Hi there,
I have spend a few weeks now setting up a qPCR assay in the lab. I hope my question is straight forward without going into too much detail:
After reading a lot about how to test primers before using them, I ended up with some primers that give robust amplification, but their efficiency as calculated from the slope of the linear regression on a dilution curve, is outside of the acceptable range.
Now I was wondering if it would be worth to use this information to "normalise" the expression data according to the primer efficiency.
For example, if I have a primer with 100% and one with 60% efficiency, would it be conceivable to just take the relative expression data and normalise it by this factor to make up for the inefficiency of the primer, and calculate what the expression would be if the primer was 100%?
Or is it not possible to compare primers with different efficiency this way?
What do you think? Is that something people do? I have read a lot about it but I haven't come accross that.
Thanks and best wishes,
Laura
Hi,
The reason why efficiency should normally be between 90-110% is because it is the same the as the reference gene (which is normally 100%).
I think it depends on your reason - why can't you redesign to get a higher efficiency?
No - you can't normalise by 60% - you have to change CT equation
so relative expression = 1.6^-deltaCT if efficiency was 60%. ( this would really blunt your result)
I advise 85-105% for effecency for any publication. I understand that some error can be in the dilution curve.
Hi Asif,
thanks for your thoughts on this. You are probably right, I just wanted to see if that is something people do.
I guess I will have to re-design!
Cheers,
Laura
I wouldn't trust quantifications when the amplification efficiency is recognizeably compromized (no matter how one would try to compensate this by math-tricks). I would design a different primer, and if this woulnd't work I would try a different PCR mix.
Many times, a problem with PCR efficiency is due to high GC content of the region of interest. If that is the case, you might take a look at this thread:
https://www.researchgate.net/post/How_can_I_sequence_human_COQ2_DNA_exon_1/1
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