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MIQE qPCR and dPCR APP for iPhone, iPad and iPod
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Get help from a special team of experts in
quantitative PCR (qPCR) and digital PCR (dPCR). The MIQE APP helps you in reviewing scientific works and checking your own experiments, when qPCR is involved. Check your project's compliance to MIQE in minutes, have all required references to hand, and follow qPCR events and news.

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Since September 2011 we provide a direct translation of the MIQE guidelines in CHINESE,  JAPANESE,  KOREAN and  RUSSIAN. Please recognize this is an automatic and robotic based translation service, and therefore we provide NO guarantee about the automatic generated content. It should help the world wide qPCR community to understand the core content of the MIQE guidelines.

The MIQE Guidelines - Minimum Information for Publication of Quantitative Real-Time PCR Experiments
Stephen A. Bustin 1,  Vladimir Benes 2,  Jeremy A. Garson 3,4,  Jan Hellemans 5,  Jim Huggett 6, Mikael Kubista 7,8,  Reinhold Mueller 9,  Tania Nolan 10,  Michael W. Pfaffl 11,  Gregory L. Shipley 12, Jo Vandesompele 5,  and  Carl T. Wittwer 13,14
Clinical Chemistry 2009, 55(4): 611-622

picture of trhe MIQE authors
by  S. Bustin
1   Centre for Academic Surgery, Barts and the London School of Medicine and Dentistry, UK
2   Genomics Core Facility, EMBL Heidelberg, Germany
3   Centre for Virology, Department of Infection, University College London, London, UK
4   Department of Virology, UCL Hospitals NHS Foundation Trust, London, UK
5   Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium
6   Centre for Infectious Diseases, University College London, London, UK
7   TATAA Biocenter, Göteborg, Sweden
8   Institute of Biotechnology AS CR, Prague, Czech Republic
9   Sequenom, San Diego, USA
10  Sigma-Aldrich, Haverhill, UK
11  Physiology Weihenstephan, Technical University Munich, Freising, Germany
12  Quantitative Genomics Core Laboratory, The University of Texas Health Science Center Houston, USA
13  Department of Pathology, University of Utah, Salt Lake City, Utah, USA
14  ARUP Institute for Clinical and Experimental Pathology, Salt Lake City, Utah, USA 

MIQE checklist
BACKGROUND:  Currently, a lack of consensus exists on how best to perform and interpret quantitative real-time PCR (qPCR) experiments. The problem is exacerbated by a lack of sufficient experimental detail in many publications, which impedes a reader's ability to evaluate critically the quality of the results presented or to repeat the experiments.
CONTENT:  The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines target the reliability of results to help ensure the integrity of the scientific literature, promote consistency between laboratories, and increase experimental transparency. MIQE is a set of guidelines that describe the minimum information necessary for evaluating qPCR experiments. Included is a checklist to accompany the initial submission of a manuscript to the publisher. By providing all relevant experimental conditions and assay characteristics, reviewers can assess the validity of the protocols used. Full disclosure of all reagents, sequences, and analysis methods is necessary to enable other investigators to reproduce results. MIQE details should be published either in abbreviated form or as an online supplement.
Following these guidelines will encourage better experimental practice, allowing more reliable and unequivocal interpretation of qPCR results.

MIQE & qPCR iBook
How to apply the MIQE guidelines - a visual, interactive and practical qPCR guide

2nd edition published 26th July 2016
Editors:  Afif M. Abdel Nour & Michael W. Pfaffl
ISBN 9783000488061
Free download via iTunes

MIQE & qPCR iBook Preface:   The qPCR and dPCR MIQE guidelines – A success story!
(Editorial for 2nd edition published in July 2016)

The MIQE guidelines and the resulting scientific validity will be supported by more and more researchers, biological journals, academic and commercial institutions. Today in July 2016 we count more than 4600 citations for the MIQE guideline applied in qPCR and around 160 citations for the digital PCR (dPCR) MIQE guideline (measured by Google Scholar). Hence the qPCR and dPCR MIQE guidelines are a worldwide full success story which will be driven forward by the scientific community, e.g.

The present second edition of the MIQE & qPCR iBook should help to spread this MIQE idea even further in any laboratory worldwide and beyond in the scientists’ workflow and minds. It should clearly show how to apply the guidelines and serve as a handy, visual, interactive and practical guide. For now in the first year after publication of the first edition we could count more than 1200 downloads of the MIQE & qPCR iBook from more than 30 countries. Our goal for the second edition is to update the existing content by new chapters, and to improve this fancy interactive tool, interfacing scientific publications with educating pictures, videos and scientific talks. We implemented multiple new chapters, describing the significance of the reverse transcription reaction, why PCR assay validation is so important for high sensitivity and good reproducibility, and one reviewing chapter about the necessity of performing quality control at all levels in the qPCR workflow. In summary we are proud to present a selection of international highly recognized authors from the academic field as well from industrial research presenting their latest applications. Described qPCR / dPCR methods and applications are linked to the MIQE context and show it on the basis of educational questionnaires or interactive ‘how to do’ instruction sheets. The at-hand MIQE & qPCR iBook should deliver the MIQE guidelines directly to the researcher and help to solve the daily problems in the molecular biology laboratory using quantitative PCR, digital PCR, single-cell qPCR, microRNA applications or any comparable techniques using PCR.

We hope you like our explanatory, interactive and educational iBook concept, showing the advantages of the MIQE guidelines in an easy and understandable way, and to guarantee the successful qPCR or dPCR application at the lab bench.

The editors
Afif M. Abdel Nour & Michael W. Pfaffl

MIQE & qPCR iBook cover
MIQE & qPCR iBook
How to apply the MIQE guidelines - a visual, interactive and practical qPCR guide

1st edition published 11th May 2015
Editors:  Afif M. Abdel Nour & Michael W. Pfaffl
ISBN 9783000488061

Throughout the past 30 years Polymerase Chain Reaction (PCR) has proven to be the most powerful technique in a scientist toolbox. Only few techniques had a comparable success story like PCR. This iBook will guide you in better practicing in your laboratory thanks to the MIQE guideline.

MIQE & qPCR iBook – a digital publication: How making the MIQE guidelines easier to follow.
Afif M. Abdel Nour & Michael W. Pfaffl
Presentation at qPCR & NGS 2015 Symposium --

Please let us know, if you want to participate with an own application or chapter in the MIQE & qPCR iBook
Contact us via

MIQE Guidelines - Chinese translation MIQE Guidelines - Japanese translation MIQE Guidelines - Arabian translation

MIQE has been frequently cited by other researchers:  => 4280  times until April 2016

Authors from 85 different countries cited the MIQE guidelines =>

The reproducibility of biomedical research -- Sleepers awake!
Stephen A. Bustin,
Biomolecular Detection and Quantification, Volume 2, December 2014, Pages 35–42

There is increasing concern about the reliability of biomedical research, with recent articles suggesting that up to 85% of research funding is wasted. This article argues that an important reason for this is the inappropriate use of molecular techniques, particularly in the field of RNA biomarkers, coupled with a tendency to exaggerate the importance of research findings.

In the past decade, the techniques of quantitative PCR (qPCR) and reverse transcription (RT)-qPCR have become accessible to virtually all research labs, producing valuable data for peer-reviewed publications and supporting exciting research conclusions. However, the experimental design and validation processes applied to the associated projects are the result of historical biases adopted by individual labs that have evolved and changed since the inception of the techniques and associated technologies. This has resulted in wide variability in the quality, reproducibility and interpretability of published data as a direct result of how each lab has designed their RT-qPCR experiments. The 'minimum information for the publication of quantitative real-time PCR experiments' (MIQE) was published to provide the scientific community with a consistent workflow and key considerations to perform qPCR experiments. We use specific examples to highlight the serious negative ramifications for data quality when the MIQE guidelines are not applied and include a summary of good and poor practices for RT-qPCR.

