Gene networks are popularly used in systems biology to show functional associations among genes within a single genome, taking advantage of available experimental data on intermolecular interactions. Co-evolutionary networks are another way of showing functional associations among genes, in this case using presence/absence patterns of homologous genes across genomes to predict likely interaction partners. A nice example from proteins that I'm interested in are the components of the selenocysteine incorporation machinery for incorporating the amino acid selenocysteine into growing peptides. Not all organisms utilise selenonocysteine, but those who do encode a whole package of genes for its synthesis, charging onto tRNA and delivery to the ribosome. If a gene X was to be found in only that strange collection of (not always closely related) organisms with the selenocysteine machinery, chances are that X either uses selenocysteine or is also involved in its metabolism. As an aside, STRING is a really nice web application for visualising networks of functional associations compiled from various sources of evidence (co-occurence, co-expression, gene neighbourhood, and experiments).
A new paper by Zhang et al. in GBE presents a new and interesting approach for analysing co-evolutionary networks, by detecting Mutually Exclusive Orthologous Modules (MEOMs). In their words: "A MEOM is composed of two sets of gene families, each including gene families that tend to appear in the same organisms, such that the two sets tend to mutually exclude each other (if one set appears in a certain organism the second set does not)."
MEOMs are interesting because they reflect the replacement of one set of genes by another. This could be due to lineage-specific or environment-specific adaptations. The authors analyze a co-evolutionary network based on 383 organisms from across the tree of life and find that MEOMs most often include gene families involved in transport, energy production, metabolism, and translation. They suggest that changes in the metabolic environment of an organism require adaptation to new sources of energy, and this triggers of replacement of genes, complexes and pathways in individual lineages. They also find many outer membrane proteins in their MEOMs, suggesting that as these proteins interact with the extracellular environment, they are frequently replaced during adaptation.
It's all very interesting, and I hope the authors will consider making a searchable web interface to their database of MEOMs. Their supplementary data is a bit awkward to navigate, and this kind of data is just crying out for visualisation. I would love to be able to scan proteins in my data sets for potential MEOM membership.
Xiuwei Zhang, Martin Kupiec, Uri Gophna, & Tamir Tuller (2011). Analysis of Co-evolving Gene Families Using Mutually Exclusive Orthologous Modules Genome Biology and Evolution : 10.1093/gbe/evr030
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