We have isolated genomic DNA from three biological replicates (3 different petri plates of filamentous fungi) of our samples (2 treatments and a control). We are then proceeding to qPCR, examining the effect of our chemical treatment on starting copy number available for amplification. In order to optimize the assay, I would like to run a standard curve to determine our reaction efficiency (I believe this is also a suggestion for high-quality data from MIQE). I am looking at a 5-point serial dilution with three technical replicates of each point, taken from my control sample's gDNA. But how do my biological replicates play into this? Do I pick just one at random, or do I have to run a standard curve for each bio-rep and hope that all three are statistically similar? And if the latter is the appropriate course, then I won't be able to run my standard curves and samples on the same plate (I'm limited to 48 wells). In such a case, would it be appropriate to run my samples immediately after my standard curves?
I'm new to this, so I appreciate any advice!
Yes - it is OK to run the curves and samples on separate plates - but be certain to use a mastermix that is initially pooled/created for all reactions up-front. You don't want variation to arise from mastermix prep.
Having a standard curve for each bio-rep would be important if different PCR inhibitors are expected depending on treatment. If you do not expect this, then curves for each bio-rep will be less useful - although performing them can allow you to calculate a more accurate efficiency for each target reaction. But you would average the different Eamp values using the formula: 10^(1/Average(1/log(EAMP1),1/log(EAMP2),log(EAMP3)))
rather than just a simple arithmetic averaging.
If it will be helpful for you, I can suggest you this paper where the procedure of biological and technical replicates is reported for qPCR and its standard curve. http://www.sciencedirect.com/science/article/pii/S0167701213000961
Make your curves with a pool of samples. The standard curve for qPCR helps you in defining the sample concentration and calculation of efficiency (ideal between 0.95 and 1.05) and equation of the line (R ² closer to 1).
You can do all the races of the curves in genedisks separated. In this case, has 48 wells and five curves can run 9 genes (45 wells) and uses the remaining white.
Important to remember that when you run your samples, you need to have at least one concentration curve in this race to import the curve ever made.
Mikael Kubista's comment (above) here is especially specific, revealing and informative, and is the most important comment here to read. Be certain to check out his work and his publications. This is no small question.
I also do strongly agree with Fabricio in his suggestion of using a pool of samples for creating standard curves - since they are examples of things that are most like in "kind" to the way your actual field samples will bahave and report. Finding that valid dilution range within which trustworthy reporting occurs is key for all targets.
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