Top Tips for Consistent qPCR

How to Guide 1 Top Tips for Consistent qPCR Aditi Verma, PhD Quantitative real-time PCR (qPCR) has become a staple of molecular biology laboratories worldwide, with a broad range of applications including gene expression analysis, single nucleotide polymorphism (SNP) genotyping, pathogen detection, copy number variation (CNV) analysis, drug discovery and clinical diagnosis.1 qPCR offers several advantages including, a high dynamic range, high sensitivity, reproducibility and the ability to study multiple samples and genes simultaneously through multiplexing.2 The technique uses a fluorescent probe or dye to enable the detection of the amplification products, allowing them to be quantified in real time. Determining the amplification cycle at which the fluorescence reaches a certain threshold of detection (Ct value) can provide an estimate of the relative abundance of the starting material, while the inclusion of standards of known copy number can enable absolute quantitation. Careful experimental design with appropriate positive and negative controls is extremely important to obtain reliable results in a qPCR experiment. Furthermore, given the sensitivity of qPCR, maintaining good laboratory technique is essential for reproducible results, which applies at all stages of the process from experimental design and sample preparation to data analysis. Let’s look at some of the key considerations for achieving consistent qPCR results. 1. Designing the experiment Before you begin an experiment, it is useful to have a plan of what the experiment requires laid out clearly. This includes the total number of samples to be analyzed, the number of genes to be investigated and the exact comparisons that are to be made. For example, if your experiment involves comparing the transcription of multiple genes after administration of a drug to a cell line, you need to design the experiment so that you have enough (typically three to five) biological replicates of the drug treatment with an equal number of replicates for control (vehicle-treated cells). For each sample and each gene, multiple technical replicates need to be set up too. In addition, you need to include positive, negative and no template controls (NTCs). Calculate the total number of reactions based on all these parameters and choose a suitably sized multi-well plate or set of reaction strips that is/are compatible with your instrument. As an example, if you are investigating 2 genes (1 gene of interest and 1 normalization control) in a total of 8 samples (4 tests and 4 controls) with 3 technical replicates for each reaction, you would have a total of 48 reactions. In addition, you would run NTCs and negative controls for each gene primer set in triplicate, which will add another 12 reactions. You will also need to include positive controls, which may for some experiments be in the form of a standard curve. For standard curves, up to five dilutions for each primer set are typically included using a sample known to be positive for the target. If using complementary DNA (cDNA), ensure the positive control transcribes the target gene at robust and consistent levels. The standard curve, when run in triplicate, will add another 30 reactions. Thus, you will have a total of 90 reactions and choose a 96-well plate for the experiment. TOP TIPS FOR CONSISTENT QPCR 2 How to Guide It is helpful to have the multi-well plate layout printed on a sheet that can be filled prior to starting the experiment so that you know exactly where the samples, reaction mixes with primers and controls go on the plate. This comes in handy when you are loading the plate manually and helps to avoid mistakes. 2. Pipetting technique Good pipetting technique is crucial for successful qPCR experiments. This is because the reaction volumes are quite small and the sensitivity of the technique is high, meaning small errors or carryover can have a big impact on results. Quantification of the genetic material hinges on the extent of detection of the PCR amplicons via the fluorescent probe or dye. Thus, if the amount of the starting material is not consistent, the results will be skewed in favor of the samples for which more starting material was added and the comparison will not be accurate. Even a fraction of a microliter of extra starting material can skew the results, and therefore careful pipetting is very important. Although the normalization controls help to ensure that errors due to erroneous pipetting do not creep in, it is good practice to set at least two or preferably three technical replicates for each reaction to highlight inconsistencies. To help minimize pipetting errors, pipettes should be calibrated regularly, kept clean and well-maintained. Pipetting technique needs to be practiced, ensuring precise volumes are dispensed and remain consistent across multiple wells. Slow and careful pipetting while keeping a visual check on the volumes aspirated and dispensed is good practice. Further, ensuring that excess samples or reagents do not stick to the outside of the pipette tip, making sure that the pipette tip touches the walls of the well while dispensing and avoiding bubbles are some other points to remember. Using filtered pipette tips can help to reduce the introduction of contaminants. Additionally, it is important to ensure reagents are mixed thoroughly. 