Quantitative real-time PCR (qPCR) and digital PCR (dPCR) have much in common with each other—and with traditional, standard PCR. Yet there are some notable differences between them, not only in how they work, but also in what applications they are best used for. Here we compare the two techniques’ workflows, as well as their advantages and disadvantages for various applications—all with an eye toward helping researchers choose the solution that best meets their needs.
The polymerase chain reaction (PCR) is a reiterative process of melting double-stranded DNA (dsDNA) and allowing it to cool enough for sequence-specific primers, flanking a target-of-interest, to bind to the (now) single-stranded DNA templates. This is followed by a rise in temperature to allow DNA polymerase to extend the primers, forming new copies of the original dsDNA—one for each single stranded template—and the process repeats. The amount of target (amplification product) is thus doubled with each cycle, leading to exponential amplification. The product is typically detected after a set number of cycles in end-point PCR by looking for appropriately sized band(s) using agarose gel electrophoresis.
qPCR and dPCR build on traditional PCR.
With qPCR, instead of looking at the reaction at the endpoint, the amount of product is tracked in real time during each cycle. A dye such as SYBR Green will greatly increase its fluorescence when bound to double-stranded DNA, and so the amount of fluorescence will intensify proportionally to the amount of PCR product in the reaction. Alternatively, sequence-specific probes such as TaqMan can similarly be used to track the appearance of double-stranded product. By plotting fluorescence against cycle number, and comparing to a standard curve, it is possible to quantify the amount of amplified product—and thus the amount of sequence-specific target template in the starting sample.
dPCR works on the principle of partitioning the PCR reaction into thousands of individual reactions prior to amplification—each containing a single (or no) template molecule. The reactions are then allowed to go to completion. If a partition contains the sequence of interest, that partition will produce a signal as the dye or probe in the reaction fluoresces. The number of partitions that fluoresce is counted and compared to the number of non-fluorescent partitions, allowing for absolute quantification of the starting material. In contrast to qPCR, no standard curve is necessary for quantification.
Both qPCR and dPCR are versatile technologies, capable of a wide variety of applications. Nonetheless each has its relative strengths and weaknesses. Here are a few areas in which one has an edge over the other.
By its nature, dPCR delivers absolute quantification. qPCR can offer relative quantitation by comparing to a housekeeping gene, or by running titrated reference standards along with experimental samples and constructing a standard curve.
qPCR currently allows for higher-throughput applications, with instruments capable of handling 384 samples (compared to 96 for dPCR), and is amenable to automation. Time-to-result is quicker as well, with “fast” protocols taking as little as 40 minutes.
dPCR can detect smaller fold changes of the amount of target per sample—it can detect the difference between 5 copies of the template in the genome versus 6, for example—while qPCR cannot differentiate less than a 2-fold change. dPCR also requires running fewer replicates compared to qPCR.
dPCR is more tolerant of sample impurities than qPCR; the partitioning of a dPCR sample into microreactions leads to dilution of potential PCR inhibitors. This allows for some “dirtier” samples to be used—such as samples isolated directly from soil or wastewater—potentially reducing the time spent on sample preparation.
Both qPCR and dPCR are extremely valuable for estimating the amount of target molecules in a sample and allow researchers to perform a host of applications. That being said, after factoring in considerations such as number of samples, speed, throughput, and comfort level, there are several such applications for which one or the other is better suited.
To look for single nucleotide polymorphisms (SNPs) and mutations, copy number variations, and genome edits, try dPCR. It is more sensitive and accurate than qPCR, making it the preferred choice for, for example, some gene expression studies and rare event detection.
For applications such as pathogen detection and microbiome analysis, qPCR’s broader dynamic range makes it the recommended technology. Its ability to discriminate splice variants and its amenability to higher throughput are among the considerations making it preferred for some larger-scale gene expression studies as well.
qPCR is a more mature technology than dPCR. That can be interpreted in at least two ways. The first is that qPCR is tried and true, with a host of commercial options and a large catalog of literature and expertise to draw from. The second is that dPCR is still in the exciting stage of development with infinite possibilities ahead. For now, it’s likely that one or both will provide the solution you need.
For additional information on how to choose between qPCR and dPCR, visit go.roche.com/dpcr