Genomewide architecture of adaptation in experimentally evolved Drosophila characterized by widespread pleiotropy.

Dissecting the molecular basis of adaptation remains elusive despite our ability to sequence genomes and transcriptomes. At present, most genomic research on selection focusses on signatures of selective sweeps in patterns of heterozygosity. Other research has studied changes in patterns of gene expression in evolving populations but has not usually identified the genetic changes causing these shifts in expression. Here we attempt to go beyond these approaches by using machine learning tools to explore interactions between the genome, transcriptome, and life-history phenotypes in two groups of 10 experimentally evolved Drosophila populations subjected to selection for opposing life history patterns. Our findings indicate that genomic and transcriptomic data have comparable power for predicting phenotypic characters. Looking at the relationships between the genome and the transcriptome, we find that the expression of individual transcripts is influenced by many sites across the genome that are differentiated between the two types of populations. We find that single-nucleotide polymorphisms (SNPs), transposable elements, and indels are powerful predictors of gene expression. Collectively, our results suggest that the genomic architecture of adaptation is highly polygenic with extensive pleiotropy.

Building Bridges from Genome to Physiology Using Machine Learning and Drosophila Experimental Evolution.

Drosophila experimental evolution, with its well-defined selection protocols, has long supplied useful genetic material for the analysis of functional physiology. While there is a long tradition of interpreting the effects of large-effect mutants physiologically, identifying and interpreting gene-to-phenotype relationships has been challenging in the genomic era, with many labs not resolving how physiological traits are affected by multiple genes throughout the genome. Drosophila experimental evolution has demonstrated that multiple phenotypes change because of the evolution of many loci across the genome, creating the scientific challenge of sifting out differentiated but noncausal loci for individual characters. The fused lasso additive model method allows us to infer some of the differentiated loci that have relatively greater causal effects on the differentiation of specific phenotypes. The experimental material that we use in the present study comes from 50 populations that have been selected for different life histories and levels of stress resistance. Differentiation of cardiac robustness, starvation resistance, desiccation resistance, lipid content, glycogen content, water content, and body masses was assayed among 40-50 of these experimentally evolved populations. Through the fused lasso additive model, we combined physiological analyses from eight parameters with whole-body pooled-seq genomic data to identify potentially causally linked genomic regions. We have identified approximately 2,176 significantly differentiated 50-kb genomic windows among our 50 populations, with 142 of those identified genomic regions that are highly likely to have a causal effect connecting specific genome sites to specific physiological characters.

The effects of adaptation to urea on feeding rates and growth in Drosophila larvae.

A collection of forty populations were used to study the phenotypic adaptation of Drosophila melanogaster larvae to urea-laced food. A long-term goal of this research is to map genes responsible for these phenotypes. This mapping requires large numbers of populations. Thus, we studied fifteen populations subjected to direct selection for urea tolerance and five controls. In addition, we studied another twenty populations which had not been exposed to urea but were subjected to stress or demographic selection. In this study, we describe the differentiation in these population for six phenotypes: (1) larval feeding rates, (2) larval viability in urea-laced food, (3) larval development time in urea-laced food, (4) adult starvation times, (5) adult desiccation times, and (6) larval growth rates. No significant differences were observed for desiccation resistance. The demographically/stress-selected populations had longer times to starvation than urea-selected populations. The urea-adapted populations showed elevated survival and reduced development time in urea-laced food relative to the control and nonadapted populations. The urea-adapted populations also showed reduced larval feeding rates relative to controls. We show that there is a strong linear relationship between feeding rates and growth rates at the same larval ages feeding rates were measured. This suggests that feeding rates are correlated with food intake and growth. This relationship between larval feeding rates, food consumption, and efficiency has been postulated to involve important trade-offs that govern larval evolution in stressful environments. Our results support the idea that energy allocation is a central organizing theme in adaptive evolution.

Diet and Botanical Supplementation: Combination Therapy for Healthspan Improvement?

Healthspan science aims to add healthy, functional years to human life. Many different methods of improving healthspan have been investigated, chiefly focusing on just one aspect of an organism's health such as survival. Studies in Drosophila melanogaster have demonstrated that a reversal to a long-abandoned ancestral diet results in improved functional health, particularly at later ages. Meanwhile, pharmaceutical studies have demonstrated that botanical extracts have potent antiaging properties, capable of extending the mean lifespan of D. melanogaster by up to 25%, without a decrease in early fecundity. In this study, we combine these two different approaches to healthspan extension to examine whether a combination of such treatments results in a synergistic or antagonistic effect on Drosophila healthspan. One botanical extract, derived from Rhodiola rosea, mimicked the effects of the ancestral apple diet with better performance at later ages compared with the control. Another extract, derived from Rosa damascena, decreased age-specific survivorship when combined with the apple diet providing support for the "Poisoned Chalice" hypothesis that combinations of various supplements or diets can elicit adverse physiological responses. More experiments in model organisms should be completed researching the effects of combining healthspan-extending substances in various diet backgrounds.

