Impact of polymorphic transposable elements on linkage disequilibrium along chromosomes.

Recombination and selection drive the extent of linkage disequilibrium (LD) among loci and therefore affect the reshuffling of adaptive genetic variation. However, it is poorly known to what extent the enrichment of transposable elements (TEs) in recombinationally-inert regions reflects their inefficient removal by purifying selection and whether the presence of polymorphic TEs can modify the local recombination rate. In this study, we investigate how TEs and recombination interact at fine scale along chromosomes and possibly support linked selection in natural populations. Whole-genome sequencing data of 304 individuals from nearby alpine populations of Arabis alpina were used to show that the density of polymorphic TEs is specifically correlated with local LD along chromosomes. Consistent with TEs modifying recombination, the characterization of 28 such LD blocks of up to 5.5 Mb in length revealed strong evidence of selective sweeps at a few loci through either site frequency spectrum or haplotype structure. A majority of these blocks were enriched in genes related to ecologically relevant functions such as responses to cold, salt stress or photoperiodism. In particular, the S-locus (i.e., supergene responsible for strict outcrossing) was identified in a LD block with high levels of polymorphic TEs and evidence of selection. Another such LD block was enriched in cold-responding genes and presented evidence of adaptive loci related to photoperiodism and flowering being increasingly linked by polymorphic TEs. These results are consistent with the hypothesis that TEs modify recombination landscapes and thus interact with selection in driving blocks of linked adaptive loci in natural populations.

Integrating very high resolution environmental proxies in genotype-environment association studies.

Landscape genomic analyses associating genetic variation with environmental variables are powerful tools for studying molecular signatures of species' local adaptation and for detecting candidate genes under selection. The development of landscape genomics over the past decade has been spurred by improvements in resolutions of genomic and environmental datasets, allegedly increasing the power to identify putative genes underlying local adaptation in non-model organisms. Although these associations have been successfully applied to numerous species across a diverse array of taxa, the spatial scale of environmental predictor variables has been largely overlooked, potentially limiting conclusions to be reached with these methods. To address this knowledge gap, we systematically evaluated performances of genotype-environment association (GEA) models using predictor variables at multiple spatial resolutions. Specifically, we used multivariate redundancy analyses to associate whole-genome sequence data from the plant Arabis alpina L. collected across four neighboring valleys in the western Swiss Alps, with very high-resolution topographic variables derived from digital elevation models of grain sizes between 0.5 m and 16 m. These comparisons highlight the sensitivity of landscape genomic models to spatial resolution, where the optimal grain sizes were specific to variable type, terrain characteristics, and study extent. To assist in selecting variables at appropriate spatial resolutions, we demonstrate a practical approach to produce, select, and integrate multiscale variables into GEA models. After generalizing fine-grained variables to multiple spatial resolutions, a forward selection procedure is applied to retain only the most relevant variables for a particular context. Depending on the spatial resolution, the relevance for topographic variables in GEA studies calls for integrating multiple spatial scales into landscape genomic models. By carefully considering spatial resolutions, candidate genes under selection by a more realistic range of pressures can be detected for downstream analyses, with important applied implications for experimental research and conservation management of natural populations.

Genome-wide variation in nucleotides and retrotransposons in alpine populations of Arabis alpina (Brassicaceae).

Advances in high-throughput sequencing have promoted the collection of reference genomes and genome-wide diversity. However, the assessment of genomic variation among populations has hitherto mainly been surveyed through single-nucleotide polymorphisms (SNPs) and largely ignored the often major fraction of genomes represented by transposable elements (TEs). Despite accumulating evidence supporting the evolutionary significance of TEs, comprehensive surveys remain scarce. Here, we sequenced the full genomes of 304 individuals of Arabis alpina sampled from four nearby natural populations to genotype SNPs as well as polymorphic long terminal repeat retrotransposons (polymorphic TEs; i.e., presence/absence of TE insertions at specific loci). We identified 291,396 SNPs and 20,548 polymorphic TEs, comparing their contributions to genomic diversity and divergence across populations. Few SNPs were shared among populations and overall showed high population-specific variation, whereas most polymorphic TEs segregated among populations. The genomic context of these two classes of variants further highlighted candidate adaptive loci having a putative impact on functional genes. In particular, 4.96% of the SNPs were identified as nonsynonymous or affecting start/stop codons. In contrast, 43% of the polymorphic TEs were present next to Arabis genes enriched in functional categories related to the regulation of reproduction and responses to biotic as well as abiotic stresses. This unprecedented data set, mapping variation gained from SNPs and complementary polymorphic TEs within and among populations, will serve as a rich resource for addressing microevolutionary processes shaping genome variation.

Increased diversity of egg-associated bacteria on brown trout (Salmo trutta) at elevated temperatures.

The taxonomic composition of egg-associated microbial communities can play a crucial role in the development of fish embryos. In response, hosts increasingly influence the composition of their associated microbial communities during embryogenesis, as concluded from recent field studies and laboratory experiments. However, little is known about the taxonomic composition and the diversity of egg-associated microbial communities within ecosystems; e.g., river networks. We sampled late embryonic stages of naturally spawned brown trout at nine locations within two different river networks and applied 16S rRNA pyrosequencing to describe their bacterial communities. We found no evidence for a significant isolation-by-distance effect on the composition of bacterial communities, and no association between neutral genetic divergence of fish host (based on 11 microsatellites) and phylogenetic distances of the composition of their associated bacterial communities. We characterized core bacterial communities on brown trout eggs and compared them to corresponding water samples with regard to bacterial composition and its presumptive function. Bacterial diversity was positively correlated with water temperature at the spawning locations. We discuss this finding in the context of the increased water temperatures that have been recorded during the last 25 years in the study area.