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Title: The quality of metabolic pathway resources depends on initial enzymatic function assignments and level of manual curation: A case for maize

item WALSH, JESSE - Iowa State University
item Schaeffer, Mary
item ZHANG, PEIFEN - Carnegie Institute - Washington
item RHEE, SEUNG - Carnegie Institute - Washington
item DICKERSON, JULIE - Iowa State University
item Sen, Taner

Submitted to: BMC Systems Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/9/2016
Publication Date: 11/29/2016
Citation: Walsh, J., Schaeffer, M.L., Zhang, P., Rhee, S., Dickerson, J., Sen, T.Z. 2016. The quality of metabolic pathway resources depends on initial enzymatic function assignments and level of manual curation: A case for maize. BMC Systems Biology. 10:129.

Interpretive Summary: In order to manipulate agronomically important traits, we need to understand the physical and chemical interactions of proteins in plant cells. A large number of the chemical interactions involve the sequential action of enzymes that form metabolic pathways. Assigning enzymes of a specific species to metabolic pathways is an enormous task, and therefore it is usually performed through computational methods followed by a curator’s painstaking evaluation of the scientific literature. Though different computational methods are used to build metabolic pathways, our understanding of their comparative quality is limited. Here we address this problem and compare two metabolic pathway resources created by two different computational methods for the same species, maize. We discovered that using different computational methods can create resources of differing quality. Our work will especially help maize researchers, as well as the larger community of geneticists, to discriminate among available metabolic pathways to use the one best suited to further our understanding of how genes influence agronomical important traits.

Technical 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.