Andow, D. A., & Alstad, D. N. (1998). F2 screen for rare resistance alleles. Journal of Economic Entomology, 91(3), 572–578. https://doi.
org/10.1093/jee/91.3.572
Chen, H., Rangasamy, M., Tan, S. Y., Wang, H., & Siegfried, B. D. (2010).
Evaluation of five methods for total DNA extraction from western corn rootworm beetles. PLoS One, 5(8), e11963. https://doi.
org/10.1371/journal.pone.0011963
Cowell, R. G., Lauritzen, S. L., & Mortera, J. (2007). A gamma model for
DNA mixture analyses. Bayesian Analysis, 2(2), 333–3 48. https://
doi.org/10.1214/07-BA214
Dias, P. J., Sollelis, L., Cook, E. J., Piertney, S. B., Davies, I. M., & Snow,
M. (2008). Development of a real-t ime PCR assay for detection of
Mytilus species specific alleles: application to a sampling survey
in Scotland. Journal of Experimental Marine Biology and Ecology,
367(2), 253–2 58. https://doi.org/10.1016/j.jembe.2008.10.011
Donnelly, M. J., Isaacs, A. T., & Weetman, D. (2016). Identification, validation, and application of molecular diagnostics for insecticide resistance in malaria vectors. Trends in Parasitology, 32(3), 197–206.
https://doi.org/10.1016/j.pt.2015.12.001
Eypasch, E., Lefering, R., Kum, C. K., & Troidl, H. (1995). Probability of
adverse events that have not yet occurred: A statistical reminder.
BMJ, 311(7005), 619–620.
SUDO and OSAKABE
ffrench-Constant, R. H. (2013). The molecular genetics of insecticide resistance. Genetics, 194(4), 807–815. https://doi.org/10.1534/genet
ics.112.141895
Fukaya, K., Kondo, N. I., Matsuzaki, S. I. S., & Kadoya, T. (2021).
Multispecies site occupancy modeling and study design for spatially
replicated environmental DNA metabarcoding. bioRxiv. https://doi.
org/10.1101/2021.02.14.431192
Fung, T., & Keenan, K. (2014). Confidence intervals for population allele
frequencies: The general case of sampling from a finite diploid population of any size. PLoS One, 9(1), e85925. https://doi.org/10.1371/
journal.pone.0085925
Germer, S., Holland, M. J., & Higuchi, R. (2000). High-throughput SNP
allele-frequency determination in pooled DNA samples by kinetic
PCR. Genome Research, 10(2), 258–266. https://doi.org/10.1101/
gr.10.2.258
Gouws, E. J., Gaston, K. J., & Chown, S. L. (2011). Intraspecific body size
frequency distributions of insects. PLoS One, 6(3), e16606. https://
doi.org/10.1371/journal.pone.0016606
Hedrick, P. W. (2013). Adaptive introgression in animals: examples and
comparison to new mutation and standing variation as sources of
adaptive variation. Molecular Ecology, 22, 4606–4618. https://doi.
org/10.1111/mec.12415
Hothorn, T., Zeileis, A., Farebrother (pan.f), R. W., Cummins (pan.f), C.,
Millo, G., & Mitchell, D. (2019). lmtest: Testing Linear Regression
Models (0.9-37) [Computer software]. https://CRAN.R-projec t.org/
package=lmtest
Knapp, M. (2016). Relative importance of sex, pre-starvation body mass
and structural body size in the determination of exceptional starvation resistance of Anchomenus dorsalis (Coleoptera: Carabidae). PLoS
One, 11(3), e0151459. https://doi.org/10.1371/journal.pone.0151459
Kundu, D., & Manglick, A. (2005). Discriminating between the log-normal
and gamma distributions. Journal of the Applied Statistical Sciences,
14, 175–187.
Leitwein, M., Duranton, M., Rougemont, Q., Gagnaire, P. A., & Bernatchez,
L. (2020). Using haplotype information for conservation genomics. Trends in Ecology & Evolution, 35(3), 245–258. https://doi.
org/10.1016/j.tree.2019.10.012
Livak, K. J., & Schmittgen, T. D. (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT
method. Methods, 25(4), 402–4 08. https://doi.org/10.1006/
meth.2001.1262
Luikart, G., Cornuet, J. M., & Allendorf, F. W. (1999). Temporal changes
in allele frequencies provide estimates of population bottleneck size. Conservation Biology, 13(3), 523–
530. https://doi.
org/10.1046/j.1523-1739.1999.98133.x
Maeoka, A., Yuan, L., Itoh, Y., Saito, C., Doi, M., Imamura, T., Yamaguchi,
T., Imura, T., & Osakabe, M. (2020). Diagnostic prediction of acaricide resistance gene frequency using quantitative real-time PCR
with resistance allele-specific primers in the two-spotted spider
mite Tetranychus urticae population (Acari: Tetranychidae). Applied
Entomology and Zoology, 55, 329–
335. https://doi.org/10.1007/
s13355-020-0 0686-7
May, R. M. (1976). Patterns in multi-species communities. In R. M. May
(Ed.), Theoretical ecology: Principles and applications (pp. 142–162).
