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Title: A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

item MUSUNGU, B - Southern Illinois University
item Bhatnagar, Deepak
item Brown, Robert
item FAKHOURY, A - Southern Illinois University
item GEISLER, M - Southern Illinois University

Submitted to: Frontiers in Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/21/2015
Publication Date: 6/4/2015
Citation: Musungu, B.M., Bhatnagar, D., Brown, R.L., Fakhoury, A.M., Geisler, M. 2015. A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize. Frontiers in Genetics. 6:201. doi:10.3389/fgene.2015-00201.

Interpretive Summary: The fungus named Aspergillus flavus produces a poison called aflatoxin when it infects corn kernels. Aflatoxin prevents the corn from being used commercially. The best strategy for controlling this problem is to develop corn that is resistant to aflatoxin contamination. Towards this aim, we isolated and identified through comparisons of resistant with susceptible corn lines, proteins that are produced in relatively higher amounts in the resistant lines. Proteins also physically interact with other proteins to provide resistance to corn. To determine protein-protein interactions, we developed a roadmap of protein-protein interactions called a corn interactome. We constructed this using interactomes of other species. This will help us to predict and confirm proteins and their interactions with other proteins that are important to regulating resistance in corn. This knowledge may be useful to breeders for selecting markers to transfer resistance and develop aflatoxin-resistant commercial corn. This could lead to future savings of millions of dollars to growers, as a result of the elimination of aflatoxin contamination of corn.

Technical Abstract: An interactome is the genome-wide roadmap of protein-protein interactions that occur within an organism. Interactomes for humans, the fruit fly, and now plants such as Arabidopsis thaliana and Oryza sativa have been generated using high throughput experimental methods. It is possible to use these experimentally derived interactomes to predict interactomes for other species based on orthology of genes between species. To build an interactome for Zea mays (maize), orthologs were identified to determine a one-to-one orthology between genomes of maize and reference species where both maize orthologs occurred for an interaction in the reference species; this implied that the proteins likely interacted in maize. We predicted 60,174 (one to one/ many to many) interactions for 6,257 maize proteins, including 1,532 (homo-interactions) and 58,642 (hetero-interactions) in the interactome. The maize interactomes were annotated with various layers of GO-ontology, Interpro, and gene expression data to form multiple layers of confidence throughout the maize interactome network. The proposed interactome provides researchers with a tool to identify possible interactions that occur between key proteins in maize.