Genomics of microgeographic adaptation in the hyperdominant Amazonian tree Eperua falcata Aubl. (Fabaceae).
Articolo
Data di Pubblicazione:
2020
Abstract:
Plant populations are able to undergo very localized adaptive processes, that allow continuous
populations to adapt to divergent habitats in spite of recurrent gene flow. Here, we carried out
a genome scan for selection through whole-genome sequencing of pools of populations,
sampled according to a nested sampling design, to evaluate microgeographic adaptation in the
hyperdominant Amazonian tree
Eperua falcata
Aubl. (Fabaceae). A high-coverage genomic
resource of ~250 Mb was assembled
de novo
and annotated, leading to 32 789 predicted
genes. 97 062 bi-allelic SNPs were detected in 25 803 contigs were detected, and a custom
Bayesian model we implemented to uncover candidate genomic targets of divergent selection.
A set of 290 'divergence' outlier SNPs was detected at the regional scale (between study
sites), while 185 SNPs located in the vicinity of 106 protein-coding genes were detected as
replicated outliers between microhabitats within regions. These genes possibly underlie
ecologically important phenotypes
and tend to indicate that adaptation to microgeographic
habitat patchiness would affect genomic regions involved in a variety of physiological
processes, among which plant response to stress (for e.g., oxidative stress, hypoxia and metal
toxicity) and biotic interactions. Identification of genomic targets of microgeographic
adaptation in the Neotropics supports the hypothesis - frequently raised at the community
level - that local adaptation would be a key driver of ecological diversification, probably
operating across multiple spatial scales, from large- (i.e. regional) to microgeographic- (i.e.
landscape) scales.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Amazonia; Neotropics; Eperua falcata; Pool-Seq; de novo assembly; genome scan; SNPs; G ST; Bayesian modelling; adaptive divergence; local adaptation.
Elenco autori:
Vendramin, GIOVANNI GIUSEPPE
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