Quantifying Parallel Evolution

Parallel evolution is consistently observed across the tree of life. However, the degree of parallelism between replicate populations in evolution experiments is rarely quantified at the gene level. Here we examine parallel evolution as the degree of covariance between replicate populations, providing a justification for the use of dimensionality reduction. We examine the extent that signals of gene-level covariance can be inferred in microbial evolve-and-resequence evolution experiments, finding that deviations from parallelism are difficult to quantify at a given point in time. However, this low statistical signal means that covariance between replicate populations is unlikely to interfere with the ability to detect divergent evolutionary trajectories for populations in different environments. Finally, we find evidence suggesting that temporal patterns of parallelism are comparatively easier to detect and that these patterns may reflect the evolutionary dynamics of microbial populations.