bioRxiv ScienceSearch

bioRxiv · 10.1101/575753

Combining genetic crosses and pool targeted DNA-seq for untangling genomic variations associated with resistance to multiple insecticides in the dengue vector Aedes aegypti

Abstract

In addition to combating vector-borne diseases, studying the adaptation of mosquitoes to insecticides provides a remarkable example of evolution-in-action driving the selection of complex phenotypes. Indeed, most resistant mosquito populations show multi-resistance phenotypes as a consequence of the variety of insecticides employed and of the complexity of selected resistance mechanisms. Such complexity makes challenging the identification of alleles conferring resistance to specific insecticides and prevents the development of molecular assays to track them in the field. Here we showed that combining simple genetic crosses with pool targeted DNA-seq can enhance the specificity of resistance alleles detection while maintaining experimental work and sequencing effort at reasonable levels. A multi-resistant population of the mosquito Aedes aegypti was exposed to three distinct insecticides (deltamethrin, bendiocarb and fenitrothion) and survivors to each insecticide were crossed with a susceptible strain to generate 3 distinct lines. F2 individuals from each line were then segregated with 2 insecticide doses. Bioassays supported the improved segregation of resistance alleles between lines. Hundreds of genes covering all detoxifying enzymes and insecticide targets together with more than 7,000 intergenic regions equally spread over mosquito genome were sequenced from pools of F0 and F2 individuals unexposed or surviving insecticide. Differential coverage analysis identified 39 detoxification enzymes showing an increased gene copy number in association with resistance. Combining an allele frequency filtering approach with a Bayesian FST-based genome scan identified multiple genomic regions showing strong selection signatures together with 50 non-synonymous variations associated with resistance. This study provides a simple and cost-effective approach to improve the segregation of resistant alleles in multi-resistant populations while reducing false positives frequently arising when comparing populations showing divergent genetic backgrounds. The identification of these insecticide resistance markers paves the way for the design of novel DNA-based resistance tracking assays.\n\nAuthor summaryIn addition to combating vector-borne diseases, understanding how mosquitoes adapt to insecticides provides a remarkable example of evolution-in-action. However, the variety of insecticides used and the complexity of adaptive mechanisms make it difficult to identify the genetic changes conferring resistance to each insecticide. Here we combined simple controlled crosses with mass DNA sequencing for enhancing the specificity of resistance gene detection. A multi-resistant mosquito population was exposed to three distinct insecticides and survivors were crossed with a susceptible strain to generate 3 distinct mosquito lines. Individuals from the second generation of each line were then segregated based on their resistance to each insecticide. Bioassays supported the improved segregation of genetic resistance markers between lines. Hundreds of genes potentially involved in resistance together with thousands non-genic regions equally spread over mosquito genome were sequenced from individuals from each line. Genomic analyses identified detoxification enzymes showing an increased gene copy number in association with resistance and multiple genomic regions showing strong selection signatures and carrying point mutations associated with resistance. Such approach improves the specificity of resistance gene detection in field mosquito populations resisting to multiple insecticides and paves the way for the design of novel DNA-based resistance tracking tools.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Cattel, J., Faucon, F., Leperon, B., Sherpa, S., Monchal, M., Grillet, L., Gaude, T., Laporte, F., Dusfour, I., Reynaud, s., David, J.-P.. 2019-03-12. Combining genetic crosses and pool targeted DNA-seq for untangling genomic variations associated with resistance to multiple insecticides in the dengue vector Aedes aegypti. https://doi.org/10.1101/575753

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Sequence and epigenetic characterization of chromosome 21 centromeres in a family with recurrent Trisomy 21

