Evidence map›Paper›PMID 28379969›Full record

ArticlePLoS neglected tropical diseases2017

In the hunt for genomic markers of metabolic resistance to pyrethroids in the mosquito Aedes aegypti: An integrated next-generation sequencing approach.

Frederic Faucon, Thierry Gaude, Isabelle Dusfour, Vincent Navratil, Vincent Corbel, Waraporn Juntarajumnong, Romain Girod, Rodolphe Poupardin, Frederic Boyer, Stephane Reynaud and 1 more

Open access · goldAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
9.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

51 citing papers in PubMed, 94 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Frederic FauconLaboratoire d'Ecologie Alpine (LECA), CNRS, UMR 5553, 2233 rue de la piscine Grenoble, France.
Thierry GaudeLaboratoire d'Ecologie Alpine (LECA), CNRS, UMR 5553, 2233 rue de la piscine Grenoble, France.
Isabelle DusfourUnité d'Entomologie Médicale, Institut Pasteur de la Guyane, 23 avenue Pasteur, Cayenne, France.
Vincent NavratilPôle Rhône Alpes de Bioinformatique, Université Lyon 1, France.
Vincent CorbelInstitut de Recherche pour le Développement (IRD), Maladies Infectieuses et Vecteurs, Ecologie, Génétique, Evolution et Contrôle (IRD 224-CNRS 5290 UM1-UM2), Montpellier, France.
Waraporn JuntarajumnongDepartment of Entomology, Faculty of Agriculture, Kasetsart University, Lat Yao Chatuchak Bangkok, Thailand.
Romain GirodUnité d'Entomologie Médicale, Institut Pasteur de la Guyane, 23 avenue Pasteur, Cayenne, France.
Rodolphe PoupardinInstitut für Populations genetik, Vetmeduni Vienna, Wien, Austria.
Frederic BoyerLaboratoire d'Ecologie Alpine (LECA), CNRS, UMR 5553, 2233 rue de la piscine Grenoble, France.
Stephane ReynaudLaboratoire d'Ecologie Alpine (LECA), CNRS, UMR 5553, 2233 rue de la piscine Grenoble, France.
Jean-Philippe DavidLaboratoire d'Ecologie Alpine (LECA), CNRS, UMR 5553, 2233 rue de la piscine Grenoble, France.ORCID 0000-0002-3950-5909
Centre National de la Recherche Scientifique · FRInstitut Pasteur · FRKasetsart University · THUniversité Claude Bernard Lyon 1 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe capacity of Aedes mosquitoes to resist chemical insecticides threatens the control of major arbovirus diseases worldwide. Until alternative control tools are widely deployed, monitoring insecticide resistance levels and identifying resistance mechanisms in field mosquito populations is crucial for implementing appropriate management strategies. Metabolic resistance to pyrethroids is common in Aedes aegypti but the monitoring of the dynamics of resistant alleles is impeded by the lack of robust genomic markers. METHODOLOGY/PRINCIPAL

findingsIn an attempt to identify the genomic bases of metabolic resistance to deltamethrin, multiple resistant and susceptible populations originating from various continents were compared using both RNA-seq and a targeted DNA-seq approach focused on the upstream regions of detoxification genes. Multiple detoxification enzymes were over transcribed in resistant populations, frequently associated with an increase in their gene copy number. Targeted sequencing identified potential promoter variations associated with their over transcription. Non-synonymous variations affecting detoxification enzymes were also identified in resistant populations. CONCLUSION /SIGNIFICANCE: This study not only confirmed the role of gene copy number variations as a frequent cause of the over expression of detoxification enzymes associated with insecticide resistance in Aedes aegypti but also identified novel genomic resistance markers potentially associated with their cis-regulation and modifications of their protein structure conformation. As for gene transcription data, polymorphism patterns were frequently conserved within regions but differed among continents confirming the selection of different resistance factors worldwide. Overall, this study paves the way of the identification of a comprehensive set of genomic markers for monitoring the spatio-temporal dynamics of the variety of insecticide resistance mechanisms in Aedes aegypti.

Indexed as

DNA Copy Number VariationsGenomicsAedesAnimalsFemaleGene Expression ProfilingGenetic MarkersHigh-Throughput Nucleotide SequencingInactivation, MetabolicInsecticide ResistanceInsecticidesNitrilesPyrethrinsSequence Analysis, DNASequence Analysis, RNAdecamethrinGenetic MarkersInsecticidesNitrilesPyrethrins

Identifiers

PMID28379969
PMCPMC5393893
OpenAlexW2605166627

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.