Impact of Amplification Efficiency Approaches on Telomere Length Measurement via Quantitative-Polymerase Chain Reaction - Hastings, Waylon J.; Eisenberg, Dan T. A.; Shalev, Idan (Frontiers in Genetics, 2021)
Background: Precise determination of amplification efficiency is critical for reliable conversion of within-sample changes in fluorescence occurring on a logarithmic scale to between-sample differences in DNA content occurring on a linear scale. This endeavor is especially challenging for the telomere length (TL) qPCR assay, where amplification efficiency can vary between reactions targeting telomeric repeats (T) and those targeting a single-copy gene (S) to calculate TL as the T/S ratio. Methods: We compared standard-curve methods to estimate amplification efficiency utilized by the qPCR-instrument software to alternative approaches which estimate efficiency on a reaction-by-reaction basis. After calculating T/S ratios using efficiency estimates from each approach (N=363), we tested their performance on metrics of assay precision and correlates of external validity. Results: Estimated efficiency for telomere reactions was significantly lower than estimates for single-copy gene reactions. Efficiency estimates for both reaction sets were significantly higher when estimated with the qPCR-instrument standard-curve relative to estimates reconstructed during the log-linear phase with LinRegPCR. While single-copy gene efficiency reconstructed using LinRegPCR measured within 90% of perfect exponential doubling (E=1.92), estimates generated using the standard-curve were inflated beyond 100% (E=2.10-2.12), indicating poor fidelity. Despite differences in raw value, TL measurements calculated with LinRegPCR efficiency estimates exhibited similar relationships with external-validity correlates to measurements generated using the qPCR-instrument software. Conclusions: Since methods to estimate amplification efficiency can vary across qPCR instruments, we suggest that future analyses empirically consider external methods of efficiency calculations such as LinRegPCR, and that already generated data be re-analyzed to glean possible improvements.