Genomics Research Core

Considerations for Design and analysis of Realtime PCR projects

Realtime PCR is a relative quantification technology. Every study must have at least one endogenous control gene to normalize within samples and a baseline or calibrator sample to which all other samples are compared. It is critical that expression levels of the endogenous control gene remain constant throughout the experimental conditions of the project.

  • There is no single gene that will serve this purpose for all possible biological specimens and treatment conditions.
  • Literature review for relevant genes and the use of more than one endogenous control assay are highly recommended. See Vandesompele et. al 2002.

Primer efficiencies for genes of interest and endogenous controls must be equivalent. A primer efficiency test must be performed on all custom assays.

  • Primer efficiency is determined by using all PCR assays on serial dilutions of a single cDNA sample.
  • The slope of Ct vs input cDNA must be within +/- 10% for all assays.

Calibrator samples can be one of the control samples, a pool of all samples, or an altogether unrelated sample such as one of the commercially available universal references.

  • All genes to be assayed must be expressed at measurable levels in the calibrator sample.
  • If assay runs are to be performed repeatedly at different times on different cohorts of samples, calibrator sample must be of sufficient quantity that an aliquot can be run from reverse transcription through PCR with each set of assays.

Real time PCR results are expressed as Ct (cycle threshold), dCt (delta Ct) and ddCt (delta delta Ct). Cycle threshold (Ct) is the cycle number at which the fluorescence for the reaction well crosses the threshold value.

  • The threshold is a user definable parameter.
  • Delta Ct is the difference in Ct between the gene of interest (goi) and the endogenous control (end ctl) for a given sample. dCt = Ct(goi) - Ct(end.ctl)
  • Delta delta Ct is the difference between the dCt of a particular gene for an experimental sample and the dCt of that same gene for the calibrator sample. ddCt = dCt(exp) - dCt(cal) Ct is on a log scale, base 2.
  • To find the linear fold change in gene expression between the experimental and calibrator sample the formula is: 2(-ddCt)