Abstract
PCR techniques, both quantitative (qPCR) and non-quantitative, have been used to estimate allele frequency in a population. However, the labor required to sample more individuals and handle each sample makes it difficult to quantify rare mutations, such as pesticide-resistance genes at the early stages of resistance development. Pooling DNA from multiple individuals as a “bulk sample” may reduce handling costs. The output of qPCR on a bulk sample, however, contains uncertainty owing to variations in DNA yields from each individual, in addition to measurement error. In this study, we developed a statistical model for the interval estimation of allele frequency via ΔΔCq-based qPCR analyses of multiple bulk samples taken from a population. We assumed a gamma distribution as the individual DNA yield and developed an R package for parameter estimation, which was verified with real DNA samples from acaricide-resistant spider mites, as well as a numerical simulation. Our model resulted in unbiased point estimates of the allele frequency compared with simple averaging of the ΔΔCq values, and their confidence intervals suggested collecting more samples from individuals and pooling them may produce higher precision than individual PCR tests with moderate sample sizes.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Allele-frequency estimation based on ΔΔCq
