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 the latest publications  real-time PCR optimisation (5)

Eleven golden rules of quantitative RT-PCR    ... NEW !

The MIQE guidlines  &  The MIQE press review   ...UPDATE !

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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.
Current problems in quantitative real-time RT-PCR by T. Nolan, RE. Hands & SA Bustin;  Nature Protocols (2006) Vol. 1, No. 3; p1559-1582 The real-time reverse transcription polymerase chain reaction (RT-qPCR) addresses the evident requirement for quantitative data analysis in molecular medicine, biotechnology, microbiology and diagnostics and has become the method of choice for the quantification of mRNA. Although it is often described as a ‘‘gold’’ standard, it is far from being a standard assay. The significant problems caused by variability of RNA templates, assay designs and protocols, as well as inappropriate data normalization and inconsistent data analysis, are widely known but also widely disregarded. The widespread use of this technology has resulted in the development of numerous protocols that generate quantitative data using: fresh, frozen or archival FFPE (formalin-fixed, paraffinembedded) samples, whole-tissue biopsies, microdissected samples, single cells, tissue culture cells, total or mRNA, a range of different cDNA priming strategies, different enzymes or enzyme combinations, assays of variable efficiency, sensitivity and robustness, diverse detection chemistries, reaction conditions, thermal cyclers and individual analysis and reporting methods. This obvious lack of standardization at every step of the assay (Figure 1) is exacerbated by significant differences in sample processing, use of controls, normalization methods and quality control management and has serious implications for the reliability, relevance and reproducibility of RT-qPCR. An overview of the considerations relating to procedures and alternative steps for carrying out the RT-qPCR reaction is shown in Figure 2.
Click to enlarge!	Click to enlarge! Quantification of mRNA using real-time RT-PCR Tania Nolan, Rebecca E Hands & Stephen A Bustin Nature Protocols (2006) Vol. 1, No. 3; p1559-1582
PCR Troubleshooting and Optimization - The Essentail Guide edited by Suzanne Kennedy & Nick Oswald Chapter 5 - RT-PCR Optimisation Strategies by Martina Reiter & Michael W. Pfaffl Physiology Weihenstephan, Weihenstephaner Berg 3, 85354 Freising, Germany PCR technology is based on a simple principle; an enzymatic reaction that increases the initial amount of nucleic acids. This method makes it possible to detect specific mRNA transcripts in any biological sample. Performing RT-PCR analysis does not only comprehend this experimental PCR step. Following the whole workflow of a RT-PCR quantitative analysis, it starts with the sampling step, followed by nucleic acid extraction and stabilization, cDNA synthesis and finally the qPCR where the mRNA quantification takes place. Problems arise when optimization of the experimental work flow becomes necessary because of high technical variations. The PCR reaction itself is a quite stable reaction with reproducibility between 2-8%. Therefore the source of experimental variances can often be found in the pre-PCR analytical steps. Usually this is neglected and optimization is done for PCR reaction only. In this chapter – RT-PCR optimization strategies - the whole workflow of RT-PCR experiment will be discussed, because the identification of the source of variability is only possible following error accumulation in every single step. Reliable data can be created when the technical variance caused by the experimental steps is kept as low as possible. In this chapter many recommendations to decrease the technical variance can be found.
Thermocycler Calibration Guide by Cyclertest.com PCR was invented over 25 years ago by Kary Mullis [Saiki, 1985], for which he received the Nobel Prize in chemistry in 1993 [Malmström, 1997]. PCR is considered to be the innovation which allowed molecular biology to evolve to the current level. It has become an indispensable technique in life science research and more recently in routine human and veterinary diagnostics. PCR has evolved over the past decades from a technically complicated method to a simple and easy to apply method. There is a wide variety of ready-to-use reagents available that allows those with some basic training and who master the skill of pipetting to perform a PCR. Enzymes and instruments have been continously engineered to speed up the PCR process, so that a PCR can presently be performed in less than half an hour. However, the simplicity of the method is its strength and weakness at the same time. As it is relatively easy to generate a result many PCR users fail to appreciate the quality control that is required to generate reliable and meaningful results. With the more recent use of PCR in diagnostics the call for quality control is increasing in accredited and quality aware laboratories. An increasing number of laboratories either elect or are required to obtain an ISO 17025 [CEN, 2005] or ISO 15189 [CEN, 2007] accreditation to guarantee the quality of the results generated. At the same time, the research community’s call for biologically meaningful conclusions is increasing in parallel. In 2009 a group of leading PCR scientists published guidelines (MIQE) [Bustin, 2009], that assist qPCR users to design a robust qPCR experiment that leads to trustworthy and biologically meaningful results which can be reproduced in any other laboratory. The main variables of the (q)PCR reaction are the purity and quality of the template DNA or cDNA, the design, purity and concentration of the primers and probes, the concentration of the different reagents, the type of buffer and the type of enzyme, the tubes, strips or plates and the thermocycler used (figure 1). The vast majority of (q)PCR optimizations are performed on the variables of DNA, primers and template. Yet, very little attention is paid to the contribution of the variability of tubes and thermocycler to the (q)PCR result, as they are incorrectly considered to be constants rather than variables. Figure 1:   Main variables of qPCR process The goal of this Thermocycler Calibration Guide is to illustrate which types of thermocycler variability do exist, show the impact of thermocycler variability on the outcome of PCRs or qPCRs, and offer practical solutions how to eliminate or control thermocycler variability. The practical protocols allows us to put into practical use the data from CYCLERtest Calibration Certificates and Reports. Examples will be given showing how thermocyclers can be aligned and programmed to mimic each other. Furthermore, examples will be given showing how calibration results can be used for validation purposes when working under ISO 17025, ISO 15189 accreditation and many other regulations. This guide will allow PCR and qPCR users to explore the full potential of CYCLERtest thermocycler calibration data. download => Cyclertest thermocycler calibration guide
The below publications, protocols, and international programs should help, to optimize your PCR and qRT-PCR assays: International Programs Eleven golden rules of quantitative RT-PCR Recent papers for optimising your qPCR PCR additives - NEW NEW publications and manuals
REVIEW - qPCR Satellite Symposium Optimisation,  Normalisation  &  Standardisation 10-11th March 2005 http://leipzig05.gene-quantification.info
Real-Time PCR Troubleshooting Tool Having problems with your gene expression or SNP genotyping experiments? Do your amplification curves look sigmoidal, or do you have no curves at all? Do your allelic discrimination plots have diffuse or trailing clusters? Our interactive troubleshooting tool will guide you step by step to a solution.

