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

PCR techniques, both quantitative (qPCR) and nonquantitative, have been used to estimate the frequency of a specific allele in a population. However, the labour required to sample numerous individuals and subsequently handle each sample renders the quantification of rare mutations (e.g., pesticide r...

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Autores principales: Sudo, Masaaki, Osakabe, Masahiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300209/
https://www.ncbi.nlm.nih.gov/pubmed/34882971
http://dx.doi.org/10.1111/1755-0998.13554
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author Sudo, Masaaki
Osakabe, Masahiro
author_facet Sudo, Masaaki
Osakabe, Masahiro
author_sort Sudo, Masaaki
collection PubMed
description PCR techniques, both quantitative (qPCR) and nonquantitative, have been used to estimate the frequency of a specific allele in a population. However, the labour required to sample numerous individuals and subsequently handle each sample renders the quantification of rare mutations (e.g., pesticide resistance gene mutations at the early stages of resistance development) challenging. Meanwhile, pooling DNA from multiple individuals as a “bulk sample” combined with qPCR 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 have developed a statistical model to estimate the frequency of the specific allele and its confidence interval when the sample allele frequencies are obtained in the form of ΔΔCq in the qPCR analyses on 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 using 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. The confidence intervals suggest that dividing the bulk samples into more parts will improve precision if the total number of individuals is equal; however, if the cost of PCR analysis is higher than that of sampling, increasing the total number and pooling them into a few bulk samples may also yield comparable precision.
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spelling pubmed-93002092022-07-21 freqpcr: Estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples Sudo, Masaaki Osakabe, Masahiro Mol Ecol Resour RESOURCE ARTICLES PCR techniques, both quantitative (qPCR) and nonquantitative, have been used to estimate the frequency of a specific allele in a population. However, the labour required to sample numerous individuals and subsequently handle each sample renders the quantification of rare mutations (e.g., pesticide resistance gene mutations at the early stages of resistance development) challenging. Meanwhile, pooling DNA from multiple individuals as a “bulk sample” combined with qPCR 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 have developed a statistical model to estimate the frequency of the specific allele and its confidence interval when the sample allele frequencies are obtained in the form of ΔΔCq in the qPCR analyses on 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 using 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. The confidence intervals suggest that dividing the bulk samples into more parts will improve precision if the total number of individuals is equal; however, if the cost of PCR analysis is higher than that of sampling, increasing the total number and pooling them into a few bulk samples may also yield comparable precision. John Wiley and Sons Inc. 2021-12-09 2022-05 /pmc/articles/PMC9300209/ /pubmed/34882971 http://dx.doi.org/10.1111/1755-0998.13554 Text en © 2021 The Authors. Molecular Ecology Resources published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle RESOURCE ARTICLES
Sudo, Masaaki
Osakabe, Masahiro
freqpcr: Estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples
title freqpcr: Estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples
title_full freqpcr: Estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples
title_fullStr freqpcr: Estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples
title_full_unstemmed freqpcr: Estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples
title_short freqpcr: Estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples
title_sort freqpcr: estimation of population allele frequency using qpcr δδcq measures from bulk samples
topic RESOURCE ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300209/
https://www.ncbi.nlm.nih.gov/pubmed/34882971
http://dx.doi.org/10.1111/1755-0998.13554
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