Genomic signatures of population decline in the malaria mosquito Anopheles gambiae
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
BACKGROUND: Population genomic features such as nucleotide diversity and linkage disequilibrium are expected to be strongly shaped by changes in population size, and might therefore be useful for monitoring the success of a control campaign. In the Kilifi district of Kenya, there has been a marked decline in the abundance of the malaria vector Anopheles gambiae subsequent to the rollout of insecticide-treated bed nets. METHODS: To investigate whether this decline left a detectable population genomic signature, simulations were performed to compare the effect of population crashes on nucleotide diversity, Tajima's D, and linkage disequilibrium (as measured by the population recombination parameter ρ). Linkage disequilibrium and ρ were estimated for An. gambiae from Kilifi, and compared them to values for Anopheles arabiensis and Anopheles merus at the same location, and for An. gambiae in a location 200 km from Kilifi. RESULTS: In the first simulations ρ changed more rapidly after a population crash than the other statistics, and therefore is a more sensitive indicator of recent population decline. In the empirical data, linkage disequilibrium extends 100-1000 times further, and ρ is 100-1000 times smaller, for the Kilifi population of An. gambiae than for any of the other populations. There were also significant runs of homozygosity in many of the individual An. gambiae mosquitoes from Kilifi. CONCLUSIONS: These results support the hypothesis that the recent decline in An. gambiae was driven by the rollout of bed nets. Measuring population genomic parameters in a small sample of individuals before, during and after vector or pest control may be a valuable method of tracking the effectiveness of interventions.
Date Issued
2016-03-24
Date Acceptance
2016-03-05
Citation
Malaria Journal, 2016, 15
ISSN
1475-2875
Publisher
BioMed Central
Journal / Book Title
Malaria Journal
Volume
15
Copyright Statement
© 2016 O’Loughlin et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License
(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/
publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/
publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Sponsor
Commission of the European Communities
The Royal Society
Grand Challenges in Global Health
Identifier
PII: 10.1186/s12936-016-1214-9
Grant Number
228421
WM110082
BURT12/VCTR
Subjects
Science & Technology
Life Sciences & Biomedicine
Infectious Diseases
Parasitology
Tropical Medicine
Anopheles gambiae
Kilifi
Linkage disequilibrium
Population recombination
Population control
Pest management
INSECTICIDE-TREATED BEDNETS
LINKAGE DISEQUILIBRIUM
KENYAN COAST
DROSOPHILA-MELANOGASTER
DNA POLYMORPHISM
NEUTRAL MODEL
RECOMBINATION
HISTORY
TRANSMISSION
SEQUENCES
Medical Microbiology
Publication Status
Published
Article Number
182