independent dilutions (1:10000, 1:20000) which Illumina recommends? Do you really dilute 2 µl in 20 ml and 40 ml?

    When compared to the usual serial dilutions (1:1000, 1:2000, 1:4000, 1:8000), these two independent dilutions yield concentrations which aren't nearly similar to results from the serial dilutions.
    E.g.
    1:1000 -> 3.1 nM
    1:2000 -> 4.2 nM
    1:4000 -> 4.0 nM
    1:8000 -> 4.2 nM
    1:10000 -> 0.457 nM
    1:20000 -> 0.397 nM

    Another issue I'm having is a discrepancy between the first and other serial dilutions, in which the concentration is almost double what is obtained from the first dilution.
    E.g.
    1:1000 -> 4.5 nM
    1:2000 -> 8.2 nM
    1:4000 -> 8.2 nM
    1:8000 -> 7.4 nM

    What might I be doing wrong? Should I just take the results of dilutions which show at least some consistency (1:2000-1:8000) or should I include all serial ones (1:1000-1:8000)? What about the two independent dilutions which give weird results?

    Thanks!

    PS. I'm going to take a standard from the kit and try diluting it in the same manner to see if maybe my volume handling is the cause of these discrepancies between the dilutions.
  • TonyBrooks
    Senior Member
    • Jun 2009
    • 303

    #2
    Here's a few tips from what I tend to do

    Use the Bioanalyser to normalise to 10nM, then take a 1:10^5 dilution of that library for qPCR in triplicate (ALWAYS do serial dilutions of 1:100, 1:100 then 1:10 with minimum volumes of 2µL) Pipetting small and large volumes leads to inaccuracies (i.e. don't try and pipette 999µL or 1µL).
    This should put me somewhere in the middle of the standard curve (~0.1pM)

    Make sure your R2 is >0.99. If not, check there are no outliers in your standard curve (I think Kapa told me to remove anything greater or less than 0.2ct from the mean of any replicates).
    Also, check that the background normalisation step in your qPCR software is performing correctly - our ABI machine always defaults to using cycles 1-15 to estimate background. The problem with that is that the 20pM sample begins to be detectable for us around cycle 8. If we tell it to use an automatic baseline, everything looks much better.

    I always do the 90s elongation step, not the 45s

    Finally, normalise using the average bp from the Bioanlyser (in the region tab).

    Comment

    • lorendarith

      #3
      Thank you TonyBrooks! I will try to repeat the same runs with your tips and see if there's a difference.
      I didn't mention in the first post, but I mainly use it to quantify PCR-free libraries. Not sure if this makes any difference, apart maybe for the diluting based on the Bioanalyzer since it can't be used for accurately for this type of libraries (different running behavior due to partially ligated adapters and other artifacts).

      Regarding the dilutions, indeed I mostly use 1µl volumes. However, I first did a 1:10 (1+9µl), and then diluted this to 1:1000 (1+99µl), 1:2000 (30+30µl), 1:4000 (30+30µl) and 1:8000 (30+30µl). I'll try to do the initial dilutions with 2µl instead.

      In the meantime I had tried to quantify the 20pM standard from another batch with the kit. The values I got:
      1:1000 -> 24.71 pM
      1:2000 -> 27.67 pM
      1:4000 -> 31.23 pM
      1:8000 -> 34.70 pM
      average ---> 29.58 pM

      It looks like my pipetting and diluting could probably be off, no?
      Though the efficiency was 99% and all the replicates were consistent. R^2 for the standard curve was even 1.00!

      I asked a colleague to repeat the same run with the 20pM standard quantification and her results look somewhat similar maybe a bit better, but the dilution strategy was the same one as I used.

      For the 20 pM standard:
      1:1000 -> 14.78 pM
      1:2000 -> 16.45 pM
      1:4000 -> 19.23 pM
      1:8000 -> failed
      average ---> 16.82 pM

      Still far away from perfect, but the difference is smaller than the almost 10 pM greater value I obtained...

      Anyhow, I'll try the suggestions...

      Comment

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