A Brief RT-qPCR “Field Guide” for MIQE Adherence
News Dec 09, 2013
Scientists and journals have been slow to adopt the Minimum Information for the Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines that were established in 2009 to bolster the reliability of real-time PCR (qPCR) and reverse transcription qPCR (RT-qPCR) data. To help boost adoption, Bio-Rad scientists published a brief and practical guide that concisely summarizes the key steps required to produce high-quality, reproducible data for labs conducting RT-qPCR experiments.
“This paper makes a clear and persuasive case for why it is so important to implement the MIQE guidelines by taking each of the major parameters and highlighting the consequences of not implementing quality control procedures,” said Stephen Bustin, one of the scientists who developed the MIQE guidelines.
In the Journal of Molecular Microbiology and Biotechnology article, Bio-Rad’s Sean Taylor and Eli Mrkusich noted that since 2010, only 5% of papers presenting qPCR data have applied the 2009 guidelines. The adoption rate appears to be increasing — a recent MIQE adoption survey in Nature Methods showed a rate of 11% in 2013 — but almost nine out of ten papers published today do not provide the minimum data necessary to be critically evaluated and could therefore include misleading results and conclusions.
“We believe the reason MIQE is not being widely adopted is primarily that techniques used by labs and even by individual lab members are based on teachings from senior scientists or students who have learned from previous labs,” said Taylor. “This has resulted in wide variability in approaches to designing and performing qPCR experiments between and even within labs that have passed from scientist to scientist without critical examination.”
To encourage adoption of the guidelines, Bio-Rad’s new paper uses concrete examples that demonstrate both good and bad practices for RT-qPCR, from experimental design and sample handling to primer validation and reference gene selection. For example, many researchers do not validate their primers because the sequences were sourced from the literature, obtained from other lab members, or from vendors as off-the-shelf assays that may not have been wet-lab validated. This omission is problematic, because the use of unvalidated primers can lead to gene expression data that at best give good results for the target gene and at worst can lead to “incorrect and even opposite conclusions” and sometimes even yield data for the wrong target. The authors detail precisely how primer validation should be performed to avoid these problems.
Bio-Rad has been at the forefront of promoting good PCR practices since 1999 when the company introduced its first qPCR instrument. In 2010, Taylor published an article in the journal Methods outlining the key steps in RT-qPCR data production that “lead to high-quality, reproducible, and publishable data.” More recently Taylor teamed up with researchers at the INRS-Institut Armand-Frappier in Quebec to demonstrate the consequences of choosing the wrong reference gene in the journal Molecular Biotechnology.
The Journal of Molecular Microbiology and Biotechnology article extends Bio-Rad’s commitment to MIQE guidelines.
“This paper continues the exemplary support that Bio-Rad has given, from the very beginning, to the MIQE initiative,” said Bustin. “Bio-Rad has arguably done more than any other real-time PCR company to support, popularize, and help implement MIQE.”
“For the many researchers in highly competitive fields where turnaround time from experiments to publication is critical, this article is a must-read to ensure that the data from this very sensitive assay give results that reflect the true biology of the tested systems,” said Taylor.
The paper can be accessed below . You can also watch Taylor review the paper via video at http://bit.ly/JMMB_video.
Previous work by the International Multiple Sclerosis Genetics Consortium (IMSGC) has identified 233 genetic risk variants. However, these only account for about 20% of overall disease risk, with the remaining genetic culprits proving elusive. A new study has tracked down four of these hard-to-find genes.READ MORE