Elucidating the molecular architecture of adaptation via evolve and resequence experiments

Abstract

Evolve and resequence (E&R) experiments use experimental evolution to adapt populations to a novel environment, then next-generation sequencing to analyse genetic changes. They enable molecular evolution to be monitored in real time on a genome-wide scale. Here, we review the field of E&R experiments across diverse systems, ranging from simple non-living RNA to bacteria, yeast and the complex multicellular organism Drosophila melanogaster. We explore how different evolutionary outcomes in these systems are largely consistent with common population genetics principles. Differences in outcomes across systems are largely explained by different starting population sizes, levels of pre-existing genetic variation, recombination rates and adaptive landscapes. We highlight emerging themes and inconsistencies that future experiments must address.

Figure 1

A conceptual experimental evolution experiment. Starting with a population of organisms, cells, or in vitro molecules, initially the distribution of phenotypes will track the average fitness conditional on phenotype (arrow) in the ancestral environment (top panel). In an experimental evolution experiment the fitness optimum is manipulated through a shift in the environmental conditions under which the system is propagated (e.g., changing the temperature, adding a chemical to the media, forcing molecules to bind to a ligand; second panel). This shift redefines the phenotypic optimum relative to the population's average phenotype. The population will then attempt to track the new optima via natural selection, using standing variation and/or newly arising mutations (third and fourth panels). The speed and mode of adaptation will depend on the system.

Figure 2

E&R experiments reveal the dynamics of adaptation at a genome-wide scale. From sequencing datasets of individuals or pooled populations (Pool-seq), the evolution of haplotype diversity (upper panel of each figure part) and that of allele diversity at each site of the genome (bottom panel of each figure part) can be uncovered. Haplotypes are coloured according to the initial genome-wide haplotypes, and the middle panels of each figure part show example haplotypes from the start, middle and end of the E&R experiment. Population heterozygosity is shown at each site of the simulated genome, with red transitioning to green heat colours indicating decreasing levels of heterozygosity. A) For in vitro experiments, the great initial haplotypic diversity is lost within a few generations as the best haplotype(s) quickly increase in frequency, and the large majority of initial haplotypes have a fitness of near zero. Per-site heterozygosity is homogeneous and mostly decays through the adaptive process. B) In asexual microbial evolution from an isogenic starting population, the initial diversity is minimal, and can only build up through newly arising mutations. In the clonal interference regime depicted here, several haplotypes compete with one another to reach fixation (upper panel). Diversity in the genome is only maintained at the beneficial sites and is therefore highly heterogeneous across the different sites of the genome (lower panel). New mutations are eventually lost or fixed hence heterozygosity is transitory. C) In yeast asexual evolution from a synthetic outbred starting population, the initial diversity is high but organized in blocks resulting from recombination between the founding parents. Similar to in vitro studies adaptation is characterized by a genome-wide loss of haplotype diversity. However, the rate of heterozygosity loss is lower than in the in vitro case as there is much lower variation in initial fitness and perhaps selection is not as strong. The regional loss of diversity will depend on the variance in fitness of the different haplotype blocks present, with regions not affecting fitness losing diversity later. For details on the parameters used to generate the panels in this figure, see Supplementary information S1 (box).

Figure 3

E&R experiments in sexually reproducing species. Evolutionary patterns are different in obligate sexual E&R experiments initiated from an outbred population, compared to the asexually evolving examples of Figure 2 As a result of recombination, haplotypes at the beginning of the experiments are shuffled and therefore genome-wide haplotype evolution cannot be tracked by sequencing pools of individuals (Pool-seq). Instead, investigators tend to track sliding window haplotype change over the course of the entire experiment as a function of genome position , as presented in the top panel. Population sizes are also typically much smaller than the systems of Figure 2 as a result the variance in haplotype and allele frequency change is an important consideration. Recombination occurring in the course of the adaptation further shuffles the initial haplotypes as shown in the middle panels of example haplotypes. The pattern of heterozygosity presented in the lower panel contrasts with the ones of Figure 2. Heterozygosity remains globally high over the genome apart from the few regions harbouring the variants that are important for adaptation that show reduced diversity (two cases are indicated by arrows). For details on the parameters used to generate the lower panels in this figure, see Supplementary information S1 (box).

Figure 4

The molecular bases of adaptation. (A) rpoB sequence alignments for replicate populations (rows) evolved at high temperature (top panel) and naturally occurring isolates (bottom panel) showing that rpoB is targeted repeatedly in laboratory-based adaptation to high temperature, yet is largely invariant between naturally occurring E. coli strains. Colors correspond to different base changes (A, green; C, blue; G, orange; T red; deletions black) (B) The RAS–cAMP pathway is targeted by both de novo mutations and standing variants involved in yeast adaptation to multiple stress conditions. Colours indicate alleles detected in experiments initiated from a single clone (red), an outbred synthetic population (green), or both (blue). (C) Adenosine aptamer sequences recovered from an in vitro selection experiment and subsequently optimized for strong binding. The pattern of sequence evolution is different for the ligand-binding loop (red) and the helical segments (marked as h1 and h2), which are defined by solely by sequence covariation. A structure-based search for the identified motif and genomic systematic evolution of ligands by exponential enrichment (SELEX) for adenosine/ATP novel aptamers revealed the adenosine aptamer sequences in bullfrog, mouse, and humans, suggesting molecular convergence between in vitro evolved molecules and genomic sequences. Part B is adapted from Parts et al. 2011 .