Genomic basis of parallel adaptation varies with divergence in Arabidopsis and its relatives
AbstractParallel adaptation provides valuable insight into the predictability of evolutionary change through replicated natural experiments. A steadily increasing number of studies have demonstrated genomic parallelism, yet the magnitude of this parallelism varies depending on whether populations, species or genera are compared. This led us to hypothesize that the magnitude of genomic parallelism scales with genetic divergence between lineages, but whether this is the case and the underlying evolutionary processes remain unknown. Here, we resequenced seven parallel lineages of two Arabidopsis species which repeatedly adapted to challenging alpine environments. By combining genome-wide divergence scans with model-based approaches we detected a suite of 151 genes that show parallel signatures of positive selection associated with alpine colonization, involved in response to cold, high radiation, short season, herbivores and pathogens. We complemented these parallel candidates with published gene lists from five additional alpine Brassicaceae and tested our hypothesis on a broad scale spanning ~ 0.02 to 18 million years of divergence. Indeed, we found quantitatively variable genomic parallelism whose extent significantly decreased with increasing divergence between the compared lineages. We further modeled parallel evolution over the Arabidopsis candidate genes and showed that a decreasing probability of repeated selection of the same standing or introgressed alleles drives the observed pattern of divergence-dependent parallelism. We therefore conclude that genetic divergence between populations, species and genera, affecting the pool of shared variants, is an important factor in the predictability of genome evolution.Significance statementRepeated evolution tends to be more predictable. The impressive spectrum of recent reports on genomic parallelism, however, revealed that the fraction of the genome that evolves in parallel largely varies, possibly reflecting different evolutionary scales investigated. Here, we demonstrate divergence-dependent parallelism using a comprehensive genome-wide dataset comprising 12 cases of parallel alpine adaptation and identify decreasing probability of adaptive re-use of genetic variation as the major underlying cause. This finding empirically demonstrates that evolutionary predictability is scale dependent and suggests that availability of pre-existing variation drives parallelism within and among populations and species. Altogether, our results inform the ongoing discussion about the (un)predictability of evolution, relevant for applications in pest control, nature conservation, or the evolution of pathogen resistance.
