Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster

Lineage-based scaling of germline intercellular bridges during oogenesis

The size of subcellular structures must be tightly controlled to maintain normal cell function. Despite its importance, few studies have determined how the size of organelles or other structures is maintained during development, when cells are growing, dividing and rearranging. The developing Drosophila egg chamber is a powerful model in which to study the relative growth rates of subcellular structures. The egg chamber contains a cluster of 16 germline cells, which are connected through intercellular bridges called ring canals. As the egg chamber grows, the germline cells and the ring canals that connect them increase in size. Here, we demonstrate that ring canal size scaling is related to lineage; the largest, 'first-born' ring canals increase in size at a relatively slower rate than ring canals derived from subsequent mitotic divisions. This lineage-based scaling relationship is maintained even if directed transport is reduced, ring canal size is altered, or in egg chambers with twice as many germline cells. Analysis of lines that produce larger or smaller mature eggs reveals that different strategies could be used to alter final egg size.

Lineage-based scaling of germline intercellular bridges during oogenesis

The size of subcellular structures must be tightly controlled to maintain normal cell function. Despite its importance, few studies have determined how the size of organelles or other structures is maintained during development, when cells are growing, dividing, and rearranging. The developing egg chamber is a powerful model in which to study the relative growth rates of subcellular structures. The egg chamber contains a cluster of sixteen germline cells, which are connected through intercellular bridges called ring canals. As the egg chamber grows, the germline cells and the ring canals that connect them increase in size. Here, we demonstrate that ring canal size scaling is related to lineage; the largest, "first born" ring canals increase in size at a relatively slower rate than ring canals derived from subsequent mitotic divisions. This lineage-based scaling relationship is maintained even if directed transport is reduced, ring canal size is altered, or in egg chambers with twice as many germline cells. Analysis of lines that produce larger or smaller mature eggs reveals different strategies could be used to alter final egg size.

Summary Statement

Using the fruit fly egg chamber as a model, this study demonstrates that the size and scaling of germline intercellular bridges vary based on lineage.

Rapid response of fly populations to gene dosage across development and generations

Although the effects of genetic and environmental perturbations on multicellular organisms are rarely restricted to single phenotypic layers, our current understanding of how developmental programs react to these challenges remains limited. Here, we have examined the phenotypic consequences of disturbing the bicoid regulatory network in early Drosophila embryos. We generated flies with two extra copies of bicoid, which causes a posterior shift of the network's regulatory outputs and a decrease in fitness. We subjected these flies to EMS mutagenesis, followed by experimental evolution. After only 8-15 generations, experimental populations have normalized patterns of gene expression and increased survival. Using a phenomics approach, we find that populations were normalized through rapid increases in embryo size driven by maternal changes in metabolism and ovariole development. We extend our results to additional populations of flies, demonstrating predictability. Together, our results necessitate a broader view of regulatory network evolution at the systems level.

A high throughput method for egg size measurement in Drosophila

Life-history traits are used as proxies of fitness in insects including Drosophila. Egg size is an adaptive and ecologically important trait potentially with genetic variation across different populations. However, the low throughput of manual measurement of egg size has hampered the widespread use of this trait in evolutionary biology and population genetics. We established a method for accurate and high throughput measurement of Drosophila egg size using large particle flow cytometry (LPFC). The size estimates using LPFC are accurate and highly correlated with the manual measurements. The measurement of egg size is high throughput (average of 214 eggs measured per minute) and viable eggs of a specific size can be sorted rapidly (average of 70 eggs per minute). Sorting by LPFC does not reduce the survival of eggs making it a suitable approach for sorting eggs for downstream analyses. This protocol can be applied to any organism within the detectable size range (10-1500 µm) of the large particle flow cytometers. We discuss the potential applications of this method and provide recommendations for optimizing the protocol for other organisms.

A Single Nucleotide Variant in the PPARγ-homolog Eip75B Affects Fecundity in Drosophila

Single nucleotide polymorphisms are the most common type of genetic variation, but how these variants contribute to the adaptation of complex phenotypes is largely unknown. Experimental evolution and genome-wide association studies have demonstrated that variation in the PPARγ-homolog Eip75B has associated with longevity and life-history differences in the fruit fly Drosophila melanogaster. Using RNAi knockdown, we first demonstrate that reduced expression of Eip75B in adult flies affects lifespan, egg-laying rate, and egg volume. We then tested the effects of a naturally occurring SNP within a cis-regulatory domain of Eip75B by applying two complementary approaches: a Mendelian randomization approach using lines of the Drosophila Genetic Reference Panel, and allelic replacement using precise CRISPR/Cas9-induced genome editing. Our experiments reveal that this natural polymorphism has a significant pleiotropic effect on fecundity and egg-to-adult viability, but not on longevity or other life-history traits. Our results provide a rare functional validation at the nucleotide level and identify a natural allelic variant affecting fitness and life-history adaptation.

Adaptation in Outbred Sexual Yeast is Repeatable, Polygenic and Favors Rare Haplotypes

We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations.

Natural alleles at the Doa locus underpin evolutionary changes in Drosophila lifespan and fecundity

'Evolve and resequence' (E&R) studies in Drosophila melanogaster have identified many candidate loci underlying the evolution of ageing and life history, but experiments that validate the effects of such candidates remain rare. In a recent E&R study we have identified several alleles of the LAMMER kinase Darkener of apricot (Doa) as candidates for evolutionary changes in lifespan and fecundity. Here, we use two complementary approaches to confirm a functional role of Doa in life-history evolution. First, we used transgenic RNAi to study the effects of Doa at the whole-gene level. Ubiquitous silencing of expression in adult flies reduced both lifespan and fecundity, indicating pleiotropic effects. Second, to characterize segregating variation at Doa, we examined four candidate single nucleotide polymorphisms (SNPs; Doa-1, -2, -3, -4) using a genetic association approach. Three candidate SNPs had effects that were qualitatively consistent with expectations based on our E&R study: Doa-2 pleiotropically affected both lifespan and late-life fecundity; Doa-1 affected lifespan (but not fecundity); and Doa-4 affected late-life fecundity (but not lifespan). Finally, the last candidate allele (Doa-3) also affected lifespan, but in the opposite direction from predicted.

