Can I use a standard curve established for a range of 10^7 to 10^2 to calculate copies per ml for a sample at 10^9?

Using a Standard Curve Beyond Its Established Range for qPCR Quantification

You should not use a standard curve established for a range of 10^2 to 10^7 to calculate copies per ml for a sample at 10^9 concentration, as this would produce unreliable results due to extrapolation beyond the validated linear range of the assay.

Understanding Standard Curve Limitations in qPCR

The accuracy and reliability of qPCR quantification depends heavily on the quality of the standard curve used for calibration. When analyzing samples that fall outside the established range of your standard curve, several important considerations must be addressed:

Dynamic Range Limitations

• Standard curves in qPCR establish a log-linear relationship between Ct values and log-transformed gene copy quantities within a defined range 1
• The dynamic range of a qPCR assay is specifically defined as the log concentration range over which the standard curve is confirmed to be linear 1
• Extrapolating beyond this validated range introduces significant uncertainty in your measurements

Technical Reasons for Not Extrapolating to 10^9

1. Linearity concerns:

   • The linear relationship between Ct values and log copy numbers is only validated within your established range (10^2 to 10^7)
   • PCR efficiency may change at very high template concentrations due to:
     • Reagent limitations
     • Primer competition
     • Fluorescence signal saturation

2. Reporting requirements:

   • Guidelines for molecular quantification recommend that results should not be reported outside the established reportable range 1
   • When results exceed the upper detection limit, they should be reported as greater than the upper limit of quantification (e.g., >10^7 copies/mL) 1

Proper Approach for High Concentration Samples

To accurately quantify a sample at 10^9 copies/mL, you have two appropriate options:

Option 1: Sample Dilution (Recommended)

1. Dilute your sample to bring it within the validated range (10^2 to 10^7)
2. Perform the qPCR analysis on the diluted sample
3. Apply the dilution factor to calculate the original concentration
4. Example: Dilute sample 1:100, measure concentration, then multiply result by 100

Option 2: Extend Your Standard Curve

1. Create a new standard curve that includes higher concentrations (up to 10^9)
2. Validate the linearity, efficiency, and reproducibility of this extended range
3. Ensure the r² value remains >0.98 across the entire range 1
4. Verify PCR efficiency remains within 90-110% across the extended range 1

Common Pitfalls to Avoid

• Accuracy degradation: PCR efficiency can vary significantly at extreme concentrations. A small change in PCR efficiency from 100% to 97% over 30 cycles causes a 57% difference in estimated input DNA 1

• Reporting errors: Providing numerical values outside the validated range violates good laboratory practice and reporting guidelines 1

• Misinterpreting results: Extrapolated values may appear precise but can be highly inaccurate due to non-linearity at extreme concentrations

• Ignoring dilution errors: Serial dilution introduces propagation of measurement errors that can significantly impact accuracy at the extremes of the range 2, 3

By following proper dilution protocols and adhering to established reporting guidelines, you can ensure accurate and reliable quantification of your high-concentration samples while maintaining scientific integrity in your results.