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

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 genom...

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Detalles Bibliográficos
Autores principales: Sang, Yupeng, Long, Zhiqin, Dan, Xuming, Feng, Jiajun, Shi, Tingting, Jia, Changfu, Zhang, Xinxin, Lai, Qiang, Yang, Guanglei, Zhang, Hongying, Xu, Xiaoting, Liu, Huanhuan, Jiang, Yuanzhong, Ingvarsson, Pär K., Liu, Jianquan, Mao, Kangshan, Wang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626627/
https://www.ncbi.nlm.nih.gov/pubmed/36319648
http://dx.doi.org/10.1038/s41467-022-34206-8
Descripción
Sumario: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.