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Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8185951/ https://www.ncbi.nlm.nih.gov/pubmed/34103015 http://dx.doi.org/10.1186/s12864-021-07722-y |
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author | Campos, Melina Rona, Luisa D. P. Willis, Katie Christophides, George K. MacCallum, Robert M. |
author_facet | Campos, Melina Rona, Luisa D. P. Willis, Katie Christophides, George K. MacCallum, Robert M. |
author_sort | Campos, Melina |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07722-y. |
format | Online Article Text |
id | pubmed-8185951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81859512021-06-09 Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae Campos, Melina Rona, Luisa D. P. Willis, Katie Christophides, George K. MacCallum, Robert M. BMC Genomics Research Article 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07722-y. BioMed Central 2021-06-08 /pmc/articles/PMC8185951/ /pubmed/34103015 http://dx.doi.org/10.1186/s12864-021-07722-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Campos, Melina Rona, Luisa D. P. Willis, Katie Christophides, George K. MacCallum, Robert M. Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae |
title | Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae |
title_full | Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae |
title_fullStr | Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae |
title_full_unstemmed | Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae |
title_short | Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae |
title_sort | unravelling population structure heterogeneity within the genome of the malaria vector anopheles gambiae |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8185951/ https://www.ncbi.nlm.nih.gov/pubmed/34103015 http://dx.doi.org/10.1186/s12864-021-07722-y |
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