The gene neighborhood in prokaryotic genomes has been effectively utilized in inferring co-functional networks in various organisms. Previously, such genomic context information has been sought among completely assembled prokaryotic genomes. Here, we present a method to infer functional gene networks according to the gene neighborhood in metagenome contigs, which are incompletely assembled genomic fragments. Given that the amount of metagenome sequence data has now surpassed that of completely assembled prokaryotic genomes in the public domain, we expect benefits of inferring networks by the metagenome-based gene neighborhood. We generated co-functional networks for diverse taxonomical species using metagenomics contigs derived from the human microbiome and the ocean microbiome. We found that the networks based on the metagenome gene neighborhood outperformed those based on 1748 completely assembled prokaryotic genomes. We also demonstrated that the metagenome-based gene neighborhood could predict genes related to virulence-associated phenotypes in a bacterial pathogen, indicating that metagenome-based functional links could be sufficiently predictive for some phenotypes of medical importance. Owing to the exponential growth of metagenome sequence data in public repositories, metagenome-based inference of co-functional networks will facilitate understanding of gene functions and pathways in diverse species.
All Science Journal Classification (ASJC) codes
- Animal Science and Zoology
- Biochemistry, Genetics and Molecular Biology(all)