Ploidy-variable species allow direct inference of the effects of chromosome copy number on fundamental evolutionary processes. While an abundance of theoretical work suggests polyploidy should leave distinct population genomic signatures, empirical data remains sparse. We sequenced ~300 individuals from 39 populations of Arabidopsis arenosa, a naturally diploid-autotetraploid species. We find the impacts of polyploidy on population genomic processes are subtle yet pervasive, including reduced efficiency on linked and purifying selection as well as rampant gene flow from diploids. Initial masking of deleterious mutations, faster rates of nucleotide substitution, and interploidy introgression all conspire to shape the evolutionary potential of polyploids.

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Five different ploidy levels (from 2x to 6x) were found, with triploids of K. arvensis being recorded for the first time. The species also exhibited variation in the monoploid genome size, corresponding to the types of habitats occupied (grassland diploid populations had larger genome sizes than relict and subalpine diploid populations). Disregarding relict populations, the distribution of 2x and 4x cytotypes was largely parapatric, with a diffuse secondary contact zone running along the north-west margin of the Pannonian basin. Spatial segregation of the cytotypes was also observed on regional and microgeographic scales. The newly detected sympatric growth of diploids and tetraploids in isolated relict habitats most likely represents the primary zone of cytotype contact. Ploidy level was found to be a major determinant of the strength of inter-cytotype reproductive barriers. While mixed 2x + 4x populations virtually lacked the intermediate ploidy level at any ontogenetic stage, pentaploid hybrids were common in 4x +6x populations, despite the cytotypes representing different taxonomic entities.

Parallel 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 My 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 on 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.

The duplication of an entire genome is no small affair. Whole genome duplication (WGD) is a dramatic mutation with long-lasting effects, yet it occurs repeatedly in all eukaryotic kingdoms. Plants are particularly rich in documented WGDs, with recent and ancient polyploidization events in all major extant lineages. However, challenges immediately following WGD, such as the maintenance of stable chromosome segregation or detrimental ecological interactions with diploid progenitors, commonly do not permit establishment of nascent polyploids. Despite these immediate issues some lineages nevertheless persist and thrive. In fact, ecological modeling commonly supports patterns of adaptive niche differentiation in polyploids, with young polyploids often invading new niches and leaving their diploid progenitors behind. In line with these observations of polyploid evolutionary success, recent work documents instant physiological consequences of WGD associated with increased dehydration stress tolerance in first-generation autotetraploids. Furthermore, population genetic theory predicts both short-and long-term benefits of polyploidy and new empirical data suggests that established polyploids may act as "sponges" accumulating adaptive allelic diversity. In addition to their increased genetic variability, introgression with other tetraploid lineages, diploid progenitors, or even other species, further increases the available pool of genetic variants to polyploids. Despite this, the evolutionary advantages of polyploidy are still questioned, and the debate over the idea of polyploidy as an evolutionary dead-end carries on. Here we broadly synthesize the newest empirical data moving this debate forward. Altogether, evidence suggests that if early barriers are overcome, WGD can offer instantaneous fitness advantages opening the way to a transformed fitness landscape by sampling a higher diversity of alleles, including some already preadapted to their local environment. This occurs in the context of intragenomic, population genomic, and physiological modifications that can, on occasion, offer an evolutionary edge. Yet in the long run, early advantages can turn into long-term hindrances, and without ecological drivers such as novel ecological niche availability or agricultural propagation, a restabilization of the genome via diploidization will begin the cycle anew.

Quaternary climatic oscillations profoundly impacted temperate biodiversity. For many diverse yet undersampled areas, however, the consequences of this impact are still poorly known. In Europe, particular uncertainty surrounds the role of Balkans, a major hotspot of European diversity, in postglacial recolonization of more northerly areas, and the Carpathians, a debatable candidate for a northern 'cryptic' glacial refugium. Using genome-wide SNPs and microsatellites, we examined how the interplay of historical processes and niche shifts structured genetic diversity of diploid Arabidopsis arenosa, a little-known member of the plant model genus that occupies a wide niche range from sea level to alpine peaks across eastern temperate Europe. While the northern Balkans hosted one isolated endemic lineage, most of the genetic diversity was concentrated further north in the Pannonian Basin and the Carpathians, where it likely survived the last glaciation in northern refugia. Finally, a distinct postglacial environment in northern Europe was colonized by populations of admixed origin from the two Carpathian lineages. Niche differentiation along altitude-related bioclimatic gradients was the main trend in the phylogeny of A. arenosa. The most prominent niche shifts, however, characterized genetically only slightly divergent populations that expanded into narrowly defined alpine and northern coastal postglacial environments. Our study highlights the role of eastern central European mountains not only as refugia for unique temperate diversity but also sources for postglacial expansion into novel high-altitude and high-latitude niches. Knowledge of distinct genetic substructure of diploid A. arenosa also opens new opportunities for follow-up studies of this emerging model of evolutionary biology.

Analysis of population genetic structure has become a standard approach in population genetics. In polyploid complexes, clustering analyses can elucidate the origin of polyploid populations and patterns of admixture between different cytotypes. However, combining diploid and polyploid data can theoretically lead to biased inference with (artefactual) clustering by ploidy. We used simulated mixed-ploidy (diploid-autotetraploid) data to systematically compare the performance of k-means clustering and the model-based clustering methods implemented in Structure, Admixture, FastStructure and InStruct under different scenarios of differentiation and with different marker types. Under scenarios of strong population differentiation, the tested applications performed equally well. However, when population differentiation was weak, Structure was the only method that allowed unbiased inference with markers with limited genotypic information (co-dominant markers with unknown dosage or dominant markers). Still, since Structure was comparatively slow, the much faster but less powerful FastStructure provides a reasonable alternative for large datasets. Finally, although bias makes k-means clustering unsuitable for markers with incomplete genotype information, for large numbers of loci (>1000) with known dosage k-means clustering was superior to FastStructure in terms of power and speed. We conclude that Structure is the most robust method for the analysis of genetic structure in mixed-ploidy populations, although alternative methods should be considered under some specific conditions.

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