There is still some confusion. Real-Time-PCR (rtPCR) is a method to record the growing amount of PCR products during the PCR by employing fluorescent techniques. This method can be used to quantify nucelic acids. This is then called a quantitative PCR (qPCR), more specifically quantitative real-time PCR (qrtPCR). If mRNA should be quantified, a DNA template has to be generated first. This is done in a reverse-transcription (RT) step and we have a RT-qrtPCR.

The delta-delta-Ct method is to quantify gene expression changes (in terms of relative mRNA concentrations). This has nothing to do with the quantification of gene copy numbers.

There are no different methods to calculate delta-delta Ct values. It is just a difference of a difference. The key is to be aware what gets subtracted from what. This is a little brain-eating in qrtPCRs because of the fact that the Ct values are *inversely* proportional to the logaritm of initial amount of the target molecule: Ct = p*(-log(N)) where p is a proportionality factor. As a consequence, Ct[goi] - Ct[ref] represents the log ratio log(ref/goi), what actually is the concentration of the reference gene (ref) normalized to the concentration of the gene-of-interest (goi). I think this is the way Schmittgen calculated the delta-ct. This is absolutely correct - but unfortunately counter-intuitive. I would always calculate delta Ct as dCt = Ct[ref]-Ct[goi]. This way, the ddCt as ddCt = dCt[treat]-dCt[control] directly represents the log fold-change, where positive values indicate "up-regulation" and negative values indicate "down-regulation". Note that Schmittgen calculated the ddCt values in this way, but because the dCt values were calculated "inversely", they get the -log fold-change (mind the "minus"). However, in the end it doesn't matter much what you do as long as you know what you are doing :)

Sorry, Dziedzom, but it is just not possible to get a copy number for a gene based on data from RT-PCR (RT = reverse-transcription; analyzing mRNA concentrations!).

Since you are talking about "delta-delta-ct": do you actually mean the change in relative expression (e.g. between two conditions)? This has nothing to do with gene copy numbers.

Thanks Jochen. I meant Real Time (RT) PCR. I am comparing the expression of selected target genes in different samples. But any information on how to determine my ddCt values would be helpful. I have tried to use the methods of Livak and Schmittgen. 2001. METHODS 25: 402-408.

There is still some confusion. Real-Time-PCR (rtPCR) is a method to record the growing amount of PCR products during the PCR by employing fluorescent techniques. This method can be used to quantify nucelic acids. This is then called a quantitative PCR (qPCR), more specifically quantitative real-time PCR (qrtPCR). If mRNA should be quantified, a DNA template has to be generated first. This is done in a reverse-transcription (RT) step and we have a RT-qrtPCR.

The delta-delta-Ct method is to quantify gene expression changes (in terms of relative mRNA concentrations). This has nothing to do with the quantification of gene copy numbers.

There are no different methods to calculate delta-delta Ct values. It is just a difference of a difference. The key is to be aware what gets subtracted from what. This is a little brain-eating in qrtPCRs because of the fact that the Ct values are *inversely* proportional to the logaritm of initial amount of the target molecule: Ct = p*(-log(N)) where p is a proportionality factor. As a consequence, Ct[goi] - Ct[ref] represents the log ratio log(ref/goi), what actually is the concentration of the reference gene (ref) normalized to the concentration of the gene-of-interest (goi). I think this is the way Schmittgen calculated the delta-ct. This is absolutely correct - but unfortunately counter-intuitive. I would always calculate delta Ct as dCt = Ct[ref]-Ct[goi]. This way, the ddCt as ddCt = dCt[treat]-dCt[control] directly represents the log fold-change, where positive values indicate "up-regulation" and negative values indicate "down-regulation". Note that Schmittgen calculated the ddCt values in this way, but because the dCt values were calculated "inversely", they get the -log fold-change (mind the "minus"). However, in the end it doesn't matter much what you do as long as you know what you are doing :)

Hi, abbreviation of Real Time isn't RT-PCR! It's qPCR! RT-PCR is Reverse Transcriptase-PCR (RNA --> cDNA). Cheers, Nadine

In agreement with Jochen - that a housekeeping (reference) gene is not appropriate in this matter as, ideally, you would already have a standard curve of known copies of your gene. Plasmid most likely if your gDNA copy number is unknown...

