Why efficiency matters
In real-time PCR (qPCR), the amount of DNA ideally doubles at each cycle. Efficiency tells you how close an assay comes to that ideal. Quantification methods such as ΔΔCt assume an efficiency near 100%, so a poor assay gives misleading fold changes.
From the standard curve
Run a dilution series of a template, often five 10-fold dilutions in triplicate, and plot the Ct values against log10 of the starting quantity. The slope of the line gives the efficiency:
Efficiency = 10^(−1 ÷ slope) − 1
- A slope of −3.32 gives an efficiency of 100%: each cycle doubles the product, so a 10-fold dilution shifts Ct by 3.32 cycles.
- A slope of −3.6 gives about 90%; a slope of −3.1 about 110%.
Example
A standard curve has a slope of −3.40: efficiency = 10^(1 ÷ 3.40) − 1 ≈ 96.8%, an amplification factor of 1.968 per cycle. A ΔCt of 2 between two samples then corresponds to a 1.968² ≈ 3.87-fold difference, rather than the 4-fold given by 2^ΔCt.
Acceptable values
| Efficiency | Interpretation |
|---|---|
| 90% to 110% | acceptable for most assays |
| under 90% | poor primers, secondary structures, suboptimal conditions |
| over 110% | inhibition in concentrated samples, pipetting errors, primer dimers, nonspecific products |
The MIQE guidelines for publishing qPCR data also ask for the R² of the curve, usually above 0.98, and the dynamic range.
Improving efficiency
- Redesign primers to amplify a short product (70 to 200 bp), with a Tm of about 60 °C and no dimers.
- Optimize the annealing temperature with a gradient.
- Check the melt curve for a single peak.
- Dilute samples to reduce inhibitors, and use calibrated pipettes and fresh dilutions.
ΔΔCt and the Pfaffl method
The Livak ΔΔCt method assumes both the target and reference genes amplify at about 100%. If their efficiencies differ by more than a few percent, the Pfaffl method uses each gene’s own efficiency:
Ratio = (E target)^ΔCt target ÷ (E reference)^ΔCt reference
where E is the amplification factor, for example 1.968.