Reverse transcription followed by quantitative polymerase chain reaction analysis, or qRT-PCR, is an extremely sensitive, cost-effective method for quantifying gene transcripts from plant cells. The availability of nonspecific double-stranded DNA (dsDNA) binding fluorophors, such as SYBR Green, and 384-well-plate real-time PCR machines that can measure fluorescence at the end of each PCR cycle make it possible to perform qRT-PCR on hundreds of genes or treatments in parallel. This has facilitated the comparative analysis of all members of large gene families, such as transcription factor genes (Czechowski et al., 2004Go). Given the relatively low cost of PCR reagents, and the precision, sensitivity, flexibility, and scalability of qRT-PCR, it is little wonder that thousands of research labs around the world have embraced it as the method of choice for measuring transcript levels. However, despite its popularity, we continue to see systematic errors in the application of methods for qRT-PCR analysis, which can compromise the interpretation of results. The letter to the editor by Gutierrez et al. in this issue highlights one of many common sources of error, namely, the inappropriate choice of reference genes for normalizing transcript levels of test genes prior to comparative analysis of different biological samples. The following are 11 golden rules of qRT-PCR that, when observed, should ensure reproducible and accurate measurements of transcript abundance in plant and other cells. These rules are for relative quantification of RNA using two-step RT-PCR (where the product of a single RT reaction is used as template in multiple PCR reactions), SYBR Green to detect gene-specific PCR products, and reference genes for normalizing transcript levels of test genes before comparing samples. Further details can be found elsewhere (Czechowski et al., 2004Go, 2005Go). Most of these rules also apply to relative quantification methods that employ sequence-specific fluorescent probes, such as TaqMan probes, and to absolute quantification methods.
Full Text