Hi Bola,

First, if you have already determined the amplification efficiency (E) for each primer pair,

go for Absolute Quantification, perform reactions for your reference genes and your target genes, and extract the Cts (export tool). Then forget about the ABI software and switch to Excel. Run GeNorm using a table of relative expression values for your endogenous genes (E^[Calibrator sampleCt - Sample Ct]), as described in the handbook.

GeNorm will then give you the geometric mean of rel. expression values of the most stable endogenous genes. Each geom. mean (called NF - Normalisation Factor) will be used to normalise the expression data for each sample.

Then, calculate the relative (and still non-normalised) expression values of your target genes (again, E^[calibratorCt - Sample Ct]). Then normalise by dividing this by the NF for each sample. There you go, you'll have normalised expression values that are relative to the calibrator. These data can be further processed and calculated as fold change (treated/untreated) or whatever.

Some people do not determine the amplification efficiency for their primers, and consider E=100% (E=2). The calibrator sample can be a pool of cDNA or just anyone within your samples, as long as you use the very same calibrator for all the endogenous genes. Also, use the same calibrator for your target genes to account for technical variations between two separate plates - that is, if you're using more than one plate in this experiment.

OK Bola here's what you do. You run your target gene which is your "gene of interest" along with your 7 reference genes for all 6 samples. Then use GeNorm to choose the most stable ref genes across experimental and control conditions and how many you should include for normalization. Lets say the algorithm shows you that using 3 reference genes gives you the best stability, then you will use the geomean of the 3 reference gene Cts in your delta delta Ct calculations. Hope this helps.

Thank you for the reply. If I'm using AB-7500 for the Real-time PCR, which program will i choose , (comparative quantification or relative) and also, since the machine asks for one endogenous reference, which one do i use since I'm using so many references?

Hi Bola

As suggested by John above first you select the good and stable reference genes......there are two types of analysis you can do in any real-time PCR machine: 1) absolute quantification where you can actually estimate the numbers of transcript molecules....however you will have to run a series of reactions of each gene to draw a standard curve that will be used to calculate the number of transcript molecules in the unknown sample...

2) relative quantification where you just estimate the fold increase/decrease of your target gene relative to reference gene in the test sample as compared to the control sample....most of the times people are actually doing 'relative quantification' in realtime PCR analysis.....and 'absolute quantification' actaully is used when the actual transcript estimation is really very important

bye

Hey Bola, Ajay is right. I also use a 7500 machine and I almost always perform relative quantification (delta delta Ct method). As far as endogenous controls go, in the set up menu you can select for multiple controls and pick the targets you want designate as reference genes. You can also do this after the run in the relative quantification tab under the Analysis Tab.

Hello there. As John said, once you get the geometric mean of your most stable reference genes using GeNorm, you could as well use Excel to calculate relative expression values. If you're not using the ABI software to do that, you'll just need the Ct values, regardless of the program setup you choose.

@Gerson

I also agree with Gerson as I also try to use Excel for analysis once I have the Ct values......It gives you more flexibility and if the Real-time PCR machine is busy you can always analyze the data on another PC

Thank you for all the kind replies.

@ John... I couldn't find the menu that shows multiple controls..unless you mean that I should use the reference genes as targets..? Then if I use the delta delta Ct method, which genes will i use as reference gene and reference samples?

@ all.......... I saw an example in the Primer design geNorm kit handbook.

The table has no endogenous gene or reference samples. If i follow that method, which experiment type should I use? comparative quantification or relative standardization?

I did an earlier experiment using the comparative method and i had all my samples and genes sorted out but now, i'm trying to find a good endog. ref gene out of a couple of ref. genes. i dont think i can just go ahead and do what i did earlier.

Hi Bola,

First, if you have already determined the amplification efficiency (E) for each primer pair,

go for Absolute Quantification, perform reactions for your reference genes and your target genes, and extract the Cts (export tool). Then forget about the ABI software and switch to Excel. Run GeNorm using a table of relative expression values for your endogenous genes (E^[Calibrator sampleCt - Sample Ct]), as described in the handbook.

GeNorm will then give you the geometric mean of rel. expression values of the most stable endogenous genes. Each geom. mean (called NF - Normalisation Factor) will be used to normalise the expression data for each sample.

Then, calculate the relative (and still non-normalised) expression values of your target genes (again, E^[calibratorCt - Sample Ct]). Then normalise by dividing this by the NF for each sample. There you go, you'll have normalised expression values that are relative to the calibrator. These data can be further processed and calculated as fold change (treated/untreated) or whatever.

Some people do not determine the amplification efficiency for their primers, and consider E=100% (E=2). The calibrator sample can be a pool of cDNA or just anyone within your samples, as long as you use the very same calibrator for all the endogenous genes. Also, use the same calibrator for your target genes to account for technical variations between two separate plates - that is, if you're using more than one plate in this experiment.

Thank you for the detailed explanation Gerson.

Hi, are your samples the same as the treated and untreated groups? If so, then a positive control isn't necessary. But if you want a positive control, your samples will become three (a group treated to get a positive reaction).

Regarding your second question, what kind of PCR plate will you be using? Before making a layout, 'will have to know the number of genes, and the number of treatment-time-points you require for your analysis. (I normally use a 96-well plate on AB 7500 cycler)

For a 96-well plate, you can analyze only 4 samples (including the control sample), using 6 genes and a no template control (to check for the purity of your reagents). All ur samples have to be analyzed in one run and so, if you will like to do all 5 samples (4 treatment groups and untreated control) u need to get the 384-well PCR plate.

Or analyze each sample in duplicates instead of triplicates (using two wells), but you may not have a correctly confirmed data.