%0 Journal Article %T Validation of a primer optimisation matrix to improve the performance of reverse transcription ¨C quantitative real-time PCR assays %A Thomas Mikeska %A Alexander Dobrovic %J BMC Research Notes %D 2009 %I BioMed Central %R 10.1186/1756-0500-2-112 %X 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.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.The need for gene expression platforms that can simultaneously assay multiple gene transcripts from routine pathological biopsies is increasing. Microarrays are not the ideal solution as they suffer from poor dynamic range and the need for high quality material. In particular, high quality material is often not available such as when formalin-fixed paraffin-embedded (FFPE) sections are being used.Reverse transcription ¨C quantitative real-time PCR (RT-qPCR) is the preferred method to quantify RNA when a wide dynamic range and high signal to noise ratios are desired. RT-qPCR involving a multiple gene transcript panel needs to be custom-designed to provide the most flexibility in gene transcript selection.A robust, reproducible, and optimised RT-qPCR assay is one of the key requirements for reliable gene expression data. Running an RT-qPCR under suboptimal conditions results in higher variability between replicates [1] and may also result in decreased sensitivity [2]. Unfortunately, RT-qPCR optimisation has become disregarded by many research groups in the era of high throughput analysis and rapid data reporting [2].In order to set up multiple RT-qPCR assays for gene expression profiling it is necessary to run them at common thermal cycling parameters, %U http://www.biomedcentral.com/1756-0500/2/112