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freqpcr: estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples

View ORCID ProfileMasaaki Sudo, View ORCID ProfileMasahiro Osakabe
doi: https://doi.org/10.1101/2021.01.19.427228
Masaaki Sudo
1Tea Pest Management Unit, Institute of Fruit Tree and Tea Science, NARO: Kanaya Tea Research Station, 2769, Shishidoi, Kanaya, Shimada, Shizuoka 428-8501, Japan
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  • For correspondence: masaaki@sudori.info
Masahiro Osakabe
2Laboratory of Ecological Information, Graduate School of Agriculture, Kyoto University: Kyoto, Japan
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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 numerous individuals, and subsequently handle each sample, makes quantification of rare mutations, including pesticide resistance genes at the early stages of resistance development, challenging. Meanwhile, pooling DNA from multiple individuals as a “bulk sample” may reduce handling costs. The qPCR output for a bulk sample, however, contains uncertainty owing to variations in DNA yields from each individual, in addition to measurement errors. In this study, we developed a statistical model for the interval estimation of allele frequency using ΔΔCq-based qPCR analyses of multiple bulk samples collected 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, while their confidence intervals suggest that collecting and pooling additional samples from individuals may produce higher precision than individual PCR tests with moderate sample sizes.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Model section was shortened as the first draft was too descriptive on the basic structure of conventional DeltaDeltaCq methods. Figure (graphical summary) 1 was added.

  • https://github.com/sudoms/freqpcr

  • https://doi.org/10.6084/m9.figshare.c.5258027.v1

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 16, 2021.
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freqpcr: estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples
Masaaki Sudo, Masahiro Osakabe
bioRxiv 2021.01.19.427228; doi: https://doi.org/10.1101/2021.01.19.427228
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freqpcr: estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples
Masaaki Sudo, Masahiro Osakabe
bioRxiv 2021.01.19.427228; doi: https://doi.org/10.1101/2021.01.19.427228

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