Hi Ahmed,

I personally would not use only CT value of a sample as proof of expression. There are several other more accurate ways to determine and quantify expression. For example, you could do relative quantification by comparing expression to a control sample (thereby actually measuring change in expression), or you could make a standard curve with control cDNA and thereby quantitatively measure your expression.

The comparison to a NTC is not sufficient. An NTC may show contaminations. If you talk about a ct value that is then 2 lower than the ct of the NTC, it means that there was (roughly) four-times as much initial target as in the NTC, what I would'n consider "negative". But this is only useful when the amplification in both samples is specific (with SBYR Gree detection, for instance, the amplification of primer-dimers will also give a ct-value). When primer-dimers occur and are measured, ct-values of low initial target amounts may be grossly misleading.

For the judgement of the presence of expression (not its quantity!) it is better to simply look if there is a specific amplification (either yes or no). The ability to detect a single molecule should be checked with a known standard (diluted to have an average concentration of 1 molecule per PCR). Following the Poisson distribution, 63% of such reactions are expected to be "positive". If one finds considerably fewer positive reactions, the sensitivity is not optimal. Given optimal sensitivity, the likelihood for k positive reactions in n samples can be calculated for the hypothesis that the average number of molecules is at least one (or any other conc that is considered as relevant expression). This hypothesis may then be rejected when the likelihood of the observed data is very small (concluding that the gene is not expressed). The distribution of "k out of n" is binomial, and the null hypothesis value for p(single positive PCR) is taken from the Poisson distribution.

For my gene expression assays, I will first perform a standard curve from a known concentration to see how the assay behaves. For actual analysis I use the comparative CT method (see paper Analyzing real-time PCR data by the comparative CT method by Schmittgen & Livak 2008).

If you are just trying to determine expression, I was taught you typically want to see CT values below 35. If the CT is above 35 then the expression is more questionable-

if it is real.

Thank you all,, I think I have to go for quantitative analysis comparing expression to a control sample, using reference gene as you suggested.

Thanks

Strange... what will the comparison with a control sample help in finding whether or not a gene is expressed? I don't get it.

Jochen Wilhelm, I would measure the change in expression compare to normal control. Do you mean that is not correct to know whether the gene is expressed or not? I still new in QPCR. Thank you

Jochen, Ahmed, I refer to my previous answer....measuring the change in expression compared to a normal control is called "relative quantification of expression". It is a good way to measure CHANGES in expression due to some experimental parameter. HOWEVER...you need to know your gene is expressed in your samples. So it all depends on your question....if you simply want a YES/NO answer to if your gene of interest is expressed, I would suggest absolute quantification where you "measure" your expression quantitatively compared to a known control sample concentration series. There are other ways where you simply see if there is more amplification in your sample than in your NTC, but that is not as accurate or trustworthy, but it is an option if you do not have control cDNA. I hope this is more clear?

Chrisna Gouws,, its clear now,, I want to measure the fold change in the expression of gene compare to normal control, then I have to do relative quantification measuring delta Ct between the gene of interest and the reference gene in both the treatment group and control one.

Thank you

Yes Ahmed, Just remember to choose your reference/household gene very carefully! You tipically want a gene that will amplify close to the same cycle as your target gene if possible!Good luck!

Ok, asking for a fold-change (how much more or less is a gene expressed in condition A as compared to conditionB) is a different question than asking for the expression (is a gene expressed at all in these cells and under this condition).

To answer the latter question no quantification is used at all; it is simply a detection problem. Given a sensitive and specific reaction, a negative result indicates that there is no expression and any positive result would indicate that there is expression. No need to quantify anything.

So, Chrisna, to come back to your statement "if you simply want a YES/NO answer to if your gene of interest is expressed, I would suggest absolute quantification where you "measure" your expression quantitatively compared to a known control sample concentration series." - I again must say that (i) a quantification itself is not required and (ii) a quantification relative to a control sample is neither sensible (what whoule one need to know the expression in a reference sample?) nor generally possible (if the gene is not expressed, one does not get quantitative information, e.g. no finite = undefined Ct value).

The original question was a question of expression, not for a fold-change. Obviousely Ahmed changed his question during this discussion... You are right that such a quantification of fold-changes requires the gene to be expressed (under all conditions) and that it can be tackled with standard relative quantification assays. However, checking if the gene is expressed won't make much sense here. When it is not expressed, one won't get ct values and a quantification won't be possible anyway. Under "bad" circumstances, the gene may be expressed under on condition but not under the other condition. Such "on/off"-analyses can not be done with standard relative quantification protocols. Here one has to go back to binomial and Poisson model to assess the likelihood of "on" and "off" states.