When we want to assess the gene expression assay by Real Time PCR, there are mainly Taqman gene expression assay or SYBR green gene expression method in which we need to set up the primer set by ourselves. By SYBR method, again there are Standard curve or delta delta Ct methods for detection of gene expression. Is there anyone who has had experience in comparing these two methods? Can you suggest which of the Standard curve or delta delta Ct method better?
I am planning to use two Endogenous controls but I don't have any positive control for this experiment. Please help me.
I have mainly been using standard curves for determining primer efficiencies in order to get the most accurate gene expression values as possible. During each cycle of the PCR reaction the efficiency might be lower or higher than the standard of 2 (indicating a doubling of the template amount per each cycle). Your efficiency will have a value according to the slope in the standard curve for each set of primers. I.e. this means that instead of the simple delta delta ct method;
Expr = 2^(Ct,GOI(control)-Ct,GOI(sample)) / 2^(Ct,norm(control)-Ct,norm(sample))
you will be using this instead:
Expr = E(GOI)^(Ct,GOI(control)-Ct,GOI(sample)) / E(norm)^(Ct,norm(control)-Ct,norm(sample)
where E(GOI) and E(norm) indicates the PCR efficiencies as determined from the standard curve experiments.
See Pfaffl, PMID: 11328886..
if you have a limited amount of sample, is better the delta delta Ct method, as these method required less number of reactions. Then you should calculate the efficiency of the each individual reaction using the data derived from the amplification curve and estimate the efficiency of amplification of each particular gene and substitute in the formula of delta delta Ct method the value of the efficiency.
you could use for calculation of efficiency a software like LinReg and for delta delta Ct the software REST. A description, papers and a link to download the software is available in http://rest.gene-quantification.info/
It depends on your application-do you need Relative or Absolute quantification. If we want to compare gene expression levels across samples or treatments etc, we are interested only in relative quantification that is we can set one sample Ct as control and compare all other samples to that using delta delta Ct . If your experiment requires the exact AMOUNT of a particular RNA/transcript for example ratio between alternately spliced forms or amount of viral load in samples then standard curve needs to be generated for absolute quantification. Good luck!
I would always go for a standard curve method based upon diluted standards (eg plasmid ) of known concentrations with both the target gene and a reference (housekeeping) gene measured. The simple reason for this is that real copy numbers give you hard data which you can relate to your input. If I put the cDNA from the equivalent of 100,000 cells and did a PCR for a known highly expressed gene (eg ribosomal RNA) and got 100 copies, then I have reason to question my sample or cDNA. If you generate a Ct of eg 39 what does it tell you? The difference between a Ct of 45 and a Ct of 50 is the same as that between Ct 30 and Ct 35, but in terms of copy numbers a Ct of 50 in most instances is less than single copies. delta Cts and delta-delta Cts are fast , easy and lazy ways of getting data. When analysing someone else's data, unless you know the range of Cts from which the delta Cts were obtained it is difficult to determine whether the data is truly within the range of believable results.(someone once presented me a graph of a 30 fold difference based a upon a Ct difference of 50-55 cycles ). A value of 1000 copies of x per million copies of ribosomal RNA is a hard number.These real values can then be used to determine the fold change in expression. It also makes direct comparison between experiments more realistic.
Remember: High impact factor = High input effort
Good thread and Dr. Julio‘s help me most as cited below
if you have a limited amount of sample, is better the delta delta Ct method, as these method required less number of reactions. Then you should calculate the efficiency of the each individual reaction using the data derived from the amplification curve and estimate the efficiency of amplification of each particular gene and substitute in the formula of delta delta Ct method the value of the efficiency.
you could use for calculation of efficiency a software like LinReg and for delta delta Ct the software REST. A description, papers and a link to download the software is available in http://rest.gene-quantification.info/
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