Blackwell Scientific Publications. ISBN 0-7216-6205-6.
Mitchell, E. M., Lyles, R. H., & Schisterman, E. F. (2015). Positing, fitting,
and selecting regression models for pooled biomarker data. Statistics
in Medicine, 34(17), 2544–2558. https://doi.org/10.1002/sim.6496
Narasimhan, B., Koller, M., Johnson, S. G., Hahn, T., Bouvier, A., Kiêu,
K., & Gaure, S. (2019). cubature: Adaptive Multivariate Integration
over Hypercubes (2.0.4) [Computer software]. https://CRAN.R-proje
ct.org/package=cubature
Nielsen, R. (2005). Molecular signatures of natural selection. Annual
Review of Genetics, 39, 197–218. https://doi.org/10.1146/annur
ev.genet.39.073003.112420
SUDO and OSAKABE
A Self-archived copy in
Kyoto University Research Information Repository
https://repository.kulib.kyoto-u.ac.jp
Osakabe, M., Imamura, T., Nakano, R., Kamikawa, S., Tadatsu, M.,
Kunimoto, Y., & Doi, M. (2017). Combination of restriction endonuclease digestion with the ΔΔCt method in real-time PCR to monitor etoxazole resistance allele frequency in the two-spotted spider
mite. Pesticide Biochemistry and Physiology, 139, 1–8. https://doi.
org/10.1016/j.pestbp.2017.04.003
Quail, M. A., Smith, M., Coupland, P., Otto, T. D., Harris, S. R., Connor,
T. R., Bertoni, A., Swerdlow, H. P., & Gu, Y. (2012). A tale of three
next generation sequencing platforms: comparison of Ion Torrent,
Pacific Biosciences and Illumina MiSeq sequencers. BMC Genomics,
13(1), 1–13. https://doi.org/10.1186/1471-2164-13-3 41
R Core Team (2019). R version 3.6.1. https://www.r-projec t.org/
Rode, N. O., Holtz, Y., Loridon, K., Santoni, S., Ronfort, J., & Gay, L. (2018).
How to optimize the precision of allele and haplotype frequency estimates using pooled-sequencing data. Molecular Ecology Resources,
18(2), 194–203. https://doi.org/10.1111/1755-0998.12723
Samayoa, L. F., Malvar, R. A., Olukolu, B. A., Holland, J. B., & Butrón, A.
(2015). Genome-wide association study reveals a set of genes associated with resistance to the Mediterranean corn borer (Sesamia
nonagrioides L.) in a maize diversity panel. BMC Plant Biology, 15(1),
35. https://doi.org/10.1186/s12870 -014-0 403-3
Schwartz, M. K., Luikart, G., & Waples, R. S. (2007). Genetic monitoring as a promising tool for conservation and management. Trends
in Ecology & Evolution, 22(1), 25–
33. https://doi.org/10.1016/j.
tree.2006.08.009
Snoeck, S., Kurlovs, A. H., Bajda, S., Feyereisen, R., Greenhalgh, R.,
Villacis-Perez, E., Kosterlitz, O., Dermauw, W., Clark, R. M., & Van
Leeuwen, T. (2019). High-resolution QTL mapping in Tetranychus
urticae reveals acaricide-specific responses and common target-
site resistance after selection by different METI-
I acaricides.
Insect Biochemistry and Molecular Biology, 110, 19–33. https://doi.
org/10.1016/j.ibmb.2019.04.011
Sonoda, S., Inukai, K., Kitabayashi, S., Kuwazaki, S., & Jouraku, A. (2017).
Molecular evaluation of diamide resistance in diamondback moth
(Lepidoptera: Yponomeutidae) populations using quantitative sequencing. Applied Entomology and Zoology, 52(2), 353–357. https://
doi.org/10.1007/s13355-017-0 482-3
Sudo, M., Takahashi, D., Andow, D. A., Suzuki, Y., & Yamanaka, T. (2018).
Optimal management strategy of insecticide resistance under various insect life histories: Heterogeneous timing of selection and
interpatch dispersal. Evolutionary Applications, 11(2), 271–283.
