In silico predicted essential genes required for zebrafish ( Danio rerio ) steroid hormone production
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abstract
Genome-scale metabolic models associate genes and transcript enzymes involved in biochemical reactions. We present a genome-scale stoichiometric reconstruction of the zebrafish (Danio rerio) steroidogenic network and apply linear programming methods to investigate the association between steroidogenic gene expression and network redundancy required for the productions of the key reproductive steroid hormone of 17-estradiol. Network-wide gene deletions helped identify essential genes required for its production with the in silico identified genes giving good agreement with those required in vivo during reproductive development and maturation. The essential genes were shown to be mainly involved with the initial reactions of steroidogenesis. Furthermore, the productions of intermediate metabolites (17-hydroxyprogesterone and androstenedione), highly participant within steroidogenic reactions were also shown to allow network redundancy. This analysis is of importance as steroidogenic enzyme genes down-regulated in vivo in zebrafish exposed to the environmental stressor of hypoxia or low oxygen stress ( 2 mg/L dissolved oxygen) showed 71% agreement with in silico genes identified as being essential for 17-estradiol production. This agreement is relevant, as the in vivo down-regulated steroidogenic genes were also correlated with lowered sex steroid hormone concentrations in zebrafish. Copyright 2010 ACM.
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Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