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International Programs:

The MIQE Guidelines Minimum Information for Publication of Quantitative Real-Time PCR Experiments Stephen A. Bustin, Vladimir Benes, Jeremy A. Garson, Jan Hellemans, Jim Huggett, Mikael Kubista, Reinhold Mueller, Tania Nolan, Michael W. Pfaffl, Gregory L. Shipley, Jo Vandesompele, & Carl T. Wittwer Clinical Chemistry 2009, 55(4): 611-622 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. SUMMARY:  Following these guidelines will encourage better experimental practice, allowing more reliable and unequivocal interpretation of qPCR results. http://miqe.gene-quantification.info/

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Nucleic Acids Research Group (NARG)

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Eleven golden rules of quantitative RT-PCR

Eleven golden rules of quantitative RT-PCR
Udvardi MK, Czechowski T, Scheible WR.
Plant Cell. 2008 20(7): 1727

Reverse transcription followed by quantitative polymerase chain reaction analysis, or qRT-PCR, is an extremely sensitive, cost-effective method for quantifying gene transcripts from plant cells. The availability of nonspecific double-stranded DNA (dsDNA) binding fluorophors, such as SYBR Green, and 384-well-plate real-time PCR machines that can measure fluorescence at the end of each PCR cycle make it possible to perform qRT-PCR on hundreds of genes or treatments in parallel. This has facilitated the comparative analysis of all members of large gene families, such as transcription factor genes (Czechowski et al., 2004). Given the relatively low cost of PCR reagents, and the precision, sensitivity, flexibility, and scalability of qRT-PCR, it is little wonder that thousands of research labs around the world have embraced it as the method of choice for measuring transcript levels. However, despite its popularity, we continue to see systematic errors in the application of methods for qRT-PCR analysis, which can compromise the interpretation of results. The letter to the editor by Gutierrez et al. in this issue highlights one of many common sources of error, namely, the inappropriate choice of reference genes for normalizing transcript levels of test genes prior to comparative analysis of different biological samples. The following are 11 golden rules of qRT-PCR that, when observed, should ensure reproducible and accurate measurements of transcript abundance in plant and other cells. These rules are for relative quantification of RNA using two-step RT-PCR (where the product of a single RT reaction is used as template in multiple PCR reactions), SYBR Green to detect gene-specific PCR products, and reference genes for normalizing transcript levels of test genes before comparing samples. Further details can be found elsewhere (Czechowski et al., 2004, 2005). Most of these rules also apply to relative quantification methods that employ sequence-specific fluorescent probes, such as TaqMan probes, and to absolute quantification methods.