Design and Validation of Real-Time PCR Primers

Bio-Rad collaborated with Biogazelle, leaders in real-time PCR research, to design and experimentally validate PCR primers for gene expression assays across the human and mouse transcriptomes. All PCR primers were designed to meet stringent performance standards following the MIQE guidelines (minimum information for publication of quantitative real-time PCR experiments; Bustin et al. 2009).

Assay Performance Standards
  •  Sensitivity    Accurate detection of 20 copies
  •  Specificity    Amplicon sequence validated with next generation sequencing (NGS). Minimal primer dimer formation and genomic DNA cross reactivity.
  •  Amplification Efficiency    90–110%
  •  Linear Dynamic Range    Minimum of six orders of magnitude. Detection of a synthetic template standard curve from 20 to 20 million copies.
  •  standard curve R2    >0.99
These DNA primer pairs were designed by prioritizing the gene regions most commonly found in transcript variants. Strict design criteria were used to ensure optimal real-time PCR results for each target:
  • Target regions without SNPs
  • PCR primer pairs annealing across intron/exon junctions when possible
  • No secondary structure in primer annealing sites
  • Maximum number of transcript isoforms detected
  • PCR primers compatible with standard assay conditions
  • Every PCR primer pair was experimentally validated using Bio-Rad’s iScript™ advanced cDNA synthesis kit and SsoAdvanced™ SYBR® Green supermix. PrimePCR assay design and validation are fully described in the following publication.
PrimePCR Assays: Meeting the MIQE Guidelines by Full Wet-lab Validation

The need for transparency and good practices in the qPCR literature

Stephen A Bustin, Vladimir Benes,Jeremy Garson, Jan Hellemans, Jim Huggett, Mikael Kubista, Reinhold Mueller, Tania Nolan, Michael W Pfaffl, Gregory Shipley, Carl T Wittwer, et al.
Nature Methods 2013, 10(11): 1063–1067
Published online 30 October 2013

Two surveys of over 1,700 publications whose authors use quantitative real-time PCR (qPCR) reveal a lack of transparent and comprehensive reporting of essential technical information. Reporting standards are significantly improved in publications that cite the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines, although such publications are still vastly outnumbered by those that do not.

The MIQE guidelines aim “to encourage better experimental practice and more transparent reporting, resulting in more reliable, comparable and unequivocal interpretation of qPCR results”. They are a response to the considerable misgivings with which many researchers perceive the quality of published qPCR data. That unease comes as a surprise to those who incorrectly believe that the conceptual simplicity and accessibility of qPCR translates into an equally uncomplicated experimental procedure.

In reality, it is very easy to publish qPCR results that are meaningless. Without transparency for optimization, validation and quality-control procedures, it is impossible for the reader of a publication to distinguish a reliable from a biased result or technical variation. This is particularly true for protocols aimed at quantifying RNA targets using reverse transcription qPCR (RT-qPCR), for which the relevance of the results is critically dependent on sampling procedure, sample properties, template quality and analysis procedures in addition to any relevant qPCR parameters.


SPECIAL REPORT -- Guidelines for Minimum Information for Publication of Quantitative Digital PCR Experiments.
Huggett JF, Foy CA, Benes V, Emslie K, Garson JA, Haynes R, Hellemans J, Kubista M, Mueller RD, Nolan T, Pfaffl MW, Shipley GL, Vandesompele J, Wittwer CT, Bustin SA.
Clin Chem 2013 59(6): 892-902

There is growing interest in digital PCR (dPCR) because technological progress makes it a practical and increasingly affordable technology. dPCR allows the precise quantification of nucleic acids, facilitating the measurement of small percentage differences and quantification of rare variants. dPCR may also be more reproducible and less susceptible to inhibition than quantitative real-time PCR (qPCR). Consequently, dPCR has the potential to have a substantial impact on research as well as diagnostic applications. However, as with qPCR, the ability to perform robust meaningful experiments requires careful design and adequate controls. To assist independent evaluation of experimental data, comprehensive disclosure of all relevant experimental details is required. To facilitate this process we present the Minimum Information for Publication of Quantitative Digital PCR Experiments guidelines. This report addresses known requirements for dPCR that have already been identified during this early stage of its development and commercial implementation. Adoption of these guidelines by the scientific community will help to standardize experimental protocols, maximize efficient utilization of resources, and enhance the impact of this promising new technology.

Why the need for qPCR publication guidelines?  -  The case for MIQE
Stephen A. Bustin
Methods.  2010 April    in       qPCR special issue - The ongoing evolution of qPCR
  Institute of Cell and Molecular Science, Barts and the London School of Medicine and Dentistry
Queen Mary University of London, Whitechapel, London E1 1BB, UK

The polymerase chain reaction (PCR) has matured from a labour- and time-intensive, low throughput qualitative gel-based technique to an easily automated, rapid, high throughput quantitative technology. Real-time quantitative PCR (qPCR) has become the benchmark technology for the detection and quantification of nucleic acids in a research, diagnostic, forensic and biotechnology setting. However, ill-assorted pre-assay conditions, poor assay design and inappropriate data analysis methodologies have resulted in the recurrent publication of data that are at best inconsistent and at worst irrelevant and even misleading. Furthermore, there is a lamentable lack of transparency of reporting, with the "Materials and Methods" sections of many publications, especially those with high impact factors, not fit for the purpose of evaluating the quality of any reported qPCR data. This poses a challenge to the integrity of the scientific literature, with serious consequences not just for basic research, but potentially calamitous implications for drug development and disease monitoring. These issues are being addressed by a set of guidelines that propose a minimum standard for the provision of information for qPCRexperiments ("MIQE"). MIQE aims to restructure to-day's free-for-all qPCR methods into a more consistent format that will encourage detailed auditing of experimental detail, data analysis and reporting principles. General implementation of these guidelines is an important requisite for the maturing of qPCR into a robust, accurate and reliable nucleic acid quantification technology.

MIQE precis:
Practical implementation of minimum standard guidelines for fluorescence-based
quantitative real-time PCR experiments

Stephen A Bustin, Jean-Francois Beaulieu, Jim Huggett, Rolf Jaggi, Frederick SB Kibenge, Pal A Olsvik,
Louis C Penning email and Stefan Toegel    
BMC Molecular Biology 2010   -   Published:  21 September 2010

The conclusions of thousands of peer-reviewed publications rely on data obtained using fluorescence-based quantitative real-time PCR technology. However, the inadequate reporting of experimental detail, combined with the frequent use of flawed protocols is leading to the publication of papers that may not be technically appropriate. We take the view that this problem requires the delineation of a more transparent and comprehensive reporting policy from scientific journals. This editorial aims to provide practical guidance for the incorporation of absolute minimum standards encompassing the key assay parameters for accurate design, documentation and reporting of qPCR experiments (MIQE precis) and guidance on the publication of pure 'reference gene' articles.

New MIQE and miRQC papers 2014:

Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study
Mestdagh P, Hartmann N, Baeriswyl L, Andreasen D, Bernard N, Chen C, Cheo D, D'Andrade P, DeMayo M, Dennis L, Derveaux S, Feng Y, Fulmer-Smentek S, Gerstmayer B, Gouffon J, Grimley C, Lader E, Lee KY, Luo S, Mouritzen P, Narayanan A, Patel S, Peiffer S, Rüberg S, Schroth G, Schuster D, Shaffer JM, Shelton EJ, Silveria 9, Ulmanella U, Veeramachaneni V, Staedtler F, Peters T, Guettouche T, Vandesompele J
Nature Methods 11, 809–815 (2014)

MicroRNAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies such as small RNA sequencing, reverse transcription-quantitative PCR (RT-qPCR) and (microarray) hybridization. In this study, we systematically compared 12 commercially available platforms for analysis of microRNA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples and synthetic spikes from microRNA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative microRNA gene expression platform for particular study goals.

