Check out our SlideShare to gain more “control” over your RT-qPCR results


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:

Control Purpose
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:

Want to join the live presentation and ask your questions at the Q&A? The next live session will be on September 6, at 9:30 a.m. EDT. Sign up for free!
Ali Bierly

Ali Bierly, PhD is a Global Market Manager in Translational Sciences at QIAGEN, and has written on a number of scientific topics in the biotech industry as the author of QIAGEN's Reviews Online. She received her PhD from Cornell University in 2009, studying the immune response to a protozoan parasite, Toxoplasma gondii. Ali has a keen interest in the emerging importance of microRNA and other circulating nucleic acids as biomarkers for disease.

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