1. Harvest material from at least three biological replicates to facilitate statistical analysis of data, freeze immediately in liquid nitrogen, and store at –80°C to preserve full-length RNA.
2. Use an RNA isolation procedure that produces high-quality total RNA from all samples to be analyzed. Check RNA quality using an Agilent 2100 Bioanalyzer (RNA integrity number, RIN > 7 and ideally > 9) or by electrophoretic separation on a high-resolution agarose gel (look for sharp ethidium bromide–stained rRNA bands) and spectrophotometry (A260/A280 > 1.8 and A260/A230 > 2.0). Quantify RNA using A260 values.
3. Digest purified RNA with DNase I to remove contaminating genomic DNA, which can act as template during PCR and lead to spurious results. Subsequently, perform PCR on the treated RNA, using gene-specific primers, to confirm absence of genomic DNA.
4. Perform RT reactions with a robust reverse transcriptase with no RNaseH activity (like SuperScriptIII from Invitrogen or ArrayScript from Ambion) to maximize cDNA length and yield. Use ultraclean oligo(dT) primer of high integrity. qRT-PCR gene expression measurements are comparable only when the same priming strategy and reaction conditions are used in all experiments and reactions contain the same total amount of RNA (Ståhlberg et al., 2004).
5. Test cDNA yield and quality. Perform qPCR on an aliquot of cDNA from each sample, using primers to one or more reference genes that are known to be stably expressed in the organ(s) / tissue(s) under the range of experimental conditions tested. Threshold cycle (Ct) values should be within the range mean ±1 for each reference gene across all samples to ensure similar cDNA yield from each RT reaction. Quality of cDNA can be assessed using two pairs of primers for a reference gene that are ~1 kb apart. Typically, the Ct value for the primer pair at the 5'-end of a cDNA will be higher than the Ct value of the primer pair at the 3'-end, as reverse transcription begins at the 3' [poly(A)] end of the template mRNA and does not always extend to the 5'-end of the template. Ideally, the Ct value of the 5'-end primer pair should not exceed that of the 3'-end pair by more than one cycle number.
6. Design gene-specific PCR primers using a standard set of design criteria (e.g., primer Tm = 60 ± 1°C, length 18 to 25 bases, GC content between 40 and 60%), which generate a unique, short PCR product (between 60 and 150 bp) of the expected length and sequence from a complex cDNA sample in preliminary tests, to facilitate multiparallel qPCR using a standard PCR program. The 3'-untranslated region is a good target for primer design because it is generally more unique than coding sequence and closer to the RT start site.
7. Reduce technical errors in PCR reaction setup by standardizing (robotize if possible) and minimizing the number of pipetting steps. Mix cDNA with qPCR reagents, then aliquot a standard volume of this "master mix" into each reaction well containing a standard volume of specific primers. Set up reactions in a clean environment free of dust, preferably under a positive airflow hood. Routinely check for DNA contamination of primer and reagent stocks by performing PCR reactions on no template (water) controls.
8. For relative quantification of transcript levels, design and test gene-specific primers for at least four potential reference genes selected from the literature (e.g., Czechowski et al., 2005) or from your own experience that are likely to be stably expressed throughout all organs and treatments to be compared. Validate reference genes in preliminary experiments on the range of tissues and treatments you wish to compare using a foreign cRNA added to each RNA sample prior to RT-PCR to normalize data for reference gene transcripts prior to assessment of their expression stability (Czechowski et al., 2005).
9. Perform real-time PCR on test and reference genes in parallel for each sample to capture fluorescence data on dsDNA after each cycle of amplification. Also, perform dsDNA melting curve analysis at the end of the PCR run. When relying on nonspecific DNA binding fluorophors, such as SYBR Green, to quantify relative dsDNA amount, ensure that only a single PCR amplicon of the expected length and melting temperature is produced using gel electrophoresis and PCR amplicon melting curve data, respectively. We typically use a commercial mixture of hot-start Taq polymerase, SYBR Green, and other reagents, such as Power SYBR Green Master Mix from Applied Biosystems, and have observed significant differences in the efficacy (PCR efficiency, specificity, and/or yield) of such products from different suppliers.
10. Determine which reference gene(s) is best for normalization of test gene transcript levels amongst all samples (e.g., using geNorm [Vandesompele et al., 2002] or BestKeeper software [Pfaffl et al., 2004]), which use as input not only the Ct value, but also the PCR efficiency for each reaction. PCR efficiency can be derived conveniently from amplification plots using the program LinRegPCR (Ramakers et al., 2003). Estimation via the classical calibration dilution curve and slope calculation is also possible, albeit more complicated.
11. Finally, calculate relative transcript abundance for each gene in each sample using a formula that incorporates PCR efficiency for the test gene and Ct values for both test and reference genes.
    
