Publications & Reports

Validation of a primer optimisation matrix to improve the performance of reverse transcription - quantitative real-time PCR assays.

Thomas Mikeska, Alexander Dobrovic
Molecular Pathology Research and Development Laboratory, Department of Pathology, Peter MacCallum Cancer Centre, Locked Bag 1, A'Beckett Street, Melbourne, Victoria 8006, Australia. [email protected]


BACKGROUND: The development of reverse transcription - quantitative real-time PCR (RT-qPCR) platforms that can simultaneously measure the expression of multiple genes is dependent on robust assays that function under identical thermal cycling conditions. The use of a primer optimisation matrix to improve the performance of RT-qPCR assays is often recommended in technical bulletins and manuals. Despite this recommendation, a comprehensive introduction to and evaluation of this approach has been absent from the literature. Therefore, we investigated the impact of varying the primer concentration, leaving all the other reaction conditions unchanged, on a large number of RT-qPCR assays which in this case were designed to be monitored using hydrolysis probes from the Universal Probe Library (UPL) library. FINDINGS: Optimal RT-qPCR conditions were determined for 60 newly designed assays. The calculated Cq (Quantification Cycle) difference, non-specific amplification, and primer dimer formation for a given assay was often dependent on primer concentration. The chosen conditions were further optimised by testing two different probe concentrations. Varying the primer concentrations had a greater effect on the performance of a RT-qPCR assay than varying the probe concentrations. CONCLUSION: Primer optimisation is important for improving the performance of RT-qPCR assays monitored by UPL probes. This approach would also be beneficial to the performance of other RT-qPCR assays such as those using other types of probes or fluorescent intercalating dyes.


  • Journal: BMC Research Notes
  • Published: 23/06/2009
  • Volume: 2
  • Pagination: 112