Research

Research Summary

The ultimate goal of biological research is to manipulate traits that are important for medicine, agriculture, and bio-industry. This challenging task first requires good understanding of association between genotype and phenotype. Because of high complexity of genotype as well as phenotype, complexity of the genotype-phenotype association could be even untouchable by combinatorial explosion of the number of possible associations. Therefore, modern genetics needs to be more systematic and predictive. Recently we proposed network-guided approach for genetics of complex traits. First, we construct probabilistic functional gene networks for cells or organisms by benchmarking and integrating heterogeneous multi-omics data that are in general publicly available. Then, using guilt-by-association, and other algorithms of network propagation of known biological information, we predict gene functions, phenotypic effect of loss-of-function, and epistatic interaction. The information can contribute to reconstruction of map between genotype and phenotype. The network-guided genetics method has been effectively applied for various organisms; from simple microbe yeast, to multicellular animal C. elegans, to the reference plant Arabidopsis, to the reference crop rice, and to the human.

Research Highlight

• 2011 Nature Reviews Genetics, Research highlight (Predicting genetic interaction)
• 2008 Bioessay, What the papers say (WormNet)
• 2008 Genome Biology, Minireview (WormNet)
• 2008 Nature methods, Research highlight (WormNet)
• 2008 Nature Genetics coverstory (WormNet): Network perturbation predicts phenotype

Collaborators

Human/Animal Systems Biology

• Edward Marcotte, University of Texas at Austin, USA
• Ben Lehner, Systems Biology Unit, EMBL-CRG, Spain
• Jonghoon Kim, Korea University, Korea

Crop/Plant Systems Biology

• Sue Rhee, Carnegie Institution of Science, USA
• Pamela Ronald, University of California at Davis, USA
• Thomas Brutnell, Danforth Plant Science Center, USA
• Sangdong Yoo, Korea University, Korea

Microbial Systems Biology

• Yongsun Bahn, Yonsei University, Korea
• Sangsun Yoon, Yonsei Medical School, Korea