Inferring evolutionary dynamics is difficult because there is not a one-to-one relationship between genotype and phenotype. One phenotype may be the product of different genotypes. Conversely, the expression of a given genotype depends on the environment. This leads Michael Travisano and Ruth Shaw to guarded pessimism in this open access article published in February’s Evolution. The authors argue that more work is needed that directly examines process – something their own research programmes in experimental evolution demonstrate very well.
It is possible to generalise this. The ubiquity of genome-level data (driven by the low cost of high-throughput sequencing) is worrying if it leads to an emphasis on descriptions of genome-level phenomena without attention to their evolutionary causes. If this were chemistry we might end up counting the molecular masses of elements thinking that these are fundamental chemical properties rather than being contingent on isotope proportions. Fortunately a body of evolutionary theory has built up allowing us to interpret genome data although recent strident criticism of the ENCODE project suggests that consistency with theory is not always achieved. This dispute centres on what it means to impute “function” to a genome region. From an evolutionary perspective sequence conservation is the best guide, but, given the complexity of evolution, it is far from perfect and it is precisely this complexity with which we should engage if we want to understand genome structure and function.
This blog is named after an example of complexity in evolutionary dynamics and I’d like it to prioritise our developing understanding of processes – which is increasingly enhanced through experimental evolution as well as via the development of theory and application of the comparative method.
This week’s PLoS Biology brings a rapid answer to Travisano’s and Shaw’s call in a paper by Matthew Herron and Michael Doebeli that explores the fate of mutations in a system undergoing diversifying (and frequency-dependent) selection. This kind of selection leads to divergent genetic changes between subpopulations and here it leads to the evolution of two ecotypes that exploit the two available carbon sources differently (see this summary in the same journal).
This is a really nice example of evolutionary complexity on several levels. First, parallel and divergent changes were observed in populations indicating a role for chance and for necessity in this system – and suggesting partial degeneracy in the genotype-phenotype map. Second, the role of history was indicated by the manner in which mutations spread within the two ecotypes. Some mutations inferred to be from one ecotype would only increase in frequency after mutations from the other ecotype had risen to intermediate frequencies. The last point is critical because it also indicates that ecological interactions were responsible: overall the best explanation of the data supported a role for clonal interference within ecotypes, but also for frequency-dependent selection between them.