Relative expression software tool (REST©) for group-wise comparison and statistical analysis of relative expression results in real-time PCR -: art. no. e36

被引:6287
作者
Pfaffl, MW
Horgan, GW
Dempfle, L
机构
[1] Tech Univ Munich, Inst Physiol, Life Sci Zentrum Weihenstephan, D-85350 Freising Weihenstephan, Germany
[2] Rowett Res Inst, Aberdeen AB21 9SB, Scotland
[3] Tech Univ Munich, Dept Anim Sci, Ctr Life & Food Sci, D-85350 Freising Weihenstephan, Germany
关键词
D O I
10.1093/nar/30.9.e36
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Real-time reverse transcription followed by polymerase chain reaction (RT-PCR) is the most suitable method for the detection and quantification of mRNA. It offers high sensitivity, good reproducibility and a wide quantification range. Today, relative expression is increasingly used, where the expression of a target gene is standardised by a non-regulated reference gene. Several mathematical algorithms have been developed to compute an expression ratio, based on real-time PCR efficiency and the crossing point deviation of an unknown sample versus a control. But all published equations and available models for the calculation of relative expression ratio allow only for the determination of a single transcription difference between one control and one sample. Therefore a new software tool was established, named REST(C) (relative expression software tool), which compares two groups, with up to 16 data points in a sample and 16 in a control group, for reference and up to four target genes. The mathematical model used is based on the PCR efficiencies and the mean crossing point deviation between the sample and control group. Subsequently, the expression ratio results of the four investigated transcripts are tested for significance by a randomisation test. Herein, development and application of REST(C) is explained and the usefulness of relative expression in real-time PCR using REST(C) is discussed. The latest software version of REST(C) and examples for the correct use can be downloaded at http://www.wzw.tum.de/gene-quantification/.
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页数:10
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