    

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  New papers for optimising your qPCR:

• Standardization of real-time PCR gene expression data from independent biological replicates.
• Control of Contamination Associated with PCR and Other Amplification Reactions.
• Enhancing the efficiency of a PCR using gold nanoparticles.
• Increasing Detection of Polymerase Chain Reaction (PCR) by Isolation of PCR Products (IPCRp).
• Increased efficiency of genetic profiling through quantity and quality assessment of fluorescently labeled oligonucleotide primers.
• Primers with 5′ flaps improve real-time PCR.
• A real-time polymerase chain reaction-based evaluation of cDNA synthesis priming methods.
• Comparison of quantitative competitive polymerase chain reaction–enzyme-linked immunosorbent assay with LightCycler-based polymerase chain reaction for measuring cytomegalovirus DNA in patients after hematopoietic stem cell transplantation.
• Performance evaluation of thermal cyclers for PCR in a rapid cycling condition.
• Sensitivity comparison of real-time PCR probe designs on a model DNA plasmid.
• Real-time RT-PCR and SYBR Green I melting curve analysis for the identification of Plum pox virus strains C, EA, and W: Effect of amplicon size, melt rate, and dye translocation.
• Comparison of two standardisation methods in real-time quantitative RT-PCR to follow Staphylococcus aureus genes expression during in vitro growth.

Recent papers for optimising your qPCR:

• Standardizing the standards !
• Evaluation of probe chemistries and platforms to improve the detection limit of real-time PCR.
• Optimized real-time quantitative PCR measurement of male fetal DNA in maternal plasma.
• Determination of allele frequency in pooled DNA: comparison of three PCR-based methods.
• Evaluation of dual-labeled fluorescent DNA probe purity versus performance in real-time PCR.
• Diagnostic PCR: validation and sample preparation are two sides of the same coin.
• Risk assessment of false-positive qPCR results in food, due to detection of DNA originating from dead cells.
• EQUAL-quant: an international external quality assessment scheme for real-time PCR.
• Faster quantitative real-time PCR protocols may lose sensitivity and show increased variability.
• Real-time RT-PCR: considerations for efficient and sensitive assay design
• Gene expression analysis by real-time reverse transcription polymerase chain reaction: influence of tissue handling 
• High temperature fluorescence acquisition 
• How to reduce primer dimers (3 papers) 
• Standardization and quality control of PCR analyses
• qPCR optimisation for low copy number
• Homemade SYBR Green Mix
• Normalisation
• Single cell qPCR  (1)                                           More single-cell qPCR papers => HERE
  
• Single cell qPCR (2)
• Potential influence of the first PCR cycles in real-time comparative gene quantifications.
  
• Reagent volume and plate bias in real-time polymerase chain reaction.
• cDNA synthesis conditions 

Novel UNIQ qPCR PT Scheme

 http://www.mfbprog.org.uk

A new PT scheme has been developed, providing an opportunity for users to obtain confidential and unbiased assessment of their QPCR performance.  The PT has been developed under the DTI-funded Measurements for Biotechnology (MfB) programme as part of an initiative to improve the comparability of results between laboratories, and the materials for the first round will be sent out this September.
The scheme takes an innovative approach, and uses synthetic DNA targets in a proprietary artificial matrix to allow researchers and analysts from all sectors to participate without fears of laboratory contamination.  Participants will be required to perform basic DNA quantification of a high concentration DNA stock, DNA extraction of 9 unknown samples and QPCR analysis of the 9 unknown samples plus 3 additional unknowns. Results will be compared between participating laboratories, and performance will be scored using a conventional PT Z-scoring approach. By taking part in the scheme, participants will be able to demonstrate the overall effectiveness of their performance, which is increasingly important to maintain the confidence of customers and funding bodies.               UNIQ-PT-scheme-flier.pdf

  Steps and variables of a successful mRNA quantification using real-time RT-PCR

Click to enlarge !	Click to enlarge !