First, a basic model representing parallel evolution was developed. This model focuses on two populations and a single gene that might or might not contribute to parallel adaptation in each of the populations (but the results readily extend to systems with a large number of loci). The model provides the probability that a gene is involved in adaptation in both populations evolving in parallel, depending on multiple parameters (e.g. mutation rate, gene flow between populations, and the strength of selection). In these simulations it was also possible to track the origin of each adaptive gene. Therefore it was possible to distinguish between a shared genetic basis due to separate mutations in the same gene and a shared genetic basis due to the sharing of genetic information e.g. via gene flow between populations.
Explicit calculations representing the same model under some simplifying assumptions were also set up. These were mainly based on a transition matrix approach, a method where large matrices are used to track changes in gene frequencies in each population over time.
Together, the results of the simulations and the theoretical work show under which conditions a similar genetic basis is likely, how the similarity of the genetic basis changes over time, and which processes lead to a similarity of the genetic basis (e.g. gene flow between populations). Among other things, we found that both the shared genetic basis, as well as the time to reach maximum similarity, depend most strongly on the strength of selection and gene flow between populations, and more weakly on the history of the populations. The manuscripts describing these results are currently in preparation. The results were presented at the European Society for Evolutionary Biology Congress in 2019, as well as at multiple invited seminar talks.
At the start of the empirical work, preliminary analyses of whole-genome sequencing data of Littorina saxatilis revealed an unexpected large contribution of chromosomal inversions (large mutations that reverse the gene order) to parallel adaptation. As a consequence, the project was adjusted to focus more on these inversions, as understanding parallel adaptation in this system is not possible without understanding the evolution of inversions. We first analysed the inversions in detail on a small geographical scale (in a single Swedish population), detecting 17 inversions, some of which are large (e.g. almost half the chromosome). We also studied inversions in a set of geographically close populations in Sweden (within tens of kilometers), finding strong evidence for their contribution to adaptation in all populations at this scale. We then quantified the contribution of inversions to parallel adaptation on large geographical scales (11 locations in 4 European countries) and discovered that some inversions contribute in only a few locations, while others drive parallel adaptation in all studied locations. Finally, we related the inversions to specific phenotypic traits using laboratory crosses, finding that they are associated particularly with shell size and shape. These results have led to various publications (2 empirical papers published, 2 reviews published, 2 empirical papers currently in review). They have also been presented at six invited conference / seminar talks.
The work on understanding the detailed history of adaptive loci outside inversions in L. saxatilis has been delayed by the discovery of chromosomal inversions and the focus on their histories, but analyses scanning along the genome and quantifying the contribution of different histories are currently in progress.