Reverse transcription-quantitative PCR (RT-qPCR) has been widely adopted to measure differences in mRNA levels; however, biological and technical variation strongly affects the accuracy of the reported differences. RT-qPCR specialists have warned that, unless researchers minimize this variability, they may report inaccurate differences and draw incorrect biological conclusions. The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines describe procedures for conducting and reporting RT-qPCR experiments. The MIQE guidelines enable others to judge the reliability of reported results; however, a recent literature survey found low adherence to these guidelines. Additionally, even experiments that use appropriate procedures remain subject to individual variation that statistical methods cannot correct. For example, since ideal reference genes do not exist, the widely used method of normalizing RT-qPCR data to reference genes generates background noise that affects the accuracy of measured changes in mRNA levels. However, current RT-qPCR data reporting styles ignore this source of variation. In this commentary, we direct researchers to appropriate procedures, outline a method to present the remaining uncertainty in data accuracy, and propose an intuitive way to select reference genes to minimize uncertainty. Reporting the uncertainty in data accuracy also serves for quality assessment, enabling researchers and peer reviewers to confidently evaluate the reliability of gene expression data.

Variability of the Reverse Transcription Step: Practical Implications.
Bustin SA, Dhillon HS, Kirvell S, Greenwood C, Parker M, Shipley GL, Nolan T.
Clin Chem. 2014 Oct 31

BACKGROUND: The reverse transcription (RT) of RNA to cDNA is a necessary first step for numerous research and molecular diagnostic applications. Although RT efficiency is known to be variable, little attention has been paid to the practical implications of that variability.
METHODS: We investigated the reproducibility of the RT step with commercial reverse transcriptases and RNA samples of variable quality and concentration. We quantified several mRNA targets with either singleplex SYBR Green I or dualplex probe-based real-time quantitative PCR (qPCR), with the latter used to calculate the correlation between quantification cycles (Cqs) of mRNA targets amplified in the same qPCR assay.
RESULTS: RT efficiency is enzyme, sample, RNA concentration, and assay dependent and can lead to variable correlation between mRNAs from the same sample. This translates into relative mRNA expression levels that generally vary between 2- and 3-fold, although higher levels are also observed.
CONCLUSIONS: Our study demonstrates that the variability of the RT step is sufficiently large to call into question the validity of many published data that rely on quantification of cDNA. Variability can be minimized by choosing an appropriate RTase and high concentrations of RNA and characterizing the variability of individual assays by use of multiple RT replicates.

Minimum Information Necessary for Quantitative Real- Time PCR Experiments
Gemma Johnson, Afi f Abdel Nour, Tania Nolan, Jim Huggett, and Stephen Bustin
Roberto Biassoni and Alessandro Raso (eds.), Quantitative Real-Time PCR: Methods and Protocols, Methods in Molecular Biology,
vol. 1160, Springer Science+Business Media New York 2014

The MIQE (minimum information for the publication of quantitative real-time PCR) guidelines were published in 2009 with the twin aims of providing a blueprint for good real-time quantitative polymerase chain reaction (qPCR) assay design and encouraging the comprehensive reporting of qPCR protocols. It had become increasingly clear that variable pre-assay conditions, poor assay design, and incorrect data analysis were leading to the routine publication of data that were often inconsistent, inaccurate, and wrong. The problem was exacerbated by a lack of transparency of reporting, with the details of technical information inadequate for the purpose of assessing the validity of published qPCR data. This had, and continues to have serious implications for basic research, reducing the potential for translating fi ndings into valuable applications and potentially devastating consequences for clinical practice. Today, the rationale underlying the MIQE guidelines has become widely accepted, with more than 2,200 citations by March 2014 and editorials in Nature and related publications acknowledging the enormity of the problem. However, the problem we now face is rather serious: thousands of publications that report suspect data are populating and corrupting the peer-reviewed scientifi c literature. It will be some time before the many contradictions apparent in every area of the life sciences are corrected.

Five Years MIQE Guidelines: The Case of the Arabian Countries
Afif M. Abdel Nour, Esam Azhar, Ghazi Damanhouri, Stephen A. Bustin
PLoS ONE 9(2) (2014): e88266.

The quantitative real time polymerase chain reaction (qPCR) has become a key molecular enabling technology with an immense range of research, clinical, forensic as well as diagnostic applications. Its relatively moderate instrumentation and reagent requirements have led to its adoption by numerous laboratories, including those located in the Arabian world, where qPCR, which targets DNA, and reverse transcription qPCR (RT-qPCR), which targets RNA, are widely used for regionspecific biotechnology, agricultural and human genetic studies. However, it has become increasingly apparent that there are significant problems with both the quality of qPCR-based data as well as the transparency of reporting. This realisation led to the publication of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines in 2009 and their more widespread adoption in the last couple of years. An analysis of the performance of biomedical research in the Arabian world between 2001–2005 suggests that the Arabian world is producing fewer biomedical publications of lower quality than other Middle Eastern countries. Hence we have analysed specifically the quality of RT-qPCR-based peer-reviewed papers published since 2009 from Arabian researchers using a bespoke iOS/Android app developed by one of the authors. Our results show that compliance with 15 essential MIQE criteria was low (median of 40%, range 0–93%) and few details on RNA quality controls (22% compliance), assays design (12%), RT strategies (32%), amplification efficiencies (30%) and the normalisation process (3%). These data indicate that one of the reasons for the poor performance of Arabian world biomedical research may be the low standard of any supporting qPCR experiments and identify which aspects of qPCR experiments require significant improvements.

Keeping qRT-PCR rigorous and biologically relevant.
Bennett J, Hondred D, Register JC 3rd.
Plant Cell Rep. 2014 Oct 11.

MIQE has received support from journals, authors and suppliers of equipment, reagents, and software ( De Keyser et al. (2013) and Saha and Blumwald (2014) proved that qRT-PCR data can be rigorously conducted and reported without inclusion of a MIQE checklist. However, we do advocate that the items on the checklist be addressed during experimental design and execution and recommend that a checklist be made available to referees during the review process. Except for rare and justified cases (Bustin et al. 2010), reference genes should be published in conjunction with their use in normalizing target genes within a biological context. Finally, we emphasize that, for every manuscript that includes qRT-PCR data, it is vital that authors give careful attention to the qRT-PCR experimental details to ensure that gene expression data from this powerful method are valid.

Toward Enhanced MIQE Compliance: Reference Residual Normalization of qPCR Gene Expression Data
Richard C. Edmunds, Jenifer K. McIntyre, J. Adam Luckenbach, David H. Baldwin, and John P. Incardona

Normalization of fluorescence-based quantitative real-time PCR (qPCR) data varies across quantitative gene expression studies, despite its integral role in accurate data quantification and interpretation. Identification of suitable reference genes plays an essential role in accurate qPCR normalization, as it ensures that uncorrected gene expression data reflect normalized data. The reference residual normalization (RRN) method presented here is a modified approach to conventional 2CtqPCR normalization that increases mathematical transparency and incorporates statistical assessment of reference gene stability. RRN improves mathematical transparency through the use of sample-specific reference residuals (RRi) that are generated from the mean Ct of one or more reference gene(s) that are unaffected by treatment. To determine stability of putative reference genes, RRN uses ANOVA to assess the effect of treatment on expression and subsequent equivalence-threshold testing to establish the minimum permitted resolution. Step-by-step instructions and comprehensive examples that demonstrate the influence of reference gene stability on target gene normalization and interpretation are provided. Through mathematical transparency and statistical rigor, RRN promotes compliance with Minimum Information for Quantitative Experiments and, in so doing, provides increased confidence in qPCR data analysis and interpretation.