The molecular basis of socially induced egg-size plasticity in honey bees

Reproduction involves the investment of resources into offspring. Although variation in reproductive effort often affects the number of offspring, adjustments of propagule size are also found in numerous species, including the Western honey bee, Apis mellifera. However, the proximate causes of these adjustments are insufficiently understood, especially in oviparous species with complex social organization in which adaptive evolution is shaped by kin selection. Here, we show in a series of experiments that queens predictably and reversibly increase egg size in small colonies and decrease egg size in large colonies, while their ovary size changes in the opposite direction. Additional results suggest that these effects cannot be solely explained by egg-laying rate and are due to the queens' perception of colony size. Egg-size plasticity is associated with quantitative changes of 290 ovarian proteins, most of which relate to energy metabolism, protein transport, and cytoskeleton. Based on functional and network analyses, we further study the small GTPase Rho1 as a candidate regulator of egg size. Spatio-temporal expression analysis via RNAscope and qPCR supports an important role of Rho1 in egg-size determination, and subsequent RNAi-mediated gene knockdown confirmed that Rho1 has a major effect on egg size in honey bees. These results elucidate how the social environment of the honey bee colony may be translated into a specific cellular process to adjust maternal investment into eggs. It remains to be studied how widespread this mechanism is and whether it has consequences for population dynamics and epigenetic influences on offspring phenotype in honey bees and other species.

Intralocus conflicts associated with a supergene

Chromosomal inversions frequently underlie major phenotypic variation maintained by divergent selection within and between sexes. Here we examine whether and how intralocus conflicts contribute to balancing selection stabilizing an autosomal inversion polymorphism in the ruff Calidris pugnax. In this lekking shorebird, three male mating morphs (Independents, Satellites and Faeders) are controlled by an inversion-based supergene. We show that in a captive population, Faeder females, who are smaller and whose inversion haplotype has not undergone recombination, have lower average reproductive success in terms of laying rate, egg size, and offspring survival than Independent females, who lack the inversion. Satellite females, who carry a recombined inversion haplotype and have intermediate body size, more closely resemble Independent than Faeder females in reproductive performance. We inferred that the lower reproductive output of Faeder females is most likely balanced by higher than average reproductive success of individual Faeder males. These findings suggest that intralocus conflicts may play a major role in the evolution and maintenance of supergene variants.

Shotgun and TMT-Labeled Proteomic Analysis of the Ovarian Proteins of an Insect Vector, Aedes aegypti (Diptera: Culicidae)

Aedes aegypti [Linnaeus in Hasselquist; yellow fever mosquito] transmits several viruses that infect millions of people each year, including Zika, dengue, yellow fever, chikungunya, and West Nile. Pathogen transmission occurs during blood feeding. Only the females blood feed as they require a bloodmeal for oogenesis; in the bloodmeal, holo-transferrin and hemoglobin provide the females with a high iron load. We are interested in the effects of the bloodmeal on the expression of iron-associated proteins in oogenesis. Previous data showed that following digestion of a bloodmeal, ovarian iron concentrations doubles by 72 hr. We have used shotgun proteomics to identify proteins expressed in Ae. aegypti ovaries at two oogenesis developmental stages following blood feeding, and tandem mass tag-labeling proteomics to quantify proteins expressed at one stage following feeding of a controlled iron diet. Our findings provide the first report of mosquito ovarian protein expression in early and late oogenesis. We identify proteins differentially expressed in the two oogenesis development stages. We establish that metal-associated proteins play an important role in Ae. aegypti oogenesis and we identify new candidate proteins that might be involved in mosquito iron metabolism. Finally, this work identified a unique second ferritin light chain subunit, the first reported in any species. The shotgun proteomic data are available via ProteomeXchange with identifier PXD005893, while the tandem mass tag-labeled proteomic data are available with identifier PXD028242.

Combining Metabolomics and Experimental Evolution Reveals Key Mechanisms Underlying Longevity Differences in Laboratory Evolved Drosophila melanogaster Populations

Experimental evolution with Drosophila melanogaster has been used extensively for decades to study aging and longevity. In recent years, the addition of DNA and RNA sequencing to this framework has allowed researchers to leverage the statistical power inherent to experimental evolution to study the genetic basis of longevity itself. Here, we incorporated metabolomic data into to this framework to generate even deeper insights into the physiological and genetic mechanisms underlying longevity differences in three groups of experimentally evolved D. melanogaster populations with different aging and longevity patterns. Our metabolomic analysis found that aging alters mitochondrial metabolism through increased consumption of NAD+ and increased usage of the TCA cycle. Combining our genomic and metabolomic data produced a list of biologically relevant candidate genes. Among these candidates, we found significant enrichment for genes and pathways associated with neurological development and function, and carbohydrate metabolism. While we do not explicitly find enrichment for aging canonical genes, neurological dysregulation and carbohydrate metabolism are both known to be associated with accelerated aging and reduced longevity. Taken together, our results provide plausible genetic mechanisms for what might be driving longevity differences in this experimental system. More broadly, our findings demonstrate the value of combining multiple types of omic data with experimental evolution when attempting to dissect mechanisms underlying complex and highly polygenic traits such as aging.

Crossing design shapes patterns of genetic variation in synthetic recombinant populations of Saccharomyces cerevisiae

"Synthetic recombinant" populations have emerged as a useful tool for dissecting the genetics of complex traits. They can be used to derive inbred lines for fine QTL mapping, or the populations themselves can be sampled for experimental evolution. In the latter application, investigators generally value maximizing genetic variation in constructed populations. This is because in evolution experiments initiated from such populations, adaptation is primarily fueled by standing genetic variation. Despite this reality, little has been done to systematically evaluate how different methods of constructing synthetic populations shape initial patterns of variation. Here we seek to address this issue by comparing outcomes in synthetic recombinant Saccharomyces cerevisiae populations created using one of two strategies: pairwise crossing of isogenic strains or simple mixing of strains in equal proportion. We also explore the impact of the varying the number of parental strains. We find that more genetic variation is initially present and maintained when population construction includes a round of pairwise crossing. As perhaps expected, we also observe that increasing the number of parental strains typically increases genetic diversity. In summary, we suggest that when constructing populations for use in evolution experiments, simply mixing founder strains in equal proportion may limit the adaptive potential.

Plasticity and artificial selection for developmental mode in a poecilogonous sea slug

The contribution of phenotypically plastic traits to evolution depends on the degree of environmental influence on the target of selection (the phenotype) as well as the underlying genetic structure of the trait and plastic response. Likewise, maternal effects can help or hinder evolution through affects to the response to selection. The sacoglossan sea slug Alderia willowi exhibits intraspecific variation for developmental mode (= poecilogony) that is environmentally modulated with populations producing more yolk-feeding (lecithotrophic) larvae during the summer, and more planktonic-feeding (planktotrophic) larvae in the winter. I found significant family-level variation in the reaction norms between 17 maternal families of A. willowi when reared in a split-brood design in low (16 ppt) versus high (32 ppt) salinity, conditions which mimic seasonal variation in salinity of natural populations. I documented a significant response to selection for lecithotrophic larvae in high and low salinity. The slope of the reaction norm was maintained following one generation of selection for lecithotrophy. When the maternal environment was controlled in the laboratory, I found significant maternal effects, which reduced the response to selection. These results suggest there is standing genetic variation for egg-mass type in A. willowi, but the ability of selection to act on that variation may depend on the environment in which the phenotype is expressed in preceding generations.

