Fitness effects but no temperature-mediated balancing selection at the polymorphic Adh gene of Drosophila melanogaster

The Precision and Power of Population Branch Statistics in Identifying the Genomic Signatures of Local Adaptation

Population branch statistics, which estimate the branch lengths of focal populations with respect to two outgroups, have been used as an alternative to FST-based genome-wide scans for identifying loci associated with local selective sweeps. In addition to the original population branch statistic (PBS), there are subsequently proposed branch rescalings: normalized population branch statistic (PBSn1), which adjusts focal branch length with respect to outgroup branch lengths at the same locus, and population branch excess (PBE), which also incorporates median branch lengths at other loci. PBSn1 and PBE have been proposed to be less sensitive to allele frequency divergence generated by background selection or geographically ubiquitous positive selection rather than local selective sweeps. However, the accuracy and statistical power of branch statistics have not been systematically assessed. To do so, we simulate genomes in representative large and small populations with varying proportions of sites evolving under genetic drift or background selection (approximated using variable Ne), local selective sweeps, and geographically parallel selective sweeps. We then assess the probability that local selective sweep loci are correctly identified as outliers by FST and by each of the branch statistics. We find that branch statistics consistently outperform FST at identifying local sweeps. When background selection and/or parallel sweeps are introduced, PBSn1 and especially PBE correctly identify local sweeps among their top outliers at a higher frequency than PBS. These results validate the greater specificity of rescaled branch statistics such as PBE to detect population-specific positive selection, supporting their use in genomic studies focused on local adaptation.

Rapid evolutionary change, constraints and the maintenance of polymorphism in natural populations of Drosophila melanogaster

Allele frequencies can shift rapidly within natural populations. Under certain conditions, repeated rapid allele frequency shifts can lead to the long-term maintenance of polymorphism. In recent years, studies of the model insect Drosophila melanogaster have suggested that this phenomenon is more common than previously believed and is often driven by some form of balancing selection, such as temporally fluctuating or sexually antagonistic selection. Here we discuss some of the general insights into rapid evolutionary change revealed by large-scale population genomic studies, as well as the functional and mechanistic causes of rapid adaptation uncovered by single-gene studies. As an example of the latter, we consider a regulatory polymorphism of the D. melanogaster fezzik gene. Polymorphism at this site has been maintained at intermediate frequency over an extended period of time. Regular observations from a single population over a period of 7 years revealed significant differences in the frequency of the derived allele and its variance across collections between the sexes. These patterns are highly unlikely to arise from genetic drift alone or from the action of sexually antagonistic or temporally fluctuating selection individually. Instead, the joint action of sexually antagonistic and temporally fluctuating selection can best explain the observed rapid and repeated allele frequency shifts. Temporal studies such as those reviewed here further our understanding of how rapid changes in selection can lead to the long-term maintenance of polymorphism as well as improve our knowledge of the forces driving and limiting adaptation in nature.

Hybridization alters the shape of the genotypic fitness landscape, increasing access to novel fitness peaks during adaptive radiation

Estimating the complex relationship between fitness and genotype or phenotype (i.e. the adaptive landscape) is one of the central goals of evolutionary biology. However, adaptive walks connecting genotypes to organismal fitness, speciation, and novel ecological niches are still poorly understood and processes for surmounting fitness valleys remain controversial. One outstanding system for addressing these connections is a recent adaptive radiation of ecologically and morphologically novel pupfishes (a generalist, molluscivore, and scale-eater) endemic to San Salvador Island, Bahamas. We leveraged whole-genome sequencing of 139 hybrids from two independent field fitness experiments to identify the genomic basis of fitness, estimate genotypic fitness networks, and measure the accessibility of adaptive walks on the fitness landscape. We identified 132 single nucleotide polymorphisms (SNPs) that were significantly associated with fitness in field enclosures. Six out of the 13 regions most strongly associated with fitness contained differentially expressed genes and fixed SNPs between trophic specialists; one gene (mettl21e) was also misexpressed in lab-reared hybrids, suggesting a potential intrinsic genetic incompatibility. We then constructed genotypic fitness networks from adaptive alleles and show that scale-eating specialists are the most isolated of the three species on these networks. Intriguingly, introgressed and de novo variants reduced fitness landscape ruggedness as compared to standing variation, increasing the accessibility of genotypic fitness paths from generalist to specialists. Our results suggest that adaptive introgression and de novo mutations alter the shape of the fitness landscape, providing key connections in adaptive walks circumventing fitness valleys and triggering the evolution of novelty during adaptive radiation.

Temperature-dependent genetics of thermotolerance between yeast species

Many traits of industrial and basic biological interest arose long ago, and manifest now as fixed differences between a focal species and its reproductively isolated relatives. In these systems, extant individuals can hold clues to the mechanisms by which phenotypes evolved in their ancestors. We harnessed yeast thermotolerance as a test case for such molecular-genetic inferences. In viability experiments, we showed that extant Saccharomyces cerevisiae survived at temperatures where cultures of its sister species S. paradoxus died out. Then, focusing on loci that contribute to this difference, we found that the genetic mechanisms of high-temperature growth changed with temperature. We also uncovered an enrichment of low-frequency variants at thermotolerance loci in S. cerevisiae population sequences, suggestive of a history of non-neutral selective forces acting at these genes. We interpret these results in light of models of the evolutionary mechanisms by which the thermotolerance trait arose in the S. cerevisiae lineage. Together, our results and interpretation underscore the power of genetic approaches to explore how an ancient trait came to be.

