Taqman Assay for Genotyping CKD-Associated APOL1 SNP rs60910145: A Cautionary Note.
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ABSTRACT:
SUBMITTER: David VA
PROVIDER: S-EPMC6308993 | biostudies-literature | 2019 Jan
REPOSITORIES: biostudies-literature
Publications
Taqman Assay for Genotyping CKD-Associated APOL1 SNP rs60910145: A Cautionary Note.
David Victor A VA Binns-Roemer Elizabeth A EA Winkler Cheryl A CA
Kidney international reports 20181001 1
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Project description:BackgroundPesticide resistance monitoring is a crucial part to achieving sustainable integrated pest management (IPM) in agricultural production systems. Monitoring of resistance in arthropod populations is initially performed by bioassay, a method that detects a phenotypic response to pesticides. Molecular diagnostic assays, offering speed and cost improvements, can be developed when the causative mutation for resistance has been identified. However, improvements to throughput are limited as genotyping methods cannot be accurately applied to pooled DNA. Quantifying an allele frequency from pooled DNA would allow faster and cheaper monitoring of pesticide resistance.Methodology/principal findingsWe demonstrate a new method to quantify a resistance allele frequency (RAF) from pooled insects via TaqMan assay by using raw fluorescence data to calculate the transformed fluorescence ratio k' at the inflexion point based on a four parameter sigmoid curve. Our results show that k' is reproducible and highly correlated with RAF (r >0.99). We also demonstrate that k' has a non-linear relationship with RAF and that five standard points are sufficient to build a prediction model. Additionally, we identified a non-linear relationship between runs for k', allowing the combination of samples across multiple runs in a single analysis.Conclusions/significanceThe transformed fluorescence ratio (k') method can be used to monitor pesticide resistance in IPM and to accurately quantify allele frequency from pooled samples. We have determined that five standards (0.0, 0.2, 0.5, 0.8, and 1.0) are sufficient for accurate prediction and are statistically-equivalent to the 13 standard points used experimentally.
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