|MONACO, MARCELA - Cold Spring Harbor Laboratory|
|REN, LIYA - Cold Spring Harbor Laboratory|
|DHARMAWARDHANA, PALITHA - Oregon State University|
|AMARASINGHE, VINDHYA - Oregon State University|
|THOMASON, JIM - Cold Spring Harbor Laboratory|
|NAITHANI, SUSHMA - Oregon State University|
|GARDINER, JACK - Iowa State University|
|JAISWAL, PANKAJ - Oregon State University|
Submitted to: Conference on Genome Informatics
Publication Type: Abstract Only
Publication Acceptance Date: 8/12/2011
Publication Date: 11/2/2011
Citation: Monaco, M., Sen, T.Z., Ren, L., Dharmawardhana, P., Schaeffer, M.L., Amarasinghe, V., Thomason, J., Harper, E.C., Naithani, S., Gardiner, J.M., Lawrence, C.J., Ware, D., Jaiswal, P. 2011. MaizeCyc: Metabolic networks in maize [abstract]. In: Conference on Genome Informatics, November 2-5, 2011, Cold Spring Harbor, New York. p. 1.
Technical Abstract: MaizeCyc is a catalog of known and predicted metabolic and transport pathways that enables plant researchers to graphically represent the metabolome of maize (Zea mays), thereby supporting integrated systems-biology analysis. Supported analyses include molecular and genetic/phenotypic profiling (e.g., transcriptomics, proteomics, and metabolomics data sets) and their comparison across species, tissues/organs, and developmental stages. Pathways, reactions, and genes in the catalog are based on the electronic and manual annotations of 39,656 maize gene models in the RefGen_v2 filtered set (Maize Genome Sequencing Project, release 5b.60), and phylogenetically-derived projections from related plant models, including Arabidopsis and rice. This resource includes sequence-based associations provided by Gramene, MaizeSequence.org, and MaizeGDB (Maize Genetics and Genomics Database) external database entries from EntrezGene, UniProt-SwissProt, and Gene Ontology. Mapping of classical phenotypes to sequenced genomic loci were obtained from Schnable and Freeling (2011), proteomics-supported gene annotations from Friso et al. (2010), and EC code mappings from MaizeGDB Pathways. We used expression-profiling data from the ATLAS transcriptomics data set (Sekhon et al., 2010) to create exemplar visualizations of spacio-temporally regulated global gene expression in maize, and will provide these representations freely to the community. MaizeCyc is currently available at Gramene and MaizeGDB, and as of version 2.0, it will also be included in the SEED website for public view and data download. The database was created using the PathoLogic module of Pathway Tools (ver 15.0). This work is supported by the National Science Foundation (Gramene: A Platform for Comparative Plant Genomics), and the USDA-ARS (The Maize Genetics and Genomics Database).