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Integrating population information using DNA methylation to explore the spatiotemporal dynamics and developmental mechanisms of populations
  • +8
  • Wei Liu,
  • Chu Jiang,
  • Zheng-Feng Wang,
  • Jie Chen,
  • Hong-Ling Cao,
  • Yong-Biao Lin,
  • Xue-Jun Oyang,
  • Ru-Fang Deng,
  • Yang Liu,
  • Wanhui Ye,
  • Ju-Yu Lian
Wei Liu
South China Botanical Garden, Chinese Academy of Sciences

Corresponding Author:liuwei@scbg.ac.cn

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Chu Jiang
South China Botanical Garden, Chinese Academy of Sciences
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Zheng-Feng Wang
South China Botanical Garden, Chinese Academy of Sciences
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Jie Chen
Research Institute of Tropical Forestry Chinese Academy of Forestry
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Hong-Ling Cao
South China Botanical Garden, Chinese Academy of Sciences
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Yong-Biao Lin
South China Botanical Garden, Chinese Academy of Sciences
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Xue-Jun Oyang
South China Botanical Garden, Chinese Academy of Sciences
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Ru-Fang Deng
South China Botanical Garden, Chinese Academy of Sciences
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Yang Liu
University of the Chinese Academy of Sciences
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Wanhui Ye
South China Botanical Garden, Chinese Academy of Sciences
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Ju-Yu Lian
South China Botanical Garden, Chinese Academy of Sciences
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Abstract

Serious disconnection among researches on individual physiological adaption, population genetic diversity and spatiotemporal demography has obstructed us in the knowledge of plant population ecology. Here we develop an approach to integrate those three research aspects by taking advantage of recent knowledge about DNA methylation and multivariate analysis. We show that by using various epigenetic parameters corresponding to individual physiological metabolic reprogramming potential, gene expression repression degree and physiological reaction characteristics, the contribution of various biotic and abiotic factors to an individual state and population structure can be quantified. Furthermore, population dynamics can be narrowly estimated by analysing DNA methylation of populations at different developmental stages. This study demonstrates an approach for the overall analysis of plant populations and exploring the spatiotemporal dynamics and developmental mechanisms of a population using Castanopsis chinensis as the model species.