@article{CordobaTongBurgosetal.2023,
  author    = {C{\´o}rdoba, Sandra Correa and Tong, Hao and Burgos, Asdrubal and Zhu, Feng and Alseekh, Saleh and Fernie, Alisdair R. and Nikoloski, Zoran},
  title     = {Identification of gene function based on models capturing natural variability of Arabidopsis thaliana lipid metabolism},
  series = {Nature Communications},
  volume    = {14},
  journal   = {Nature Communications},
  number    = {1},
  publisher = {Springer Nature},
  address   = {London},
  issn      = {2041-1723},
  doi       = {10.1038/s41467-023-40644-9},
  pages     = {12},
  year      = {2023},
  abstract  = {The use of automated tools to reconstruct lipid metabolic pathways is not warranted in plants. Here, the authors construct Plant Lipid Module for Arabidopsis rosette using constraint-based modeling, demonstrate its integration in other plant metabolic models, and use it to dissect the genetic architecture of lipid metabolism. 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.},
  language  = {en}
}