Posts tagged ‘MIQE’
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.
Bio-Rad Laboratories, Inc. announced that it is sponsoring a new version of the MIQE qPCR app. Researchers can use the new version to validate their digital PCR (dPCR) experiments according to the recently published digital MIQE (dMIQE) guidelines (Huggett et al. 2013).
Professors Michael Pfaffl (TU Munich, Weihenstephan, Germany) and Afif Nour (LaSalle Beauvais, France) designed the original MIQE qPCR app to help researchers improve their real-time PCR (qPCR) assay protocols by making it easier to adopt a set of best practices described in an earlier publication: The MIQE guidelines: Minimum information for publication of quantitative real-time PCR experiments (Bustin et al. 2009). Progress bars in the app show the percentage of assay compliance as each item in the MIQE checklist is completed.
“We were pleased to find that the MIQE qPCR app encouraged our customers to follow the new MIQE guidelines,” said Jean-Pierre Dakkak, a laboratory equipment trading company manager.
“Researchers are really eager to learn how this app can make their life easier,” said Dr. Nour. “They report it instills confidence in the validity of every qPCR or dPCR project.”
The new updates include:
- Project-specific checklists — checklists remove unnecessary items; for example, reverse transcription items are irrelevant in DNA research
- Updated references — researchers can stay current with the latest MIQE and dMIQE literature and qPCR symposiums
- Easy export — users can save their projects and share them with colleagues
The MIQE qPCR app runs on the Apple iPhone, iPod touch, and iPad. It has been downloaded more than 6,500 times in 87 countries. To get your copy, visit http://bit.ly/MIQEapp.
Real-Time PCR can be tough. It requires careful planning and much optimization. When it works, you feel great. When it fails…fill in the blank. There are times in our research career when we feel like giving up. Nothing we do seems to yield positive results. Then…along comes a kit. Sure, at first we are wary about using a kit. After all, weren’t we put on this planet to troubleshoot and suffer through tortuous experiments? Alas, many of us quickly overcome that guilt and put our trust and faith in the hands of others. But how do we know that commercially available kits are indeed trustworthy? Perhaps they too will yield erroneous results and lead us down the dark path of non-publishable gobbledygook data. So what do we do? We troubleshoot. We troubleshoot the commercially available kit. The kit that we purchased to avoid troubleshooting! Curses! It’s one thing to troubleshoot my own experimental protocol, but to troubleshoot someone else’s? And one that I paid for nonetheless?
Well, fellow scientists, feel the pain no more. At least not in the world of qPCR. Bio-Rad Laboratories has teamed up with leaders in Real-Time PCR to bring you the most robust, commercial qPCR kit on the market, PrimePCR. Bio-Rad’s PrimePCR™ Assays and Panels have been designed to meet MIQE criteria and incorporate the following key requirements:
- high assay specificity without the use of a probe
- compatibility with standard assay conditions
- avoided secondary structures in primer annealing sites
- avoided SNPs in target regions
- maximized fraction of transcript isoforms being detected
- designed intron-spanning assays whenever possible
- used latest release of genome builds and annotation databases
Moreover, the kits have undergone wet-lab validation at the hands of PCR professionals so you don’t have to waste precious time validating and troubleshooting an assay that you spent money on acquiring.
To learn more about Bio-Rad’s Prime PCR Assays read PrimePCR™ Assays: Meeting the MIQE guidelines by full wet-lab validation.
Bio-Rad Laboratories, Inc. published a case study that shows how real-time PCR (qPCR) can lead to erroneous conclusions if the key steps set out in the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines are not followed. The study examined the effects of RNA sample quality and reference gene stability — two critical components of the MIQE checklist — on gene expression, comparing differences between normal and tumor breast cancer samples.
“These data demonstrate the importance of the MIQE methodology on the final conclusions drawn from qPCR experiments,” said Sean Taylor, lead author of the case study and a Bio-Rad senior field application specialist. “The guidelines were designed to offer a standardized, methodical approach to this highly sensitive technique to ensure that all data published with qPCR are consistent, reproducible, and — most important — a true reflection of the conclusions.”
As a result of its high sensitivity, qPCR has become the gold standard for validating DNA microarray data and is routinely used to determine gene expression differences in a wide variety of samples. However, inadequate sample processing and handling, poor primer design and validation, and inappropriate reference gene selection may result in data being misinterpreted. The MIQE guidelines were published to assist the scientific community to produce consistent, high-quality data from qPCR experiments.
The case study (Bio-Rad Tech Note 6245) used the minichromosome maintenance (MCM) protein MCM7 as a model target gene to investigate the importance of appropriate reference gene selection and RNA sample quality from breast cancer samples as described by MIQE. Following the MIQE guidelines, a significant increase in gene expression of MCM7 was observed between normal and tumor samples when using high-quality and -purity RNA with normalization using stable reference genes. However, inconclusive and even opposite results were obtained when using poor-quality RNA samples and unstable reference genes. These results demonstrate that inappropriate conclusions may be drawn from qPCR data if key steps from the MIQE guidelines are ignored.
Bio-Rad is dedicated to promoting the integrity of qPCR research and offers an array of technology and resources that will help researchers become MIQE compliant. To learn more, read the case study at http://bit.ly/MIQE_case, a published version of the case study in Molecular Biotechnology at http://bit.ly/qPCRPitfalls, or watch the video at http://bit.ly/MIQE_Video.
Following hot on the heals of yesterdays post “A Practical Approach to Assay Design for qPCR“, we are proud to present you with another practical SlideShare on Fast qPCR assay optimization and validation techniques for HTS (high throughput screening). As with the previous presentation, the slide deck can be maximized for easier reading.
Designing good qPCR assays can be fun! Have a look at the presentation below to learn how to overcome difficult assays, designs and optimization while conforming to MIQE guidelines. If the slides are hard to read in their current format, click on the full screen button on the bottom right corner of the slide deck to enlarge.
So you’ve heard all the hoopla about MIQE and how important it is to follow the guidelines when conducting your real time qPCR experiments, (if you haven’t, you better check this out!), but where’s the proof that following MIQE actually makes a difference? After all, qPCR was around for several years before anyone came up with this MIQE stuff. Right? Well…maybe not! As it turns out, qPCR experiments that don’t follow MIQE guidelines can be very difficult for others to reproduce and can even lead to incorrect conclusions in gene expression studies.
In a recently released case study involving breast cancer patients, researchers found that the MIQE guidelines played a central role in obtaining the expected conclusions with a positive control target. The article was written to show readers in a simple, stepwise process how to design a good qPCR experiment that covers the major components of the MIQE guidelines. While each step of the experimental design was found to impact the final conclusion (sample collection, RNA quality and purity and the use of appropriate primers), the most striking result was the impact of reference gene selection on the results. At one extreme, normalization by the commonly used GAPDH and 18S reference genes gave either no significant results of statistically significant data that was opposite to the expected outcome, while other more stable reference genes, (HPRT1 and TBP), gave statistically significant data that supported the conclusions from previously published results with this target.
The study concludes that the application of the MIQE guidelines to qPCR experiments result in reliable, quantifiable and reproducible data. With a growing list of journals that are now requiring the submission of supplemental data supporting adherence to the MIQE guidelines,the publication of qPCR data will become more challenging if they are ignored.
So don’t miss out on significant data. Use MIQE!
To read the case study click here.