The genomic and epigenetic footprint of local adaptation to variable climates in kiwifruit

生物 局部适应 群体基因组学 人口 进化生物学 适应不良 适应(眼睛) 基因组学 生态学 遗传学 基因 基因组 社会学 人口学 神经科学
作者
Xu Zhang,Rui Guo,Ruinan Shen,Jacob B. Landis,Quan Jiang,Fang Liu,Hengchang Wang,Xiaohong Yao
出处
期刊:Horticulture research [Nature Portfolio]
卷期号:10 (4) 被引量:2
标识
DOI:10.1093/hr/uhad031
摘要

Abstract A full understanding of adaptive genetic variation at the genomic level will help address questions of how organisms adapt to diverse climates. Actinidia eriantha is a shade-tolerant species, widely distributed in the southern tropical region of China, occurring in spatially heterogeneous environments. In the present study we combined population genomic, epigenomic, and environmental association analyses to infer population genetic structure and positive selection across a climatic gradient, and to assess genomic offset to climatic change for A. eriantha. The population structure is strongly shaped by geography and influenced by restricted gene flow resulting from isolation by distance due to habitat fragmentation. In total, we identified 102 outlier loci and annotated 455 candidate genes associated with the genomic basis of climate adaptation, which were enriched in functional categories related to development processes and stress response; both temperature and precipitation are important factors driving adaptive variation. In addition to single-nucleotide polymorphisms (SNPs), a total of 27 single-methylation variants (SMVs) had significant correlation with at least one of four climatic variables and 16 SMVs were located in or adjacent to genes, several of which were predicted to be involved in plant response to abiotic or biotic stress. Gradient forest analysis indicated that the central/east populations were predicted to be at higher risk of future population maladaptation under climate change. Our results demonstrate that local climate factors impose strong selection pressures and lead to local adaptation. Such information adds to our understanding of adaptive mechanisms to variable climates revealed by both population genome and epigenome analysis.
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