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Here is the thing. I am using a method, called TU-Tagging, to isolate cell type specific RNA. You can find more about the method here:

To explain it very briefly, there is an enzyme called UPRT (Uracil Phosphoribosyltransferase) which is expressed in Toxoplasma gondii. Under normal circumstances UPRT creates UMP from host cells' uracil and this UMP incorporated in RNA. However, they found that this enzyme cannot distinguish uracil and uracil analog 4-Thiouracil (Basically has thio on 4th position of the uracil). So, when 4-TU provided externally, UPRT incorporates 4-TU into RNA and you get thio-RNA. Then with basic biotinylation and streptaividin isolation you can get thio-RNA from your total RNA isolate. (Of course UPRT should be put to specific cell types of your interest)

Anyway, after the explanation (maybe it was unnecessary though) here is my question.

After I isolate my so called specific RNA, I check the purity by qPCR by using cell type specific markers. I do not have a reference gene. The only thing I am interested in is the presence or absence of markers (and also the fold change of course). Now, I have some data but I do not know how to present them (There is nobody in my lab experienced with qPCR and my experience is just so limited).

Do you have an idea how I can overcome this issue? I looked into some calculations but most of them are needed for reference genes or some other stuff. The only thing that I have is cycle numbers and my primers' efficiency. Do you think I can do something with these inputs? (I know that cycle numbers mean nothing in a plot, so I do not want to put cycle numbers basically.)

Thank you for reading it. Any help/idea would be very appreciated. I am so desperate. Thank you.

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Great/clear/easy to follow explanation of the TU-tagging technique. However, I am confused as to what you are really asking for. You isolated a cell specific RNA and you want to check the "purity" of your isolate? What do you mean by this? – MeLikeyCode May 19 '14 at 22:16
Thanks. So imagine like, I have a fly line which has the UPRT in their neurons. When I do the TU-Tagging experiment, in theory I just isolate RNA from neurons. So, I should not see any glia specific markers lets say. So, with qPCR I am checking cell type specific markers in order to see my RNA is clean or contaminated by other cells. However, I do not know how to plot these qPCR results. I just have cycle numbers and do not know how to present them. – golgicik May 19 '14 at 22:22
Does your qPCR software not provide you with the progressive graphs where you can see each sample crossing the threshold? That might be a nice picture to show. – Armatus May 19 '14 at 23:13

1 Answer 1

up vote 4 down vote accepted

OK, let us start from the beginning. We know what makes one cell type different from another cell type is its expression - i.e. what genes are actually being transcribed into RNA. Therefore, there should be certain RNA in one cell type that should not exit in another cell type. If you isolate RNA from a certain cell type, say a neuron and you want to show that your sample RNA contains only neuronal RNA, than you have to prove 2 things:

  1. That your sample contains certain RNA sequences that are known to be in neurons
  2. That your sample does NOT contain certain RNA sequences that are known NOT to be in neurons

There are several lab procedures for identifying the presence/absence of certain RNA sequences in a sample, your chosen technique is qPCR. Here is a brief explanation of how qPCR works.

You put your RNA sample along with a sequence specific primer in the qPCR machine. The primer will bind to a specific sequence and then that strand will be replicated. This will keep on repeating, cycle after cycle. So if you start with 1 sequence of say sequenceA, after cycle 1, you will end up with 2, then 4, then 8 and so on.

Anyways, if your goal is to use qPCR to prove your RNA sample comes from a neuron then you must find some sequences that are known to be specific to neurons. Then find primers for these sequences. Then use these primers to amplify some RNA from your sample. If you get amplification, then you must have had that sequence in your RNA sample. To further support yourself, you may also want to look up a few sequences that are known NOT to be expressed in neurons and using the same principle prove that these sequences are NOT in your sample.

The above will give you qualitative data, it will simply tell you if a certain sequence exits or does not exist in your RNA sample. Since you are only interested in the presence or absence of markers, this should be sufficient. Howver, if you would like to quantify your data, i.e. find out how much a certain sequence is expressed then read on.

You can also get quantitative data from qPCR (after all qPCR stands for quantitative PCR). The number of copies of an RNA sequence after a certain number of cycles is proportional to the initial number of copies of that sequence in your sample. In other words, if your initial RNA sample has a lot of sequenceA and a little sequenceB, then at any cycle, you should see more sequenceA.

We can take advantage of this relationship. There are two general methods you can use to quantify your results. One is called Absolute quantification and the other Relative quantification.

The idea behind absolute quantification is that you run two qPCRs. In one, you do your RNA sample. In the second, you run a standard sample, for which a standard curve is available. You can then compare your RNA sample results with the standard's results to get an idea of the number of copies in your sample.

The idea behind relative quantification is that you compare the qPCR results for your sequence of interest with the qPCR results of a refrence gene. This will only give you an idea of how many times more or less your sequence of interest if expressed than the reference gene. Since you do not have a refrence gene you cannot use this method, but you can use the absolute quantification method explained in the paragraph above!

Here are very useful links on quantifying using qPCR:

Let me know if you need further clarifications.

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Hey thanks! As you told also I am just interested in to show presence and absence. I already did lots of qPCR experiments with neuronal and glial primers and have the data as cycle number. So I just want to show them but I can not show the cycle number, I need to express it as some numbers which will show fold change for example. I need to plot the data. So can I just assume that every cycle will double my cDNA and could use an equation like this: 2^-Ct ? Or it is not the way? – golgicik May 20 '14 at 8:57
if "C" is your initial concentration, and "t" is the number of cycles, then yes your equation will tell you the fold change. Sorry for the late response, haven't been on here for a while. – MeLikeyCode May 30 '14 at 21:15

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