Uncovering the genetic signature of quantitative trait evolution with replicated time series data.

The genetic architecture of adaptation in natural populations has not yet been resolved: it is not clear to what extent the spread of beneficial mutations (selective sweeps) or the response of many quantitative trait loci drive adaptation to environmental changes. Although much attention has been given to the genomic footprint of selective sweeps, the importance of selection on quantitative traits is still not well studied, as the associated genomic signature is extremely difficult to detect. We propose 'Evolve and Resequence' as a promising tool, to study polygenic adaptation of quantitative traits in evolving populations. Simulating replicated time series data we show that adaptation to a new intermediate trait optimum has three characteristic phases that are reflected on the genomic level: (1) directional frequency changes towards the new trait optimum, (2) plateauing of allele frequencies when the new trait optimum has been reached and (3) subsequent divergence between replicated trajectories ultimately leading to the loss or fixation of alleles while the trait value does not change. We explore these 3 phase characteristics for relevant population genetic parameters to provide expectations for various experimental evolution designs. Remarkably, over a broad range of parameters the trajectories of selected alleles display a pattern across replicates, which differs both from neutrality and directional selection. We conclude that replicated time series data from experimental evolution studies provide a promising framework to study polygenic adaptation from whole-genome population genetics data.

Phylogeographic differentiation versus transcriptomic adaptation to warm temperatures in Zostera marina, a globally important seagrass.

Populations distributed across a broad thermal cline are instrumental in addressing adaptation to increasing temperatures under global warming. Using a space-for-time substitution design, we tested for parallel adaptation to warm temperatures along two independent thermal clines in Zostera marina, the most widely distributed seagrass in the temperate Northern Hemisphere. A North-South pair of populations was sampled along the European and North American coasts and exposed to a simulated heatwave in a common-garden mesocosm. Transcriptomic responses under control, heat stress and recovery were recorded in 99 RNAseq libraries with ~13 000 uniquely annotated, expressed genes. We corrected for phylogenetic differentiation among populations to discriminate neutral from adaptive differentiation. The two southern populations recovered faster from heat stress and showed parallel transcriptomic differentiation, as compared with northern populations. Among 2389 differentially expressed genes, 21 exceeded neutral expectations and were likely involved in parallel adaptation to warm temperatures. However, the strongest differentiation following phylogenetic correction was between the three Atlantic populations and the Mediterranean population with 128 of 4711 differentially expressed genes exceeding neutral expectations. Although adaptation to warm temperatures is expected to reduce sensitivity to heatwaves, the continued resistance of seagrass to further anthropogenic stresses may be impaired by heat-induced downregulation of genes related to photosynthesis, pathogen defence and stress tolerance.

Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation.

Evolve and resequence (E&R) is a new approach to investigate the genomic responses to selection during experimental evolution. By using whole genome sequencing of pools of individuals (Pool-Seq), this method can identify selected variants in controlled and replicable experimental settings. Reviewing the current state of the field, we show that E&R can be powerful enough to identify causative genes and possibly even single-nucleotide polymorphisms. We also discuss how the experimental design and the complexity of the trait could result in a large number of false positive candidates. We suggest experimental and analytical strategies to maximize the power of E&R to uncover the genotype-phenotype link and serve as an important research tool for a broad range of evolutionary questions.