Dear Fahimeh

• In short yes: The principal  reason for this is that a standard curve is designed to let you know how efficiently your primers work. This is required for calculation of relative expression
• The most popular method for calculating relative expression is the so called Delta Delta Ct or livak method: That assumes a perfect doubling during the exponential phase of amplification and for that to apply and render your relative expression value(s) valid the efficiency of your primer must be ideally 95% to 105%) or at the very least > 80% if you are dealing with orders of magnitude expression difference rather than for example 1-2 fold in crease in expression
• Find attached the original Delta Delta Ct paper by Livak explaining the rationale behind the method
• Alternatively, if your primer efficiencies fall between 80% and 90% you also need to know the exact value in order to factor this in to your  relative expression calculation using something called the pfaffl method
• Find attached the original paper by Pfaffl and a chapter from a book explaining his method
• Finally, Primer efficiency deduced by a standard curve is effected by primer efficacy in turn rooted in optimal primer design; Secondary structure in your target affected by high GC content ( > 70%) or consecutive runs of G/C residues ( > 4 in any given loci); High AT content, both reducing replication efficiency; length of amplicon (~ 100bp is best for maximal amplification efficiency); copy number of your target; whether your primers are 3' biased ( RNA degrades from the 5' end and thus primers situated within 1kb of the 3' terminus of your transcript, leading to higher and more accurate representation of those regions of mRNA in your cDNA library, especially if your RNA is visibly degraded) and purity of your RNA and thus efficiency of cDNA synthesis
• Thus, best practice would indicate that you do not just perform a standard curve for each new set of primers but you replicate this standard curve for each new biological replicate, i.e. cDNA sample, although most person (s) in reality tend to just calculate efficiency for new primer pairs; especially if your starting RNA has a 260/280 > 1.7 (low protein contamination including potentially RNASes)  and a 260/230 ratio > 1.0 (implying low salt contamination and in particular GITC bleeding through from the lysis buffer which will inhibit reverse transcriptases); and also if RNA integrity has been verified by agarose gel or better still Agilent Biochip 

Dear Fahimeh

• In short yes: The principal  reason for this is that a standard curve is designed to let you know how efficiently your primers work. This is required for calculation of relative expression
• The most popular method for calculating relative expression is the so called Delta Delta Ct or livak method: That assumes a perfect doubling during the exponential phase of amplification and for that to apply and render your relative expression value(s) valid the efficiency of your primer must be ideally 95% to 105%) or at the very least > 80% if you are dealing with orders of magnitude expression difference rather than for example 1-2 fold in crease in expression
• Find attached the original Delta Delta Ct paper by Livak explaining the rationale behind the method
• Alternatively, if your primer efficiencies fall between 80% and 90% you also need to know the exact value in order to factor this in to your  relative expression calculation using something called the pfaffl method
• Find attached the original paper by Pfaffl and a chapter from a book explaining his method
• Finally, Primer efficiency deduced by a standard curve is effected by primer efficacy in turn rooted in optimal primer design; Secondary structure in your target affected by high GC content ( > 70%) or consecutive runs of G/C residues ( > 4 in any given loci); High AT content, both reducing replication efficiency; length of amplicon (~ 100bp is best for maximal amplification efficiency); copy number of your target; whether your primers are 3' biased ( RNA degrades from the 5' end and thus primers situated within 1kb of the 3' terminus of your transcript, leading to higher and more accurate representation of those regions of mRNA in your cDNA library, especially if your RNA is visibly degraded) and purity of your RNA and thus efficiency of cDNA synthesis
• Thus, best practice would indicate that you do not just perform a standard curve for each new set of primers but you replicate this standard curve for each new biological replicate, i.e. cDNA sample, although most person (s) in reality tend to just calculate efficiency for new primer pairs; especially if your starting RNA has a 260/280 > 1.7 (low protein contamination including potentially RNASes)  and a 260/230 ratio > 1.0 (implying low salt contamination and in particular GITC bleeding through from the lysis buffer which will inhibit reverse transcriptases); and also if RNA integrity has been verified by agarose gel or better still Agilent Biochip 

Mr. Stuart Hall, Thank you very much for your detailed explanation

Dear Fahimeh,

When using the standard curve method, the quantity of each experimental sample is first determined using a standard curve, and is then expressed relative to a calibrator sample.

In order to use this quantification method, prepare five (5) 2-fold, 5-fold, or 10-fold serial dilutions of cDNA template known to express the gene of interest in high abundance. Use each serial dilution in separate real-time reactions, and determine their threshold cycle values.

In a base-10 semi-logarithmic graph, plot the threshold cycle versus the dilution factor and fit the data to a straight line. Confirm that the correlation coefficient (R2) for the line is 0.99 or greater.

This plot is then used as a standard or calibration curve for extrapolating relative expression level information for the same gene of interest in unknown experimental samples. The relative quantification calibration curve result for the gene of interest is normalized to that of a housekeeping gene in the same sample, and then the normalized numbers are compared between samples to get a fold change in expression.

A standard or calibration curve must be generated separately for each gene of interest and each housekeeping gene.

Brijesh, thank u

Fahimeh:

• As indicated by the above discussion thread, in its broadest context, standard curves provide 2 utilities:
• In the first, as detailed in my first answer, they provide primer/target reaction efficiency. This is required for relative gene expression using the livak or Pfaffl method of gene expression relative to an untreated control sample:
• http://blog.mcbryan.co.uk/2013/06/qpcr-normalisation.html
• https://www.ncbi.nlm.nih.gov/pubmed/11846609
• For relative expression to hold true with this method a co efficient of '2' is used to calculate expression as detailed in the worked example attached and the links provided. This presupposes perfect doubling (x2) per cycle; in other words 100% efficiency
• For this to be valid the standard curve must yield efficiency values > 85%
• Alternatively, if efficiency values are ~ 80% a correction factor must be introduced. This is known as the pfaffl method of relative gene expression analysis:
• http://www.bio-rad.com/en-uk/applications-technologies/real-time-pcr-experimental-design
• See also a detailed explanation attached
• Finally, in this context the standard curve provided the optimal titrant for cDNA; that is the dilution of cDNA yielding a Ct value between 20 and 30:
• For a low copy number gene in my experience it is typical to require neat or a 1:2 or 1:4 dilution of cDNA from a standard curve based on a 1:2 serial dilution of cDNA. In contrast from a 1:10 dilution of cDNA a housekeeper might yield Ct values in the same interval between 1:10 to 1:100 dilution as will other high copy number GOI's
• Note: For practical purposes it is often necessary to use a different dilution of your cDNA for a housekeeping gene compared to a low copy number GOI: In these instances the important parameter is keeping your respective Ct values between 20-30 ideally or at the very least trying to ensure that your GOI Ct does not exceed 35 cycles
• The other principal use of a standard curve is to ascertain actual relative gene expression. This method is used instead of the Livak and Pfaffl methods described