MIQE:  Guidelines for the Design and Publication of a Reliable Real-time PCR Assay
Jim Huggett, Tania Nolan and Stephen A. Bustin
Real-Time PCR: Advanced Technologies and Applications
published 1st July 2013, Caister Academic Press
edited by Nick A. Saunders, Martin A. Lee

The capacity to amplify and detect trace amounts of nucleic acids has made the polymerase chain reaction (PCR) the most formidable molecular technology in use today. Its versatility and scope was further broadened first with the development of reverse transcription (RT)-PCR, which opened up the entire RNA field to thorough exploration and then, most conspicuously, with its evolution into real-time quantitative PCR (qPCR). Speed, simplicity, specificity, wide linear dynamic range, multiplexing and high-throughput potential, reduced contamination risk, simplified detection and data analysis procedures as well as availability of increasingly affordable instrumentation and reduced reagent cost have made qPCR the molecular method of choice when quantifying nucleic acids. Detection of pathogens, SNP analyses and quantification of RNA, even real-time analysis of gene expression in vivo have become routine applications and constant enhancements of chemistries, enzymes, mastermixes and instruments continue to extend the scope of qPCR technology by promising added benefits such as extremely short assay times measured in minutes, low reagent usage and exceptionally rapid heating/cooling rates. The whole process is driven by the insatiable demand for ever-more specific, sensitive, convenient and cost-effective protocols.
However, it has also become clear that variable pre-assay conditions, poor assay design and incorrect data analysis have resulted in the regular publication of data that are often inconsistent, inaccurate and often simply wrong. The problem is exacerbated by a lack of transparency of reporting, with the details of technical information wholly inadequate for the purpose of assessing the validity of reported qPCR data. This has serious consequences for basic research, reducing the potential for translating findings into valuable applications and potentially devastating implications for clinical practice. In response, guidelines proposing
a minimum standard for the provision of information for qPCR experiments (‘MIQE’) have been launched. These aim to establish a standard for accurate and reliable qPCR experimental design as well as recommendations to ensure comprehensive reporting of technical detail, indispensable conditions for the maturing of qPCR into a robust, accurate and reliable nucleic acid quantification technology.

Critical appraisal of quantitative PCR results in colorectal cancer research: Can we rely on published qPCR results?
J.R. Dijkstraemail address, L.C. van Kempen, I.D. Nagtegaal, S.A. Bustin

The use of real-time quantitative polymerase chain reaction (qPCR) in cancer research has become ubiquitous. The relative simplicity of qPCR experiments, which deliver fast and cost-effective results, means that each year an increasing number of papers utilizing this technique are being published. But how reliable are the published results? Since the validity of gene expression data is greatly dependent on appropriate normalisation to compensate for sample-to-sample and run-to-run variation, we have evaluated the adequacy of normalisation procedures in qPCR-based experiments. Consequently, we assessed all colorectal cancer publications that made use of qPCR from 2006 until August 2013 for the number of reference genes used and whether they had been validated. Using even these minimal evaluation criteria, the validity of only three percent (6/179) of the publications can be adequately assessed. We describe common errors, and conclude that the current state of reporting on qPCR in colorectal cancer research is disquieting. Extrapolated to the study of cancer in general, it is clear that the majority of studies using qPCR cannot be reliably assessed and that at best, the results of these studies may or may not be valid and at worst, pervasive incorrect normalisation is resulting in the wholesale publication of incorrect conclusions. This survey demonstrates that the existence of guidelines, such as MIQE, is necessary but not sufficient to address this problem and suggests that the scientific community should examine its responsibility and be aware of the implications of these findings for current and future research.

•Reliability-assessment of 179 qPCR studies in CRC-associated publications 2006–2013.
•Evaluation based on number of reference genes and their validation of suitability.
•97% of the qPCR-studies cannot be reliably assessed and results may not be valid.
•Guidelines, such as MIQE, are useful but by themselves are not sufficient.
•Scientific community should shoulder its responsibility.

The State of RT-Quantitative PCR: Firsthand Observations of Implementation of Minimum Information for the Publication of Quantitative Real-Time PCR Experiments (MIQE)
Taylor SC, Mrkusich EM.
Bio-Rad Laboratories Canada, Mississauga, Ont., Canada.
J Mol Microbiol Biotechnol. 2013 Nov 28;24(1): 46-52

In the past decade, the techniques of quantitative PCR (qPCR) and reverse transcription (RT)-qPCR have become accessible to virtually all research labs, producing valuable data for peer-reviewed publications and supporting exciting research conclusions. However, the experimental design and validation processes applied to the associated projects are the result of historical biases adopted by individual labs that have evolved and changed since the inception of the techniques and associated technologies. This has resulted in wide variability in the quality, reproducibility and interpretability of published data as a direct result of how each lab has designed their RT-qPCR experiments. The 'minimum information for the publication of quantitative real-time PCR experiments' (MIQE) was published to provide the scientific community with a consistent workflow and key considerations to perform qPCR experiments. We use specific examples to highlight the serious negative ramifications for data quality when the MIQE guidelines are not applied and include a summary of good and poor practices for RT-qPCR.
Watch Taylor review the paper on =>  YouTube

Standardisation and reporting for nucleic acid quantification
  Jim Huggett & Stephen A. Bustin
Accred Qual Assur 2011

The real-time quantitative polymerase chain reaction (qPCR) is probably the most common molecular technique in use today, having become the method of choice for nucleic acid detection and quantification and underpinning applications ranging from basic research through biotechnology and forensic applications to clinical diagnostics. This key technology relies on fluorescence to detect and quantify nucleic acid amplification products, and its homogeneous assay format has transformed legacy polymerase chain reaction (PCR) from a low-throughput qualitative gel-based technique to a requently automated, rapid, high-throughput quantitative technology. However, the enormous range of protocols together with frequently inappropriate pre-assay conditions, poor assay design and unsuitable data analysis methodologies are impeding its status as a mature ,‘gold standard’ technology. This, combined with in consistent and in sufficient reporting procedures, has resulted in the wide spread publication of datat hat can be misleading, in particular when this tech-nology is used to quantify cellular mRNA or miRNA levels by RT-qPCR. This affects the integrity of the scientific literature, with consequences for not only basic research, but with potentially major implications for the potential development of molecular diagnostic and prognostic monitoring tools. These issues have been addressed by a set of guidelines that propose a minimum standard for the provision of information for qPCR experiments (‘MIQE’). MIQE aims to systematise current variable qPCR methods into a more consistent form at that will encourage detailed auditing of experimental detail, data analysis and reporting principles. General implementation of these guidelines is an important requisite for the maturing of qPCR into a robust, accurate and reliable nucleic acid quantification technology.

A MIQE-Compliant Real-Time PCR Assay for Aspergillus Detection
Johnson GL, Bibby DF, Wong S, Agrawal SG, Bustin SA.
Blizard Institute of Cell and Molecular Science, Queen Mary University, London, United Kingdom
PLoS One. 2012;7(7): e40022

The polymerase chain reaction (PCR) is widely used as a diagnostic tool in clinical laboratories and is particularly effective for detecting and identifying infectious agents for which routine culture and microscopy methods are inadequate. Invasive fungal disease (IFD) is a major cause of morbidity and mortality in immunosuppressed patients, and optimal diagnostic criteria are contentious. Although PCR-based methods have long been used for the diagnosis of invasive aspergillosis (IA), variable performance in clinical practice has limited their value. This shortcoming is a consequence of differing sample selection, collection and preparation protocols coupled with a lack of standardisation of the PCR itself. Furthermore, it has become clear that the performance of PCR-based assays in general is compromised by the inadequacy of experimental controls, insufficient optimisation of assay performance as well as lack of transparency in reporting experimental details. The recently published “Minimum Information for the publication of real-time Quantitative PCR Experiments” (MIQE) guidelines provide a blueprint for good PCR assay design and unambiguous reporting of experimental detail and results. We report the first real-time quantitative PCR (qPCR) assay targeting Aspergillus species that has been designed, optimised and validated in strict compliance with the MIQE guidelines. The hydrolysis probe-based assay, designed to target the 18S rRNA DNA sequence of Aspergillus species, has an efficiency of 100% (range 95–107%), a dynamic range of at least six orders of magnitude and limits of quantification and detection of 6 and 0.6 Aspergillus fumigatus genomes, respectively. It does not amplify Candida, Scedosporium, Fusarium or Rhizopus species and its clinical sensitivity is demonstrated in histological material from proven IA cases, as well as concordant PCR and galactomannan data in matched broncho-alveolar lavage and blood samples. The robustness, specificity and sensitivity of this assay make it an ideal molecular diagnostic tool for clinical use.