Hamiltonian patterns of age-dependent adaptation to novel environments.

Our intuitive understanding of adaptation by natural selection is dominated by the power of selection at early ages in large populations. Yet, as the forces of natural selection fall with adult age, we expect adaptation to be attenuated with age. Explicit simulations of age-dependent adaptation suggest that populations adapt to a novel environment quickly at early ages, but only slowly and incompletely at later adult ages. Experimental tests for age-dependent adaptation to a novel diet were performed on populations of Drosophila melanogaster. The results support the prediction that populations should perform better on an ancestral, long-abandoned diet, compared to an evolutionarily recent diet, only at later ages. D. melanogaster populations also perform poorly on a novel diet compared to an evolutionarily recent diet that has been sustained for hundreds of generations, particularly at earlier ages. Additional experiments demonstrate that the timing of the shift to better performance in our populations on the long-abandoned diet is dependent on when the forces of natural selection weaken in the evolutionary history of experimental populations. Taken together, these experimental findings suggest that the forces of natural selection scale the rate of adaptation to novel environments.

Predicting death by the loss of intestinal function.

The ability to predict when an individual will die can be extremely useful for many research problems in aging. A technique for predicting death in the model organism, Drosophila melanogaster, has been proposed which relies on an increase in the permeability of the fly intestinal system, allowing dyes from the diet to permeate the body of the fly shortly before death. In this study we sought to verify this claim in a large cohort study using different populations of D. melanogaster and different dyes. We found that only about 50% of the individuals showed a visible distribution of dye before death. This number did not vary substantially with the dye used. Most flies that did turn a blue color before death did so within 24 hours of death. There was also a measurable effect of the dye on the fly mean longevity. These results would tend to limit the utility of this method depending on the application the method was intended for.

Genomics of Early Cardiac Dysfunction and Mortality in Obese Drosophila melanogaster.

In experimental evolution, we impose functional demands on laboratory populations of model organisms using selection. After enough generations of such selection, the resulting populations constitute excellent material for physiological research. An intense selection regime for increased starvation resistance was imposed on 10 large outbred Drosophila populations. We observed the selection responses of starvation and desiccation resistance, metabolic reserves, and heart robustness via electrical pacing. Furthermore, we sequenced the pooled genomes of these populations. As expected, significant increases in starvation resistance and lipid content were found in our 10 intensely selected SCO populations. The selection regime also improved desiccation resistance, water content, and glycogen content among these populations. Additionally, the average rate of cardiac arrests in our 10 obese SCO populations was double the rate of the 10 ancestral CO populations. Age-specific mortality rates were increased at early adult ages by selection. Genomic analysis revealed a large number of single nucleotide polymorphisms across the genome that changed in frequency as a result of selection. These genomic results were similar to those obtained in our laboratory from less direct selection procedures. The combination of extensive genomic and phenotypic differentiation between these 10 populations and their ancestors makes them a powerful system for the analysis of the physiological underpinnings of starvation resistance.

Drosophila transcriptomics with and without ageing.

The genomic basis of ageing still remains unknown despite being a topic of study for many years. Here, we present data from 20 experimentally evolved laboratory populations of Drosophila melanogaster that have undergone two different life-history selection regimes. One set of ten populations demonstrates early ageing whereas the other set of ten populations shows postponed ageing. Additionally, both types of populations consist of five long standing populations and five recently derived populations. Our primary goal was to determine which genes exhibit changes in expression levels by comparing the female transcriptome of the two population sets at two different time points. Using three different sets of increasingly restrictive criteria, we found that 2.1-15.7% (82-629 genes) of the expressed genes are associated with differential ageing between population sets. Conversely, a comparison of recently derived populations to long-standing populations reveals little to no transcriptome differentiation, suggesting that the recent selection regime has had a larger impact on the transcriptome than its more distant evolutionary history. In addition, we found very little evidence for significant enrichment for functional attributes regardless of the set of criteria used. Relative to previous ageing studies, we find little overlap with other lists of aging related genes. The disparity between our results and previously published results is likely due to the high replication used in this study coupled with our use of highly differentiated populations. Our results reinforce the notion that the use of genomic, transcriptomic, and phenotypic data to uncover the genetic basis of a complex trait like ageing can benefit from experimental designs that use highly replicated, experimentally-evolved populations.