The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime

Background

Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates.

Results

Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime.

Conclusions

These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02425-9.

Meta-analysis suggests the microbiome responds to Evolve and Resequence experiments in Drosophila melanogaster

BACKGROUND

Experimental evolution has a long history of uncovering fundamental insights into evolutionary processes, but has largely neglected one underappreciated component--the microbiome. As eukaryotic hosts evolve, the microbiome may also respond to selection. However, the microbial contribution to host evolution remains poorly understood. Here, we re-analyzed genomic data to characterize the metagenomes from ten Evolve and Resequence (E&R) experiments in Drosophila melanogaster to determine how the microbiome changed in response to host selection.

RESULTS

Bacterial diversity was significantly different in 5/10 studies, primarily in traits associated with metabolism or immunity. Duration of selection did not significantly influence bacterial diversity, highlighting the importance of associations with specific host traits.

CONCLUSIONS

Our genomic re-analysis suggests the microbiome often responds to host selection; thus, the microbiome may contribute to the response of Drosophila in E&R experiments. We outline important considerations for incorporating the microbiome into E&R experiments. The E&R approach may provide critical insights into host-microbiome interactions and fundamental insight into the genomic basis of adaptation.

The Genomic Architecture of Adaptation to Larval Malnutrition Points to a Trade-off with Adult Starvation Resistance in Drosophila

Periods of nutrient shortage impose strong selection on animal populations. Experimental studies of genetic adaptation to nutrient shortage largely focus on resistance to acute starvation at adult stage; it is not clear how conclusions drawn from these studies extrapolate to other forms of nutritional stress. We studied the genomic signature of adaptation to chronic juvenile malnutrition in six populations of Drosophila melanogaster evolved for 150 generations on an extremely nutrient-poor larval diet. Comparison with control populations evolved on standard food revealed repeatable genomic differentiation between the two set of population, involving >3,000 candidate SNPs forming >100 independently evolving clusters. The candidate genomic regions were enriched in genes implicated in hormone, carbohydrate, and lipid metabolism, including some with known effects on fitness-related life-history traits. Rather than being close to fixation, a substantial fraction of candidate SNPs segregated at intermediate allele frequencies in all malnutrition-adapted populations. This, together with patterns of among-population variation in allele frequencies and estimates of Tajima’s D, suggests that the poor diet results in balancing selection on some genomic regions. Our candidate genes for tolerance to larval malnutrition showed a high overlap with genes previously implicated in acute starvation resistance. However, adaptation to larval malnutrition in our study was associated with reduced tolerance to acute adult starvation. Thus, rather than reflecting synergy, the shared genomic architecture appears to mediate an evolutionary trade-off between tolerances to these two forms of nutritional stress.

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

"Evolve and resequence" (E&R) studies combine experimental evolution and whole-genome sequencing to interrogate the genetics underlying adaptation. Due to ease of handling, E&R work with asexual organisms such as bacteria can employ optimized experimental design, with large experiments and many generations of selection. By contrast, E&R experiments with sexually reproducing organisms are more difficult to implement, and design parameters vary dramatically among studies. Thus, efforts have been made to assess how these differences, such as number of independent replicates, or size of experimental populations, impact inference. We add to this work by investigating the role of time sampling-the number of discrete time points sequence data are collected from evolving populations. Using data from an E&R experiment with outcrossing Saccharomyces cerevisiae in which populations were sequenced 17 times over ~540 generations, we address the following questions: (a) Do more time points improve the ability to identify candidate regions underlying selection? And (b) does high-resolution sampling provide unique insight into evolutionary processes driving adaptation? We find that while time sampling does not improve the ability to identify candidate regions, high-resolution sampling does provide valuable opportunities to characterize evolutionary dynamics. Increased time sampling reveals three distinct trajectories for adaptive alleles: one consistent with classic population genetic theory (i.e., models assuming constant selection coefficients), and two where trajectories suggest more context-dependent responses (i.e., models involving dynamic selection coefficients). We conclude that while time sampling has limited impact on candidate region identification, sampling eight or more time points has clear benefits for studying complex evolutionary dynamics.

Latitudinal variation in climate-associated genes imperils range edge populations

The ecological impacts of increasing global temperatures are evident in most ecosystems on Earth, but our understanding of how climatic variation influences natural selection and adaptive resilience across latitudes remains largely unknown. Latitudinal gradients allow testing general ecosystem-level theories relevant to climatic adaptation. We assessed differences in adaptive diversity of populations along a latitudinal region spanning highly variable temperate to subtropical climates. We generated and integrated information from environmental mapping, phenotypic variation and genome-wide data from across the geographical range of the rainbowfish Melanotaenia duboulayi, an emerging aquatic system for studies of climate change. We detected, after controlling for spatial population structure, strong interactions between genotypes and environment associated with variation in stream flow and temperature. Some of these hydroclimate-associated genes were found to interact within functional protein networks that contain genes of adaptive significance for projected future climates in rainbowfish. Hydroclimatic selection was also associated with variation in phenotypic traits, including traits known to affect fitness of rainbowfish exposed to different flow environments. Consistent with predictions from the "climatic variability hypothesis," populations exposed to extremes of important environmental variables showed stronger adaptive divergence and less variation in climate-associated genes compared to populations at the centre of the environmental gradient. Our findings suggest that populations that evolved at environmental range margins and at geographical range edges may be more vulnerable to changing climates, a finding with implications for predicting adaptive resilience and managing biodiversity under climate change.

