Laboratory selection experiments are alluring in their simplicity, power, and ability to inform us about how evolution works. A longstanding challenge facing evolution experiments with metazoans is that significant generational turnover takes a long time. In this work, we present data from a unique system of experimentally evolved laboratory populations of Drosophila melanogaster that have experienced three distinct life-history selection regimes. The goal of our study was to determine how quickly populations of a certain selection regime diverge phenotypically from their ancestors, and how quickly they converge with independently derived populations that share a selection regime. Our results indicate that phenotypic divergence from an ancestral population occurs rapidly, within dozens of generations, regardless of that population's evolutionary history. Similarly, populations sharing a selection treatment converge on common phenotypes in this same time frame, regardless of selection pressures those populations may have experienced in the past. These patterns of convergence and divergence emerged much faster than expected, suggesting that intermediate evolutionary history has transient effects in this system. The results we draw from this system are applicable to other experimental evolution projects, and suggest that many relevant questions can be sufficiently tested on shorter timescales than previously thought.
Energy allocation is believed to drive trade-offs in life history evolution. We develop a physiological and genetic model of energy allocation that drives evolution of feeding rate in a well-studied model system. In a variety of stressful environments Drosophila larvae adapt by altering their rate of feeding. Drosophila larvae adapted to high levels of ammonia, urea, and the presence of parasitoids evolve lower feeding rates. Larvae adapted to crowded conditions evolve higher feeding rates. Feeding rates should affect gross food intake, metabolic rates, and efficiency of food utilization. We develop a model of larval net energy intake as a function of feeding rates. We show that when there are toxic compounds in the larval food that require energy for detoxification, larvae can maximize their energy intake by slowing their feeding rates. While the reduction in feeding rates may increase development time and decrease competitive ability, we show that genotypes with lower feeding rates can be favored by natural selection if they have a sufficiently elevated viability in the toxic environment. This work shows how a simple phenotype, larval feeding rates, may be of central importance in adaptation to a wide variety of stressful environments via its role in energy allocation.
Model organisms subjected to sustained experimental evolution often show levels of phenotypic differentiation that dramatically exceed the phenotypic differences observed in natural populations. Genome-wide sequencing of pooled populations then offers the opportunity to make inferences about the genes that are the cause of these phenotypic differences. We tested, through computer simulations, the efficacy of a statistical learning technique called the "fused lasso additive model" (FLAM). We focused on the ability of FLAM to distinguish between genes which are differentiated and directly affect a phenotype from differentiated genes which have no effect on the phenotype. FLAM can separate these two classes of genes even with relatively small samples (10 populations, in total). The efficacy of FLAM is improved with increased number of populations, reduced environmental phenotypic variation, and increased within-treatment among-replicate variation. FLAM was applied to SNP variation measured in both twenty-population and thirty-population studies of Drosophila subjected to selection for age-at-reproduction, to illustrate the application of the method.
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