Effects of evolutionary history on genome wide and phenotypic convergence in Drosophila populations.

BACKGROUND: Studies combining experimental evolution and next-generation sequencing have found that adaptation in sexually reproducing populations is primarily fueled by standing genetic variation. Consequently, the response to selection is rapid and highly repeatable across replicate populations. Some studies suggest that the response to selection is highly repeatable at both the phenotypic and genomic levels, and that evolutionary history has little impact. Other studies suggest that even when the response to selection is repeatable phenotypically, evolutionary history can have significant impacts at the genomic level. Here we test two hypotheses that may explain this discrepancy. Hypothesis 1: Past intense selection reduces evolutionary repeatability at the genomic and phenotypic levels when conditions change. Hypothesis 2: Previous intense selection does not reduce evolutionary repeatability, but other evolutionary mechanisms may. We test these hypotheses using D. melanogaster populations that were subjected to 260 generations of intense selection for desiccation resistance and have since been under relaxed selection for the past 230 generations. RESULTS: We find that, with the exception of longevity and to a lesser extent fecundity, 230 generations of relaxed selection has erased the extreme phenotypic differentiation previously found. We also find no signs of genetic fixation, and only limited evidence of genetic differentiation between previously desiccation resistance selected populations and their controls. CONCLUSION: Our findings suggest that evolution in our system is highly repeatable even when populations have been previously subjected to bouts of extreme selection. We therefore conclude that evolutionary repeatability can overcome past bouts of extreme selection in Drosophila experimental evolution, provided experiments are sufficiently long and populations are not inbred.

Genome-Wide Mapping of Gene-Phenotype Relationships in Experimentally Evolved Populations.

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.

Starvation but not locomotion enhances heart robustness in Drosophila.

Insects and vertebrates have multiple major physiological systems, each species having a circulatory system, a metabolic system, and a respiratory system that enable locomotion and survival in stressful environments, among other functions. Broadening our understanding of the physiology of Drosophila melanogaster requires the parsing of interrelationships among such major component physiological systems. By combining electrical pacing and flight exhaustion assays with manipulative conditioning, we have started to unpack the interrelationships between cardiac function, locomotor performance, and other functional characters such as starvation and desiccation resistance. Manipulative sequences incorporating these four physiological characters were applied to five D. melanogaster lab populations that share a common origin from the wild and a common history of experimental evolution. While exposure to starvation or desiccation significantly reduced flight duration, exhaustion due to flight only affected subsequent desiccation resistance. A strong association was found between flight duration and desiccation resistance, providing additional support for the hypothesis that these traits depend on glycogen and water content. However, there was negligible impact on rate of cardiac arrests from exhaustion by flight or exposure to desiccant. Brief periods of starvation significantly lowered the rate of cardiac arrest. These results provide suggestive support for the adverse impact of lipids on Drosophila heart robustness, a parallel result to those of many comparable studies in human cardiology. Overall, this study underscores clear distinctions among the connections between specific physiological responses to stress and specific types of physiological performance.

Experimental Evolution and Heart Function in Drosophila.

Drosophila melanogaster is a good model species for the study of heart function. However, most previous work on D. melanogaster heart function has focused on the effects of large-effect genetic variants. We compare heart function among 18 D. melanogaster populations that have been selected for altered development time, aging, or stress resistance. We find that populations with faster development and faster aging have increased heart dysfunction, measured as percentage heart failure after electrical pacing. Experimental evolution of different triglyceride levels, by contrast, has little effect on heart function. Evolved differences in heart function correlate with allele frequency changes at many loci of small effect. Genomic analysis of these populations produces a list of candidate loci that might affect cardiac function at the intersection of development, aging, and metabolic control mechanisms.

Genome-wide analysis of long-term evolutionary domestication in Drosophila melanogaster.

Experimental evolutionary genomics now allows biologists to test fundamental theories concerning the genetic basis of adaptation. We have conducted one of the longest laboratory evolution experiments with any sexually-reproducing metazoan, Drosophila melanogaster. We used next-generation resequencing data from this experiment to examine genome-wide patterns of genetic variation over an evolutionary time-scale that approaches 1,000 generations. We also compared measures of variation within and differentiation between our populations to simulations based on a variety of evolutionary scenarios. Our analysis yielded no clear evidence of hard selective sweeps, whereby natural selection acts to increase the frequency of a newly-arising mutation in a population until it becomes fixed. We do find evidence for selection acting on standing genetic variation, as independent replicate populations exhibit similar population-genetic dynamics, without obvious fixation of candidate alleles under selection. A hidden-Markov model test for selection also found widespread evidence for selection. We found more genetic variation genome-wide, and less differentiation between replicate populations genome-wide, than arose in any of our simulated evolutionary scenarios.