Detecting selected haplotype blocks in evolve and resequence experiments

Shifting from the analysis of single nucleotide polymorphisms to the reconstruction of selected haplotypes greatly facilitates the interpretation of evolve and resequence (E&R) experiments. Merging highly correlated hitchhiker SNPs into haplotype blocks reduces thousands of candidates to few selected regions. Current methods of haplotype reconstruction from Pool‐seq data need a variety of data‐specific parameters that are typically defined ad hoc and require haplotype sequences for validation. Here, we introduce haplovalidate, a tool which detects selected haplotypes in Pool‐seq time series data without the need for sequenced haplotypes. Haplovalidate makes data‐driven choices of two key parameters for the clustering procedure, the minimum correlation between SNPs constituting a cluster and the window size. Applying haplovalidate to simulated E&R data reliably detects selected haplotype blocks with low false discovery rates. Importantly, our analyses identified a restriction of the haplotype block‐based approach to describe the genomic architecture of adaptation. We detected a substantial fraction of haplotypes containing multiple selection targets. These blocks were considered as one region of selection and therefore led to underestimation of the number of selection targets. We demonstrate that the separate analysis of earlier time points can significantly increase the separation of selection targets into individual haplotype blocks. We conclude that the analysis of selected haplotype blocks has great potential for the characterization of the adaptive architecture with E&R experiments.

Resource quality determines the evolution of resistance and its genetic basis

Parasites impose strong selection on their hosts, but the level of any evolved resistance may be constrained by the availability of resources. However, studies identifying the genomic basis of such resource-mediated selection are rare, particularly in nonmodel organisms. Here, we investigated the role of nutrition in the evolution of resistance to a DNA virus (PiGV), and any associated trade-offs in a lepidopteran pest species (Plodia interpunctella). Through selection experiments and whole-genome resequencing, we identify genetic markers of resistance that vary between the nutritional environments during selection. We do not find consistent evolution of resistance in the presence of virus but rather see substantial variation among replicate populations. Resistance in a low-nutrition environment is negatively correlated with growth rate, consistent with an established trade-off between immunity and development, but this relationship is highly context dependent. Whole-genome resequencing of the host shows that resistance mechanisms are likely to be highly polygenic and although the underlying genetic architecture may differ between high and low-nutrition environments, similar mechanisms are commonly used. As a whole, our results emphasize the importance of the resource environment on influencing the evolution of resistance.

The target of selection matters: An established resistance-development-time negative genetic trade-off is not found when selecting on development time

Trade-offs are fundamental to evolutionary outcomes and play a central role in eco-evolutionary theory. They are often examined by experimentally selecting on one life-history trait and looking for negative correlations in other traits. For example, populations of the moth Plodia interpunctella selected to resist viral infection show a life-history cost with longer development times. However, we rarely examine whether the detection of such negative genetic correlations depends on the trait on which we select. Here, we examine a well-characterized negative genotypic trade-off between development time and resistance to viral infection in the moth Plodia interpunctella and test whether selection on a phenotype known to be a cost of resistance (longer development time) leads to the predicted correlated increase in resistance. If there is tight pleiotropic relationship between genes that determine development time and resistance underpinning this trade-off, we might expect increased resistance when we select on longer development time. However, we show that selecting for longer development time in this system selects for reduced resistance when compared to selection for shorter development time. This shows how phenotypes typically characterized by a trade-off can deviate from that trade-off relationship, and suggests little genetic linkage between the genes governing viral resistance and those that determine response to selection on the key life-history trait. Our results are important for both selection strategies in applied biological systems and for evolutionary modelling of host-parasite interactions.

Mutations in a Novel Cadherin Gene Associated with Bt Resistance in Helicoverpa zea

Transgenic corn and cotton produce crystalline (Cry) proteins derived from the soil bacterium Bacillus thuringiensis (Bt) that are toxic to lepidopteran larvae. Helicoverpa zea, a key pest of corn and cotton in the U.S., has evolved widespread resistance to these proteins produced in Bt corn and cotton. While the genomic targets of Cry selection and the mutations that produce resistant phenotypes are known in other lepidopteran species, little is known about how selection by Cry proteins shape the genome of H. zea. We scanned the genomes of Cry1Ac-selected and unselected H. zea lines, and identified twelve genes on five scaffolds that differed between lines, including cadherin-86C (cad-86C), a gene from a family that is involved in Cry1A resistance in other lepidopterans. Although this gene was expressed in the H. zea larval midgut, the protein it encodes has only 17 to 22% identity with cadherin proteins from other species previously reported to be involved in Bt resistance. An analysis of midgut-expressed cDNAs showed significant between-line differences in the frequencies of putative nonsynonymous substitutions (both SNPs and indels). Our results indicate that cad-86C is a likely target of Cry1Ac selection in H. zea. It remains unclear, however, whether genomic changes at this locus directly disrupt midgut binding of Cry1Ac and cause Bt resistance, or indirectly enhance fitness of H. zea in the presence of Cry1Ac by some other mechanism. Future work should investigate phenotypic effects of these nonsynonymous substitutions and their impact on fitness of H. zea larvae that ingest Cry1Ac.

An Overview of Embryogenesis: External Morphology and Transcriptome Profiling in the Hemipteran Insect Nilaparvata lugens

During embryogenesis of insects, the morphological and transcriptional changes are important signatures to obtain a better understanding of insect patterning and evolution. The brown planthopper Nilaparvata lugens is a serious insect pest of rice plants, but its embryogenesis has not uncovered. Here, we described embryonic development process of the pest and found it belongs to an intermediate-germ mode. The RNA-seq data from different times (6, 30, 96, and 150 h, after egg laying) of embryogenesis were then analyzed, and a total of 10,895 genes were determined as differentially expressed genes (DEGs) based on pairwise comparisons. Afterward, 1,898 genes, differentially expressed in at least two comparisons of adjacent embryonic stages were divided into 10 clusters using K means cluster analysis (KMCA). Eight-gene modules were established using a weighted gene co-expression network analysis (WGCNA). Gene expression patterns in the different embryonic stages were identified by combining the functional enrichments of the stage-specific clusters and modules, which displayed the expression level and reprogramming of multiple developmental genes during embryogenesis. The "hub" genes at each embryonic stage with possible crucial roles were identified. Notably, we found a "center" set of genes that were related to overall membrane functions and might play important roles in the embryogenesis process. After parental RNAi of the MSTRG.3372, the hub gene, the embryo was observed as abnormal. Furthermore, some homologous genes in classic embryonic development processes and signaling pathways were also involved in embryogenesis of this insect. An improved comprehensive finding of embryogenesis within the N. lugens reveals better information on genetic and genomic studies of embryonic development and might be a potential target for RNAi-based control of this insect pest.

