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A fitness assay for comparing RNAi effects across multiple C. elegans genotypes
A fitness assay for comparing RNAi effects across multiple C. elegans genotypes
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A fitness assay for comparing RNAi effects across multiple C. elegans genotypes
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A fitness assay for comparing RNAi effects across multiple C. elegans genotypes
A fitness assay for comparing RNAi effects across multiple C. elegans genotypes

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A fitness assay for comparing RNAi effects across multiple C. elegans genotypes
A fitness assay for comparing RNAi effects across multiple C. elegans genotypes
Journal Article

A fitness assay for comparing RNAi effects across multiple C. elegans genotypes

2011
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Overview
Background RNAi technology by feeding of E. coli containing dsRNA in C. elegans has significantly contributed to further our understanding of many different fields, including genetics, molecular biology, developmental biology and functional genomics. Most of this research has been carried out in a single genotype or genetic background. However, RNAi effects in one genotype do not reveal the allelic effects that segregate in natural populations and contribute to phenotypic variation. Results Here we present a method that allows for rapidly comparing RNAi effects among diverse genotypes at an improved high throughput rate. It is based on assessing the fitness of a population of worms by measuring the rate at which E. coli is consumed. Critically, we demonstrate the analytical power of this method by QTL mapping the loss of RNAi sensitivity (in the germline) in a recombinant inbred population derived from a cross between Bristol and a natural isolate from Hawaii. Hawaii has lost RNAi sensitivity in the germline. We found that polymorphisms in ppw-1 contribute to this loss of RNAi sensitivity, but that other loci are also likely to be important. Conclusions In summary, we have established a fast method that improves the throughput of RNAi in liquid, that generates quantitative data, that is easy to implement in most laboratories, and importantly that enables QTL mapping using RNAi.