Editorial - Transparency of Reporting in Molecular Diagnostics
Stephen Bustin;  Postgraduate Medical Institute, Anglia Ruskin University, Chelmsford CM1 1SQ, UK
Int. J. Mol. Sci. 2013, 14(8), 15878-15884

The major advances made over the past few years in molecular and cell biology are providing a progressively more detailed understanding of the molecular pathways that control normal processes and become dysregulated in disease. This has resulted in the documentation of numerous genetic, epigenetic, transcriptomic, proteomic and metabolomic biomarkers that promise earlier disease detection, more accurate patient stratification and better prognosis. Furthermore, molecular fingerprinting of diseases can be predictive of drug response and so assist with specific targeting of drugs against disease-associated molecules and function.   ....

The MIQE Guidelines Uncloaked
Gregory L. Shipley
Chapter 8 in   PCR Troubleshooting and Optimization:    The Essential Guide,   ISBN: 978-1-904455-72-1
Publication date - January 2011   Publisher: Caister Academic Press
Editors: Suzanne Kennedy and Nick Oswald MO BIO Laboratories, Inc., Carlsbad, CA 92010, USA and BitesizeBio, Edinburgh, UK

The MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines have been presented to serve as a practical guide for authors when publishing experimental data based on real-time qPCR. Each item is presented in tabular form as a checklist within the MIQE manuscript. However, this format has left little room for explanation of precisely what is expected from the items listed and no information on how one might go about assimilating the information requested. This chapter presents an expanded explanation of the guideline items with commentary on how those requirements might be met prior to publication.

Quantification noise in single cell experiments
Reiter M, Kirchner B, Müller H, Holzhauer C, Mann W, Pfaffl MW.
Nucleic Acids Res. 2011 Oct;39(18):e124

In quantitative single-cell studies, the critical part is the low amount of nucleic acids present and the resulting experimental variations. In addition biological data obtained from heterogeneous tissue are not reflecting the expression behaviour of every single-cell. These variations can be derived from natural biological variance or can be introduced externally. Both have negative effects on the quantification result. The aim of this study is to make quantitative single-cell studies more transparent and reliable in order to fulfil the MIQE guidelines at the single-cell level. The technical variability introduced by RT, pre-amplification, evaporation, biological material and qPCR itself was evaluated by using RNA or DNA standards. Secondly, the biological expression variances of GAPDH, TNFα, IL-1β, TLR4 were measured by mRNA profiling experiment in single lymphocytes. The used quantification setup was sensitive enough to detect single standard copies and transcripts out of one solitary cell. Most variability was introduced by RT, followed by evaporation, and pre-amplification. The qPCR analysis and the biological matrix introduced only minor variability. Both conducted studies impressively demonstrate the heterogeneity of expression patterns in individual cells and showed clearly today's limitation in quantitative single-cell expression analysis.

How to do successful gene expression analysis using real-time PCR
Derveaux S, Vandesompele J, Hellemans J.
Methods. 2010 50(4): 227-230  in       qPCR special issue - The ongoing evolution of qPCR
Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium.

Reverse transcription quantitative PCR (RT-qPCR) is considered today as the gold standard for accurate, sensitive and fast measurement of gene expression. Unfortunately, what many users fail to appreciate is that numerous critical issues in the workflow need to be addressed before biologically meaningful and trustworthy conclusions can be drawn. Here, we review the entire workflow from the planning and preparation phase, over the actual real-time PCR cycling experiments to data-analysis and reporting steps. This process can be captured with the appropriate acronym PCR: plan/prepare, cycle and report. The key message is that quality assurance and quality control are essential throughout the entire RT-qPCR workflow; from living cells, over extraction of nucleic acids, storage, various enzymatic steps such as DNase treatment, reverse transcription and PCR amplification, to data-analysis and finally reporting.

Improving the analysis of quantitative PCR data in veterinary research
Bustin S, Penning LC.
Vet J. 2012 191(3): 279-281

Comment on:
Identification of internal control genes for quantitative expression analysis by real-time PCR in bovine peripheral lymphocytes. [Vet J. 2011]
Quantitative real-time PCR detection of insulin signalling-related genes in pancreatic islets isolated from healthy cats. [Vet J. 2010]

Common statistical and research design problems in manuscripts submitted to high-impact medical journals
Fernandes-Taylor S, Hyun JK, Reeder RN, Harris AH.
BMC Res Notes. 2011 Aug 19;4:304. doi: 10.1186/1756-0500-4-304.
Center for Health Care Evaluation, VA Palo Alto Health Care System and Stanford University School of Medicine, 795 Willow Road (MPD-152), Menlo Park, CA 94025, USA

BACKGROUND: To assist educators and researchers in improving the quality of medical research, we surveyed the editors and statistical reviewers of high-impact medical journals to ascertain the most frequent and critical statistical errors in submitted manuscripts.
FINDINGS: The Editors-in-Chief and statistical reviewers of the 38 medical journals with the highest impact factor in the 2007 Science Journal Citation Report and the 2007 Social Science Journal Citation Report were invited to complete an online survey about the statistical and design problems they most frequently found in manuscripts. Content analysis of the responses identified major issues. Editors and statistical reviewers (n = 25) from 20 journals responded. Respondents described problems that we classified into two, broad themes: A. statistical and sampling issues and B. inadequate reporting clarity or completeness. Problems included in the first theme were (1) inappropriate or incomplete analysis, including violations of model assumptions and analysis errors, (2) uninformed use of propensity scores, (3) failing to account for clustering in data analysis, (4) improperly addressing missing data, and (5) power/sample size concerns. Issues subsumed under the second theme were (1) Inadequate description of the methods and analysis and (2) Misstatement of results, including undue emphasis on p-values and incorrect inferences and interpretations.
CONCLUSIONS: The scientific quality of submitted manuscripts would increase if researchers addressed these common design, analytical, and reporting issues. Improving the application and presentation of quantitative methods in scholarly manuscripts is essential to advancing medical research.

Johnson G, Nolan T, Bustin SA.
Blizard Institute of Cell and Molecular Science, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Methods Mol Biol. 2013 943: 1-16

Nucleic acids are the ultimate biomarker and real-time PCR (qPCR) is firmly established as the method of choice for nucleic acid detection. Together, they allow the accurate, sensitive and specific identification of pathogens, and the use of qPCR has become routine in diagnostic laboratories. The reliability of qPCR-based assays relies on a combination of optimal sample selection, assay design and validation as well as appropriate data analysis and the "Minimal Information for the Publication of real-time PCR" (MIQE) guidelines aim to improve both the reliability of assay design as well as the transparency of reporting, essential conditions if qPCR is to remain the benchmark technology for molecular diagnosis.

Improving biological relevancy of transcriptional biomarkers experiments by applying the MIQE guidelines to pre-clinical and clinical trials
Dooms M, Chango A, Barbour E, Pouillart P, Abdel Nour AM.
LaSalle Beauvais, 19 rue Pierre Waguet, 60 000 Beauvais, France.
Methods. 2013 59(1): 147-153

The "Minimum Information for the Publication of qPCR Experiments" (MIQE]) guidelines are very much targeted at basic research experiments and have to our knowledge not been applied to qPCR assays carried out in the context of clinical trials. This report details the use of the MIQE qPCR app for iPhone (App Store, Apple) to assess the MIQE compliance of one clinical and five pre-clinical trials. This resulted in the need to include 14 modifications that make the guidelines more relevant for the assessment of this special type of application. We also discuss the need for flexibility, since while some parameters increase experimental quality, they also require more reagents and more time, which is not always feasible in a clinical setting.