3. Endogenous (normalization), negative and positive controls There are several types of controls used in a qPCR experiment. Genes that are constitutively transcribed in the sample of interest can serve as endogenous or normalization controls when performing gene transcription studies using cDNA as the template. For genomic DNA (gDNA), a gene that is stable in the genome and unlikely to be lost, such as a housekeeping gene, can be used. The idea behind using these reference genes as normalization controls is that their copy number is expected to be similar across samples and, hence, variation in these genes would reflect differences in sample loading. Normalizing for these reference genes can, thus, provide a more accurate result. Normalizing controls are indispensable for gene transcriptional studies and often multiple reference genes are used in the same experiment to improve rigor. 3 Negative controls and NTCs should be included in the qPCR experiment to rule out contamination in the master mix (NTC) or cross-reactivity in the sample (negative control). Both should result in the absence of a detectable signal for the target gene but, in the case of the negative control only, should still show amplification in the normalization control (if included). Further, positive controls, such as samples in which the genes are known to be present in the case of gDNA or transcribed at robust levels in the case of cDNA, can help verify that the components of the reaction mix are working. Appropriate controls thus help to ensure that the results obtained are accurate by ruling out false positives, false negatives and, in the case of normalization controls, they help to counteract the effects of sample quantity variations. TOP TIPS FOR CONSISTENT QPCR 3 How to Guide 4. Sample preparation The quality and quantity of the DNA that serves as the starting material for qPCR is important for the success of an experiment. It is a good idea to calculate overall how much sample will be required for the experiment as discussed in the section on experimental design. This helps to estimate the amount of starting material, such as tissue or cell culture volumes, that is required. This can also help to decide which method of RNA/DNA extraction will yield an appropriate amount of sample. High quality DNA samples are paramount for successful experiments. Spectrophotometric absorbance readings of RNA and DNA can provide a good estimate of the quality. Further, the integrity value for RNA can be used to decide if the RNA can be used to synthesize cDNA for the qPCR assay. The final concentration of the cDNA/DNA that will be used for the qPCR should be estimated using a spectrophotometric method and an optimum quantity of the sample used for the experiment. Too high or too low a sample concentration will lead to Ct (threshold cycle) values that do not fall in the dynamic range of the instrument and are not reliable. 5. Primer design and standardization Primer design and standardization is crucial to a successful qPCR and great care needs to be taken to ensure that the primers are highly specific and suit the experimental design.4 Several online tools are available to aid with qPCR primer design. You should consider the primer length, annealing temperature, GC content, primer specificity and check for primer dimer formation. A primer length of 18–20 nucleotides is optimal for qPCR primers. Annealing temperatures typically range from 55–60 0 C . If you plan to run multiplex qPCRs or many different single primer reactions on the same plate, the primer annealing temperatures need to match. Aim for a GC content around 40–60%. To check for primer specificity, you will need to perform in silico oligonucleotide alignment checks – for which there are a variety of free online tools – with all the existing RNA/DNA in the species and ensure that the designed primers anneal specifically to the target and to no other sequence of nucleotides. Further, it is good practice to check if the forward and reverse primers have a tendency to anneal to each other and form primer dimers. The designed primer pairs also need to be checked by running small-scale PCR reactions and checking the amplified products by gel electrophoresis to ensure that the primers work, and the PCR reactions result in a single amplicon of the desired size. Additionally, when running the qPCR experiment using DNA intercalating dyes, it is useful to perform melt curve analysis as additional non-specific or off-target products can be identified if present. If performing multiplex qPCR, the qPCR can be run simultaneously in a singleplex and multiplex manner with a small subset of the samples to make sure that the amplification curves match in both cases. As discussed previously, it is important to include the appropriate controls to ensure the primers are working as expected. 