ArticleNature communications2023
Identification of gene function based on models capturing natural variability of Arabidopsis thaliana lipid metabolism.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Plasticity of metabolism in plants.The Plant journal : for cell and molecular biology · 2026Review
- Constraint-based metabolic modeling reveals metabolic properties underpinning the unprecedented growth of Chlorella ohadii.The New phytologist · 2025Article
- Evaluating plant growth-defense trade-offs by modeling the interaction between primary and secondary metabolism.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A data-integrative modeling approach accurately characterizes the effects of mutations on Arabidopsis lipid metabolism.Plant physiology · 2025Article
- Go with the flux: Modeling accurately predicts phenotypes of Arabidopsis lipid mutants.Plant physiology · 2024Article
- Modulating Microbial Materials - Engineering Bacterial Cellulose with Synthetic Biology.ACS synthetic biology · 2024Review
- Metabolic Flux Analysis ofInternational journal of molecular sciences · 2024Article
- Identification of gene function based on models capturing natural variability of Arabidopsis thaliana lipid metabolism.Nature communications · 2023Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lipids play fundamental roles in regulating agronomically important traits. Advances in plant lipid metabolism have until recently largely been based on reductionist approaches, although modulation of its components can have system-wide effects. However, existing models of plant lipid metabolism provide lumped representations, hindering detailed study of component modulation. Here, we present the Plant Lipid Module (PLM) which provides a mechanistic description of lipid metabolism in the Arabidopsis thaliana rosette. We demonstrate that the PLM can be readily integrated in models of A. thaliana Col-0 metabolism, yielding accurate predictions (83%) of single lethal knock-outs and 75% concordance between measured transcript and predicted flux changes under extended darkness. Genome-wide associations with fluxes obtained by integrating the PLM in diel condition- and accession-specific models identify up to 65 candidate genes modulating A. thaliana lipid metabolism. Using mutant lines, we validate up to 40% of the candidates, paving the way for identification of metabolic gene function based on models capturing natural variability in metabolism.
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