Quantitative PCR (qPCR) and the guide to good practices MIQE: adapting and relevance in the clinical biology context
Dooms M, Chango A, Abdel-Nour A [Article in French]
Ann Biol Clin (Paris). 2014 72(3): 265-269

The qPCR has been introduced in clinical and biomedical research for over 10 years from now. Its use in trials and diagnostics is continuously increasing. Due to this heavy use, the question of relyability and relevance of qPCR results has to be asked. This review proposes a documented and evidence based answer to this question, thanks to the MIQE (minimum information for publication of quantitative real-time PCR experiments) guideline. The whole analysis process is addressed, from nucleic acids extraction to data management. Simple answers are given, taking into account the technical constraints from clinical research in order to allow a realistic application of this guideline.
Cell-free microRNAs: potential biomarkers in need of standardized reporting
Michaela B. Kirschner, Nico van Zandwijk and Glen Reid
Asbestos Diseases Research Institute, University of Sydney, Sydney, NSW, Australia
Front. Genet., 19 April 2013

MicroRNAs are abundantly present and surprisingly stable in multiple biological fluids. These findings have been followed by numerous reverse transcription real-time quantitative PCR (RT-qPCR)-based reports revealing the clinical potential of using microRNA levels in body fluids as a biomarker of disease. Despite a rapidly increasing body of literature, the field has failed to adopt a set of standardized criteria for reporting the methodology used in the quantification of cell-free microRNAs. Not only do many studies based on RT-qPCR fail to address the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) criteria but frequently there is also a distinct lack of detail in descriptions of sample source and RNA isolation. As a direct result, it is often impossible to compare the results of different studies, which in turn, hinders progress in the field. To address this point, we propose a simple set of criteria to be used in conjunction with MIQE to reveal the true potential of cell-free microRNAs as biomarkers.

Micro-RNA (miRNA) based analysis of body fluids and composition of complex crime stains has recently been introduced as a potential and powerful tool to forensic genetics. Analysis of miRNA has several advantages over mRNA but reliable miRNA detection and quantification using quantitative PCR requires a solid and forensically relevant normalization strategy. In our study we evaluated a panel of 13 carefully selected reference genes for their suitability as endogenous controls in miRNA qPCR normalization in forensically relevant settings. We analyzed assay performances and variances in venous blood, saliva, semen, menstrual blood, and vaginal secretion and mixtures thereof integrating highly standardized protocols with contemporary methodologies and included several well established computational algorithms. Based on these empirical results, we recommend normalization to the group of SNORD24, SNORD38B, and SNORD43 as this signature exhibits the most stable expression levels and the least expected variation among the evaluated candidate reference genes in the given set of forensically relevant body fluids. To account for the lack of consensus on how best to perform and interpret quantitative PCR experiments, our study's documentation is compliant to MIQE guidelines, defining the "minimum information for publication of quantitative real-time PCR experiments".

Messenger-RNA (mRNA)-based analysis of organ tissues and their differentiation in complex crime stains has recently been introduced as a potential and powerful tool to forensic genetics. Given the notoriously low quality of many forensic samples it seems advisable, though, to substitute mRNA with micro-RNA (miRNA) which is much less susceptible to degradation. However, reliable miRNA detection and quantification using quantitative PCR requires a solid and forensically relevant normalization strategy. In our study we evaluated a panel of 15 carefully selected reference genes for their suitability as endogenous controls in miRNA qPCR normalization in forensically relevant settings. We analyzed assay performances and expression variances in 35 individual samples and mixtures thereof integrating highly standardized protocols with contemporary methodologies and included several well-established computational algorithms. Based on these empirical results, we recommend SNORD48, SNORD24, and RNU6-2 as endogenous references since these exhibit the most stable expression levels and the least expected variation among the evaluated candidate reference genes in the given set of forensically relevant organ tissues including skin. To account for the lack of consensus on how best to perform and interpret quantitative PCR experiments, our study's documentation is according to MIQE guidelines, defining the "minimum information for publication of quantitative real-time PCR experiments".

MIQE Guidelines in CHINESE

The MIQE Guidelines - Minimum Information for Publication of Quantitative Real-Time PCR Experiments

Stephen A. Bustin 1,  Vladimir Benes 2,  Jeremy A. Garson 3,4,  Jan Hellemans 5,  Jim Huggett 6, Mikael Kubista 7,8,  Reinhold Mueller 9,  Tania Nolan 10,
Michael W. Pfaffl 11,  Gregory L. Shipley 12, Jo Vandesompele 5,  and  Carl T. Wittwer 13,14

Overseas Laboratory Medicine 2010:  3, 1

Related papers:

RDML:  structured language and reporting guidelines for real-time quantitative PCR data.
Lefever S, Hellemans J, Pattyn F, Przybylski DR, Taylor C, Geurts R, Untergasser A, Vandesompele J; on behalf of the RDML consortium. Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium.
Nucleic Acids Res. 2009 Apr;37(7): 2065-2069

Reliability of real-time reverse-transcription PCR in clinical diagnostics: gold standard or substandard?
Murphy J, Bustin SA.
Expert Rev Mol Diagn. 2009 9(2):187-197

Unreliable real-time PCR analysis of human endogenous retrovirus-W (HERV-W) RNA expression and DNA copy number in multiple sclerosis.
Garson JA, Huggett JF, Bustin SA, Pfaffl MW, Benes V, Vandesompele J, Shipley GL.
AIDS Res Hum Retroviruses. 2009 25(3): 377-378

Real-time polymerasechain reaction – towardsa more reliable, accurateand relevant assay.
SA Bustin

In-House Nucleic Acid Amplification Assays in Research: How Much Quality ControlIs Needed before One Can Rely upon the Results?
Petra Apfalter, UdoReischl and Margaret R. Hammerschlag


Quantitative polymerase chain reaction (qPCR) assays measure the copies of a specific DNA target in a sample as that sample is repeatedly passed through the polymerase chain reaction. Special qPCR machines are required to quantify the amplification products at each step of the cycle. MIQE specifies the minimum information needed for a correct interpretation of the experiment.

Checklist for Quantitative PCR Assays

  1. Sample
    • Fresh - How rapidly processed?
    • Frozen - How frozen?
    • Whole vs. microdissected
    • Sample storage conditions and duration
    • Fixed - How fixed, how old?

  2. Nucleic acid
    • Quantification
    • Quality/integrity
    • Inhibition dilution or spike
    • DNA contamination assessment of RNA sample
    • DNase treatment
    • Manufacturer of reagents used
    • Amount of sample used for extraction

  3. Reverse treanscriptions
    • cDNA priming method + concentration
    • Amount of RNA used per reaction
    • Enzyme type and concentration
    • Detailed reaction conditions
    • Manufacturer of reagents used
    • Reaction volume
    • Storage of cDNA

  4. Target
    • Database name and target gene accession number
    • Intronless, targeting of all splice variants/splice variant-specific targeting
    • Official gene symbol
    • Location of amplicon with respect to reference sequence
    • Information about (retro)pseudogenes

  5. Primers and probes
    • Primer sequences
    • Location of modification
    • End concentration of primers and optional probe(s) used
    • Primer purification method
    • Manufacturer of oligonucleotides
    • Probe sequence

  6. Assay details
    • Amplicon length
    • Specific BLAST or equivalent in silico specific screen
    • Experimental validation of specificity
    • NTC; Sensitivity
    • PCR efficiency, PCR efficiency standard curve slope and r-squared value
    • RTPrimerDB ID
    • Secondary structure analysis around priming sites

  7. PCR Cycling
    • Amount of cDNA/DNA used per reaction
    • Detailed reaction conditions, thermocycling parameters
    • Manufacturer of reagents used
    • Manual/robotic dispensing of reagents
    • Manufacturer of plates/tubes
    • Manufacturer of real-time instrument

  8. Data analysis
    • Cq value determination method
    • Treatment of NTCs and technical replicates
    • Normalisation method
    • Is r-squared value of regression curve satisfactory?
    • Has assay sensitivity been adequately evaluated and described?
    • Has assay specificity been adequately described?
    • Is the dynamic range of the assay acceptable?
    • Is the coefficient of variation for inter and intra-assay reproducibility reasonable?
    • Concordance of biological replicates
    • Analysis program
    • Assay carried out by core lab or investigator's lab
    • Acknowledgement of author's contribution to analysis and interpretation
    • Submission of Cq values of raw data using RDML

RDML guidelines (formaly known as MIqPCR)
Working draft, 4th April, 2008.

