Genomic Signatures of Environmental Adaptation in <i>Castanopsis hainanensis</i> (Fagaceae)

As an endemic <i>Castanopsis</i> species on Hainan Island, <i>Castanopsis hainanensis</i> Merr. is uniquely adapted to tropical climatic conditions and occupies a relatively narrow habitat range. Given its long generation times, limited dispersal capacity, and ecological and...

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Main Authors: Sha Li, Xing Chen, Yang Wu, Ye Sun
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Plants
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Online Access:https://www.mdpi.com/2223-7747/14/7/1128
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author Sha Li
Xing Chen
Yang Wu
Ye Sun
author_facet Sha Li
Xing Chen
Yang Wu
Ye Sun
author_sort Sha Li
collection DOAJ
description As an endemic <i>Castanopsis</i> species on Hainan Island, <i>Castanopsis hainanensis</i> Merr. is uniquely adapted to tropical climatic conditions and occupies a relatively narrow habitat range. Given its long generation times, limited dispersal capacity, and ecological and economic importance, understanding the genomic processes shaping this dominant tree species is critical for conservation. Its adaptation to specialized habitats and distinct geographical distribution provide valuable insights into biodiversity challenges in island ecosystems. This study employs genome-wide single-nucleotide polymorphism (SNP) markers to investigate genetic structure, population dynamics, and adaptive variation. Analyses revealed weak genetic divergence among populations, suggesting high gene flow. Demographic reconstruction indicated a historical population bottleneck, consistent with MaxEnt modeling projections of future range contraction under climate change. Selective sweep and genotype–environment association (GEA) analyses identified SNPs strongly correlated with environmental variables, particularly moisture and temperature. Using these SNPs, we quantified the risk of non-adaptedness (RONA) across climate scenarios, pinpointing regions at heightened vulnerability. Gene Ontology (GO) enrichment highlighted the key genes involved in plant growth and stress adaptation. By integrating genomic and environmental data, this study establishes a framework for deciphering adaptive mechanisms of <i>C. hainanensis</i> and offers actionable insights for informed conservation strategies to mitigate climate-driven biodiversity loss.
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spelling doaj-art-8ee4e45e17d8477db25a7a64445a7f7e2025-08-20T03:03:27ZengMDPI AGPlants2223-77472025-04-01147112810.3390/plants14071128Genomic Signatures of Environmental Adaptation in <i>Castanopsis hainanensis</i> (Fagaceae)Sha Li0Xing Chen1Yang Wu2Ye Sun3Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaGuangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaGuangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaGuangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaAs an endemic <i>Castanopsis</i> species on Hainan Island, <i>Castanopsis hainanensis</i> Merr. is uniquely adapted to tropical climatic conditions and occupies a relatively narrow habitat range. Given its long generation times, limited dispersal capacity, and ecological and economic importance, understanding the genomic processes shaping this dominant tree species is critical for conservation. Its adaptation to specialized habitats and distinct geographical distribution provide valuable insights into biodiversity challenges in island ecosystems. This study employs genome-wide single-nucleotide polymorphism (SNP) markers to investigate genetic structure, population dynamics, and adaptive variation. Analyses revealed weak genetic divergence among populations, suggesting high gene flow. Demographic reconstruction indicated a historical population bottleneck, consistent with MaxEnt modeling projections of future range contraction under climate change. Selective sweep and genotype–environment association (GEA) analyses identified SNPs strongly correlated with environmental variables, particularly moisture and temperature. Using these SNPs, we quantified the risk of non-adaptedness (RONA) across climate scenarios, pinpointing regions at heightened vulnerability. Gene Ontology (GO) enrichment highlighted the key genes involved in plant growth and stress adaptation. By integrating genomic and environmental data, this study establishes a framework for deciphering adaptive mechanisms of <i>C. hainanensis</i> and offers actionable insights for informed conservation strategies to mitigate climate-driven biodiversity loss.https://www.mdpi.com/2223-7747/14/7/1128adaptive variation<i>Castanopsis hainanensis</i>climate changegenome resequencingrisk of non-adaptedness
spellingShingle Sha Li
Xing Chen
Yang Wu
Ye Sun
Genomic Signatures of Environmental Adaptation in <i>Castanopsis hainanensis</i> (Fagaceae)
Plants
adaptive variation
<i>Castanopsis hainanensis</i>
climate change
genome resequencing
risk of non-adaptedness
title Genomic Signatures of Environmental Adaptation in <i>Castanopsis hainanensis</i> (Fagaceae)
title_full Genomic Signatures of Environmental Adaptation in <i>Castanopsis hainanensis</i> (Fagaceae)
title_fullStr Genomic Signatures of Environmental Adaptation in <i>Castanopsis hainanensis</i> (Fagaceae)
title_full_unstemmed Genomic Signatures of Environmental Adaptation in <i>Castanopsis hainanensis</i> (Fagaceae)
title_short Genomic Signatures of Environmental Adaptation in <i>Castanopsis hainanensis</i> (Fagaceae)
title_sort genomic signatures of environmental adaptation in i castanopsis hainanensis i fagaceae
topic adaptive variation
<i>Castanopsis hainanensis</i>
climate change
genome resequencing
risk of non-adaptedness
url https://www.mdpi.com/2223-7747/14/7/1128
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AT xingchen genomicsignaturesofenvironmentaladaptationinicastanopsishainanensisifagaceae
AT yangwu genomicsignaturesofenvironmentaladaptationinicastanopsishainanensisifagaceae
AT yesun genomicsignaturesofenvironmentaladaptationinicastanopsishainanensisifagaceae