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

Authors :
Melina Campos
Luisa D. P. Rona
Katie Willis
George K. Christophides
Robert M. MacCallum
Source :
BMC Genomics, Vol 22, Iss 1, Pp 1-15 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract Background Whole 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. Results The 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. Conclusions Our 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.

Details

Language :
English
ISSN :
14712164
Volume :
22
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Genomics
Publication Type :
Academic Journal
Accession number :
edsdoj.4f15c00d6447473e8027574235612552
Document Type :
article
Full Text :
https://doi.org/10.1186/s12864-021-07722-y