ArticlePlant physiology2023
Metabolome plasticity in 241 Arabidopsis thaliana accessions reveals evolutionary cold adaptation processes.
Article in Plant physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 25 citations in OpenAlex.
- Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging.NPJ systems biology and applications · 2025Trial
- Clusia genomes shed light on the evolution and diversity of crassulacean acid metabolism physiotypes.Nature communications · 2026Article
- Photosynthesis-related genetic and transcriptomic variations contribute to adaptive trait diversity in global Arabidopsis thaliana populations.BMC plant biology · 2026Article
- Molecular mechanisms of plant freezing tolerance: from cold signal perception to adaptive responses.Frontiers in plant science · 2026Review
- Secondary Metabolite Plasticity inACS omega · 2025Article
- A model for the adaptation of Euryale ferox leaves to aquatic environments through EfCGT1-controlled flavonoid C-glycoside-specific accumulation in epidermis cells.Plant biotechnology journal · 2025Article
- Millets for a sustainable future.Journal of experimental botany · 2025Review
- Chemical application improves stress resilience in plants.Plant molecular biology · 2025Review
- Embracing plant plasticity or robustness as a means of ensuring food security.Nature communications · 2025Review
- Metabolic plasticity and adaptive evolution inFrontiers in plant science · 2025Review
- Natural variation in the chickpea metabolome under drought stress.Plant biotechnology journal · 2024Article
- Network structure and fluctuation data improve inference of metabolic interaction strengths with the inverse Jacobian.NPJ systems biology and applications · 2024Article
- A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools.Briefings in bioinformatics · 2024Review
- A large-effect fitness trade-off across environments is explained by a single mutation affecting cold acclimation.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- COVRECON: automated integration of genome- and metabolome-scale network reconstruction and data-driven inverse modeling of metabolic interaction networks.Bioinformatics (Oxford, England) · 2023Article
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Authors and funding
13 authors at 6 institutions in 3 countries.
Funding
Abstract
Acclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis thaliana) were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome × environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.
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