Highly parallel genomic selection response in replicated Drosophila melanogaster populations with reduced genetic variation

Many adaptive traits are polygenic and frequently more loci contributing to the phenotype than needed are segregating in populations to express a phenotypic optimum. Experimental evolution provides a powerful approach to study polygenic adaptation using replicated populations adapting to a new controlled environment. Since genetic redundancy often results in non-parallel selection responses among replicates, we propose a modified Evolve and Resequencing (E&R) design that maximizes the similarity among replicates. Rather than starting from many founders, we only use two inbred Drosophila melanogaster strains and expose them to a very extreme, hot temperature environment (29°C). After 20 generations, we detect many genomic regions with a strong, highly parallel selection response in 10 evolved replicates. The X chromosome has a more pronounced selection response than the autosomes, which may be attributed to dominance effects. Furthermore, we find that the median selection coefficient for all chromosomes is higher in our two-genotype experiment than in classic E&R studies. Since two random genomes harbor sufficient variation for adaptive responses, we propose that this approach is particularly well-suited for the analysis of polygenic adaptation.

Coarse Grained Parallel Selection

Several efficient, but non-optimal, solutions to the Selection Problem on coarse grained parallel computers have appeared in the literature. We consider the example of the Saukas-Song algorithm; we analyze it without expressing the running time in terms of communication rounds. This shows that while in the best case the Saukas-Song algorithm runs in asymptotically optimal time, in general it does not. We propose another algorithm for coarse grained selection that has optimal expected running time.

Using seasonal genomic changes to understand historical adaptation: parallel selection on stickleback in highly-variable estuaries

Parallel evolution is considered strong evidence for natural selection. However, few studies have investigated the process of parallel selection as it plays out in real time. The common approach is to study historical signatures of selection in populations already well adapted to different environments. Here, to document selection in action under natural conditions, we study six populations of threespine stickleback (Gasterosteus aculeatus) inhabiting bar-built estuaries that undergo seasonal cycles of environmental changes. Estuaries are periodically isolated from the ocean due to sandbar formation during dry summer months, with concurrent environmental shifts that resemble the long-term changes associated with postglacial colonization of freshwater habitats by marine populations. We used pooled whole-genome sequencing (Pool-WGS) to track seasonal allele frequency changes in these populations and search for signatures of natural selection. We found consistent changes in allele frequency across estuaries, suggesting a potential role for parallel selection. Functional enrichment among candidate genes included transmembrane ion transport and calcium binding, which are important for osmoregulation and ion balance. The genomic changes that occur in threespine stickleback from bar-built estuaries could provide a glimpse into the early stages of adaptation that have occurred in many historical marine to freshwater transitions.