A genome-scale network reconstruction (GENRE) is a knowledgebase for an organism and has various applications. Available genome sequences have risen in recent years, but the number of curated GENREs has not kept pace. Existing yeast GENREs contain significant commission and omission errors. Current practices limit the quantity and quality of GENREs. An open and transparent phylogenomic-driven framework is outlined to address these issues. The method is demonstrated with 33 yeasts and fungi in Dikarya. A pan-fungal metabolic network called FYRMENT (Fungal and Yeast Metabolic Network) (https://github.com/LMSE/FYRMENT) is created, and annotated with ortholog groups from AYbRAH (https://github.com/LMSE/AYbRAH). Metabolic models for lower-level taxons are compiled. The fungal pan-GENRE contains 1553 orthologs, 2759 reactions, 2251 metabolites. The GENREs have higher genomic and metabolic coverage than existing yeast and fungal GENREs created with other methods. Metabolic simulations show the maximum amino acid yields from glucose differs between yeast lineages, indicating metabolic networks have evolved. Curating genomes and reactions at higher taxonomic-levels increases the quantity and quality of GENREs than conventional approaches. This approach can scale to other branches in the tree of life.
Keywords: flux balance analysis; metabolic networks; orthology; phylogenomics; yeasts.
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