Nearly a third of researchers queried are looking to add digital PCR (dPCR) tools to their labs in the coming year, according to a recent survey by market analysis firm Frost & Sullivan. The much-valued technology provides absolute counts of target nucleic acids, as well as increased sensitivity, precision, and reproducibility over quantitative real-time PCR, or qPCR.
So does this mean it’s time to say goodbye to qPCR? Not quite. Researchers have long relied on qPCR to quickly and accurately detect and quantify target DNA, and it remains the current gold standard for nucleic acid quantification.
When it comes to polymerase chain reaction technologies, it’s not a matter of “either, or.” Rather, both qPCR and dPCR have a solid role in today’s academic, industry, and clinical research labs. Here’s why.
- Established technology means valuable reference literature, well-established best practices. Real-time PCR has been around for more than two decades, which means there’s a lot of data from which to draw when designing and interpreting experiments. In addition, leading scientists have established a set of qPCR best practices called MIQE (minimum information for the publication of quantitative real-time PCR experiments). These guidelines enable researchers to develop robust qPCR experiments, allowing for increased experimental repeatability and reliability.
- Relative measurement is ideally suited for gene expression analysis. Real-time PCR is typically the method of choice for gene expression analysis. In these experiments, changes in target expression results are often compared between experimental conditions, such as the relative expression in diseased versus healthy tissue. In such experiments, the relative nature of qPCR where an unknown concentration is determined through comparison to another sample or standard curve is well-suited.
- Wide choice in detection chemistry and reaction volume equates to flexible running costs. Real-time PCR offers the most choice in detection chemistry. Researchers can select from intercalating dyes (such as SYBR green) to a variety of target-specific probes (TaqMan, molecular beacons, and FRET, for example). qPCR also affords flexible per-sample cost. This comes from being able to easily change reaction volume, throughput, and detection method to meet individual experimental needs.
- Sometimes you need a larger dynamic range. Well-designed qPCR assays can detect as few as several to as many as millions of copies of a target sequence per reaction, giving it a large dynamic range. This attribute enables detection of targets with very low and very high copy number in the same run, ideal for screening or downstream validation experiments.
- Higher-throughput automation compatibility. High sample throughput capabilities due to qPCR instruments’ varying block capacities (96- and 384-well, for example) and automation compatibility make qPCR a good choice for experiments with either high sample number or high target number screening requirements.
- Absolute measurement eliminates the need for a standard curve. Digital PCR is different from qPCR because it partitions the sample and assay reaction components into hundreds or thousands of individual reactions. This allows for the presence or absence of target molecules per partition to be counted after endpoint PCR amplification. Thus, unlike the relative measurements of qPCR, dPCR provides an absolute measurement of copies present per sample volume assayed (i.e., their concentration) and eliminates the need for a standard curve.
- Enables high precision for gene expression, absolute quantitation or copy number variation analysis. The precision and reproducibility achievable with dPCR increases with the number of partitions. High precision enables reliable copy number variation measurements for greater than three copies or detection of gene expression fold-changes lower than 50 percent (e.g., 1.4 vs. 1.6 copies or 5 vs. 6 copies). Achieving such precision and day-to-day or lab-to-lab reprocducibility is a challenge for real-time PCR.
- Greater sensitivity for rare-event detection. Digital PCR’s unique property of partitioning the sample also decreases the amount of background DNA in each reaction, giving greater target amplification specificity and sensitivity. This improves the sensitivity of rare mutation and rare sequence detection. For example, drug development company Sangamo BioSciences relies on dPCR to measure residual levels of HIV DNA in patients enrolled in trials. The company first tried using qPCR, but found the technology was not sufficiently sensitive or reproducible for this challenging application.