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RNA-seq analyses of changes in the Anopheles gambiae transcriptome associated with resistance to pyrethroids in Kenya: identification of candidate-resistance genes and candidate-resistance SNPs

Overview of attention for article published in Parasites & Vectors, September 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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1 blog
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3 X users

Citations

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38 Dimensions

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117 Mendeley
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Title
RNA-seq analyses of changes in the Anopheles gambiae transcriptome associated with resistance to pyrethroids in Kenya: identification of candidate-resistance genes and candidate-resistance SNPs
Published in
Parasites & Vectors, September 2015
DOI 10.1186/s13071-015-1083-z
Pubmed ID
Authors

Mariangela Bonizzoni, Eric Ochomo, William Augustine Dunn, Monica Britton, Yaw Afrane, Guofa Zhou, Joshua Hartsel, Ming-Chieh Lee, Jiabao Xu, Andrew Githeko, Joseph Fass, Guiyun Yan

Abstract

The extensive use of pyrethroids for control of malaria vectors, driven by their cost, efficacy and safety, has led to widespread resistance. To favor their sustainable use, the World Health Organization (WHO) formulated an insecticide resistance management plan, which includes the identification of the mechanisms of resistance and resistance surveillance. Recognized physiological mechanisms of resistance include target site mutations in the para voltage-gated sodium channel, metabolic detoxification and penetration resistance. Such understanding of resistance mechanisms has allowed the development of resistance monitoring tools, including genotyping of the kdr mutation L1014F/S in the para gene. The sequence-based technique RNA-seq was applied to study changes in the transcriptome of deltamethrin-resistant and -susceptible Anopheles gambiae mosquitoes from the Western Province of Kenya. The resulting gene expression profiles were compared to data in the most recent literature to derive a list of candidate resistance genes. RNA-seq data were analyzed also to identify sequence polymorphisms linked to resistance. A total of five candidate-resistance genes (AGAP04177, AGAP004572, AGAP008840, AGAP007530 and AGAP013036) were identified with altered expression between resistant and susceptible mosquitoes from West and East Africa. A change from G to C at position 36043997 of chromosome 3R resulting in A101G of the sulfotransferase gene AGAP009551 was significantly associated with the resistance phenotype (odds ratio: 5.10). The kdr L1014S mutation was detected at similar frequencies in both phenotypically resistant and susceptible mosquitoes, suggesting it is no longer fully predictive of the resistant phenotype. Overall, these results support the conclusion that resistance to pyrethroids is a complex and evolving phenotype, dependent on multiple gene functions including, but not limited to, metabolic detoxification. Functional convergence among metabolic detoxification genes may exist, with the role of each gene being modulated by the life history and selection pressure on mosquito populations. As a consequence, biochemical assays that quantify overall enzyme activity may be a more suitable method for predicting metabolic resistance than gene-based assays.

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 116 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 19%
Researcher 18 15%
Student > Ph. D. Student 16 14%
Student > Bachelor 8 7%
Student > Doctoral Student 5 4%
Other 16 14%
Unknown 32 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 29%
Biochemistry, Genetics and Molecular Biology 21 18%
Medicine and Dentistry 8 7%
Computer Science 3 3%
Veterinary Science and Veterinary Medicine 2 2%
Other 14 12%
Unknown 35 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 October 2015.
All research outputs
#3,581,963
of 22,828,180 outputs
Outputs from Parasites & Vectors
#755
of 5,463 outputs
Outputs of similar age
#48,265
of 272,396 outputs
Outputs of similar age from Parasites & Vectors
#14
of 146 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,463 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 272,396 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.