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ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species

Hanna, Eileen Marie; Zhang, Xiaokang; Eide, Marta; Fallahi, Shirin; Furmanek, Tomasz; Yadetie, Fekadu; Zielinski, Daniel Craig; Goksøyr, Anders; Jonassen, Inge
Peer reviewed, Journal article
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URI
https://hdl.handle.net/11250/2722935
Date
2020
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Original version
Frontiers in Molecular Biosciences. 2020, 7 345-?.   10.3389/fmolb.2020.591406
Abstract
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.
Journal
Frontiers in Molecular Biosciences

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