Then you would also have a standard curve made of the samples you wish to assess generated as well. I am assuming that you are analyzing gDNA of some kind here?

The two different curves (for this same target) will, in most cases, exhibit slightly or very different amplification efficiencies; very rarely (if ever) will the two curves give you the same efficiency.

So - in theory - assuming that user-error is a non-entity throughout the entire work-flow, you can reconcile the two efficiencies and express the Cq values in your samples in the same scale as your known-copy standard curve using the attached formula.

There is also a very unorthodox approach to this:

In general, after reading numerous things on this particular topic. 1 copy (when the qPCR is 100% efficient) has been reported to appear anywhere from a Cq of 35 (Vandesompele) to about 43.18 (Bustin-Nolan-Hands), and, in theory, (when 10^10 amplicons are generated at threshold) 1 copy could appear as early as 33.219 cycles (alluded to in the Bustin A-Z Book) at a reasonable threshold; on a very good machine I might add.

I have identified a Cq center of about 37.18 (~38.15 on the high end) to be the signature (predicted Cq) of a single-copy reaction (on the certain machine I use) for reactions that are 100% efficient - but I use the exact same master mix and hydrolysis-probe based qPCR only, every time. This Cq value can "wobble" several cycles (nil reaction analysis) either direction due to Poisson noise of single copy reactions at 100% efficiency.

Droplet digital PCR may be better at helping you determining gene copy number. But it may not be affordable or available - and may bring along with it its own unique cadre of problems (dMIQE is here and being developed for that).

qPCR is great as an idea - but its resolution at the single copy level is still dubious in most cases unless performed with "Poisson noise" (and nil reaction analysis) in the forefront of one's mind when performing any of the possible subsequent calculations.

You can use the nil reaction calculation (Poisson distribution) to identify single-copy reactions, but, (for good resolution) that usually requires running up to 48 replicates per sample suspected of being single copy by the time the reactions are assembled.

This is the basis of droplet digital PCR. 16 reactions per sample is the bare minimum to establish this. Where anywhere from 4 to 10 nil (no signal) reactions and 6 to 12 positive reactions out of 16 total reactions indicates a single copy of something in that sample reaction analysis. When these conditions have been attained, the arithmetic average of the Cq value obtained in the positive reactions establishes the y-intercept on any standard curve for any target without the need for known-copy standards. The y-intercept is the Cq at which one copy of target appears. But this also means that you would have to run at least 16 reactions for every sample you expect to house a single copy by the time it is assembled. Enough rambling ...

Here is an interesting Excel toy I made that you can play around with when exploring the Poisson noise idea...

I am interested in calculating copy number changes with reference to treatment modalities if at all it happens in vivo. These posts, reassured my understanding of the calculating copy numbers using qRT-PCR (quantitative real time PCR done with reverse transcritpase generated cDNA from RNA) is not valid. Nevertheless, the question remains what is the correct method for quantifying gene copy numbers?

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The initial confusion here was using the term "RT-PCR" which is conventional, gel-visualized reverse transcription PCR which has nothing to do with qPCR and/or reverse transcription quantitative PCR (RT-qPCR). Nadine's point is that qPCR and RT-qPCR can both be called "qPCR." Also, "gene copy number" can be misleading as well - especially since CNV (copy number variance) is another kind of polymorphism dealing with copies of a gene in gDNA only.

If what you're looking for is "transcript copy number," you can indeed try to estimate that using RT-qPCR also; if you have an absolute standard curve material that you trust has been quantified expertly at the outset. You would reconcile your absolute standard curve for a target with the relative dilution standard curve for that same target (but standards made of sample material) the same way as described above for qPCR with gDNA gene copies...

Semantics, abbreviations and misinterpretations confuses a lot of things most of the time. By the way have you heard that MOD is good for HOJF and BBNB but only when CCND is not present during JBE? Everyone knows what that means 100% of the time right? ;]

Jack, one more note to reduce further confusion: qPCR is not equal to real-time PCR. There are many different qPCR methods (competitive , limitting dilution, ...); real-time PCR is just one special case of a qPCR.

PS: I did not say that you used it incorrectly. I just gave an additional not to clarify :)

:D:D:D

Jack, you rule man