Life-History Evolution and the Genetics of Fitness Components in Drosophila melanogaster

Life-history traits or "fitness components"-such as age and size at maturity, fecundity and fertility, age-specific rates of survival, and life span-are the major phenotypic determinants of Darwinian fitness. Analyzing the evolution and genetics of these phenotypic targets of selection is central to our understanding of adaptation. Due to its simple and rapid life cycle, cosmopolitan distribution, ease of maintenance in the laboratory, well-understood evolutionary genetics, and its versatile genetic toolbox, the "vinegar fly" Drosophila melanogaster is one of the most powerful, experimentally tractable model systems for studying "life-history evolution." Here, I review what has been learned about the evolution and genetics of life-history variation in D. melanogaster by drawing on numerous sources spanning population and quantitative genetics, genomics, experimental evolution, evolutionary ecology, and physiology. This body of work has contributed greatly to our knowledge of several fundamental problems in evolutionary biology, including the amount and maintenance of genetic variation, the evolution of body size, clines and climate adaptation, the evolution of senescence, phenotypic plasticity, the nature of life-history trade-offs, and so forth. While major progress has been made, important facets of these and other questions remain open, and the D. melanogaster system will undoubtedly continue to deliver key insights into central issues of life-history evolution and the genetics of adaptation.

Distinct genomic signals of lifespan and life history evolution in response to postponed reproduction and larval diet in Drosophila

Reproduction and diet are two major factors controlling the physiology of aging and life history, but how they interact to affect the evolution of longevity is unknown. Moreover, although studies of large-effect mutants suggest an important role of nutrient sensing pathways in regulating aging, the genetic basis of evolutionary changes in lifespan remains poorly understood. To address these questions, we analyzed the genomes of experimentally evolved Drosophila melanogaster populations subjected to a factorial combination of two selection regimes: reproductive age (early versus postponed), and diet during the larval stage ("low," "control," "high"), resulting in six treatment combinations with four replicate populations each. Selection on reproductive age consistently affected lifespan, with flies from the postponed reproduction regime having evolved a longer lifespan. In contrast, larval diet affected lifespan only in early-reproducing populations: flies adapted to the "low" diet lived longer than those adapted to control diet. Here, we find genomic evidence for strong independent evolutionary responses to either selection regime, as well as loci that diverged in response to both regimes, thus representing genomic interactions between the two. Overall, we find that the genomic basis of longevity is largely independent of dietary adaptation. Differentiated loci were not enriched for "canonical" longevity genes, suggesting that naturally occurring genic targets of selection for longevity differ qualitatively from variants found in mutant screens. Comparing our candidate loci to those from other "evolve and resequence" studies of longevity demonstrated significant overlap among independent experiments. This suggests that the evolution of longevity, despite its presumed complex and polygenic nature, might be to some extent convergent and predictable.

Accurate Allele Frequencies from Ultra-low Coverage Pool-Seq Samples in Evolve-and-Resequence Experiments

Evolve-and-resequence (E+R) experiments leverage next-generation sequencing technology to track the allele frequency dynamics of populations as they evolve. While previous work has shown that adaptive alleles can be detected by comparing frequency trajectories from many replicate populations, this power comes at the expense of high-coverage (>100x) sequencing of many pooled samples, which can be cost-prohibitive. Here, we show that accurate estimates of allele frequencies can be achieved with very shallow sequencing depths (<5x) via inference of known founder haplotypes in small genomic windows. This technique can be used to efficiently estimate frequencies for any number of bi-allelic SNPs in populations of any model organism founded with sequenced homozygous strains. Using both experimentally-pooled and simulated samples of Drosophila melanogaster, we show that haplotype inference can improve allele frequency accuracy by orders of magnitude for up to 50 generations of recombination, and is robust to moderate levels of missing data, as well as different selection regimes. Finally, we show that a simple linear model generated from these simulations can predict the accuracy of haplotype-derived allele frequencies in other model organisms and experimental designs. To make these results broadly accessible for use in E+R experiments, we introduce HAF-pipe, an open-source software tool for calculating haplotype-derived allele frequencies from raw sequencing data. Ultimately, by reducing sequencing costs without sacrificing accuracy, our method facilitates E+R designs with higher replication and resolution, and thereby, increased power to detect adaptive alleles.

An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice

Evolutionary studies are often limited by missing data that are critical to understanding the history of selection. Selection experiments, which reproduce rapid evolution under controlled conditions, are excellent tools to study how genomes evolve under selection. Here we present a genomic dissection of the Longshanks selection experiment, in which mice were selectively bred over 20 generations for longer tibiae relative to body mass, resulting in 13% longer tibiae in two replicates. We synthesized evolutionary theory, genome sequences and molecular genetics to understand the selection response and found that it involved both polygenic adaptation and discrete loci of major effect, with the strongest loci tending to be selected in parallel between replicates. We show that selection may favor de-repression of bone growth through inactivating two limb enhancers of an inhibitor, Nkx3-2. Our integrative genomic analyses thus show that it is possible to connect individual base-pair changes to the overall selection response.

Fish response to hypoxia stress: growth, physiological, and immunological biomarkers

Water quality encompasses the water physical, biological, and chemical parameters. It generally affects the fish growth and welfare. Thus, the success of a commercial aquaculture project depends on supplying the optimum water quality for prompt fish growth at the minimum cost of resources. Although the aquaculture environment is a complicated system, depending on various water quality variables, only less of them have a critical role. One of these vital parameters is dissolved oxygen (DO) level, which requires continuous oversight in aquaculture systems. In addition, the processes of natural stream refinement require suitable DO levels in order to extend for aerobic life forms. The depletion of DO concentration (called hypoxia) in pond water causes great stress on fish where DO levels that remain below 1-2 mg/L for a few hours can adversely affect fish growth resulting in fish death. Furthermore, hypoxia has substantial effects on fish physiological and immune responses, making them more susceptible to diseases. Therefore, to avoid disease outbreak in modern aquaculture production systems where fish are intensified and more crowded, increasing attention should be taken into account on DO levels.

Natural and Artificial Selection for Parasitoid Resistance in Drosophila melanogaster Leave Different Genetic Signatures

Adaptation of complex traits depends on standing genetic variation at multiple loci. The allelic variants that have positive fitness effects, however, can differ depending on the genetic background and the selective pressure. Previously, we interrogated the Drosophila melanogaster genome at the population level for polymorphic positions and identified 215 single nucleotide polymorphisms (SNPs) that had significantly changed in frequency after experimental evolution for increased parasitoid resistance. In the current study, we follow up on 11 of these SNPs as putative targets of the experimental selection process (Jalvingh et al., 2014). We study the patterns of genetic variation for these SNPs in several European field populations. Furthermore, we associate the genetic variation of these SNPs to variation in resistance against the parasitoid Asobara tabida, by determining the individual phenotype and SNP genotype for 144 individuals from four Selection lines and four non-selected Control lines and for 400 individuals from 12 Field lines that differ in parasitoid resistance. For the Selection lines we additionally monitored the changes in allele frequencies throughout the five generations of experimental selection. For three genes, mbl (Zn-finger protein), mthl4 (G-protein coupled receptor) and CG17287 (protein-cysteine S-palmitoyltransferase) individual SNP genotypes were significantly associated with resistance level in the Selection and Control lines. Additionally, the minor allele in mbl and mthl4 were consistently and gradually favored throughout the five generations of experimental evolution. However, none of these alleles did appear to be associated to high resistance in the Field lines. We suggest that, within field populations, selection for parasitoid resistance is a gradual process that involves co-adapted gene complexes. Fast artificial selection, however, enforces the sudden cumulating of particular alleles that confer high resistance (genetic sweep). We discuss our findings in the context of local adaptation.

