Reprogramming of Metabolome and Transcriptome Shaped the Elevational Adaptation of <i>Quercus variabilis</i> by Regulating Leaf Functional Traits

Exploring how plants adapt to environmental changes is key to plant survive and protection under accelerating climate change. Quercus variabilis is widely distributed in China with high economic and ecological value, yet its elevational adaptation mechanism remains unclear. Here, we investigated the leaf functional traits, metabolome and transcriptome of Q. variabilis along an elevational gradient (800-1400 m) in Mt. Li, China. Results showed that leaves at higher elevations became smaller, narrower, thicker, with smaller and denser stomata, and maintained higher levels of nitrogen, soluble sugar, total phenol, lignin and soluble sugar-to-starch ratio. With increasing elevation, Q. variabilis underwent a metabolic shift from being dominated by primary metabolism to secondary metabolism, and 1300 m could be identified as the transition point. Particularly, phenylpropanoid metabolism and its metabolites (flavonoids and phenolic acids) played crucial roles in its adaptation to elevations. Moreover, 24 hub transcription factors (TFs) were screened through WGCNA and verified by RT-qPCR. Environmental factors not only directly influenced leaf functional traits, but also affected metabolite accumulation through TF-mediated gene expression, which in turn influenced leaf functional traits. This study highlights that integrating plant functional traits, metabolome and transcriptome simultaneously provides novel insights into the mechanisms for shaping plants' adaptability.

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Publication Details

Journal
Plant Cell & Environment
Published
2025-05-05
DOI
https://doi.org/10.1111/pce.15595
Citations
3
Primary Topic
Plant Gene Expression Analysis
Type
article
Field-Weighted Citation Impact
2.42
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article

Reprogramming of Metabolome and Transcriptome Shaped the Elevational Adaptation of Quercus variabilis by Regulating Leaf Functional Traits

Hongyi He, Xiongzhi Zhang, Chenlin Wang, Xiuqing Yang et al.
3 citations
Plant Cell & Environment
Plant Gene Expression Analysis
2.42
article

Reprogramming of Metabolome and Transcriptome Shaped the Elevational Adaptation of Quercus variabilis by Regulating Leaf Functional Traits

Hongyi He, Xiongzhi Zhang, Chenlin Wang, Xiuqing Yang, Houjuan Song, Haibo Li, Yuchen Ren, Baixue Zhang, Xinyue Wang, Huifang Zhang, Jingjing Wang, Yaru Wang, Jieyan Yang, Siyuan Huangfu
article en
3 citations

Abstract

Exploring how plants adapt to environmental changes is key to plant survive and protection under accelerating climate change. Quercus variabilis is widely distributed in China with high economic and ecological value, yet its elevational adaptation mechanism remains unclear. Here, we investigated the leaf functional traits, metabolome and transcriptome of Q. variabilis along an elevational gradient (800-1400 m) in Mt. Li, China. Results showed that leaves at higher elevations became smaller, narrower, thicker, with smaller and denser stomata, and maintained higher levels of nitrogen, soluble sugar, total phenol, lignin and soluble sugar-to-starch ratio. With increasing elevation, Q. variabilis underwent a metabolic shift from being dominated by primary metabolism to secondary metabolism, and 1300 m could be identified as the transition point. Particularly, phenylpropanoid metabolism and its metabolites (flavonoids and phenolic acids) played crucial roles in its adaptation to elevations. Moreover, 24 hub transcription factors (TFs) were screened through WGCNA and verified by RT-qPCR. Environmental factors not only directly influenced leaf functional traits, but also affected metabolite accumulation through TF-mediated gene expression, which in turn influenced leaf functional traits. This study highlights that integrating plant functional traits, metabolome and transcriptome simultaneously provides novel insights into the mechanisms for shaping plants' adaptability.

Plant Cell & EnvironmentVol. 48(8)
Shanxi Agricultural University (CN)
Climate action
Openalex Percentile: Top 12%
Plant Gene Expression Analysis
2.42
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