Evidence map›Paper›PMID 29661226›Full record

ArticleParasites & vectors2018

Spatio-temporal genetic structure of Anopheles gambiae in the Northwestern Lake Victoria Basin, Uganda: implications for genetic control trials in malaria endemic regions.

Martin Lukindu, Christina M Bergey, Rachel M Wiltshire, Scott T Small, Brian P Bourke, Jonathan K Kayondo, Nora J Besansky

Open access · goldAbstract read
In one paragraph

Article in Parasites & vectors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
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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

7 authors at 2 institutions in 2 countries.

Martin LukinduDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA.
Christina M BergeyDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA.
Rachel M WiltshireDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA.
Scott T SmallDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA.
Brian P BourkeDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA.
Jonathan K KayondoDepartment of Entomology, Uganda Virus Research Institute (UVRI), Entebbe, Uganda.
Nora J BesanskyDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA. nbesansk@nd.edu.
University of Notre Dame · USUganda Virus Research Institute · UG

Funding

Empowering functional genomics of An. gambiae through inversion genotypingR01AI125360 · NIAID · UNIVERSITY OF NOTRE DAME · PI BESANSKY, NORA JESSIE · 2017 to 2021
$2.5M
Elucidating the An. Funestus complexR21AI123491 · NIAID · UNIVERSITY OF NOTRE DAME · PI BESANSKY, NORA JESSIE · 2016 to 2017
$437k
NIAID NIH HHS R01 AI125360NIAID NIH HHS R21 AI123491NIH HHS R01 AI125360NIH HHS R21 AI123491
6 · The paper itself

Abstract

backgroundUnderstanding population genetic structure in the malaria vector Anopheles gambiae (s.s.) is crucial to inform genetic control and manage insecticide resistance. Unfortunately, species characteristics such as high nucleotide diversity, large effective population size, recent range expansion, and high dispersal ability complicate the inference of genetic structure across its range in sub-Saharan Africa. The ocean, along with the Great Rift Valley, is one of the few recognized barriers to gene flow in this species, but the effect of inland lakes, which could be useful sites for initial testing of genetic control strategies, is relatively understudied. Here we examine Lake Victoria as a barrier between the Ugandan mainland and the Ssese Islands, which lie up to 60 km offshore. We use mitochondrial DNA (mtDNA) from populations sampled in 2002, 2012 and 2015, and perform Bayesian cluster analysis on mtDNA combined with microsatellite data previously generated from the same 2002 mosquito DNA samples.

resultsHierarchical analysis of molecular variance and Bayesian clustering support significant differentiation between the mainland and lacustrine islands. In an mtDNA haplotype network constructed from this and previous data, haplotypes are shared even between localities separated by the Rift Valley, a result that more likely reflects retention of shared ancestral polymorphism than contemporary gene flow.

conclusionsThe relative genetic isolation of An. gambiae on the Ssese Islands, their small size, level terrain and ease of access from the mainland, the relative simplicity of the vectorial system, and the prevalence of malaria, are all attributes that recommend these islands as possible sites for the testing of genetic control strategies.

Indexed as

Genetic VariationAnimalsAnophelesCluster AnalysisDNA, MitochondrialGenotypeLakesMicrosatellite RepeatsMosquito VectorsSequence Analysis, DNASpatio-Temporal AnalysisUgandaDNA, MitochondrialAnopheles gambiaeGene flowLacustrine islandsMalariaMitochondrial DNAPopulation genetic structureUganda

Identifiers

PMID29661226
PMCPMC5902950
OpenAlexW2806662077

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.