Abstract
The genomic basis of adaptation to novel environments is a fundamental problem in evolutionary biology that has gained additional importance in the light of the recent global change discussion. Here, we combined laboratory natural selection (experimental evolution) in Drosophila melanogaster with genome-wide next generation sequencing of DNA pools (Pool-Seq) to identify alleles that are favourable in a novel laboratory environment and traced their trajectories during the adaptive process. Already after 15 generations, we identified a pronounced genomic response to selection, with almost 5000 single nucleotide polymorphisms (SNP; genome-wide false discovery rates < 0.005%) deviating from neutral expectation. Importantly, the evolutionary trajectories of the selected alleles were heterogeneous, with the alleles falling into two distinct classes: (i) alleles that continuously rise in frequency; and (ii) alleles that at first increase rapidly but whose frequencies then reach a plateau. Our data thus suggest that the genomic response to selection can involve a large number of selected SNPs that show unexpectedly complex evolutionary trajectories, possibly due to nonadditive effects.
Highlights
One of the central goals in evolutionary biology is to understand adaptation
We used laboratory natural selection by exposing a freshly collected population of Drosophila melanogaster in triplicate to a novel environment that consists of laboratory culture conditions in combination with an elevated temperature regime, with daily fluctuations between 18 and 28 °C
By statistically identifying consistent allele frequency changes (AFCs) among replicates, we focused our analysis on standing genetic variation, excluding potential beneficial de novo mutations that might have occurred in only one replicate
Summary
One of the central goals in evolutionary biology is to understand adaptation. The different genetic approaches used to study adaptation can be broadly grouped into three categories: (i) QTL mapping; (ii) population genetics; and (iii) experimental evolution. Quantitative genetics has been the workhorse of evolutionary biologists who study the genetic architecture of traits thought to be associated with adaptation. Targets of selection are identified by contrasting observed data with expectations based on the population genetic theory (Schlotterer 2003; Nielsen 2005). While this approach is conceptually appealing, it has become increasingly clear that complex demographic histories that involve migration and population bottlenecks can generate a signature in the genome that cannot be distinguished from selection (Thornton et al 2007; Parsch et al 2009)
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