Molecular evidence supports a genic capture resolution of the lek paradox

The genic capture hypothesis, where sexually selected traits capture genetic variation in condition and the condition reflects genome-wide mutation load, stands to explain the presence of abundant genetic variation underlying sexually selected traits. Here we test this hypothesis by applying bidirectional selection to male mating success for 14 generations in replicate populations of Drosophila melanogaster. We then resequenced the genomes of flies from each population. Consistent with the central predictions of the genic capture hypothesis, we show that genetic variance decreased with success selection and increased with failure selection, providing evidence for purifying sexual selection. This pattern was distributed across the genome and no consistent molecular pathways were associated with divergence, consistent with condition being the target of selection. Together, our results provide molecular evidence suggesting that strong sexual selection erodes genetic variation, and that genome-wide mutation-selection balance contributes to its maintenance.

Adaptation to developmental diet influences the response to selection on age at reproduction in the fruit fly

Experimental evolution (EE) is a powerful tool for addressing how environmental factors influence life-history evolution. While in nature different selection pressures experienced across the lifespan shape life histories, EE studies typically apply selection pressures one at a time. Here, we assess the consequences of adaptation to three different developmental diets in combination with classical selection for early or late reproduction in the fruit fly Drosophila melanogaster. We find that the response to each selection pressure is similar to that observed when they are applied independently, but the overall magnitude of the response depends on the selection regime experienced in the other life stage. For example, adaptation to increased age at reproduction increased lifespan across all diets; however, the extent of the increase was dependent on the dietary selection regime. Similarly, adaptation to a lower calorie developmental diet led to faster development and decreased adult weight, but the magnitude of the response was dependent on the age-at-reproduction selection regime. Given that multiple selection pressures are prevalent in nature, our findings suggest that trade-offs should be considered not only among traits within an organism, but also among adaptive responses to different-sometimes conflicting-selection pressures, including across life stages.

Evolutionary insights from large scale resequencing datasets in Drosophila melanogaster

Drosophila melanogaster has long been used as an evolutionary model system. Its small genome size, well-annotated genome, and ease of sampling, also makes it a choice species for genome resequencing studies. Hundreds of genomic samples from populations worldwide are available and are currently being used to tackle a wide range of evolutionary questions. In this review, we focused on three insights that have increased our understanding of the evolutionary history of this species, and that have implications for the study of evolutionary processes in other species as well. Because of technical limitations, most of the studies so far have focused on SNP variants. However, long-read sequencing techniques should allow us in the near future to include other type of genomic variants that also influence genome evolution.

Regulatory and sequence evolution in response to selection for improved associative learning ability in Nasonia vitripennis

Background

Selection acts on the phenotype, yet only the genotype is inherited. While both the phenotypic and genotypic response to short-term selection can be measured, the link between these is a major unsolved problem in evolutionary biology, in particular for complex behavioural phenotypes.

Results

Here we characterize the genomic and the transcriptomic basis of associative learning ability in the parasitic wasp Nasonia vitripennis and use gene network analysis to link the two. We artificially selected for improved associative learning ability in four independent pairs of lines and identified signatures of selection across the genome. Allele frequency diverged consistently between the selected and control lines in 118 single nucleotide polymorphisms (SNPs), clustering in 51 distinct genomic regions containing 128 genes. The majority of SNPs were found in regulatory regions, suggesting a potential role for gene expression evolution. We therefore sequenced the transcriptomes of selected and control lines and identified 36 consistently differentially expressed transcripts with large changes in expression. None of the differentially expressed genes also showed sequence divergence as a result of selection. Instead, gene network analysis showed many of the genes with consistent allele frequency differences and all of the differentially expressed genes to cluster in a single co-expression network. At a functional level, both genomic and transcriptomic analyses implicated members of gene networks known to be involved in neural plasticity and cognitive processes.

Conclusions

Taken together, our results reveal how specific cognitive abilities can readily respond to selection via a complex interplay between regulatory and sequence evolution.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5310-9) contains supplementary material, which is available to authorized users.

A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila

BACKGROUND

Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large-effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation.

RESULTS

To investigate the genetic architecture of thermal adaptation - a highly complex trait - we performed experimental evolution on a natural Drosophila simulans population. Transcriptome and respiration measurements reveal extensive metabolic rewiring after only approximately 60 generations in a hot environment. Analysis of genome-wide polymorphisms identifies two interacting selection targets, Sestrin and SNF4Aγ, pointing to AMPK, a central metabolic switch, as a key factor for thermal adaptation.

CONCLUSIONS

Our results demonstrate that large-effect loci segregating at intermediate allele frequencies can allow natural populations to rapidly respond to selection. Because SNF4Aγ also exhibits clinal variation in various Drosophila species, we suggest that this large-effect polymorphism is maintained by temporal and spatial temperature variation in natural environments.

Drosophila simulans: A Species with Improved Resolution in Evolve and Resequence Studies

The combination of experimental evolution with high-throughput sequencing of pooled individuals—i.e., evolve and resequence (E&R)—is a powerful approach to study adaptation from standing genetic variation under controlled, replicated conditions. Nevertheless, E&R studies in Drosophila melanogaster have frequently resulted in inordinate numbers of candidate SNPs, particularly for complex traits. Here, we contrast the genomic signature of adaptation following ∼60 generations in a novel hot environment for D. melanogaster and D. simulans. For D. simulans, the regions carrying putatively selected loci were far more distinct, and thus harbored fewer false positives, than those in D. melanogaster. We propose that species without segregating inversions and higher recombination rates, such as D. simulans, are better suited for E&R studies that aim to characterize the genetic variants underlying the adaptive response.

