Genomic Variation of Arabis Alpina (Brassicaceae) in Heterogeneous Alpine Environments

Abstract

Natural selection is acting on the genome of individuals that are experiencing particular abiotic and biotic conditions, resulting in adaptation to local habitat. Accordingly, local genotypes will show higher fitness in their local habitats than genotypes from a foreign habitat introduced at this site (“local vs. foreign” sensu Kawecki & Ebert 2004). Understanding, how individuals are adapted to their environment is especially interesting and valuable in the context of climate change, which is thought to increase the frequency of disturbances that individuals have to cope with. Therefore, evolutionary biologist have a particular interest in genes involved in local adaptation to understand which biological functions are important in which environments and to comprehend how species will react to future climate change. The capacity of species to cope with changes will rely on sufficient genetic variation upon which selection can act. Different methods exist to detect signals of adaptation. Landscape genomics (for example environmental association analysis) has the potential to find genes under adaptation by associating genomic variation with environmental data, hence linking signatures of selection with their potentially underlying environmental drivers. In this study, the alpine rock cress, Arabis alpina, was used to investigate signals of adaptation in heterogeneous alpine environments. The high-quality reference genome available and previous studies in ecological genetics make this species suitable as model system to study which parts of the genome show signals of adaptation and investigate key functions involved. When studying local adaptation, it is important to take into account the neutral genetic structure of the studied populations as it may mimic signals of local adaptation. These patterns come from neutral processes like gene flow, genetic drift and mutation, but not from non-neutral processes like selection. The phylogeographic structure of alpine species, predominantly shaped by these neutral demographic processes, can be complex, as the recurrent glaciations during the Pleistocene confined species to refugial areas from where they repeatedly recolonized their current range. Thus, in the first chapter of this thesis, I aimed to investigate the population structure of A. alpina across the Alps (372 individuals from 127 populations) and at the regional scale (364 individuals from 22 populations) in the western Swiss Alps—the study region of the subsequent landscape genomic investigations. Based on nuclear microsatellite data, I found that the pattern of genetic clusters across the Alps was coherent with that of previous phylogeographic analyses using anonymous molecular markers. In the western Swiss Alps, I discovered that the populations from this region showed several genetic clusters associated to different putative refugia, as presumably observed in other species. Moreover, the four study regions sampled for the environmental association analysis appeared to descend from the same original population, indicating a largely common genetic background. Our results not only substantiated the congruence of large-scale genetic structure using alternative types of molecular markers, but also set a helpful basis for further studies on ecological genomics in A. alpina. Studying local adaptation at small scale requires highly resolved and accurate genomic data. Therefore, I re-sequenced the whole genomes of 304 individuals from four nearby populations sampled in the western Swiss Alps. The second chapter describes the genomic diversity of the four sampled populations based on single-nucleotide polymorphisms (SNPs) and transposable elements (TEs). The latter corresponds to a major fraction of plant genomes, but has hitherto been largely ignored regarding their role in adaptive responses to the environment. After stringent bioinformatic filtering, 291,396 SNPs and 20,548 polymorphic TEs were identified. Few SNPs were shared among the populations, unlike the TEs that were shared among populations to a large degree. Through the genomic context of both types of sequence variants, I described their potential impact on functional genes. Almost 5% of the SNPs were non-synonymous and 43% of the TEs were present within or next to 7,475 genes of A. alpina. These genes were enriched in functional categories related to reproduction and responses to biotic and abiotic stress. Overall, in addition to SNPs, TEs are likely to shape adaptive genetic variation in A. alpina as they might affect genes by their close vicinity. Finally, in the third chapter, I studied the extent of local adaptation in A. alpina. In order to capture signals of local adaptation at small scale, I ran association analyses of environmental factors, derived from digital elevation models based on high-resolution Light Detection And Ranging (LiDAR) data, with the genomic variants previously described (SNPs and TEs). Latent factor mixed models indicated that both types of variants showed significant signals of local adaptation within gene flow distance, after controlling for neutral genetic population structure. The significantly associated high-impact SNPs were mainly involved in metabolic and cellular processes, and few were involved in reproduction. TE families responding to heat stress were highlighted, but their impact is difficult to assess given the lack of functional information. The observed signals of local adaptation in response to alpine environments seem to be mainly driven by humidity and solar radiation. The impact of the reproductive strategy (predominant selfing) and the demographic history of A. alpina on the observed signals of adaptation were finally discussed. In conclusion, this thesis presents the phylogeographic diversity of A. alpina over the Alps and in a region presumably at the junction of several glacial refugia, the western Swiss Alps. The re-sequencing of the whole genome of 304 individuals of four populations sampled from this region showed that TEs and not only SNPs evidenced genomic variation, some of which are apparently involved in adaptation to the local environment. These results open new perspectives on genome architecture and the role of variants in driving evolution within natural populations, highlighting the complexity of the genomics of adaptation.