Adaptations to fluctuating selection in Drosophila

Abstract

Time-dependent selection causes the adaptive evolution of new phenotypes, and this dynamics can be traced in genomic data. We have analyzed polymorphisms and substitutions in Drosophila, using a more sensitive inference method for adaptations than the standard population-genetic tests. We find evidence that selection itself is strongly time-dependent, with changes occurring at nearly the rate of neutral evolution. At the same time, higher than previously estimated levels of selection make adaptive responses by a factor 10 -100 faster than the pace of selection changes, ensuring that adaptations are an efficient mode of evolution under time-dependent selection. The rate of selection changes is faster in noncoding DNA, i.e., the inference of functional elements can less be based on sequence conservation than for proteins. Our results suggest that selection acts not only as a constraint but as a major driving force of genomic change. P henotypic adaptations build on genomic sequence substitutions driven by a positive fitness effect. The distribution of these fitness differences (selection coefficients) has been debated since the advent of neutral theory (1-6). Coding DNA evolves under considerable constraint, i.e., nonsynonymous substitutions take place at a lower rate than synonymous changes (7). This shows that selection on protein evolution is predominantly negative. However, there is also evidence that the nonsynonymous substitutions that do occur are in part driven by positive selection (8-10). The evolutionary role of noncoding DNA is less clear. A particularly intriguing idea is that phenotypic evolution is due in a large part to changes in gene regulation, whereas proteins evolve more slowly (11,12). This hypothesis lacks quantitative evidence so far, but a number of recent studies have found fitness effects in noncoding DNA. Transcription factor binding sites in bacteria are under substantial selection for functionality (13), and putative regulatory regions in eukaryotes also show substantial selective constraints (14, 15). Evidence of positive selection has been reported for intergenic DNA in Drosophila (16, 17), albeit with near-neutral selection coefficients (17). Inference methods rely on various implicit assumptions, and they differ considerably in the inferred strength of selection and in its contribution to genomic change (6).Our phenotypic concept of adaptation contains more than the mere presence of positive selection. Migration of a population followed by adaptation to a new habitat, the conquest of an ecological niche in coevolution, incipient sympatric speciation driven frequency-dependent selection: in all these examples, fitness itself is time-dependent, and the adaptive evolution of new functions is the response to this change.Including the dynamics of selection into a quantitative picture of genome evolution is the purpose of this paper. To illustrate our rationale, let us first consider the case of static fitness, where intuition suggests that evolution reaches a balance between advantageo...

Energy-dependent fitness: A quantitative model for the evolution of yeast transcription factor binding sites

“…20). We note that evidence for selection fluctuations on evolutionary time scales has been established recently for coding and intergenic sequence in Drosophila (36). Disentangling the contributions of genetic drift and adaptation in promoter evolution is an outstanding challenge, which is important for quantifying the broader role of regulation in macroevolution.…”

“…Under this weaker condition, the equilibration time is the time for adaptive formation of a binding site, which can be much shorter than the neutral mutational time scale 1/ 0 (15). Deviations from equilibrium would not invalidate our inference of selection: the equilibrium method produces a lower bound to the actual level of selection, as shown by model studies of timedependent selection (36). We note that the phenotypic equilibrium assumption is consistent with the observation that the phenotype distributions Q(E) and P 0 (E) [and the inferred fitness landscapes F(E)] are remarkably similar in the four species of this study, despite their very different divergence times (Fig.…”

Evolution of Robustness and Plasticity under Environmental Fluctuation: Formulation in Terms of Phenotypic Variances

“…The system loses plasticity against the One possible origin for the preservation of plasticity may be environmental fluctuation [51], as has also been studied in terms of statistical physics [52][53][54]. The plasticity of a biological system is relevant for coping with the environmental change that may alter phenotypic dynamics in order to achieve a higher fitness.…”

Looking for Darwin in all the wrong places: the misguided quest for positive selection at the nucleotide sequence level

“…On the other hand, it may prove difficult to test certain claims of positive selection that have been proposed on the basis of statistical arguments alone. For example, a recent paper by Mustonen and Lässig (2007) applied a model of fluctuating selection to noncoding regions of the Drosophila genome. Even if the authors' hypothesis is correct, it will not be easy to reconstruct the environmental factors that might have given rise to this kind of selection.…”