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The quality of metabolic pathway resources depends on initial enzymatic function assignments: a case for maize

Author:
Walsh, Jesse R., Zhang, Peifen, Rhee, Seung Y., Dickerson, Julie A., Sen, Taner Z.
Source:
BMC Systems Biology 2016 v.10 pp. 1-9
ISSN:
1752-0509
Subject:
biochemical pathways, bioinformatics, biologists, computer software, corn, genes, information sources, models, prediction, proteins, researchers
Abstract:
As metabolic pathway resources become more commonly available, researchers have unprecedented access to information about their organism of interest. Despite efforts to ensure consistency between various resources, information content and quality can vary widely. Two maize metabolic pathway resources for the B73 inbred line, CornCyc4.0 and MaizeCyc2.2, are based on the same gene model set and were developed using Pathway Tools software. These resources differ in their initial enzymatic function assignments and in the extent of manual curation. We present an in-depth comparison between CornCyc and MaizeCyc to demonstrate the effect of initial computational enzymatic function assignments on the final quality and content of metabolic pathway resources. MaizeCyc contains over twice as many annotated genes and more proteins than CornCyc. CornCyc contains on average 1.6 transcripts per gene, while MaizeCyc contains almost no alternate splicing. MaizeCyc does not match CornCyc’s breadth in representing the metabolic domain, having fewer compounds, fewer reactions, and fewer pathways than CornCyc. CornCyc predictions are more accurate than those in MaizeCyc when compared to experimentally determined function assignments, demonstrating the relative strength of the enzymatic function assignment pipeline used to generate CornCyc. Our results show that the quality of initial enzymatic function assignments primarily determines the quality of the final metabolic pathway resource. Therefore, biologists should pay close attention to the methods and information sources used to develop a metabolic pathway resource to gauge the utility of using such functional assignments to construct hypotheses for experimental studies.
Agid:
5695347
Handle:
10113/5695347