Genomic insights into local adaptation and future climate-induced vulnerability of a keystone forest tree in East Asia

Yupeng Sang, Zhiqin Long, Xuming Dan, Jiajun Feng, Tingting Shi, Changfu Jia, Xinxin Zhang, Qiang Lai, Guanglei Yang, Hongying Zhang, Xiaoting Xu, Huanhuan Liu, Yuanzhong Jiang, Pär K. Ingvarsson, Jianquan Liu (), Kangshan Mao () and Jing Wang ()
Additional contact information
Yupeng Sang: Sichuan University
Zhiqin Long: Sichuan University
Xuming Dan: Sichuan University
Jiajun Feng: Sichuan University
Tingting Shi: Sichuan University
Changfu Jia: Sichuan University
Xinxin Zhang: Sichuan University
Qiang Lai: Sichuan University
Guanglei Yang: Sichuan University
Hongying Zhang: Sichuan University
Xiaoting Xu: Sichuan University
Huanhuan Liu: Sichuan University
Yuanzhong Jiang: Sichuan University
Pär K. Ingvarsson: Swedish University of Agricultural Sciences
Jianquan Liu: Sichuan University
Kangshan Mao: Sichuan University
Jing Wang: Sichuan University

Nature Communications, 2022, vol. 13, issue 1, 1-14

Abstract: Abstract Rapid global climate change is posing a substantial threat to biodiversity. The assessment of population vulnerability and adaptive capacity under climate change is crucial for informing conservation and mitigation strategies. Here we generate a chromosome-scale genome assembly and re-sequence genomes of 230 individuals collected from 24 populations for Populus koreana, a pioneer and keystone tree species in temperate forests of East Asia. We integrate population genomics and environmental variables to reveal a set of climate-associated single-nucleotide polymorphisms, insertion/deletions and structural variations, especially numerous adaptive non-coding variants distributed across the genome. We incorporate these variants into an environmental modeling scheme to predict a highly spatiotemporal shift of this species in response to future climate change. We further identify the most vulnerable populations that need conservation priority and many candidate genes and variants that may be useful for forest tree breeding with special aims. Our findings highlight the importance of integrating genomic and environmental data to predict adaptive capacity of a key forest to rapid climate change in the future.

Date: 2022
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DOI: 10.1038/s41467-022-34206-8

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