Ethanol resistance in Drosophila melanogaster has increased in parallel cold-adapted populations and shows a variable genetic architecture within and between populations

Understanding the genetic properties of adaptive trait evolution is a fundamental crux of biological inquiry that links molecular processes to biological diversity. Important uncertainties persist regarding the genetic predictability of adaptive trait change, the role of standing variation, and whether adaptation tends to result in the fixation of favored variants. Here, we use the recurrent evolution of enhanced ethanol resistance in Drosophila melanogaster during this species' worldwide expansion as a promising system to add to our understanding of the genetics of adaptation. We find that elevated ethanol resistance has evolved at least three times in different cooler regions of the species' modern range-not only at high latitude but also in two African high-altitude regions. Applying a bulk segregant mapping framework, we find that the genetic architecture of ethanol resistance evolution differs substantially not only between our three resistant populations, but also between two crosses involving the same European population. We then apply population genetic scans for local adaptation within our quantitative trait locus regions, and we find potential contributions of genes with annotated roles in spindle localization, membrane composition, sterol and alcohol metabolism, and other processes. We also apply simulation-based analyses that confirm the variable genetic basis of ethanol resistance and hint at a moderately polygenic architecture. However, these simulations indicate that larger-scale studies will be needed to more clearly quantify the genetic architecture of adaptive evolution and to firmly connect trait evolution to specific causative loci.

Genomic Responses to Climate Change: Making the Most of the Drosophila Model

It is pressing to understand how animal populations evolve in response to climate change. We argue that new sequencing technologies and the use of historical samples are opening unprecedented opportunities to investigate genome-wide responses to changing environments. However, there are important challenges in interpreting the emerging findings. First, it is essential to differentiate genetic adaptation from phenotypic plasticity. Second, it is extremely difficult to map genotype, phenotype, and fitness. Third, neutral demographic processes and natural selection affect genetic variation in similar ways. We argue that Drosophila melanogaster, a classical model organism with decades of climate adaptation research, is uniquely suited to overcome most of these challenges. In the near future, long-term time series genome-wide datasets of D. melanogaster natural populations will provide exciting opportunities to study adaptation to recent climate change and will lay the groundwork for related research in non-model systems.

A Bayesian Mutation-Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes

In recent years, codon substitution models based on the mutation–selection principle have been extended for the purpose of detecting signatures of adaptive evolution in protein-coding genes. However, the approaches used to date have either focused on detecting global signals of adaptive regimes—across the entire gene—or on contexts where experimentally derived, site-specific amino acid fitness profiles are available. Here, we present a Bayesian site-heterogeneous mutation–selection framework for site-specific detection of adaptive substitution regimes given a protein-coding DNA alignment. We offer implementations, briefly present simulation results, and apply the approach on a few real data sets. Our analyses suggest that the new approach shows greater sensitivity than traditional methods. However, more study is required to assess the impact of potential model violations on the method, and gain a greater empirical sense its behavior on a broader range of real data sets. We propose an outline of such a research program.

Natural selection on sleep duration in Drosophila melanogaster

Sleep is ubiquitous across animal species, but why it persists is not well understood. Here we observe natural selection act on Drosophila sleep by relaxing bi-directional artificial selection for extreme sleep duration for 62 generations. When artificial selection was suspended, sleep increased in populations previously selected for short sleep. Likewise, sleep decreased in populations previously selected for long sleep when artificial selection was relaxed. We measured the corresponding changes in the allele frequencies of genomic variants responding to artificial selection. The allele frequencies of these variants reversed course in response to relaxed selection, and for short sleepers, the changes exceeded allele frequency changes that would be expected under random genetic drift. These observations suggest that the variants are causal polymorphisms for sleep duration responding to natural selection pressure. These polymorphisms may therefore pinpoint the most important regions of the genome maintaining variation in sleep duration.

Different genetic basis for alcohol dehydrogenase activity and plasticity in a novel alcohol environment for Drosophila melanogaster

Phenotypic plasticity is known to enhance population persistence, facilitate adaptive evolution and initiate novel phenotypes in novel environments. How plasticity can contribute or hinder adaptation to different environments hinges on its genetic architecture. Even though plasticity in many traits is genetically controlled, whether and how plasticity's genetic architecture might change in novel environments is still unclear. Because much of gene expression can be environmentally influenced, each environment may trigger different sets of genes that influence a trait. Using a quantitative trait loci (QTL) approach, we investigated the genetic basis of plasticity in a classic functional trait, alcohol dehydrogenase (ADH) activity in D. melanogaster, across both historical and novel alcohol environments. Previous research in D. melanogaster has also demonstrated that ADH activity is plastic in response to alcohol concentration in substrates used by both adult flies and larvae. We found that across all environments tested, ADH activity was largely influenced by a single QTL encompassing the Adh-coding gene and its known regulatory locus, delta-1. After controlling for the allelic variation of the Adh and delta-1 loci, we found additional but different minor QTLs in the 0 and 14% alcohol environments. In contrast, we discovered no major QTL for plasticity itself, including the Adh locus, regardless of the environmental gradients. This suggests that plasticity in ADH activity is likely influenced by many loci with small effects, and that the Adh locus is not environmentally sensitive to dietary alcohol.