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Understanding carbon utilization routes between high and low starch-producing cultivars of cassava through Flux Balance Analysis

Analysis of metabolic flux was used for system level assessment of carbon partitioning in Kasetsart 50 (KU50) and Hanatee (HN) cassava cultivars to understand the metabolic routes for their distinct phenotypes. First, the c onstraint- b ased metabolic m odel of cassava storage r oots, rMeCBM, was de...

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Published in:Scientific reports 2019-02, Vol.9 (1), p.2964-2964, Article 2964
Main Authors: Chiewchankaset, Porntip, Siriwat, Wanatsanan, Suksangpanomrung, Malinee, Boonseng, Opas, Meechai, Asawin, Tanticharoen, Morakot, Kalapanulak, Saowalak, Saithong, Treenut
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Language:English
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Summary:Analysis of metabolic flux was used for system level assessment of carbon partitioning in Kasetsart 50 (KU50) and Hanatee (HN) cassava cultivars to understand the metabolic routes for their distinct phenotypes. First, the c onstraint- b ased metabolic m odel of cassava storage r oots, rMeCBM, was developed based on the carbon assimilation pathway of cassava. Following the subcellular compartmentalization and curation to ensure full network connectivity and reflect the complexity of eukaryotic cells, cultivar specific data on sucrose uptake and biomass synthesis were input, and rMeCBM model was used to simulate storage root growth in KU50 and HN. Results showed that rMeCBM-KU50 and rMeCBM-HN models well imitated the storage root growth. The flux-sum analysis revealed that both cultivars utilized different metabolic precursors to produce energy in plastid. More carbon flux was invested in the syntheses of carbohydrates and amino acids in KU50 than in HN. Also, KU50 utilized less flux for respiration and less energy to synthesize one gram of dry storage root. These results may disclose metabolic potential of KU50 underlying its higher storage root and starch yield over HN. Moreover, sensitivity analysis indicated the robustness of rMeCBM model. The knowledge gained might be useful for identifying engineering targets for cassava yield improvement.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-019-39920-w