Oral: Translational Research for the Management of Complex Diseases
Identifying new genetic targets for maize ear rot and mycotoxin control through computational subnetwork module analyses
W. SHIM (1), M. Kim (1), H. Zhang (1), H. Yan (1), B. Yoon (1), G. Payne (2), C. Woloshuk (3) (1) Texas A&M University, U.S.A.; (2) North Carolina State University, U.S.A.; (3) Purdue University, U.S.A.
Fumonisins and aflatoxins are two most important mycotoxins in corn with significant risk on market value and health. Tools and strategies currently available to manage mycotoxins are not consistently effective, and there is a need to develop reliable preharvest control strategies, e.g. biocontrol agents and transgenic hybrids, to minimize the entry of mycotoxins into our food supply. With this aim we began screening for new genetic targets for disrupting fungal pathogenicity. We performed Fusarium verticillioides and Aspergillus flavus RNA-Seq from multiple kernel samples (from different maize lines and conditions) and developed a systematic computational network analysis pipeline to discover pathogenicity subnetwork modules. We first built the co-expression networks of these fungi, and subsequently identified functional subnetwork modules consisting of genes that display strongly coordinated behavior in the respective datasets. A computationally efficient branch-out technique, with a probabilistic pathway activity inference scheme, was used to identify functional subnetwork modules likely involved in ear rot and mycotoxin production. These modules contain several enriched GO terms as well as potential pathogenicity genes. Subsequently, we selected putative hub genes in each subnetwork and performed molecular characterization to test their candidacy as new targets for ear rot and mycotoxin control strategies.