Temperature, rainfall and wind variables underlie environmental adaptation in natural populations of Drosophila melanogaster.
Drosophila melanogaster
allele frequency
genetic adaptation
genome-environment
transposable elements
Journal
Molecular ecology
ISSN: 1365-294X
Titre abrégé: Mol Ecol
Pays: England
ID NLM: 9214478
Informations de publication
Date de publication:
02 2021
02 2021
Historique:
received:
07
05
2020
revised:
16
12
2020
accepted:
18
12
2020
pubmed:
23
12
2020
medline:
22
6
2021
entrez:
22
12
2020
Statut:
ppublish
Résumé
While several studies in a diverse set of species have shed light on the genes underlying adaptation, our knowledge on the selective pressures that explain the observed patterns lags behind. Drosophila melanogaster is a valuable organism to study environmental adaptation because this species originated in Southern Africa and has recently expanded worldwide, and also because it has a functionally well-annotated genome. In this study, we aimed to decipher which environmental variables are relevant for adaptation of D. melanogaster natural populations in Europe and North America. We analysed 36 whole-genome pool-seq samples of D. melanogaster natural populations collected in 20 European and 11 North American locations. We used the BayPass software to identify single nucleotide polymorphisms (SNPs) and transposable elements (TEs) showing signature of adaptive differentiation across populations, as well as significant associations with 59 environmental variables related to temperature, rainfall, evaporation, solar radiation, wind, daylight hours, and soil type. We found that in addition to temperature and rainfall, wind related variables are also relevant for D. melanogaster environmental adaptation. Interestingly, 23%-51% of the genes that showed significant associations with environmental variables were not found overly differentiated across populations. In addition to SNPs, we also identified 10 reference transposable element insertions associated with environmental variables. Our results showed that genome-environment association analysis can identify adaptive genetic variants that are undetected by population differentiation analysis while also allowing the identification of candidate environmental drivers of adaptation.
Identifiants
pubmed: 33350518
doi: 10.1111/mec.15783
pmc: PMC7986194
doi:
Substances chimiques
DNA Transposable Elements
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
938-954Informations de copyright
© 2020 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.
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