Abstract
BackgroundMosquito control programmes using chemical insecticides are increasingly threatened by the development of resistance. Such resistance can be the consequence of changes in proteins targeted by insecticides (target site mediated resistance), increased insecticide biodegradation (metabolic resistance), altered transport, sequestration or other mechanisms. As opposed to target site resistance, other mechanisms are far from being fully understood. Indeed, insecticide selection often affects a large number of genes and various biological processes can hypothetically confer resistance. In this context, the aim of the present study was to use RNA sequencing (RNA-seq) for comparing transcription level and polymorphism variations associated with adaptation to chemical insecticides in the mosquito Aedes aegypti. Biological materials consisted of a parental susceptible strain together with three child strains selected across multiple generations with three insecticides from different classes: the pyrethroid permethrin, the neonicotinoid imidacloprid and the carbamate propoxur.ResultsAfter ten generations, insecticide-selected strains showed elevated resistance levels to the insecticides used for selection. RNA-seq data allowed detecting over 13,000 transcripts, of which 413 were differentially transcribed in insecticide-selected strains as compared to the susceptible strain. Among them, a significant enrichment of transcripts encoding cuticle proteins, transporters and enzymes was observed. Polymorphism analysis revealed over 2500 SNPs showing > 50% allele frequency variations in insecticide-selected strains as compared to the susceptible strain, affecting over 1000 transcripts. Comparing gene transcription and polymorphism patterns revealed marked differences among strains. While imidacloprid selection was linked to the over transcription of many genes, permethrin selection was rather linked to polymorphism variations. Focusing on detoxification enzymes revealed that permethrin selection strongly affected the polymorphism of several transcripts encoding cytochrome P450 monooxygenases likely involved in insecticide biodegradation.ConclusionsThe present study confirmed the power of RNA-seq for identifying concomitantly quantitative and qualitative transcriptome changes associated with insecticide resistance in mosquitoes. Our results suggest that transcriptome modifications can be selected rapidly by insecticides and affect multiple biological functions. Previously neglected by molecular screenings, polymorphism variations of detoxification enzymes may play an important role in the adaptive response of mosquitoes to insecticides.
Highlights
Mosquito control programmes using chemical insecticides are increasingly threatened by the development of resistance
Despite recent studies pointing out the role of polymorphism variations in insecticide resistance [22,23,24], such aspect has never been investigated at the transcriptome level in mosquitoes
Transcriptome changes associated with insecticide selection Overall, our study revealed diverse response patterns depending on the insecticide used for selection
Summary
Mosquito control programmes using chemical insecticides are increasingly threatened by the development of resistance. Insecticide selection often affects a large number of genes and various biological processes can hypothetically confer resistance In this context, the aim of the present study was to use RNA sequencing (RNA-seq) for comparing transcription level and polymorphism variations associated with adaptation to chemical insecticides in the mosquito Aedes aegypti. Polymorphism of a P450 gene has been associated with pyrethroid resistance in the mosquito culex pipiens [23] and a reduction of sequence diversity in two P450 genes conferring resistance to pyrethroids has been observed in Anopheles funestus [24] This suggests that a deep analysis of the polymorphism associated with resistance can improve our understanding of mechanisms developed by mosquitoes to resist insecticides. Today, such knowledge gap can be overcome by high throughput sequencing approaches such as mRNA sequencing (RNAseq), which can generates concomitantly gene expression and polymorphism data over the whole transcriptome from a single experiment [25,26,27]
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