Table_2_ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species.xlsx

• Main Authors: Eileen Marie Hanna, Xiaokang Zhang, Marta Eide, Shirin Fallahi, Tomasz Furmanek, Fekadu Yadetie, Daniel Craig Zielinski, Anders Goksøyr, Inge Jonassen
• Format: Dataset
• Language: unknown
• Published: 2020
• Subjects: Biochemistry; Molecular Biology; Structural Biology; Enzymes; Protein Trafficking; Proteomics and Intermolecular Interactions (excl. Medical Proteomics); Receptors and Membrane Biology; Signal Transduction; Structural Biology (incl. Macromolecular Modelling); Synthetic Biology; genome-scale metabolic reconstruction; Atlantic cod; less-annotated species; model curation; environmental toxicology; atlantic cod; Gadus morhua
• Online Access: https://doi.org/10.3389/fmolb.2020.591406.s002; https://figshare.com/articles/dataset/Table_2_ReCodLiver0_9_Overcoming_Challenges_in_Genome-Scale_Metabolic_Reconstruction_of_a_Non-model_Species_xlsx/13291646

The availability of genome sequences, annotations, and knowledge of the biochemistry underlying metabolic transformations has led to the generation of metabolic network reconstructions for a wide range of organisms in bacteria, archaea, and eukaryotes. When modeled using mathematical representations, a reconstruction can simulate underlying genotype-phenotype relationships. Accordingly, genome-scale metabolic models (GEMs) can be used to predict the response of organisms to genetic and environmental variations. A bottom-up reconstruction procedure typically starts by generating a draft model from existing annotation data on a target organism. For model species, this part of the process can be straightforward, due to the abundant organism-specific biochemical data. However, the process becomes complicated for non-model less-annotated species. In this paper, we present a draft liver reconstruction, ReCodLiver0.9, of Atlantic cod (Gadus morhua), a non-model teleost fish, as a practicable guide for cases with comparably few resources. Although the reconstruction is considered a draft version, we show that it already has utility in elucidating metabolic response mechanisms to environmental toxicants by mapping gene expression data of exposure experiments to the resulting model.