It is crucial that data acquisition, analysis and reporting become more transparent to allow reinterpretation and to guarantee compliance with quality standards. Therefore, following the example of the microarray community and their MIAME (Minimum Information About a Microarray Experiment) guidelines, we propose guidelines specifying the minimal information about qPCR experiments. A RDML guidelines compliant RDML file should contain all measured data as well as information about the samples and targets being analyzed.

In addition, data must be linked to samples and targets in an unequivocal way. Due to the complexity and diversity of experiments in which qPCR is utilized, the scope of the RDML guidelines is limited to the technology itself, which means that these guidelines can easily be integrated into other minimum information guidelines that focus on the wider experimental context. To coordinate this effort, the RDML consortium recently joined the MIBBI project (Minimum Information for Biological and Biomedical Investigations). The minimum information guidelines have been kept minimal to facilitate the creation of a compliant RDML files that make the least demand on researchers’ time, while requiring sufficient information for other researchers to interpret and reanalyze the data contained within an RDML guidelines compliant RDML file.

All information needed for the MIQE checklist can be stored in specialy designed elements or description strings inside an RDML file.

Reporting requirement for Quantitative PCR Assays

  1. Administrative information
    1. Experiment description
      • Experiment description
      • Responsible person and contact details

  2. Sample annotation
    1. Sample description
      • Sample ID
      • Sample description
      • cDNA synthesis method and DNAse treatment (cDNA samples only)
      • Template quantity (standard and optical calibrator samples only)
    2. Sample role in qPCR assay
      • Sample type
      • Inter run calibrator (true or false)
      • Calibrator sample (true or false)

  3. Target annotation
    1. Target description
      • Target ID
      • Sequence of primers OR commercial assay description
    2. Target role in qPCR assay
      • Target type

  4. Thermal Cycling Conditions Information
    1. PCR program
      • Complete description of the cycling conditions

  5. Run data
    1. Instrument information
      • Plate format
      • Instrument description
      • Software description and version
    2. Information required for each well
      • Well ID
      • Sample ID
      • Target ID
      • Amplification curve fluorescence values for each data point
      • Melting curve fluorescence values for each data point
      • Quantification Cycle

  6. Software requirements
    1. RDML-Support
      • Software solutions, including databases, must support the import and export of RDML files.
      • qPCR machines must allow the export of raw data for the amplification as well as for melting curves.

More detailed information about the terms used in the RDML guidelines can be found here
Download a document about the RDML guidelines.

qPCR Assay Quality assessment
05 January 2009
by Stephen Bustion on

Guidelines for minimum information required for publication of qPCR data are currently being assembled and will be published in Clinical Chemistry.

qPCR quality assessment relates mainly to the reverse transcription -qPCR (RT-qPCR) variant of the technology. This is widely used to measure pathogen as well as cellular RNA copy numbers; the former, given appropriate standard operating procedures and technical expertise, is fairly straightforward. The latter can be highly problematic. For both types of assay, however, RNA quality is a major consideraton.

Quality assessment is a big fat elephant sitting in the room: everyone knows what needs to be done, but most researchers do not follow basic quality control guidelines. This serves to undermine the integrity of the scientific literature to such an extent, that a high proportion of publications are reporting technical or analytic artifacts.

Incredibly, many researchers are not bothered by this; indeed some have been heard to remark that they can't be bothered assessing RNA quality, worrying about reverse transcription or determining what normalisdation strategy to follow. However, efforts are underway to establish a checklist for journal editors and reviewers, with the aim of introducing a minumum standard of assay reporting.

What are the problems?


PCR inhibition assessment generally depends on the assumption that inhibitors affect all PCR reactions to the same extent; i.e. that the reaction of interest and the control reaction are equally susceptible to inhibition. However, it appears that when copurified inhibitors are assessed in different PCR reactions, differential inhibition is observed and susceptibility to inhibition is highly variable between reactions. This has serious implications for all PCR-based gene expression studies, including the relatively new PCR array method, and for both qualitative and quantitative PCR-based molecular diagnostic assays, suggesting that careful consideration should be given to inhibition compatibility when conducting PCR analyses. Clearly, it is not safe to assume that different PCR reactions are equally susceptible to inhibition by substances co-purified in nucleic acid extracts.

Reference: Huggett JF, Novak T, Garson JA, Green C, Morris-Jones SD, Miller RF, Zumla A. Differential susceptibility of PCR reactions to inhibitors: an important and unrecognised phenomenon. BMC Res Notes 2008;1:70.

1. Inappropriate sample selection, coupled with the complexity and heterogeneity of any tissue biopy, especially from cancer and inconsistent handling procedures, results in variability and inaccurate mRNA quantification. In addition, there can be two sources of error: (i) sampling error, ie even if epithelial cells are being collected, the cell type within the epithelial population may have a different distribution compared with the collected population’ (ii) measurement error, which depends on the quality of instruments, reagents and operator.

2. The conversion of mRNA to cDNA is a major stumbling block and arguably is the single most variable step in the whole quantification procedure. It is well known, although not well publicised, that different reverse transcriptases have significantly different efficiencies of reverse transcription, and that these are target-dependent (1,2). Similarly, the mechanism of cDNA priming has a significant effect on the outcome of any quantification experiment, since gene-specific priming, random priming and oligo-dT all produce diverse results that are distinct for different mRNA targets. The choice of primer location on the target mRNA also can yield significantly different results, as mRNA adopts a tight secondary structure characterised by extensive intra-strand base pairing resulting in stem-loop structures (3). If reverse transcription primers are designed to target stems, rather than loops, or if the amplicon can adopt secondary structures, the efficiency of the RT step is significantly compromised. Characteristically, this results in non-quantitative and non-reproducible results.

3. The accuracy of gene expression profiling is highly dependent on mRNA quality (4,5). Unfortunately, this is an area that is distinguished by a prevalent lack of concern. A 2005 survey of the working practices of 100 experienced qPCR users revealed that attending a worryingly high 37% did not quality assess their RNA, with a further 4% using absorbance ratios which even then were known to be inadequate for quantification of mRNA (6). A survey of BMC publications in 2007/08 reveals that we have regressed since then, with >60% of papers not even mentioning mRNA quality and a substantial 10% continuing to rely on absorbance ratio measurements. Even when RNA quality is assessed, it is evaluated using either gel electrophoresis or microfluidics-based systems; this approach fails to take into account that such measurements only look at ribosomal RNA without relating the results to mRNA integrity, which is, after all, the real target of interest.

4. Splicing is a post-transcriptional modification in which a single gene can specify multiple proteins, allowing the synthesis of protein isoforms that are structurally and functionally distinct. Gene splicing affects most human genes (7) and plays an important role in human pathologies, including cancer (8). This generates significant problems with the interpretation of RT-qPCR and microarray data, since presence or, indeed significant changes in mRNA levels may reflect cell-, tissue- ot treatment-specific adjustments between different isoforms.

5. The increased realisation that allelic imbalance and allele-specific expression patterns are associated with increased disease risk (9,10) poses further problems for the interpretation of mRNA quantification data. Rather than avoiding SNPs when designing primers, it may be necessary to include them as part of an overall assay design strategy so as to be able to quantitate allele-specific expression accurately.

6. It is worth emphasising that in vivo mRNA is subject to constant degradation by complex interactions of deadenylation and decapping enzyme complexes as well as 3’-5, 5’-3’ exonucleases as well as endonucleases (11). This is likely to result in significant natural variability of mRNA levels between genes expressed in different tissues and individuals. This is in addition to any degradation introduced during the extraction of the RNA from tissue samples or during storage. Whilst these comments may seem obvious, their implications have never been explored.

