Detecting coevolution

Yeang and Haussler have developed an interesting model of coevolution … the selective constraints on components of a molecular apparatus which require coordinated changes of its components. The best studied of these being the compensatory mutations required in RNA secondary structure. Yeang uses a general continuous-time Markov process to model substitution at two sites. The null hypothesis being that the sites evolve neutrally. The alternative model is one where the changes observed between the two sites are co-occuring … favoring double changes over singles. The resulting probabilistic graphical model is relatively general, as demonstrated by their two recent publications.

Non-Adaptive Processes

Last week a review by Michael Lynch came out in Nature Reviews Genetics entitled, “The evolution of genetic networks by non-adaptive processes”.

In this review, Lynch takes a population genetics perspective on network evolution. Using relatively simple but powerful mathematical models of basic evolutionary processes, Lynch shows that many of the characteristic properties of networks (metabolic, developmental, and regulatory) that have been highly advertised lately (such as complexity, organization, robustness, evolvability, etc.) are just a basic consequence of the underlying nucleotide evolutionary process.