qPCR

[fibonacci]

HI...

actually I need some advices from the forum members...

i plan to do the qPCR for several gene of interest (GOI)...

and i plan to do the relative quantification...

from my reading, i have to test the primers efficiency before i start the real assay..

to do the primers efficiency, i have to generate the standard curve for each pair of primers..

from my reading, i found out that normally researcher will use the 10-fold serial dilution..

 

so, my questions is :

1) can i use 2-fold @ 5-fold serial dilution of my template??? because i have tried 10-fold dilution but the results is not so good..i think because of my GOI is not highly expressed because the Cq value for 100ng (highest concentation) is ~23..

 

2) besides that, do i need to run the assay (in the same running process) for the reference gene each time i run the GOI??? (i mean, if i have 5 GOI, so, i need to run it 5 reference gene???)..i asked this because i have several GOI and several samples...so, i cannot fit all the GOI and reference gene in the same running process...

 

really appreciate if someone can help me...

thanks..

[CharonY]

The most important information is missing. What do you want to compare? If you want to compare the expression of a single gene under different conditions, for example, you would do all your runs for each gene individually.

Comparing the expression of different genes requires more normalization and is generally still relatively imprecise.

The second question is how you want to do the normalization. With a dilution series you essentially can see the dynamic range of your assay and it gives some limited information about the efficiency, but as you do not know with what you start, its use is limited. For a calibration curve one usually takes a known quantity (most often genomic DNA).

If you want to compare a single gene e.g from different extractions, you have to run them all in one go, but you do not need the dilution series. It will only tell you at which point (e.g. 10-fold dilution of your reference extraction) the response will become useless (i.e. is outside the dynamic range). So based on what you are saying is that you are not able to detect anything at 10-fold below your reference.

Essentially always keep in mind what your reference for any given assay is as you will have to compare everything against it. Also cross-comparison between different genes is tricky and generally not recommended.

[fibonacci]

actually, i want to do the relative quantification..

 

for example, i have 5 target genes and i have 1 ref gene..so i want to compare the expression level of these 5 genes at 3 different conditions (samples are from the same organism)..

[CharonY]

So you want to compare all your genes to one reference gene? In that case you should normalize it down to gene copies, e.g. using defined amounts of genomic DNA (though you should know the copy number per genome). Normalization against PCR efficiency usually does not yield good results as the run-to-run variability is quite high. In any case these estimations will not be very accurate. qPCR in general is not too good of a tool for comparing expressions of different genes. It is much more suited to compare the different amount of a single sequence.