Clear: Composition of Likelihoods for Evolve and Resequence Experiments

The advent of next generation sequencing technologies has made whole-genome and whole-population sampling possible, even for eukaryotes with large genomes. With this development, experimental evolution studies can be designed to observe molecular evolution "in action" via evolve-and-resequence (E&R) experiments. Among other applications, E&R studies can be used to locate the genes and variants responsible for genetic adaptation. Most existing literature on time-series data analysis often assumes large population size, accurate allele frequency estimates, or wide time spans. These assumptions do not hold in many E&R studies. In this article, we propose a method-composition of likelihoods for evolve-and-resequence experiments (Clear)-to identify signatures of selection in small population E&R experiments. Clear takes whole-genome sequences of pools of individuals as input, and properly addresses heterogeneous ascertainment bias resulting from uneven coverage. Clear also provides unbiased estimates of model parameters, including population size, selection strength, and dominance, while being computationally efficient. Extensive simulations show that Clear achieves higher power in detecting and localizing selection over a wide range of parameters, and is robust to variation of coverage. We applied the Clear statistic to multiple E&R experiments, including data from a study of adaptation of Drosophila melanogaster to alternating temperatures and a study of outcrossing yeast populations, and identified multiple regions under selection with genome-wide significance.

Nucleotide diversity inflation as a genome-wide response to experimental lifespan extension in Drosophila melanogaster

Background

Evolutionary theory predicts that antagonistically selected alleles, such as those with divergent pleiotropic effects in early and late life, may often reach intermediate population frequencies due to balancing selection, an elusive process when sought out empirically. Alternatively, genetic diversity may increase as a result of positive frequency-dependent selection and genetic purging in bottlenecked populations.

Results

While experimental evolution systems with directional phenotypic selection typically result in at least local heterozygosity loss, we report that selection for increased lifespan in Drosophila melanogaster leads to an extensive genome-wide increase of nucleotide diversity in the selected lines compared to replicate control lines, pronounced in regions with no or low recombination, such as chromosome 4 and centromere neighborhoods. These changes, particularly in coding sequences, are most consistent with the operation of balancing selection and the antagonistic pleiotropy theory of aging and life history traits that tend to be intercorrelated. Genes involved in antioxidant defenses, along with multiple lncRNAs, were among those most affected by balancing selection. Despite the overwhelming genetic diversification and the paucity of selective sweep regions, two genes with functions important for central nervous system and memory, Ptp10D and Ank2, evolved under positive selection in the longevity lines.

Conclusions

Overall, the ‘evolve-and-resequence’ experimental approach proves successful in providing unique insights into the complex evolutionary dynamics of genomic regions responsible for longevity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3485-0) contains supplementary material, which is available to authorized users.

Hypoxic stress -responsive genes in air breathing catfish, Clarias magur (Hamilton 1822) and their possible physiological adaptive function

The Indian catfish, Clarias magur (previous name C. batrachus) is an air breathing fish, inhabitant of aquatic bodies characterized by low dissolved oxygen levels. It is exposed to hypoxic conditions in its natural habitat. Thus, it can be useful model to study the mechanism of hypoxia stress tolerance. In C. magur, molecular processes facilitating its adaptation to hypoxia stress remain largely unexplored, in part due to unavailability of genomic resources. The suppression subtractive hybridization technique (SSH) was employed to compare the differential expression of transcripts under experimental hypoxic conditions, to that of normoxic conditions. Twelve subtracted cDNA libraries (six each forward and reverse) were constructed from brain, heart, liver, muscle, spleen and head kidney tissues. A total of 2020 clones were screened and sequenced, resulting into 1805 high quality expressed sequence tags (ESTs). Annotation of these differentially expressed ESTs resulted into the identification of genes involved in vast majority of pathways/processes affecting metabolism, cellular processes, signal transduction and/or immune functions. Additionally, 18 potential novel genes expressed in hypoxia stress exposed fish were also identified. The study had catalogued the differentially expressed genes from hypoxia stress induced C. magur, where most of them are reported for the first time in a hypoxia-tolerant fish species. The results not only provided insights for the hypoxia stress altered cellular functions in C. magur, but also generated a valuable functional genomics resource to assist targeted studies on functional genomics and future genome projects.

Reconstruction of Haplotype-Blocks Selected during Experimental Evolution

The genetic analysis of experimentally evolving populations typically relies on short reads from pooled individuals (Pool-Seq). While this method provides reliable allele frequency estimates, the underlying haplotype structure remains poorly characterized. With small population sizes and adaptive variants that start from low frequencies, the interpretation of selection signatures in most Evolve and Resequencing studies remains challenging. To facilitate the characterization of selection targets, we propose a new approach that reconstructs selected haplotypes from replicated time series, using Pool-Seq data. We identify selected haplotypes through the correlated frequencies of alleles carried by them. Computer simulations indicate that selected haplotype-blocks of several Mb can be reconstructed with high confidence and low error rates, even when allele frequencies change only by 20% across three replicates. Applying this method to real data from D. melanogaster populations adapting to a hot environment, we identify a selected haplotype-block of 6.93 Mb. We confirm the presence of this haplotype-block in evolved populations by experimental haplotyping, demonstrating the power and accuracy of our haplotype reconstruction from Pool-Seq data. We propose that the combination of allele frequency estimates with haplotype information will provide the key to understanding the dynamics of adaptive alleles.

Ancestral population reconstitution from isofemale lines as a tool for experimental evolution

Experimental evolution is a powerful tool to study adaptation under controlled conditions. Laboratory natural selection experiments mimic adaptation in the wild with better‐adapted genotypes having more offspring. Because the selected traits are frequently not known, adaptation is typically measured as fitness increase by comparing evolved populations against an unselected reference population maintained in a laboratory environment. With adaptation to the laboratory conditions and genetic drift, however, it is not clear to what extent such comparisons provide unbiased estimates of adaptation. Alternatively, ancestral variation could be preserved in isofemale lines that can be combined to reconstitute the ancestral population. Here, we assess the impact of selection on alleles segregating in newly established Drosophila isofemale lines. We reconstituted two populations from isofemale lines and compared them to two original ancestral populations (AP) founded from the same lines shortly after collection. No significant allele frequency changes could be detected between both AP and simulations showed that drift had a low impact compared to Pool‐Seq‐associated sampling effects. We conclude that laboratory selection on segregating variation in isofemale lines is too weak to have detectable effects, which validates ancestral population reconstitution from isofemale lines as an unbiased approach for measuring adaptation in evolved populations.

