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Tania Nolan - Articles and news items
The tremendous increase in the number of laboratories using qPCR and publications relying on qPCR data are testament to the rapid uptake of this technology. When preceded by reverse transcription (RT-qPCR) it is regarded as the reference technique for validation of previously derived data such as from microarray studies and as the output with which to measure transcript changes after pathway disruption such as by transfection with siRNA or shRNA.
A pivotal attraction of qPCR technology is its apparent lack of complication; an assay consisting of the simple procedure of combining oligonucleotides, PCR mastermix buffer and nucleic acid template to produce a qPCR reaction is perceived as undemanding. This practical simplicity is complemented by the absence of any requirement for post-assay handling, as well as the development of user-friendly data analysis software that makes data generation and visualisation in the shape of amplification plots remarkably simple. However, as we have set out in the first four articles of this series, the translation of an attractive amplification plot into accurate and meaningful data is far from trivial and requires a range of additional considerations.
The deceptive simplicity of a typical qPCR assay is an important reason for the exponential growth in the adoption of qPCR-related technologies for both research and diagnostic applications. The only requirements for obtaining ostensibly quantitative data are a mixing of primers, DNA and a mastermix, their distribution into individual tubes or wells, turning on a qPCR instrument and collection of threshold cycles (Cqs). Indeed, it is remarkably difficult to make a reaction fail completely but alarmingly simple to produce poor quality data1. Furthermore, it is of great concern that many ready-to-run commercially available systems adopt protocols that discourage the user from performing assay optimisation or validation steps, resulting in the publication of vast volumes of potentially meaningless data. Inevitably this has lead to inaccurate conclusions and publication retractions2,3. Consequently, assay optimisation, validation and critical data evaluation are essential practice if the integrity of the scientific study is to be preserved4.
Real-time PCR (qPCR) data are reliable only if they result from a robust qPCR assay that has been carefully designed, validated and optimised. This process requires an extensive assay design procedure aimed at generating an optimum primer/probe/amplicon combination to allow accurate quantification of nucleic acids with minimum need for post-PCR analyses (see Figure 1).
The fluorescence-based quantitative real-time polymerase chain reaction (qPCR)1-3, is the most widely used method to detect and measure minute amounts of DNA in a wide range of samples extracted from numerous sources. Since all currently available thermostable polymerases are DNA-dependent, RNA must be converted (“reverse transcribed”) into DNA prior to its amplification reaction. Both qPCR and reverse transcription (RT)-qPCR have revolutionised life sciences, agriculture, medical research and diagnostic and forensic applications4,5.
he fluorescence-based quantitative real-time polymerase chain reaction (qPCR)1-3, has the ability to detect and measure minute amounts of DNA in a wide range of samples extracted from numerous sources. In combination with reverse transcription (RT), the use of this technology has revolutionised life sciences, agriculture and medical research4,5. In addition, many diagnostic applications have been developed, including microbial quantification, cancer recurrence risk assessment, gene dosage determination, identification of transgenes in genetically modified foods, and detection of extremely low copy targets for forensic investigations6-11. The simplicity of assay design and execution, together with sensitivity and specificity have made this the method of choice for nucleic acid quantification that is reflected by the prodigious number of peer-reviewed publications reporting qPCR data. Inevitably, a corresponding number of different protocols, reagent recipes, analysis methods and reporting formats are also being used, which is resulting in the scientific literature being corrupted with publications reporting insignificant and conflicting results. The inexperienced or casual qPCR user is vulnerable to the production of inaccurate data because even assays of extremely poor quality usually yield results that are amenable to statistical manipulation.
ABB Analytical Measurement ACD/Labs ADInstruments Ltd Advanced Analytical Technologies GmbH Analytik Jena AG Astell Scientific Ltd B&W Tek Bachem AG Bibby Scientific Limited Bio-Rad Laboratories BioNavis Ltd Biopharma Group Black Swan Analysis Limited Butterworth Laboratories Ltd CAPSUGEL NV Charles Ischi AG | Kraemer Elektronik Cherwell Laboratories CI Precision Cobalt Light Systems Coulter Partners CPC Biotech srl Dassault Systèmes BIOVIA DiscoverX Edinburgh Instruments Enterprise System Partners (ESP) Eurofins BioPharma Product Testing EUROGENTEC F.P.S. Food and Pharma Systems Srl GE Analytical Instruments IDBS JEOL Europe L.B. Bohle Maschinen + Verfahren GmbH Lab M Ltd. LabWare Linkam Scientific Instruments Limited MA Business Metrohm Molins Technologies Multicore Dynamics Ltd Nanosurf New England Biolabs, Inc. Ocean Optics Panasonic Biomedical Sales Europe B.V. PerkinElmer Inc ReAgent Russell Finex Limited Source BioScience Takara Clontech Tornado Spectral Systems Tuttnauer Viavi Solutions, Inc Watson-Marlow Fluid Technology Group Wickham Laboratories Limited Xylem Analytics YMC Europe GmbH Yusen Logistics