Patterns of physiological decline due to age and selection in Drosophila melanogaster.

In outbred sexually reproducing populations, age-specific mortality rates reach a plateau in late life following the exponential increase in mortality rates that marks aging. Little is known about what happens to physiology when cohorts transition from aging to late life. We measured age-specific values for starvation resistance, desiccation resistance, time-in-motion, and geotaxis in ten Drosophila melanogaster populations: five populations selected for rapid development and five control populations. Adulthood was divided into two stages, the aging phase and the late-life phase according to demographic data. Consistent with previous studies, we found that populations selected for rapid development entered the late-life phase at an earlier age than the controls. Age-specific rates of change for all physiological phenotypes showed differences between the aging phase and the late-life phase. This result suggests that late life is physiologically distinct from aging. The ages of transitions in physiological characteristics from aging to late life statistically match the age at which the demographic transition from aging to late life occurs, in all cases but one. These experimental results support evolutionary theories of late life that depend on patterns of decline and stabilization in the forces of natural selection.

Rapid divergence and convergence of life-history in experimentally evolved Drosophila melanogaster.

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.

The death spiral: predicting death in Drosophila cohorts.

Drosophila research has identified a new feature of aging that has been called the death spiral. The death spiral is a period prior to death during which there is a decline in life-history characters, such as fecundity, as well as physiological characters. First, we review the data from the Drosophila and medfly literature that suggest the existence of death spirals. Second, we re-analyze five cases with such data from four laboratories using a generalized statistical framework, a re-analysis that strengthens the case for the salience of the death spiral phenomenon. Third, we raise the issue whether death spirals need to be taken into account in the analysis of functional characters over age, in aging research with model species as well as human data.

The Evolution of Ovoviviparity in a Temporally Varying Environment.

Environments that vary within a generation of an organism provide opportunities for adaptation if the level of variation is severe and predictable. We describe a model of evolution in such environments with genotypes that show trade-offs in viability and fecundity. One genotype develops rapidly and has superior viability but reduced fertility relative to the alternative genotype. Conditions that allow the evolution of the rapidly developing genotypes are explored. We show how the evolution of ovoviviparity and resource specialization in Drosophila sechellia shares many important features of this model. We suggest that our model may capture many of the evolutionary forces responsible for the evolution of niche specialization and ovoviviparity seen in D. sechellia.

A model of the evolution of larval feeding rate in Drosophila driven by conflicting energy demands.

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.

The great evolutionary divide: two genomic systems biologies of aging.

There is not one systems biology of aging, but two. Though aging can evolve in either sexual or asexual species when there is asymmetric reproduction, the evolutionary genetics of aging in species with frequent sexual recombination are quite different from those arising when sex is rare or absent. When recombination is rare, selection is expected to act chiefly on rare large-effect mutations, which purge genetic variation due to genome-wide hitchhiking. In such species, the systems biology of aging can focus on the effects of large-effect mutants, transgenics, and combinations of such genetic manipulations. By contrast, sexually outbreeding species maintain abundant genetic polymorphism within populations. In such species, the systems biology of aging can examine the genome-wide effects of selection and genetic drift on the numerous polymorphic loci that respond to laboratory selection for different patterns of aging. An important question of medical relevance is to what extent insights derived from the systems biology of aging in model species can be applied to human aging.

An evolutionary and genomic approach to challenges and opportunities for eliminating aging.

While solutions to major scientific and medical problems are never perfect or complete, it is still reasonable to delineate cases where both have been essentially solved. For example, Darwin's theory of natural selection provides a successful solution to the problem of biological adaptation, while the germ theory of infection solved the scientific problem of contagious disease. Likewise in the context of medicine, we have effectively solved the problem of contagious disease, reducing it to a minor cause of death and disability for almost everyone in countries with advanced medicine and adequate resources. Evolutionary biologists claim to have solved the scientific problem of aging: we explain it theoretically using Hamilton's forces of natural selection; in experimental evolution we readily manipulate the onset, rate, and eventual cessation of aging by manipulating these forces. In this article, we turn to the technological challenge of solving the medical problem of aging. While we feel that the broad outlines of such a solution are clear enough starting from the evolutionary solution to the scientific problem of aging, we do not claim that we can give a complete or exhaustive plan for medically solving the problem of aging. But we are confident that biology and medicine will effectively solve the problem of aging within the next 50 years, providing Hamiltonian lifestyle changes, tissue repair, and genomic technological opportunities are fully exploited in public health practices, in medical practice, and in medical research, respectively.