Transcriptome-Based Phylogenomics and Adaptive Divergence Across Environmental Gradients in Epimedium brevicornu

Ecology and adaptive differentiation of Epimedium are central to understanding both its taxonomic complexity and medicinal value. In this study, we integrate transcriptomic and plastid data from four natural populations of E. brevicornu (HZ, QLH, TS, WD) to reconstruct their phylogenetic relationships, estimate divergence times, and identify candidate genes associated with local adaptation. Nuclear gene-based phylogenies provide higher resolution and greater topological consistency than plastid data, underscoring the utility of nuclear data in lineages affected by hybridization and incomplete lineage sorting. Molecular dating indicated that major intraspecific divergence occurred during the mid-Quaternary (0.61–0.45 Ma), coinciding with climatic oscillations and montane isolation. Population structure showed strong correlations with temperature and precipitation gradients, suggesting environmentally driven selection. Signatures of positive selection and accelerated evolutionary rates revealed population-specific enrichment of genes involved in stress response, protein modification, signaling, and carbohydrate metabolism—key pathways linked to high-elevation adaptation. Protein–protein interaction networks further indicated a two-tier adaptation mechanism: ancestral network rewiring combined with population co-evolution of interacting genes. Together, these findings advance our understanding of alpine plant adaptation and provide candidate genes for further functional and breeding studies in Epimedium.

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Publication Details

Journal
Agronomy
Published
2025-09-05
DOI
https://doi.org/10.3390/agronomy15092139
Citations
1
Primary Topic
Medicinal Plant Pharmacodynamics Research
Type
article
Field-Weighted Citation Impact
1.56

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article

Transcriptome-Based Phylogenomics and Adaptive Divergence Across Environmental Gradients in Epimedium brevicornu

J. Qi, Lingxiao Xing, Xiaolei Zhou, Jun Zhao et al.
1 citations
Agronomy
Medicinal Plant Pharmacodynamics Research
1.56
article

Transcriptome-Based Phylogenomics and Adaptive Divergence Across Environmental Gradients in Epimedium brevicornu

J. Qi, Lingxiao Xing, Xiaolei Zhou, Jun Zhao, Xuhu Wang, Qingbiao Song, Songsong Lu, Xiaowei Zhang, Weibo Du
article en
1 citations

Abstract

Ecology and adaptive differentiation of Epimedium are central to understanding both its taxonomic complexity and medicinal value. In this study, we integrate transcriptomic and plastid data from four natural populations of E. brevicornu (HZ, QLH, TS, WD) to reconstruct their phylogenetic relationships, estimate divergence times, and identify candidate genes associated with local adaptation. Nuclear gene-based phylogenies provide higher resolution and greater topological consistency than plastid data, underscoring the utility of nuclear data in lineages affected by hybridization and incomplete lineage sorting. Molecular dating indicated that major intraspecific divergence occurred during the mid-Quaternary (0.61–0.45 Ma), coinciding with climatic oscillations and montane isolation. Population structure showed strong correlations with temperature and precipitation gradients, suggesting environmentally driven selection. Signatures of positive selection and accelerated evolutionary rates revealed population-specific enrichment of genes involved in stress response, protein modification, signaling, and carbohydrate metabolism—key pathways linked to high-elevation adaptation. Protein–protein interaction networks further indicated a two-tier adaptation mechanism: ancestral network rewiring combined with population co-evolution of interacting genes. Together, these findings advance our understanding of alpine plant adaptation and provide candidate genes for further functional and breeding studies in Epimedium.

AgronomyVol. 15(9)
Gansu Agricultural University (CN)
Gansu Agricultural University, Science and Technology Program of Gansu Province
Openalex Percentile: Top 16%
Medicinal Plant Pharmacodynamics Research
1.56
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