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Article|21 Feb 2023|OPEN
The genomic and epigenetic footprint of local adaptation to variable climates in kiwifruit
Xu Zhang1,2 ,† , Rui Guo1,2 ,† , Ruinan Shen1,2 , Jacob B. Landis3,4 , Quan Jiang1,2 , Fang Liu1 , Hengchang Wang1 , , Xiaohong Yao,1 ,
1CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, the Chinese Academy of Sciences, Wuhan 430074, Hubei, China
2College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
3School of Integrative Plant Science, Section of Plant Biology and the L.H. Bailey Hortorium, Cornell University, Ithaca, NY 14853 USA
4BTI Computational Biology Center, Boyce Thompson Institute, Ithaca, NY 14853, USA
*Corresponding author. E-mail:,
Both authors contributed equally to the study.

Horticulture Research 10,
Article number: uhad031 (2023)
Views: 211

Received: 26 May 2022
Accepted: 14 Feb 2023
Published online: 21 Feb 2023


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.