Real-Time Quantitative PCR (qPCR)
qPCR stands out as a highly effective method for assessing copy number variants and gene expression data. The process entails real-time qPCR detection, resulting in an amplification curve that traverses initiation, exponential, and plateau phases. As the qPCR reaction progresses exponentially, fluorescence rises markedly above the baseline, marking the threshold level crucial for quantitation. The crossing of this threshold by the sample is recorded as the Ct or Cq value, serving as a pivotal quantification point.
In quantitation, the inclusion of a reference gene (RG), which remains consistently expressed across all samples regardless of biological conditions, is indispensable. Commonly utilized RGs like GAPDH and β-actin are chosen cautiously, considering their stability across experimental conditions. Analyzing qPCR data involves selecting between two quantitation methods: absolute and relative gene expression.
Absolute quantitation necessitates meticulous control measures, requiring standard cDNA concentrations for both the reference gene (FG) and gene of interest (GOI). A standard curve generated from log concentrations and Ct values allows for quantification of unknown experimental samples, particularly valuable for identifying DNA copy numbers.
On the other hand, relative quantitation involves calculating the ratio between the reference gene (RG) and the gene of interest (GOI). The accuracy of this method heavily relies on the stability of the chosen reference gene. The delta delta Ct method (2-ΔΔCq) is commonly employed, enabling comparison between clinical and non-clinical samples, validating DNA/RNA results, and quantifying viral, bacterial, or fungal loads.
Furthermore, qPCR serves as a valuable tool for disease progression monitoring in patients and assessing therapeutic efficacy. It provides a cost-effective and time-efficient alternative to sequencing for genotyping work, facilitated by melting point analysis on PCR products using special hybridization probes. Fluorescence detection modules equipped in specialized thermal cyclers monitor fluorescence signals as amplification progresses, with measured fluorescence reflecting the total amplicon amount and changes in fluorescence over time facilitating the calculation of amplicon production in each cycle.
Digital PCR (dPCR)
Digital PCR (dPCR) represents an innovative and potent methodology for precisely quantifying target nucleic acids within a sample, effectively overcoming the limitations inherent in traditional qPCR techniques. The principle behind dPCR’s absolute quantification lies in partitioning the sample into numerous independent PCR sub-reactions, where each partition either contains the target sequence (positive) or lacks it (negative). Upon completion of the PCR reaction, the ratio of fluorescence-positive partitions to the total partitions provides a basis for quantifying the target sequence concentration with a statistically defined accuracy, utilizing Poisson’s distribution statistics.
In contrast to qPCR, which relies on real-time amplification monitoring, dPCR collects fluorescence signals through endpoint measurement, leveraging the number of positive partitions to deduce the target concentration. This approach eliminates the need for a calibration curve, thereby circumventing issues associated with variations in reaction efficiencies. Consequently, dPCR’s capacity to accurately quantify target sequences is particularly advantageous for detecting rare mutations amidst a background of wild-type sequences, as it minimizes template competition.
Moreover, dPCR derives its strength from robust statistical foundations, allowing for the inference of both target concentration and quantification accuracy. The suitability of these methods depends directly on the specific applications of the dPCR assay, whether for absolute quantification or copy number variant analysis. Copy number variation, in particular, refers to the variability in the number of copies of a specific DNA segment relative to a reference genome, illustrating one of the many applications where dPCR excels.
Digital PCR (dPCR) stands as a groundbreaking and robust methodology designed to precisely quantify target nucleic acids within a sample, effectively addressing the limitations encountered with traditional qPCR techniques. The absolute quantification achieved by dPCR hinges on the initial partitioning of the sample into numerous independent PCR sub-reactions, wherein each partition contains either the target sequence (positive) or lacks it (negative). Upon completion of the PCR reaction, the ratio of fluorescence-positive partitions to the total partitions provides a basis for quantifying the concentration of the target sequence with a statistically defined accuracy, employing Poisson’s distribution statistics.
Comparing the Strengths and Applications of qPCR and dPCR
While both qPCR and dPCR offer sensitive detection and precise quantitation, they possess distinct strengths that provide different advantages and disadvantages for various applications. qPCR excels in high throughput and wide dynamic range, making it ideal for screening large numbers of samples. In contrast, dPCR offers unparalleled sensitivity for fractional abundance, such as mutant-to-wild-type ratios, and exhibits exquisite precision. The complementary capabilities of both technologies make them highly valuable, and their combined use offers a diverse range of solutions for various genomic applications.
| Real-time PCR (qPCR) |
Digital PCR |
| Quantitative, relative or absolute but standard curves or reference samples needed |
Quantitative, absolute and no standards or references needed |
Bulk PCR
- Flexible reaction volumes
- Impacted by changes in PCR efficiency as data is collected at the exponential phase
- Prone to inhibitors
|
Sample partitioning
- Higher inhibitor tolerance / increased robustness
- Unaffected by changes in amplification efficiency
- Higher statistical power subject to the Poisson statistics
|
| Measures PCR amplification at each cycle |
Measures at the end of the PCR cycles |
| Detects mutation rate at >1% |
Detects mutation rate at ≥ 0.1% (high signal-to-noise ratio) |
| qPCR relies on standard curves. The need for curves costs time, resources and negatively impacts PCR efficiency |
dPCR does not rely on standard curves, cost and time effective |
| qPCR is less precise, less reproducible and more sensitive to PCR inhibitors and contaminants than dPCR |
Limited reaction mixture volume |
Conclusion
In conclusion, the comparison between qPCR and dPCR reveals distinct strengths and advantages for each method, catering to diverse analytical needs in molecular biology and diagnostics. While qPCR offers high throughput and a wide dynamic range, making it suitable for screening large sample sets, dPCR stands out for its unparalleled sensitivity in detecting fractional abundance and exceptional precision. Both techniques provide valuable tools for gene expression analysis, copy number variation assessment, and other genomic applications. Moreover, the combination of qPCR and dPCR offers a comprehensive approach, harnessing the complementary capabilities of each method to address a broad spectrum of research and clinical challenges. As the field of nucleic acid quantification continues to evolve, the synergy between qPCR and dPCR presents a promising avenue for advancing scientific discovery and improving diagnostic accuracy in various fields.