Genomic Response to Selection for Predatory Behavior in a Mammalian Model of Adaptive Radiation

If genetic architectures of various quantitative traits are similar, as studies on model organisms suggest, comparable selection pressures should produce similar molecular patterns for various traits. To test this prediction, we used a laboratory model of vertebrate adaptive radiation to investigate the genetic basis of the response to selection for predatory behavior and compare it with evolution of aerobic capacity reported in an earlier work. After 13 generations of selection, the proportion of bank voles (Myodes [=Clethrionomys] glareolus) showing predatory behavior was five times higher in selected lines than in controls. We analyzed the hippocampus and liver transcriptomes and found repeatable changes in allele frequencies and gene expression. Genes with the largest differences between predatory and control lines are associated with hunger, aggression, biological rhythms, and functioning of the nervous system. Evolution of predatory behavior could be meaningfully compared with evolution of high aerobic capacity, because the experiments and analyses were performed in the same methodological framework. The number of genes that changed expression was much smaller in predatory lines, and allele frequencies changed repeatably in predatory but not in aerobic lines. This suggests that more variants of smaller effects underlie variation in aerobic performance, whereas fewer variants of larger effects underlie variation in predatory behavior. Our results thus contradict the view that comparable selection pressures for different quantitative traits produce similar molecular patterns. Therefore, to gain knowledge about molecular-level response to selection for complex traits, we need to investigate not only multiple replicate populations but also multiple quantitative traits.

Maternal AP determinants in the Drosophila oocyte and embryo

An animal embryo cannot initiate its journey of forming a new life on its own. It must rely on maternally provided resources and inputs to kick-start its developmental process. In Drosophila, the initial polarities of the embryo along both the anterior-posterior (AP) and dorsal-ventral (DV) axes are also specified by maternal determinants. Over the past several decades, genetic and molecular studies have identified and characterized such determinants, as well as the zygotic genetic regulatory networks that control patterning in the early embryo. Extensive studies of oogenesis have also led to a detailed knowledge of the cellular and molecular interactions that control the formation of a mature egg. Despite these efforts, oogenesis and embryogenesis have been studied largely as separate problems, except for qualitative aspects with regard to maternal regulation of the asymmetric localization of maternal determinants. Can oogenesis and embryogenesis be viewed from a unified perspective at a quantitative level, and can that improve our understanding of how robust embryonic patterning is achieved? Here, we discuss the basic knowledge of the regulatory mechanisms controlling oogenesis and embryonic patterning along the AP axis. We explore properties of the maternal Bicoid gradient in relation to embryo size in search for a unified framework for robust AP patterning. WIREs Dev Biol 2016, 5:562-581. doi: 10.1002/wdev.235 For further resources related to this article, please visit the WIREs website.

Contrasting Plasticity in Ovariole Number Induced by A Dietary Effect of the Host Plants between Cactophilic Drosophila Species

Under the preference-performance hypothesis, natural selection will favor females that choose oviposition sites that optimize the fitness of their offspring. Such a preference-performance relationship may entail important consequences mainly on fitness-related traits. We used the well-characterized cactus-Drosophila system to investigate the reproductive capacity in the pair of sibling species D. buzzatii and D. koepferae reared in two alternative host plants. According to our hypothesis, ovariole number (as a proxy of reproductive capacity) depends on host plant selection. Our results indicate that the capacity of D. buzzatii showed to be mild, only increasing the number of ovarioles by as much as 10% when reared in its preferred host. In contrast, D. koepferae exhibited a similar reproductive capacity across host cacti, even though it showed a preference for its primary host cactus. Our study also revealed that D. buzzatii has a larger genetic variation for phenotypic plasticity than its sibling, although ovariole number did not show clear-cut differences between species. We will discuss the weak preference-performance pattern observed in these cactophilic species in the light of nutritional and toxicological differences found between the natural host plants.

Rapid genomic changes in Drosophila melanogaster adapting to desiccation stress in an experimental evolution system

BACKGROUND

Experimental evolution studies, coupled with whole genome resequencing and advances in bioinformatics, have become a powerful tool for exploring how populations respond to selection at the genome-wide level, complementary to genome-wide association studies (GWASs) and linkage mapping experiments as strategies to connect genotype and phenotype. In this experiment, we analyzed genomes of Drosophila melanogaster from lines evolving under long-term directional selection for increased desiccation resistance in comparison with control (no-selection) lines.

RESULTS

We demonstrate that adaptive responses to desiccation stress have exerted extensive footprints on the genomes, manifested through a high degree of fixation of alleles in surrounding neighborhoods of eroded heterozygosity. These patterns were highly convergent across replicates, consistent with signatures of 'soft' selective sweeps, where multiple alleles present as standing genetic variation become beneficial and sweep through the replicate populations at the same time. Albeit much less frequent, we also observed line-unique sweep regions with zero or near-zero heterozygosity, consistent with classic, or 'hard', sweeps, where novel rather than pre-existing adaptive mutations may have been driven to fixation. Genes responsible for cuticle and protein deubiquitination seemed to be central to these selective sweeps. High divergence within coding sequences between selected and control lines was also reflected by significant results of the McDonald-Kreitman and Ka/Ks tests, showing that as many as 347 genes may have been under positive selection.

CONCLUSIONS

Desiccation stress, a common challenge to many organisms inhabiting dry environments, proves to be a very potent selecting factor having a big impact on genome diversity.

Shared Genetic Signals of Hypoxia Adaptation in Drosophila and in High-Altitude Human Populations

The ability to withstand low oxygen (hypoxia tolerance) is a polygenic and mechanistically conserved trait that has important implications for both human health and evolution. However, little is known about the diversity of genetic mechanisms involved in hypoxia adaptation in evolving populations. We used experimental evolution and whole-genome sequencing in Drosophila melanogaster to investigate the role of natural variation in adaptation to hypoxia. Using a generalized linear mixed model we identified significant allele frequency differences between three independently evolved hypoxia-tolerant populations and normoxic control populations for approximately 3,800 single nucleotide polymorphisms. Around 50% of these variants are clustered in 66 distinct genomic regions. These regions contain genes that are differentially expressed between hypoxia-tolerant and normoxic populations and several of the differentially expressed genes are associated with metabolic processes. Additional genes associated with respiratory and open tracheal system development also show evidence of directional selection. RNAi-mediated knockdown of several candidate genes’ expression significantly enhanced survival in severe hypoxia. Using genomewide single nucleotide polymorphism data from four high-altitude human populations—Sherpas, Tibetans, Ethiopians, and Andeans, we found that several human orthologs of the genes under selection in flies are also likely under positive selection in all four high-altitude human populations. Thus, our results indicate that selection for hypoxia tolerance can act on standing genetic variation in similar genes and pathways present in organisms diverged by hundreds of millions of years.