Making Sense of Genomic Networks

The Science

Genomes contain the information underlying an organism’s molecular functions. One way to compare the entire genomes of different organisms is to compare their gene-family content profiles, which is effectively a comparison of their functional potential. Standard networks, when used to model phylogenomic similarities, are not capable of capturing some of the underlying complexity of the relationships between genomes. To address this limitation, scientists at Oak Ridge National Laboratory, funded through the Department of Energy’s Plant-Microbe Interfaces Science Focus Area, developed a new three-way similarity metric and constructed three-way networks modeling the relationships among 211 bacterial genomes. They found that such three-way networks find cross-species genomic similarities that would otherwise have been missed by simpler models such as standard networks. Interactions within and between the multiple species that make up the complex microbial communities associated with plant roots are believed to influence the plant’s overall health and vigor and may contribute to the plant’s ability to survive adverse environmental conditions. This research is the first time the concept of three-way networks has been applied in the field of comparative genomics. These networks will be a useful tool to model and reveal complex interspecific bacterial relationships that are not found using the conventional two-way network models, and could pave the way toward deciphering intricate plant-microbe and microbe-microbe interactions.

Principal Investigator

Daniel A. Jacobson
Oak Ridge National Laboratory

BER Program Manager

Kari Perez

U.S. Department of Energy, Biological and Environmental Research (SC-33)
Biological Systems Science Division
[email protected]


Weighill, D. A., and D. A. Jacobson. 2015. “Three-Way Networks: Application of Hypergraphs for Modelling Increased Complexity in Comparative Genomics,” PLoS Computational Biology 11(3), e1004079. DOI:10.1371/journal.pcbi.1004079.