Trisomy 21 (T21) is the most common genetic cause of intellectual disability, yet the molecular mechanisms underlying maternal meiosis I errors--responsible for ~70% of free T21 cases--remain poorly understood. In this preliminary study, we used long-read sequencing and genome assembly to investigate the DNA sequence and epigenetic features of chromosome 21 (chr21) centromeres in a family with recurrent free T21 due to maternal meiosis I errors. The mother, who had two affected and three unaffected children, showed no mosaicism or structural rearrangements. One of her two chr21 centromeres lacked a pronounced centromere dip region (CDR), displaying instead a diffuse hypomethylation pattern (dCDR) with much higher methylated CpG levels (55%) compared to its homologue (36%). This dCDR was transmitted to an unaffected child and the affected proband analyzed, suggesting it was present in one of the maternal chr21 since she was at least 32 years of age. Chr21 dCDRs were not observed in seven young mothers with children with T21 or previously described in the literature in 108 population haplotypes. We hypothesize that dCDRs may weaken kinetochore function, increasing nondisjunction risk, and propose two models linking such epigenetic variation to maternal age-related T21 risk. These findings highlight the value of complete centromere characterization in families with children with T21 and suggest centromere methylation status of chr21 as a potential T21 risk factor for future investigation.

genomics

Single-Cell Analytics for Dose Response (SCADR) discriminates PTEN missense variants by lipid and protein phosphatase dysfunction

The proliferation of sequencing efforts has revealed a vast and expanding catalog of single nucleotide gene variants, many associated to, but with unclear roles in disease. Fully charactering variant impacts and linking specific protein dysfunctions to disease are challenging due to the multi-functional nature of many proteins and varying degree of variant effects on these functions. Lagging are sensitive approaches to empirically assess the impact of missense variant-induced single amino acid changes on a wide range of protein functions. To address these issues, we have developed an open-source computational analysis tool called SCADR (Single-Cell Analytics for Dose Response) for simultaneously measuring and comparing impacts of exogenously-expressed variants on multiple signaling pathways using multiplex phospho-antibody spectral flow cytometry in human cell lines. SCADR retains and correlates single-cell measures of signal protein activity states along with expression levels of exogenously-expressed variants, providing rich characterization of multiple protein functions, signaling protein interactions, and enhanced discrimination of variant impacts on different signaling pathways, highlighting each variants unique dysfunction profile. Here, we apply SCADR for analyses of the impact of 6 variants of the tumor-suppressor protein PTEN (P38H, C124S, G129E, Y138L, D268E, 4A) expressed in HEK293 cells on the phosphorylation states of the canonical and noncanonical downstream signaling proteins Akt, S6, CREB, ERK, and p38 detected with fluorophore-conjugated phospho-antibodies, along with an antibody detecting an N-terminal HA tag on PTEN variants allowing measures of dose-response effects of each variants expression on signaling cascades. Results identify variant-specific impacts on downstream signaling cascades.

genomics

Microsecond molecular dynamics of SOD1 variants suggest a structural basis for divergent ALS clinical outcomes

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterised by progressive motor neuron degeneration. Mutations in the SOD1 gene represent the second most common genetic cause of ALS (ALS), and distinct SOD1 missense variants present with markedly different clinical profiles. A4V leads to an aggressive form of the disease (median survival [~]1y), H46R confers a mild, slowly progressive course and I113T exhibits an intermediate phenotype. The molecular basis by which these mutations produce divergent clinical outcomes remains poorly understood. We performed extensive classical molecular dynamics simulations of wild-type SOD1 and the three ALS-associated variants in the apo monomeric state to attempt to investigate the mechanisms behind such phenotypic differences. Structural stability, global compactness, and conformational flexibility, as well as analysis of collective motions between residues and estimation of free energy, were assessed. The H46R, A4V, and I113T variants exhibited distinct dynamic behaviours, highlighting differences in structural stability, local flexibility, and intramolecular interactions. These findings suggest that specific structural regions may contribute differently to protein dysfunction and could represent key elements for understanding the relationship between molecular dynamic properties and the differing clinical severity associated with these variants. Most strikingly, H46R exhibited exceptional structural stability across every analytical level, the lowest global deviation, most attenuated local flexibility, strongest internal dynamic coordination, and the deepest, most confined free energy basins of any system examined. This convergent multi-layered evidence of structural restraint provides a compelling mechanistic basis for the mild and slowly progressive clinical course of H46R ALS, suggesting that enhanced conformational rigidity, rather than bulk destabilisation, is the defining biophysical feature of this variant, and that its pathogenic mechanism operates through a route fundamentally decoupled from the aggregation-driven toxicity that characterises the more aggressive SOD1-ALS mutations.

genomics