Estimation of knockdown resistance in diamondback moth using real-time PASA

• Published in: Pesticide biochemistry and physiology 2004, Vol.78 (1), p.39-48
• Main Authors: Kwon, Deok Ho, Clark, J.Marshall, Lee, Si Hyeock
• Format: Article
• Language: English
• Subjects: Allele frequency; Biological and medical sciences; Fundamental and applied biological sciences. Psychology; Genotyping; Knockdown resistance ( kdr); PASA; Phytopathology. Animal pests. Plant and forest protection; Plutella xylostella; Plutellidae; Pooled DNA; Pyrethroid resistance
• ISSN: 0048-3575; 1095-9939
• DOI: 10.1016/j.pestbp.2003.09.005

We have developed a simple and accurate real-time PASA (PCR amplification of specific allele) (rtPASA) protocol for the estimation of pyrethroid resistance allele frequency in pooled DNA samples using the T929I-mutated allele of sodium channel α-subunit gene from the diamondback moth, Plutella xylostella, as a model. Conditions for the rtPASA for the detection of the T929I mutation were optimized by adjusting annealing temperature, template, and primer concentrations. Using standard DNA mixtures of susceptible and resistant alleles in various ratios, a plot of allele frequency versus cycle threshold value ( C t value) was generated for the prediction of allele frequency. The semi log plot was linear within the 1–80% range of resistance allele frequencies with a high correlation coefficient ( r 2=0.997) when highly stringent conditions (67 °C annealing temperature and 2 ng template DNA) were used. For the detection of lower frequencies of the resistant allele (0.004–1%), another hyperbolic semi log plot was constructed ( r 2=0.983) using the C t values obtained from the rtPASA with less stringent conditions (66 °C annealing temperature and 5 ng template DNA). The rtPASA was able to detect the resistant allele at frequency as low as 0.02%. The performance of the rtPASA was evaluated by comparing with the data generated from 50 individual genotypings. We demonstrated that the actual resistance allele frequency of a field population of P. xylostella precisely matched the predicted frequency deduced by our protocol. The rtPASA format is applicable for the detection of additional mutations associated with resistance in other insect pest species and will allow rapid and efficient monitoring of resistance in field populations in a high throughput format.