you already pointed out right, the one that has lower Ct value probably has the better efficiency as compared to the other one. Unless you use two different biological samples, I do not see any possibility of expression level of the target gene for being different with one and another when two sets of primers are used. In order to see whether there is non-specific product, I suggest you to run melt curve; of course, if you use SYBR green for your chemistry of detection.

yes i agree with mr. Win Sen Heng

Thank you! The thing i noticed that the gene expression increased in the sample amplified with primer A ,, and when I performed again real time with the same sample with primer B i got lower gene experssion ,, i repeated this with 50 samples ,, so gene expression have changed with the change of primer (( the primer A is an imporoved of version B )) any comments?? 

how big is the difference if I may know? We expect to see variation between different run, or even replicates within the same run if the technique of handling is not good. Further, do you see that sample amplified with primer sets A always consistently estimated higher gene expression level? We should tolerate variation approximately 2 cycles away (of course this is not the ideal one). 

Or perhaps, you tested both sets of primers at the same time, in the same run, and you see difference in Ct? I would really recommend you to see the melt curve. It can reveal a lot. If the primer sets B have primer dimer problem, non-specific product will interfere with the amplification of your target product, thus compromising the Ct reliability. Another thing is, did you set up negative control (no template) for both sets of primer? Any amplification in there?

Ok I'll explain a little bit about what i do ,, actually primers B are perfect and work excellent this is proofed from research papers ,, However primers A are proofed in a recent research paper that they can amplify these makers in a better way ,, the samples I'm using are degraded ones ,, I wanted to compare between the gene expression of the same samples once amplified with primer A and once with primer B ,, because it is proofed that primers A are better and improved than B and can target stable regions within the same biomarker that primer B comuldn't ,, which will help in body fluid identification ,, so i thought about comparing between gene expression ,, now u said primers should not make a difference!

Ok what do u suggest to do? To compared what with what,, i want to proof that primer A is better than B and can help in detecting degraded samples because in can amplify the stable regions within the biomarker ,, can u help?? thank u a lot.

One of them is not fully specific with your target ,here its amplify more than obe target therefore you see difference in level of gene expression you can check your primers specifity by in silico PCR

Hi ,, actually ,, both primers work with the biomarker of interest but one targets a specific sequence and the other targets other sequence within the same biomarker ,, i want to proof through qpcr that the improved primer is better than the old one ,, how can i proof that via qpcr?? , thank you

I have one more questions drs,, 

in what cases gene expression increase or decrease ,, I mean is gene expression increae is a positive thing?? Or the opposite ?? Iam comparing my treated samples with a reference gene. If tthe expression of the treated samples was more than the reference gene what does that mean?? 

You said that your target is the same, logically, different primer sets should not matter, because we are detecting the level of expression in biological sample. You mentioned that the primers sets are detecting different sequences, however if the sequences have the same relative abundance in your biological sample (the target biomarker), it will not really matter, you will still have approximately the same Ct. If different primers sets really generate variable data (very much different), our research around the world would not be comparable. Unless, your sequence is some sort of repeats within the biomarker, and the other is not, that would probably make the difference, e.g, sequence 1 has 5x repeat in the biomarker, sequence 2 has 2x repeat in the biomarker.

What Ahmed suggested you is also one of the ways. You can perform in silico check for the possibility of forming other non-specific binding, thus non-specific product amplification. After that you can perform the PCR to prove that what derived from in silico is really the case. Of course, you could not 100% tell people that one sets of the primer form specific heterodimer, homodimer or hairpin, but you can obviously judge from the PCR amplification result in your negative control, in your melt curve, whether there is non-specific product.

You can also perform titer of your sample to have 5 points that would make a standard curve, e.g., 1, 1:10, 1:100, 1:1000, 1:10000 dilution and see whether you can have good amplification efficiency by plotting linear line. Good amplification should lies between 90% to 110% efficiency. R^2 would be better to be >0.99 (ideally, but I guess you can have lower, but must be >0.90).

To answer your question, you have to know what is your research objective. Increment or decrement really depends on what you look for. For instance, increased expression of oncogene is deemed to be negative thing, whereas increased expression of tumour suppressor gene is deemed positive. 

Do you mean reference gene as housekeeping gene that serve as internal control? You should compare your treated sample against your untreated sample, not with your reference gene. Reference gene serves to normalise the difference between biological samples (treated vs untreated). 

Hi

designing primers for gene expression should take into account the fact of RNA degradation and thus each sets of primers need to be analyzed as the mean, as it can be done in the Agilent genespring software. one important thing is also to test the efficiency of each sets and the quality of primers (for my experience I use Oligo7 to design primers and estimate the value of them).

fred

Thank you so much 

actually the samples iam working on are fresh and degraded samples ,, the primers B cant amplify the degraded samples however primers A can ,, this is the summary of my project i want via qpcr proove that primer A can give better results than primer B ,,

and of course fresh samples by logic will give better results .. and the degraded ones will give lesser result ,, the A primers target a stable region within the same marker which makes it better than primar B.

in this case how to use qpcr to proof this fact??? Help 

I must compare the degraded samples with fresh? But of course the fresh will give better results!! 

U got my point? Thats why i wanted to compare degraded samples of primers A with degraded samples of primer B ,,  ( both primers work on the same biomarker yet different sequence)

how to know via qpcr that this primer is better than the other?? Lower Ct = better primer?? gene expression? 

Thanks 

Hi

qPCR won't give you an idea on which primers work well. of course you'll have data, and so what? if you want I can check these primers in OLIGO7 and tell you which I would prefer use. if ok for you send me a mail, it will be absolutely private ([email protected]).

fred

Do you have the data for both sets of primers that amplify fresh sample? Is there any difference between Ct of the primers sets at that condition? Compare them with the primers both amplified in degraded sample. We assume, the primer sets A and B both performed optimally in fresh sample. Here, derive a deltaCtB-A, say 4-2= 2. Take this value as your guide. Next, performed in degraded sample, let's say you obtain deltaCtB-A 5-1 = 4. This value means either primer sets A get more efficient or primer sets B get worse, but we will assume that primer sets efficiency can no longer get better since it already performed optimally in fresh sample. Therefore, we conclude that primer sets B get worse. So you can get deltaCt (the difference of Ct) to make the conclusion you want. 

 yes i agree with mr. Win Sen Heng

Thank you for the great help

Ok i have one additional question

If I'm comparing 2 degraded samples with 2 different degradation techniques and measured the gene expression of each sample ,, one got "higher" expression in one sample than the other ,, what should I conclude?

And in this case should i additionally compare the result with a fresh sample as a control to see the difference?

(All the samples same primers)

How you clculate the gene expression by CT only ,you can decrease the differences by delta ct and delta delta ct if you have refrence gene 

Regards

I would still think that you should compare with the expression level of the fresh sample. 

ok if the expression was higher than the degraded samples than the fresh so what you will conclude?

regards

Hi

the problem is that degradation is not uniform along the genome and transcriptome, you can therefore only compare samples with the same quality, otherwise analysis will be biased. the best way is to qualify samples and under some quality point (the RIN for RNA) you need to reject the samples.

fred

ok if all the samples were the same quality,, what you will conclude? 

depends on the quality, as I said degradation is not uniform....

if qualities are good, no problem, if not, I wouldn't go further...but sometimes impossible to do else.

fred

yes i agree with mr. Frederic Lepretre