Genetic Dissection of Biotic Stress Response Using RiceNet

Rice is a staple food for half of the world's population and a model for studying monocots. Thus, it is highly important to know the key genes in rice that control simple or complex traits that may have significant biological, agricultural, and economic consequences.

Insuk Lee, scientist at Yonsei University in Seoul, Korea, and colleagues constructed an experimentally tested genome-scale gene network for monocots which they called as RiceNet. They evaluated different datasets from five different organisms and the most useful genomes were integrated into a statistical framework that gave clues for the prediction of functional relationships between pairs of genes. Genes could be linked to traits through guilt-by-association, predicting gene attributes based on network neighbors.

Then they used RiceNet to understand the genetics of biotic stress response. Using network guilt-by-association followed by focused protein–protein interaction assays, the research team identified and validated two positive regulators, (LOC_Os01g70580 and LOC_Os02g21510), and one negative regulator (LOC_Os06g12530).

The team also confirmed that RiceNet can accurately predict gene function in maize, another monocotyledonous crop. Therefore, RiceNet can be used to identify genes regulating important traits, and aid engineering pathways important to crop productivity.

The research article is published online at the Proceedings of the National Academy of Sciences of the United States of America: http://www.pnas.org/content/108/45/18548.abstract.