7. Normalisation, known to be an essential component of proper data analysis (12), continues to be used in an inappropriate manner particularly in RT-qPCR applications, with a high proportion of papers still reporting expression patterns of target genes normalised against a single, unvalidated reference gene .

8. Inappropriate experimental designs, improper analyses, subjective interpretation of RT-qPCR data, variability of microarray results depending on the choice of analysis algorithms all combine to compromise the interpretation and confident application of quantitative, mRNA-targeted data (13).

The consequence of these, and other poor standards, is that a large number of publications report data that are at best unreliable, at worst misleading, with a dramatic and damaging effect on the integrity of the scientific literature. For example, a paper published in Science and named as a “breakthrough of the year”, has had to be withdrawn, because its results could not be repeated (14). More seriously, a paper using RT-qPCR technology and purporting to confirm an association between the presence of measles virus and gut pathology in children with developmental disorder (15) was used to claim a link between the MMR vaccine and autism (16). However, the data were significantly flawed as the RT-qPCR assay was applied in an inappropriate manner (

What is the solution?

First, it is essential to step back and concentrate on getting the basic technical problems sorted out. This includes enforcing minimum quality standards for template preparation, validation and consistent use of cDNA priming methods, enzymes, protocols and, equally critically, appropriate analysis of data.

Second, it is entirely unacceptable that most publications do not address the critical issue of RNA quality assessment. It is equally unacceptable that data are not normalised in an appropriate manner. Third

Third, it is essential that data acquisition, analysis and reporting become more transparent. Consequently, it is essential for the editors of scientific and biomedical publications to issue prescriptive checklists specifying the key information to include when reporting experimental results. There are significant efforts underway to organise such ‘minimum information’ checklists, with the “Minimum information for biological and biomedical investigations” (MIBBI) project offering a common portal aimed at promoting gradual data integration (

Another development concerns the problems associated with attempting to share qPCR data between different laboratories and users. A new initiative, the “Real-time PCR Data Markup Language” (RDML) describes a structured and universal data standard for exchanging qPCR data ( Together with the accompanying guidelines for Minimal Information (MIqPCR), the data standard will contain sufficient information to understand the experimental setup, re-analyse the data and interpret the results. This is of particular importance for transparent exchange of annotated qPCR data between authors, peer reviewers, journals and readers.

Those intimately familiar with the molecular technologies underlying the advances proclaimed by the highest impact factor journals, then taken up by the popular press and finally shaping peoples’ expectations are only too familiar with their serious shortcomings. Unfortunately, it seems that very few researchers are willing to listen and even fewer are willing to change their modi operandi. It really is time to put the horse before the cart, and stop being blinded with ever-more technology.


1. Stahlberg, A., Hakansson, J., Xian, X., Semb, H., and Kubista, M. (2004) Clin Chem 50(3), 509-515

2. Stahlberg, A., Kubista, M., and Pfaffl, M. (2004) Clin Chem 50(9), 1678-1680
3. Bustin, S. A., and Nolan, T. (2004) J Biomol Tech 15(3), 155-166
4. Nolan, T., Hands, R. E., Ogunkolade, B. W., and Bustin, S. A. (2006) Anal Biochem 351, 308-310
5. Nolan, T., Hands, R. E., and Bustin, S. A. (2006) Nature Protocols 1(3), 1559-1582
6. Bustin, S. A. (2005) Expert Rev Mol Diagn 5(4), 493-498
7. Ben-Dov, C., Hartmann, B., Lundgren, J., and Valcarcel, J. (2008) J Biol Chem 283(3), 1229-1233
8. Pettigrew, C. A., and Brown, M. A. (2008) Front. Biosci. 13, 1090-1105
9. Meyer, K. B., Maia, A. T., O'Reilly, M., Teschendorff, A. E., Chin, S. F., Caldas, C., and Ponder, B. A. (2008) PLoS biology 6(5), e108
10. Chen, X., Weaver, J., Bove, B. A., Vanderveer, L. A., Weil, S. C., Miron, A., Daly, M. B., and Godwin, A. K. (2008) Hum. Mol. Genet. 17(9), 1336-1348
11. Coller, J., and Parker, R. (2004) Annu. Rev. Biochem. 73, 861-890
12. Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A., and Speleman, F. (2002) Genome Biol 3(7), 0034.0031-0034.0011
13. Bustin, S. A., and Mueller, R. (2005) Clin Sci (Lond) 109(4), 365-379
14. Huang, T., Bohlenius, H., Eriksson, S., Parcy, F., and Nilsson, O. (2005) Science 309(5741), 1694-1696
15. Uhlmann, V., Martin, C. M., Sheils, O., Pilkington, L., Silva, I., Killalea, A., Murch, S. B., Walker-Smith, J., Thomson, M., Wakefield, A. J., and O'Leary, J. (2002) Mol Pathol 55(2), 84-90
16. Bradstreet, J. J., El Dahr, J., Anthony, A., Kartzinel, J. J., and Wakefield, A. J. (2004) Journal of American Physicians and Surgeons 9, 38-45

Update on 21 January 2010

MIQE, the guidelines for minimim information required for publication of qPCR data have published in Clinical Chemistry.

The real-time polymerase chain reaction uses fluorescent reporter dyes to combine DNA amplification and detection steps in a single tube format. The increase in fluorescent signal recorded during the assay is proportional to the amount of DNA synthesised during each amplification cycle. Individual reactions are characterised by the cycle fraction at which fluorescence first rises above a defined background fluorescence, a parameter previously known as the threshold cycle (Ct) or crossing point (Cp), now standardised by MIQE as the quantification cycle (Cq). Consequently, the lower the Cq, the more abundant the initial target. This correlation permits accurate quantification of target molecules over a wide dynamic range, while retaining the sensitivity and specificity of conventional end-point PCR assays. The homogeneous format eliminates the need for post-amplification manipulation and significantly reduces hands-on time and the risk of contamination. MIQE abbreviates real-time PCR to qPCR, with reverse transcription PCR abbreviated to RT-qPCR.

There are three main chemistries in general use:

    * DNA binding dyes, such as SYBR-Green, which fluoresce upon light excitation when bound to double stranded DNA. These are cheap, easily added to legacy assays and amplification products can be verified by the use of melt curves. They can lack specificity and fluorescence varies with amplicon length. In general, they are one Cq or so more sensitive than probe-based assays. Their main drawback is that the NTCs often come up around Cqs of 36+, although melt curves can often distinguish genuine ampolification from nom-specific noise.

    * Fluorophores attached to primers, e.g. Invitrogen's Lux or Promega's Plexor primers. These are relatively inexpensive and amplification products can be verified by melt curves. Specificity depends on the primers and specific, usually company-specific design software needs to be used for optimal performance. This is not necessarily a bad thing (indeed the Plexor software is very useful), but it is not always possible to change primer design parameters.

    * Probe based methods, e.g. hydrolysis (TaqMan), Scorpions or Molecular Beacons. These are the most specific, as products are only detected if the probes hybridise to the appropriate amplification products. There are many variations on this theme, with melt curve analysis possible for some chemistries. Their main disadvantages are cost, complexity and occasional fragility of probe synthesis, especially when incorporating DNA analogues. There are potential problems associated with the fact that probe-based assays do not report primer dimers that can interfere with the efficiency of the amplification reaction. Hence establishing the efficiency of any assay is an important component of assay design.

qPCR targeting DNA is a robust assay, with assay quality determined mainly by PCR primer quality. Its derivate, RT-qPCR, which targets RNA, on the other hand, is much less robust, as the obligatory conversion of RNA into cDNA can be highly variable.


Reliable quantification requires consideration of each step of the qPCR assay. The issue of quality control is discussed on the QUALITY ASSESSMENT page.