Hi,

I uses taqman chemistry for qPCR. But the standard curve generation principle is same everywhere i guess. Dilute the cDNA into at least five points. 1st your conc. cDNA and tehn dilute ten times per point i.e

1, 1/10, 1/100, 1/1000 and 1/10000. Use the gene primer you are going to use for your actual experiments. The cDNA samples can be a control cDNA or if you have enough cDNA which you plan to use in your main experiment, you can use that.

Run the cDNA s of diff. dilutions in your qPCR set up, get the Ct values and you can plot the Ct values in Y axis with dilutions in the X axis. 

You can perform duplicates of each dilution and see for the consistent Ct number. The Best Ct values (best dilution) should fall in the range of 18-24 approx. Beyond 30 Ct, its unreliable as high Ct is low copy number.

Just google some standard curve protocols and you can the see the types of plotting from different sample types.

Hi,

I uses taqman chemistry for qPCR. But the standard curve generation principle is same everywhere i guess. Dilute the cDNA into at least five points. 1st your conc. cDNA and tehn dilute ten times per point i.e

1, 1/10, 1/100, 1/1000 and 1/10000. Use the gene primer you are going to use for your actual experiments. The cDNA samples can be a control cDNA or if you have enough cDNA which you plan to use in your main experiment, you can use that.

Run the cDNA s of diff. dilutions in your qPCR set up, get the Ct values and you can plot the Ct values in Y axis with dilutions in the X axis. 

You can perform duplicates of each dilution and see for the consistent Ct number. The Best Ct values (best dilution) should fall in the range of 18-24 approx. Beyond 30 Ct, its unreliable as high Ct is low copy number.

Just google some standard curve protocols and you can the see the types of plotting from different sample types.

If you use cDNA I suppose that you want to quantify transcripts. If these are mRNAs, it is common practice to design primers that are intron-spanning to avoid an amplification of contaminating genomic DNA. If this is the case for your assay, then using gDNA is not a good idea (either you won't get any products or the products will be considerably (kilobases!) longer and thus the amplification efficiency may not be good enough).

I suggest to generate a standard with a conventional PCR, possibly using primers that will produce a longer product containing the binding sites for the qPCR primers. This procuct can then be purified and quantified and diluted to the desired concentrations.

But take care: do all this in a different lab (really, the best is to do it in a different floor or building)! Otherwise there is a high risk of contaminations. Only take the working-dilution of the standard to the lab where you perform the qPCRs.

Hi

It is always better to use cDNA generated from pure RNA (provided by many companies species specific) to generate your ST curve. 

Usually the primers in QPCR span an interon and hence you will the product size is much larger if you use gDNA and this design is used to detect any genomic DNA contamination. 

I would recommend to use cDNA generated from a well known high quality RNA and to perform a serial dilution for you ST curve.

Wishes,

Bassem

You need to use cDNA as a template to generate the standard curve.

If you want to quantify cDNA fragments through qPCR, genomic DNA is of no (or little) use for starndard curve. As other have said, you should use a previouslly known DNA fragment (synthetic or purified by you), or the same cDNA samples you want to quantify.  Now... If we are speaking about relative quantification (i.e., relative to a set of reference genes), the calibration curve MUST be done from you cDNA samples (we have used a pool of all of the samples in the study at a time). This, because you need to determine the efficiency of the reaction, which is dependent on the chemistry used, the machine, the nature of the template, and the primers/probes used. Hence, you need to determine how your PCR perform in the specific combination of parameters you will use to study your samples. 

Hi Maryam

Using gDNA as template in a standard PCR is the first thing I do with qPCR primers, in order to check that those primers amplify one single band with the correct size (in the case the primers have not been designed between two different exons). If they don´t amplify one single band or if they don´t amplify at all, then you should readjust the PCR conditions. After this first inspection, then I move to cDNA, trying the definitive profile condition. This way you wont regret loosing cDNA with a pair of bad primers. Putting this aside, there are different ways in which you could do standard curves for calculating efficiency of your primers: a) by using serial dilutions of your template cDNA (if you don´t do the first inspection at least make sure you amplify a band from that cDNA), b) using serial dilutions of a plasmid which may hold the sequence you are amplifying (e.g. cloned transcript), or c) clone the PCR product in pGEMT (or other) plasmid and use it in a serial dilution. As others may have said, using 1, 1/10, 1/100, 1/1000 and 1/10000 dilutions usually work fine.

hope it works

cheers

I usually test the primers in a qPCR reaction with cDNA. I then check for a single melt curve peak and single band in the gel I ran afterwards. I then use that reaction as a starting point for serial dilutions to generate a standard curve (I haven't had the need to purify the amplicon before doing the serial dilution. I haven't seen any differences in the calculated efficiency when I do).

I've also used synthetic oligos as a template, as suggested by Jo Vandesompele (https://molbiohut.wordpress.com/2012/04/06/quotes-from-the-internet-qpcr-and-efficiency-curves/#comment-453). This works like a charm, but it's more expensive than what I mentioned before.

Some people clone the amplicon, as suggested by José Tomás Matus, and then do the serial dilution. I've done that, but I always linearize the plasmid before the dilutions

good!

1) make a dilution series of a standard (it is not important what dilution factors you use; you must only know the factors used. It is most simple to create serial dilutions with a constant factor between subsequent dilutions, e.g. a 1:10 or a 1:2 dilution series). To get a first impression, I would recommend to start with a 1:10 series with 10-15 dilution steps. After having the results from this experiment you will be able to define a resonable concentration range range and go for higher resulution series (1:2 for instance) to record the actual series.

2) plot the ct-values against the logarithm of the dilution factors (DF). In the useable concentration range there should be a linear relationship between dt and log(DF).

3) the standard curve is the regression line through these points. You can use the regression line to determine the concentration of unknown samples from their ct-values, *relative* to the standard (if you know the concentration of your standard, you can calculate the concentration of the unknown samples).

3b) The slope ("m") of the regression line is related to the amplification efficiency ("e") by e = b^(-1/m) where "b" is the base of the logarithm you used in step 2. The value of e should be close to 2. When it is higher you may have problems with background correction in any other part of the data processing. When it is lower, the PCR conditions may be suboptimal (presence of inhibitors...). A value close to 2 does not exclude the possibility of such problems, but at least it gives no clear indication that problems do exist.