https://doi.org/10.1111/eva.12550
Sudo, M., Yamamura, K., Sonoda, S., & Yamanaka, T. (2021). Estimating
the proportion of resistance alleles from bulk Sanger sequencing,
circumventing the variability of individual DNA. Journal of Pesticide
Science, 46(2), 1–8. https://doi.org/10.1584/jpestics.D20-064
Sugimoto, N., Takahashi, A., Ihara, R., Itoh, Y., Jouraku, A., Van Leeuwen,
T., & Osakabe, M. (2020). QTL mapping using microsatellite linkage reveals target-site mutations associated with high levels of
resistance against three mitochondrial complex II inhibitors in
Tetranychus urticae. Insect Biochemistry and Molecular Biology, 123,
103410. https://doi.org/10.1016/j.ibmb.2020.103410
Takahashi, D., Yamanaka, T., Sudo, M., & Andow, D. A. (2017). Is a larger refuge always better? Dispersal and dose in pesticide resistance evolution. Evolution, 71(6), 1494–1503. https://doi.org/10.1111/evo.13255
Takezaki, N., & Nei, M. (1996). Genetic distances and reconstruction of
phylogenetic trees from microsatellite DNA. Genetics, 144(1), 389–
399. https://doi.org/10.1093/genetics/144.1.389
Taylor, S. M., Juliano, J. J., Trottman, P. A., Griffin, J. B., Landis, S. H., Kitsa,
P., Tshefu, A. K., & Meshnick, S. R. (2010). High-throughput pooling
and real-time PCR-based strategy for malaria detection. Journal
of Clinical Microbiology, 48(2), 512–
519. https://doi.org/10.1128/
JCM.01800-09
Toda, S., Hirata, K., Yamamoto, A., & Matsuura, A. (2017). Molecular diagnostics of the R81T mutation on the D-loop region of the β1 subunit
1393
of the nicotinic acetylcholine receptor gene conferring resistance
to neonicotinoids in the cotton aphid, Aphis gossypii (Hemiptera:
Aphididae). Applied Entomology and Zoology, 52(1), 147–151. https://
doi.org/10.1007/s13355-016-0 449-9
Uesugi, R., Hinomoto, N., & Goto, C. (2016). Estimated time frame for
successful PCR analysis of diamondback moths, Plutella xylostella
(Lepidoptera: Plutellidae), collected from sticky traps in field conditions. Applied Entomology and Zoology, 51(3), 505–510. https://doi.
org/10.1007/s13355-016-0 418-3
Van Leeuwen, T., Demaeght, P., Osborne, E. J., Dermauw, W., Gohlke,
S., Nauen, R., Grbić, M., Tirry, L., Merzendorfer, H., & Clark, R. M.
(2012). Population bulk segregant mapping uncovers resistance
mutations and the mode of action of a chitin synthesis inhibitor
in arthropods. Proceedings of the National Academy of Sciences,
109(12), 4407–4 412. https://doi.org/10.1073/pnas.1200068109
Van Leeuwen, T., Vontas, J., Tsagkarakou, A., Dermauw, W., & Tirry, L.
(2010). Acaricide resistance mechanisms in the two-spotted spider
mite Tetranychus urticae and other important Acari: A review. Insect
Biochemistry and Molecular Biology, 40(8), 563–
572. https://doi.
org/10.1016/j.ibmb.2010.05.008
Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De
Paepe, A., & Speleman, F. (2002). Accurate normalization of real-
time quantitative RT-PCR data by geometric averaging of multiple
internal control genes. Genome Biology, 3(7), 1–12.
Wiens, B. L. (1999). When log-normal and gamma models give different
results: A case study. The American Statistician, 53(2), 89–93.
Wright, S. (1965). The interpretation of population structure by F-
statistics with special regard to systems of mating. Evolution, 395–
420. https://doi.org/10.1111/j.1558-5646.1965.tb01731.x
Yamamura, K., & Hino, A. (2007). Estimation of the proportion of defective units by using group testing under the existence of a threshold of
detection. Communications in Statistics—Simulation and Computation,
36(5), 949–957. https://doi.org/10.1080/03610910701539278
Yamamura, K., Mano, J., & Shibaike, H. (2019). Optimal definition of the
limit of detection (LOD) in detecting genetically modified grains
from heterogeneous grain lots. Quality Technology & Quantitative
Management, 16(1), 36–53. https://doi.org/10.1080/16843703.2017.
1347992
Yelin, I., Aharony, N., Tamar, E. S., Argoetti, A., Messer, E., Berenbaum,
D., Shafran, E., Kuzli, A., Gandali, N., Shkedi, O., Hashimshony, T.,
Mandel-
Gutfreund, Y., Halberthal, M., Geffen, Y., Szwarcwort-
Cohen, M., & Kishony, R. (2020). Evaluation of COVID-19 RT-qPCR
test in multi-sample pools. Clinical Infectious Diseases, 71, 2073–
2078. https://doi.org/10.1093/cid/ciaa531
Zaccara, S., Quadroni, S., De Santis, V., Vanetti, I., Carosi, A., Crosa, G.,
Britton, J. R., & Lorenzoni, M. (2021). Genetic and phenotypic displacement of an endemic Barbus complex by invasive European
barbel Barbus barbus in central Italy. Biological Invasions, 23(2), 521–
535. https://doi.org/10.1007/s10530 -020-02379-2
S U P P O R T I N G I N FO R M AT I O N
Additional supporting information may be found in the online version of the article at the publisher’s website.
How to cite this article: Sudo, M., & Osakabe, M. (2022).
freqpcr: Estimation of population allele frequency using qPCR
ΔΔCq measures from bulk samples. Molecular Ecology
Resources, 22, 1380–1393. https://doi.
org/10.1111/1755-0998.13554
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