What is the difference when a standard curve created using synthetic plasmids (Polymerase Chain Reaction (PCR) standards) is used for calculating copy numbers from whole genomic materials?

Differences When Using Synthetic Plasmids for Copy Number Calculations in Whole Genomic Materials

Using synthetic plasmids as standards for calculating copy numbers from whole genomic materials can lead to significant quantification biases, with potential differences of up to one order of magnitude compared to using linear standards like synthetic RNA or cDNA. 1

Key Differences and Limitations

Structural Differences

• Plasmid DNA vs. Genomic DNA/RNA Structure:
  • Synthetic plasmids are typically circular, double-stranded DNA molecules
  • Genomic materials often contain single-stranded RNA or linear DNA
  • This structural difference affects amplification efficiency during PCR 1
  • Non-linearized plasmids show significantly different amplification characteristics compared to linear templates 1

Specific Technical Issues

1. Reverse Transcription Step Variability:

   • DNA plasmid standards bypass the reverse transcription (RT) step required for RNA targets
   • This means plasmid standards fail to account for RT efficiency and variability 1
   • When quantifying RNA targets, this creates systematic underestimation of copy numbers

2. PCR Efficiency Differences:

   • Significant variations in quantification cycle (Cq) values occur between non-linearized plasmids and linear materials 1
   • Standard curves produced with plasmids show greater variability in:
     • Slopes (CV 11-15% for plasmids vs. 2-7% for linear materials)
     • Efficiencies (CV 17-19% for plasmids vs. 5-8% for linear materials) 1

3. Quantification Bias:

   • Up to 9.4-fold bias at high Cq values (40) and 5.5-fold bias at lower Cq values (25) when using circular plasmids 1
   • Chik et al. reported up to 8.4 Cq difference between linearized vs. non-linearized plasmids 1
   • Gerrity et al. found droplet digital PCR-measured copy numbers 5-fold lower than vendor-specified titers for circular plasmid controls 1

4. Reproducibility Issues:

   • Lower r² values for plasmid-based standard curves (0.943 for CDC N1 and 0.897 for CDC N2) compared to RNA/cDNA curves 1
   • This indicates increased proportion of variation attributable to factors other than standard dilution quantities

Recommendations for Accurate Quantification

1. Linearization of Plasmids:

   • Linearize plasmid standards before use to improve accuracy 1
   • Only 8% of studies report linearization of plasmid standards, despite its importance 1

2. Match Standard Type to Target:

   • For RNA targets, use RNA standards when possible
   • For DNA targets, use linear DNA standards that match the target structure

3. Correction Factors:

   • When using plasmid standards for genomic material quantification, apply correction factors to account for structural differences
   • Consider the need to adjust for the difference between double-stranded DNA controls and single-stranded RNA genomes 1

4. DNA Isolation Method Considerations:

   • The DNA isolation method significantly affects calculated copy numbers 2
   • Silica-membrane-based columns may recover plasmid DNA more efficiently than chromosomal DNA (87.4% vs. 46.5%), leading to overestimation of plasmid copy numbers 2

Common Pitfalls to Avoid

1. Assuming Equal Amplification Efficiency:

   • Never assume plasmid standards and genomic targets amplify with equal efficiency
   • PCR efficiency can vary significantly between circular and linear templates 1

2. Ignoring Standard Material Structure:

   • Failing to account for structural differences between standards and targets
   • Not linearizing plasmid standards when appropriate

3. Overlooking Extraction Efficiency:

   • Different extraction methods can recover plasmid and genomic DNA with varying efficiencies 2
   • This can introduce systematic bias in copy number calculations

4. Neglecting RT Step Variability:

   • When quantifying RNA targets using DNA standards, the RT step variability is not accounted for 1
   • This can lead to significant underestimation of target copy numbers

By understanding these differences and implementing appropriate controls and corrections, more accurate quantification of genomic material copy numbers can be achieved when using synthetic plasmid standards.