6. Reagent quality Positive, negative and NTC controls included in the qPCR experiment will enable you to know if one or more reagents are not working properly; however, you would still not know which reagent is not working. It is therefore best to proactively ensure that the reagents and samples are stored at appropriate temperatures and are of optimum quality. Master mixes whose expiry dates have passed are best avoided. TOP TIPS FOR CONSISTENT QPCR 4 How to Guide Primers, master mixes and samples can be stored as aliquots to prevent contamination of your whole stock and degradation due to temperature fluctuations from repeated freeze–thaw cycles. When starting to use a master mix from a new source or a new batch, it is a good idea to perform a small-scale experiment with controls to ensure that it works as expected. Moreover, you need to choose the master mix with the appropriate qPCR probes/dyes carefully based on the experimental design as there are many different types available, including but not limited to SYBR Green, TaqMan probes, molecular beacons, Eclipse probes, dual hybridization probes and Amplifluor assays. While SYBR Green chemistry is generally used for singleplex qPCR, TaqMan assays are often preferred for multiplex qPCR. 7. Loading the qPCR plate If loading the qPCR manually, caution needs to be exercised in handling a large number of reactions. Common mistakes that happen include loading the samples in the wrong wells, contaminating reactions with unintended samples or master mix and not mixing samples and reagents properly before starting the qPCR reaction. A qPCR experiment would typically have many of these reactions and it can get confusing to know which sample or primer mix goes in which well. Having a printed and filled plate layout comes in handy to avoid confusion in loading the plate. Moreover, it is important to stay focused and avoid distractions if loading the plate manually. To avoid cross-contamination, change pipette tips when going from one sample to another or from one primer reagent mix to the next. Ensure the plate is sealed with an optical adhesive film that is compatible with your instrument to prevent cross contamination and evaporation of the reaction mix during the qPCR. Further, you need to ensure that the reaction components have moved to the bottom of the well and are not sticking to the walls. It is a good idea to spin the plate at a low speed, e.g., 300 x g for about five minutes, after covering the plate with film. 8. Data analysis and ensuring good data quality Once the qPCR run is complete, it is a good idea to check the amplification curves to ensure that the threshold cycle has been selected accurately by the software and the Ct values are reliable for all the replicates. It is also important to check the melt curves, if using an intercalating dye such as SYBR Green, to determine if there was only a single type of amplification product. When analyzing the data, an average of the values of technical replicates is taken to make the data robust. There are several factors that you can investigate to make sure that the data that has been obtained is reliable. The first thing to check would be the controls and standard curves to see if the amplification has followed the logarithmic pattern as expected and there has been no spurious amplification. The Ct values should ideally lie within the range of 20–30. Ct values that are too low indicate saturation of the signal, where too high a concentration of sample has been used, for example. Ct values that are too high would indicate a lack of amplification. This may occur for a number of reasons, including if sample concentrations are too low, there is a problem with the reaction mix or there is a contaminating inhibitor present. This may also be seen when primer dimer formation occurs, appearing late in the reaction when there has been no true amplification of the desired product. It is important to check if the Ct values for the replicates (technical and biological) match. Too much variation among the technical replicates means that your qPCR results are unreliable and variation between biological replicates may indicate issues in the experimental treatments you are testing. TOP TIPS FOR CONSISTENT QPCR 5 How to Guide Once you are happy your data is reliable and robust, the next step is analysis. The commonly employed method of data analysis of differential gene transcription is the ΔΔCt method.5 This method involves the normalization of the data using the endogenous controls and then comparison with the experimental controls to give a relative gene transcription value. Alternative methods, such as presence/absence calling, can be employed depending on the experimental question being asked, qPCR method employed and material being analyzed. In conclusion, qPCR is a powerful technique, which has a variety of uses in research and diagnosis. However, being a sensitive technique, it is often fraught with inconsistent results. A careful approach incorporating the suggestions presented in this guide can help yield reproducible and reliable results. Sponsored by: References 1. Klein D. Quantification using real-time PCR technology: applications and limitations. Trends Mol Med. 2002;8(6):257–260. doi: 10.1016/S1471-4914(02)02355-9 2. Smith CJ, Osborn AM. Advantages and limitations of quantitative PCR (Q-PCR)-based approaches in microbial ecology. FEMS Microbiol Ecol. 2009;67(1):6–20. doi: 10.1111/j.1574-6941.2008.00629.x 3. Chapman JR, Waldenström J. With reference to reference genes: A systematic review of endogenous controls in gene expression studies. PLoS One. 2015;10(11):e0141853. doi: 10.1371/journal.pone.0141853 4. Bustin S, Huggett J. qPCR primer design revisited. Biomol Detect Quantif. 2017;14:19–28. doi:10.1016/j.bdq.2017.11.001 5. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001;25(4):402–408. doi: 10.1006/meth.2001.1262