Low concordance of short-term and long-term selection responses in experimentalDrosophilapopulations

Abstract

1Experimental evolution is becoming a popular approach to study genomic selection responses 2 of evolving populations. Computer simulation studies suggested that the accuracy of the sig-3 nature increases with the duration of the experiment. Since some assumptions of the com-4 puter simulations may be violated, it is important to scrutinize the influence of the experimen-5 tal duration with real data. Here, we use a highly replicated Evolve and Resequence study in 6 Drosophila simulans to compare the selection targets inferred at different time points. At each 7 time point approximately the same number of SNPs deviated from neutral expectations, but 8 only 10 % of the selected haplotype blocks identified from the full data set could be detected in 9 the first 20 generations. Those haplotype blocks that emerged already after 20 generations dif-10 fer from the others by being strongly selected at the beginning of the experiment and displaying 11 a more parallel selection response. Consistent with previous computer simulations, our results 12 confirm that only Evolve and Resequence experiments with a sufficient number of generations 13 can characterize complex adaptive architectures. 14 15 17 18 Deciphering the adaptive architecture is a long-term goal in evolutionary biology. In contrast 19 to natural populations, experimental evolution (EE) provides the possibility to replicate exper-20 iments under controlled, identical conditions and to study how evolution shapes populations 21 in real time (Kawecki et al. (2012); Schlötterer et al. (2015)). The combination of EE with next-22 23 (2015); Long et al. ( 2015)) -has become a popular approach to study the genomic response to se-24 lection and to identify adaptive loci. E&R has been applied to various selection regimes, such as 25 virus infection (Martins et al. (2014)), host-pathogen co-adaptation (Papkou et al. (2019)), ther-26 mal adaptation (Orozco-Terwengel et al. (2012); Barghi et al. (2019)), or body weight (Johansson 27 et al. (2010)). A wide range of experimental designs have been used, which vary in census popu-28 lation size, replication level, history of the ancestral populations, selection regime, and number and Hughes (2018); Turner and Miller (2012); Rêgo et al. (2019)), over a few dozen (Orozco-33 Terwengel et al. (2012); Johansson et al. (2010)), up to hundreds of generations (Burke et al. 34 (2010)). Computer simulations showed that the number of generations has a strong influence 35 on the power of E&R studies, and increasing the number of generations typically improved the 36 results (Baldwin-Brown et al. (2014); Kofler and Schlötterer (2014); Vlachos and Kofler (2019)). 37Since simulations make simplifying assumptions, it is important to scrutinize these conclu-38 sions with empirical data. Until recently no suitable data-sets were available, which included 39 multiple time points and replicates. We use an E&R experiment (Barghi et al. (2019)), which 40 reports allele frequency changes in 10 replicates over 60 generations in 10 generation interval...

Increased time sampling in an evolve‐and‐resequence experiment with outcrossing Saccharomyces cerevisiae reveals multiple paths of adaptive change

“…Given that our ability to identify candidate regions is largely determined by the absolute allele frequency differences over the course of the experiment and consistency across replicates, we conclude that optimizing the length of an experiment should be prioritized over devoting resources to high‐resolution time point sampling—provided that the experiment is highly replicated. This conclusion is consistent with recent work in Drosophila that empirically demonstrates the importance of experimental length in accurately identifying targets of selection (Langmüller and Schlötterer, 2020). In general, we expect these recommendations should also apply to E&R work in which the goal is to identify haplotype blocks underlying selection, rather than candidate SNPs (Barghi & Schlötterer, 2019; Michalak et al., 2018).…”

Genomic time-series data show that gene flow maintains high genetic diversity despite substantial genetic drift in a butterfly species

“…Our results show that non-trivial, genome-wide evolutionary change can occur on short time scales (5% of SNPs changing by > 0.05 and 1% changing by > 0.1). Similarly rapid genomic change has been documented in the lab (e.g., Turner et al, 2011;Gompert & Messina, 2016a;Rêgo et al, 2019;Hardy et al, 2018;Langmüller & Schlötterer, 2020) and in field experiments (e.g., Barrett et al, 2008;Anderson et al, 2013;Gompert et al, 2014a;Egan et al, 2015;Marques et al, 2018;Exposito-Alonso et al, 2019). Population-genomic studies provide some evidence that high rates of genome-wide evolution might be less common in unmanipulated, natural populations (e.g., Pinsky et al, 2021).…”

“…Such population-genetic time-series data might be especially useful for understanding contemporary evolutionary processes and eco-evolutionary dynamics (Messer et al, 2016). Indeed, time-series data were central to early studies of evolution in natural populations (Fisher & Ford, 1947;Kettlewell, 1958;Ford, 1977;Mueller et al, 1985), and play a key role in studies of experimental evolution (Burke et al, 2010;Graves Jr et al, 2017;Rêgo et al, 2019;Langmüller & Schlötterer, 2020) and recent attempts to reconstruct human history (reviewed in Pääbo et al, 2004;Slatkin & Racimo, 2016). Nonetheless, population-genomic data from natural populations sampled repeatedly through time remain relatively rare (but see, e.g., Bergland et al, 2014;Brüniche-Olsen et al, 2016;Ryan et al, 2018;Bi et al, 2019).…”

A morphological trait involved in reproductive isolation between Drosophila sister species is sensitive to temperature

“…can adapt to a laboratory environment in 20 generations only, which corresponds to about 8 540 months (Langmüller & Schlötterer, 2019). 541…”

“…This suggests that as flies adapt to the laboratory environment, the plasticity of ventral branches form towards temperature tends to be lost and ventral branches tend to be more rounded. Recent studies show that Drosophila flies can adapt to a laboratory environment in 20 generations only, which corresponds to about 8 months (Langmüller & Schlötterer, 2019).…”