↓ Skip to main content

Association mapping by pooled sequencing identifies TOLL 11 as a protective factor against Plasmodium falciparum in Anopheles gambiae

Overview of attention for article published in BMC Genomics, October 2015
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 X users

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
72 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Association mapping by pooled sequencing identifies TOLL 11 as a protective factor against Plasmodium falciparum in Anopheles gambiae
Published in
BMC Genomics, October 2015
DOI 10.1186/s12864-015-2009-z
Pubmed ID
Authors

Seth N. Redmond, Karin Eiglmeier, Christian Mitri, Kyriacos Markianos, Wamdaogo M. Guelbeogo, Awa Gneme, Alison T. Isaacs, Boubacar Coulibaly, Emma Brito-Fravallo, Gareth Maslen, Daniel Mead, Oumou Niare, Sekou F. Traore, N’Fale Sagnon, Dominic Kwiatkowski, Michelle M. Riehle, Kenneth D. Vernick

Abstract

The genome-wide association study (GWAS) techniques that have been used for genetic mapping in other organisms have not been successfully applied to mosquitoes, which have genetic characteristics of high nucleotide diversity, low linkage disequilibrium, and complex population stratification that render population-based GWAS essentially unfeasible at realistic sample size and marker density. We designed a novel mapping strategy for the mosquito system that combines the power of linkage mapping with the resolution afforded by genetic association. We established founder colonies from West Africa, controlled for diversity, linkage disequilibrium and population stratification. Colonies were challenged by feeding on the infectious stage of the human malaria parasite, Plasmodium falciparum, mosquitoes were phenotyped for parasite load, and DNA pools for phenotypically similar mosquitoes were Illumina sequenced. Phenotype-genotype mapping was carried out in two stages, coarse and fine. In the first mapping stage, pooled sequences were analysed genome-wide for intervals displaying relativereduction in diversity between phenotype pools, and candidate genomic loci were identified for influence upon parasite infection levels. In the second mapping stage, focused genotyping of SNPs from the first mapping stage was carried out in unpooled individual mosquitoes and replicates. The second stage confirmed significant SNPs in a locus encoding two Toll-family proteins. RNAi-mediated gene silencing and infection challenge revealed that TOLL 11 protects mosquitoes against P. falciparum infection. We present an efficient and cost-effective method for genetic mapping using natural variation segregating in defined recent Anopheles founder colonies, and demonstrate its applicability for mapping in a complex non-model genome. This approach is a practical and preferred alternative to population-based GWAS for first-pass mapping of phenotypes in Anopheles. This design should facilitate mapping of other traits involved in physiology, epidemiology, and behaviour.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 1%
Germany 1 1%
Brazil 1 1%
Unknown 69 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 22%
Researcher 15 21%
Student > Ph. D. Student 9 13%
Student > Doctoral Student 4 6%
Student > Bachelor 4 6%
Other 8 11%
Unknown 16 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 28%
Biochemistry, Genetics and Molecular Biology 14 19%
Medicine and Dentistry 6 8%
Immunology and Microbiology 4 6%
Computer Science 3 4%
Other 7 10%
Unknown 18 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 19 October 2015.
All research outputs
#13,449,421
of 22,830,751 outputs
Outputs from BMC Genomics
#5,000
of 10,655 outputs
Outputs of similar age
#132,181
of 279,229 outputs
Outputs of similar age from BMC Genomics
#178
of 375 outputs
Altmetric has tracked 22,830,751 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,655 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 50% 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 279,229 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 375 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.