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Iago biogeography ARG

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/sra/ERP189366
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Recent genomic research on island lineages has highlighted the role of ancestral adaptive variation in facilitating adaptation to insular environments. In this study, we examine the Iago sparrow (Passer iagoensis), a generalist endemic to the Cabo Verde archipelago, to investigate how genetic diversity is maintained in an island lineage where populations are likely ephemeral and natural selection ongoing. Given its presumably large historical population size, we hypothesize that most genetic variants, including adaptive alleles are ancient in origin. Using whole-genome sequencing and phenotypic data, we examined the species' evolutionary history, population structure, and signatures of selection. Our results show that the Iago sparrow diverged from its closest relative approximately 4.26 million years ago, with ancestral recombination graph estimates suggesting a colonization of the archipelago around 2.5 million years ago. Population structure analyses reveal three distinct lineages corresponding to geographic divisions within the archipelago, with the Rombos islets population exhibiting significant phenotypic divergence, particularly in bill morphology. Genome scans identified signatures of divergent selection in genes associated with bill size (HMG20B) and bill shape (ALX1), suggesting adaptive evolution in response to local conditions. Ancestral recombination graph analyses indicate that the adaptive variation associated with HMG20B arose after colonization of the archipelago, contrasting with patterns described in Darwin's finches, where ancestral variation likely arising prior to colonization plays a key role. Our findings highlight the interplay of genetic drift, gene flow, and selection in shaping island species' genetic diversity. The Iago sparrow, a generalist thriving across diverse habitats, provides key insights into the mechanisms driving the maintenance of genetic diversity in island lineages despite the challenges of small population sizes and environmental heterogeneity.
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2026-02-21
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