Introduction to Pathways and Gene Expression Analysis at Gramene

Gramene currently hosts ten species-specific Pathways Databases; RiceCyc (Oryza sativa japonica), SorghumCyc (Sorghum bicolor), MaizeCyc (Zea mays), BrachyCyc (Brachypodium distachyon), AraCyc(Arabidopsis thaliana), MedicCyc(Medicago truncatula), PoplarCyc(Populus trichocarpa), CoffeaCyc(Coffea canephora), LycoCyc(Solanum lycopersicum) and PotatoCyc. These Cyc databases were built using the pathway tool software developed by Peter Karp and his team at SRI international and using eukaryotic reference database MetaCyc.
Gramene developed RiceCyc, SorghumCyc, MaizeCyc and BrachyCyc, the pathways databases for monocots.  AraCyc, MedicCyc, PoplarCyc, CoffeaCyc, LycoCyc, and PotatoCyc, the pathways databases for dicots, were created by our collaborators and are mirrored by Gramene.  Gramene also hosts three reference databases; EcoCyc (Escherichia coli), MetaCyc (a generic Reference Pathway Database for eukaryotes) and PlantCyc (see Plant Metabolic Pathway Database) that were built based on the evidence collected from published biochemical studies spanning more than a century, and recent metabolic mutant studies.
A user can choose to browse any of these online database or can download a desktop copy, which can be used by installing pathway tools software from SRI international website free of charge.  One can see the total number of enzymes, transporters and compounds and polypeptides present in a given pathway database.  Both desktop and online versions allow browsing, and searching by gene name, enzyme name, metabolite name or pathway name.  Users can get into further details of the enzymes, or the gene homologs likely to encode a given enzyme, find the chemical structure of the metabolite or chemical compound or link to the cited literature.  User can also compare enzymatic reaction(s) or a pathway across two or more species.
A Cyc database also provides a cellular overview of the metabolic networks as a schematic diagram, where nodes represent metabolites (with shape indicating class of metabolite) and lines represent reactions.  One can move the mouse over a metabolite icon or a reaction line to identify respective metabolite, reaction or pathway and by clicking on it one can open the respective detailed page.
The Omics-Viewer Tool allows researchers to upload and display high-throughput expression datasets (e.g. microarray, RNA-Seq, proteome, metabolome, reaction flux data etc.) onto a cellular overview diagram.  Users can compare various samples or treatments in a context of pathways or overall cellular metabolic network.
In the following webinar, we show browsing of RiceCyc, and analysis of microarray expression data using the Omics-Viewer's tool.   In addition, the expression data can be analyzed in the context of the Genome and is being briefly discussed in the webinar. For more information  on Genome Browser see 'Visualization & Analyses of the Genomic Data on Gramene’s Ensembl Genome Browsers'