relative comparison of many samples and genes in qRT-PCR - (Nov/09/2010 )
I read through the supplemental materials in the first post as well as a few other resources, but still have a question as to how best accomplish my objective.
My question is how to best compare many samples with many genes. My objective is to get a relative comparison of gene levels between approximately 15 samples and approximately 12 primer sets, one of which is GAPDH which our lab uses as the reference gene.
Two strategies come to mind:
I can run on a single plate, triplicate of each sample (15 samples * 3 = 45 wells) for GAPDH and one gene of interest (45 wells for GAPDH + 45 wells for gene #1 = 90 wells). I would then need to run one plate for each gene to be tested for a total of 12 pcr plates (plate 1: GAPDH vs gene #1, plate 2: GAPDH vs gene #2, etc)! I would use the Pfaffl method (a modified delta-delta-Ct method) on each plate to get a comparison of the gene of interest expression level relative to the GAPDH level. At the end, I would plot those fold-changes in one graph showing the relative level of each gene in each sample. I feel that I can combine the data from the multiple plates since the reference (GAPDH) is run on every plate, so each plate is telling me the fold change of one gene relative to GAPDH levels.
I would of course run a dilution series of each gene separately to get the accurate efficiency so I can use the Pfaffl method.
I can run on a single plate, one sample with each primer set, in triplicate (12 primer sets * 3 = 36 wells). I can then fit two samples per plate (36 wells for sample #1 + 36 wells for sample #2 = 72 wells), assaying all the gene levels for each sample. This way, I have to run only 8 pcr plates in total (plate 1: samples #1 and #2, plate 2: samples #3 and #4, etc). In the end, I would overlay the results - they should be comparable since what I am reporting is the expression level relative to GAPDH for each gene in each sample.
My only hesitation here is that, what if hte GAPDH levels between two samples is different? Theoretically, it shouldn't matter too much since that is what I am normalizing to.
hi, i would strongly encourage to use the first approach and you do not even have to run the gapdh on every plate, just once together with a second target and then, for the remaining assays, you can pack two targets on one plate (would end up with a total of 6 plates if I remember correct). since you have always all samples together on one plate you don't have to worry about inter run calibration.
the second approach is not so good. since you usually want to compare samples within one target it is not a good idea to spread those samples on several plates which are hard to compare. even if you include the gapdh on every plate. you would also need an inter run calibrator to normalize for the technical variances between different runs. e.g. an assay with gapdh may give a Ct of 19 and on the next day with the same sample and exactly the same conditions (including same treshold and baseline adjustments!) a Ct of 19.6.
this is described in in figure 2 in Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J. qBase relative
quantification framework and software for management and automated analysis of
real-time quantitative PCR data. Genome Biol. 2007;8(2):R19. PubMed PMID: