Exploring Molecular and Genetic Differences in Angelica biserrata Roots Under Environmental Changes DOI Open Access
Cheng Hu, Qian Li, Xiaoqin Ding

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(8), P. 3894 - 3894

Published: April 20, 2025

Angelica biserrata (Shan et Yuan) Yuan Shan (A. biserrata) roots, a widely distributed medicinal crop with intraspecific diversity, exhibits significant variability in coumarin content across habitats. This study integrated metabolomics and transcriptomics to dissect the spatial heterogeneity metabolite profiles gene expression, revealing mechanisms driving biosynthesis divergence. By synthesizing climate-related big data machine learning Bayesian-optimized deep models, we identified key environmental drivers predicted optimal cultivation conditions. The findings were as follows: (1) differential regions most strongly influenced coumarin; (2) upstream genes (such PAL-1, PAL-2, BGLU44, etc.) modulated downstream metabolites; (3) elevation (Elev) warmest quarter temperature (Bio10) dominated variation, whereas May solar radiation (Srad5) precipitation seasonality (Bio15) controlled transcriptomic reprogramming; (4) optimized environment for bioactive compounds included mean annual (Bio1) = 9.99 °C, (Bio12) 1493 mm, Elev 1728 m, cumulative 152,643 kJ·m−2·day−1, soil organic carbon 11,883 g·kg−1. aimed clarify biological characteristics regulatory of A. roots different habitats, establish theoretical framework understanding molecular controlling metabolic changes under various contribute elucidating formation active constituents while facilitating their effective utilization.

Language: Английский

Exploring Molecular and Genetic Differences in Angelica biserrata Roots Under Environmental Changes DOI Open Access
Cheng Hu, Qian Li, Xiaoqin Ding

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(8), P. 3894 - 3894

Published: April 20, 2025

Angelica biserrata (Shan et Yuan) Yuan Shan (A. biserrata) roots, a widely distributed medicinal crop with intraspecific diversity, exhibits significant variability in coumarin content across habitats. This study integrated metabolomics and transcriptomics to dissect the spatial heterogeneity metabolite profiles gene expression, revealing mechanisms driving biosynthesis divergence. By synthesizing climate-related big data machine learning Bayesian-optimized deep models, we identified key environmental drivers predicted optimal cultivation conditions. The findings were as follows: (1) differential regions most strongly influenced coumarin; (2) upstream genes (such PAL-1, PAL-2, BGLU44, etc.) modulated downstream metabolites; (3) elevation (Elev) warmest quarter temperature (Bio10) dominated variation, whereas May solar radiation (Srad5) precipitation seasonality (Bio15) controlled transcriptomic reprogramming; (4) optimized environment for bioactive compounds included mean annual (Bio1) = 9.99 °C, (Bio12) 1493 mm, Elev 1728 m, cumulative 152,643 kJ·m−2·day−1, soil organic carbon 11,883 g·kg−1. aimed clarify biological characteristics regulatory of A. roots different habitats, establish theoretical framework understanding molecular controlling metabolic changes under various contribute elucidating formation active constituents while facilitating their effective utilization.

Language: Английский

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