Evidence map›Paper›PMID 34103015›Full record

ArticleBMC genomics2021

Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae.

Melina Campos, Luisa D P Rona, Katie Willis, George K Christophides, Robert M MacCallum

Abstract read
In one paragraph

Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

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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

3 citing papers in PubMed.

  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

5 authors.

Melina CamposDepartment of Life Sciences, Imperial College London, London, UK.
Luisa D P RonaDepartment of Life Sciences, Imperial College London, London, UK.
Katie WillisDepartment of Life Sciences, Imperial College London, London, UK.
George K Christophides *Department of Life Sciences, Imperial College London, London, UK.
Robert M MacCallum *Department of Life Sciences, Imperial College London, London, UK. r.maccallum@imperial.ac.uk.ORCID http://orcid.org/0000-0001-5070-4493

Funding

National Institute of Allergy and Infectious Diseases (US) NIH-NIAID-DMID-AI02013169Newton Fund (GB) NF161472Wellcome TrustWellcome Trust 107983/Z/15/Z
6 · The paper itself

Abstract

backgroundWhole genome re-sequencing provides powerful data for population genomic studies, allowing robust inferences of population structure, gene flow and evolutionary history. For the major malaria vector in Africa, Anopheles gambiae, other genetic aspects such as selection and adaptation are also important. In the present study, we explore population genetic variation from genome-wide sequencing of 765 An. gambiae and An. coluzzii specimens collected from across Africa. We used t-SNE, a recently popularized dimensionality reduction method, to create a 2D-map of An. gambiae and An. coluzzii genes that reflect their population structure similarities.

resultsThe map allows intuitive navigation among genes distributed throughout the so-called "mainland" and numerous surrounding "island-like" gene clusters. These gene clusters of various sizes correspond predominantly to low recombination genomic regions such as inversions and centromeres, and also to recent selective sweeps. Because this mosquito species complex has been studied extensively, we were able to support our interpretations with previously published findings. Several novel observations and hypotheses are also made, including selective sweeps and a multi-locus selection event in Guinea-Bissau, a known intense hybridization zone between An. gambiae and An. coluzzii.

conclusionsOur results present a rich dataset that could be utilized in functional investigations aiming to shed light onto An. gambiae s.l genome evolution and eventual speciation. In addition, the methodology presented here can be used to further characterize other species not so well studied as An. gambiae, shortening the time required to progress from field sampling to the identification of genes and genomic regions under unique evolutionary processes.

Indexed as

AnophelesMalariaAfricaAnimalsGuinea-BissauIslandsMosquito VectorsChromosomal inversionsMalariaPopulation geneticsT-SNEVisualization methodWhole-genome analysis

Identifiers

PMID34103015
PMCPMC8185951

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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.