Of all the methods used for gene expression studies, RT-qPCR is still the gold standard for accurate quantification of transcripts. The accuracy of RT-qPCR, as well as its accessibility, also makes it the logical next step in biomarker discovery studies following a broader RNA-seq survey of the messenger and/or noncoding RNAs in a system.
What makes RT-qPCR so reliable is the implementation of stringent controls. The most common RT-qPCR controls are listed in the table below:
|No-template control||Detects reagent or equipment contamination – confirms positive results|
|No-RT / gDNA contamination control||Detects signals generated from gDNA – confirms transcript-specific signal|
|No-amplification control||Detects background fluorescence generated by degraded dual-labeled probes|
|Positive / internal control||Detects inhibitors or malfunction – confirms reagents and equipment are working|
|References genes / quantification calibrators||Not strictly “controls,” but used in relative or absolute quantification|
Recently, QIAGEN’s Dirk Schacht presented a comprehensive overview of novel in-process monitoring tools for improving the accuracy and reproducibility of RT-qPCR results. Check out his slides at SlideShare to learn how you can improve your RT-qPCR experiments: