Caffeinated fruit flies help identify potential genes affecting insecticide resistance

Mar 26, 2014

To understand genetic mechanisms underlying insecticide resistance, scientists employed fruit flies and caffeine, a stimulant surrogate for xenobiotics in lab studies on resistance.

As Rachel Carson predicted 50 years ago in her groundbreaking book Silent Spring, crop pests are capable of outwitting the known as xenobiotics that are devised to kill them. This development of resistance to insecticides is a serious problem because it threatens crop production and thereby can influence the availability and costs of many foods as well as the economy.

To understand the underlying , University of Kansas scientists turned to the fruit fly Drosophila melanogaster and caffeine, a that is often employed as a surrogate for xenobiotics in lab studies on resistance.

The researchers tested the response to caffeine for over 1,700 lines of from the Drosophila Synthetic Population Resource (DSPR). They successfully mapped 10 quantitative trait loci, stretches of DNA containing genes linked to either resistance or susceptibility to caffeine, and subsequently identified Cyp12d1-d and Cyp12d1-p, two members of the cytochrome P450 gene family that codes for enzymes that are involved in detoxifying toxic compounds: The scientists found that the two genes contribute over 10 percent of the fruit flies' variation in resistance to caffeine.

This approach can be employed to uncover genes involved in resistance to essentially any drug of interest. In fact, in previous studies (G3: Genes|Genomes|Genetics, August 2013), the authors adopted this approach to identify 45 percent of the genetic variance in the toxicity of the chemotherapeutic medication methotrexate.

Explore further: Highly efficient CRISPR knock-in in mouse

More information: Abstract: "Quantitative genetics of caffeine resistance in Drosophila melanogaster." Chad A. Highfill, Michael A. Najarro, Stuart J. Macdonald. Department of Molecular Biosciences, University of Kansas, Lawrence, KS. abstracts.genetics-gsa.org/cgi-bin/dros14s/showdetail.pl?absno=14531586

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