Epigenetics and the environment: emerging patterns and implications

Exome-wide comparative analyses revealed differentiating genomic regions for performance traits in Indian native buffaloes

In India, 20 breeds of buffalo have been identified and registered, yet limited studies have been conducted to explore the performance potential of these breeds, especially in the Indian native breeds. This study is a maiden attempt to delineate the important variants and unique genes through exome sequencing for milk yield, milk composition, fertility, and adaptation traits in Indian local breeds of buffalo. In the present study, whole exome sequencing was performed on Chhattisgarhi (n = 3), Chilika (n = 4), Gojri (n = 3), and Murrah (n = 4) buffalo breeds and after stringent quality control, 4333, 6829, 4130, and 4854 InDels were revealed, respectively. Exome-wide FST along 100-kb sliding windows detected 27, 98, 38, and 35 outlier windows in Chhattisgarhi, Chilika, Gojri, and Murrah, respectively. The comparative exome analysis of InDels and subsequent gene ontology revealed unique breed specific genes for milk yield (CAMSAP3), milk composition (CLCN1, NUDT3), fertility (PTGER3) and adaptation (KCNA3, TH) traits. Study provides insight into mechanism of how these breeds have evolved under natural selection, the impact of these events on their respective genomes, and their importance in maintaining purity of these breeds for the traits under study. Additionally, this result will underwrite to the genetic acquaintance of these breeds for breeding application, and in understanding of evolution of these Indian local breeds.

A new perspective on microRNA-guided gene regulation specificity, and its potential generalization to transcription factors and RNA-binding proteins

Our conception of gene regulation specificity has undergone profound changes over the last 20 years. Previously, regulators were considered to control few genes, recognized with exquisite specificity by a 'lock and key' mechanism. However, recently genome-wide exploration of regulator binding site occupancy (whether on DNA or RNA targets) revealed extensive lists of molecular targets for every studied regulator. Such poor biochemical specificity suggested that each regulator controls many genes, collectively contributing to biological phenotypes. Here, I propose a third model, whereby regulators' biological specificity is only partially due to 'lock and key' biochemistry. Rather, regulators affect many genes at the microscopic scale, but biological consequences for most interactions are attenuated at the mesoscopic scale: only a few regulatory events propagate from microscopic to macroscopic scale; others are made inconsequential by homeostatic mechanisms. This model is well supported by the microRNA literature, and data suggest that it extends to other regulators. It reconciles contradicting observations from biochemistry and comparative genomics on one hand and in vivo genetics on the other hand, but this conceptual unification is obscured by common misconceptions and counter-intuitive modes of graphical display. Profound understanding of gene regulation requires conceptual clarification, and better suited statistical analyses and graphical representation.

Directionality theory and mortality patterns across the primate lineage

Empirical studies of aging in primates show that local selective forces rather than phylogenetic history determine the exceptional nature of human longevity (Bronikowski et al., Science 331:1325-1328, 2011). This article proposes an evolutionary rationale for this pattern of primate mortality by invoking the parameter, Life-Table Entropy, a measure of the uncertainty in the life span of a randomly chosen newborn. Life-table entropy is positively correlated with maximal life span, that is, the mean life span of a species living under favourable conditions.The logic which underlies the exceptional nature of human longevity derives from the terrestrial life-history of humans - a singularity within the primate lineage; and the concomitant ecological constraints-the hunter-gatherer, agricultural, and industrial modes of subsistence, that have defined human evolutionary history. The effect of these ecological constraints on the evolution of life span is encoded in the Entropic Principle of Longevity: life-table entropy increases in equilibrium species, populations evolving in environments with stable, renewable resources; and decreases in opportunistic species, populations subject to fluctuating resource endowments.The Entropic Principle of Longevity is a derivative of Directionality Theory, an analytic study of the evolutionary process of variation and selection based on Evolutionary Entropy, a statistical measure of the uncertainty in the age of the mother of a randomly chosen newborn. Evolutionary entropy is the organizing concept of The Entropic Principle of Evolution: Evolutionary Entropy increases in equilibrium species and decreases in opportunistic species.

Impacts of pleiotropy and migration on repeated genetic adaptation

Observations of genetically repeated evolution (repeatability) in complex organisms are incongruent with the Fisher-Orr model, which implies that repeated use of the same gene should be rare when mutations are pleiotropic (i.e. affect multiple traits). When spatially divergent selection occurs in the presence of migration, mutations of large effect are more strongly favored, and hence, repeatability is more likely, but it is unclear whether this observation is limited by pleiotropy. Here, we explore this question using individual-based simulations of a two-patch model incorporating multiple quantitative traits governed by mutations with pleiotropic effects. We explore the relationship between fitness trade-offs and repeatability by varying the alignment between mutation effect and spatial variation in trait optima. While repeatability decreases with increasing trait dimensionality, trade-offs in mutation effects on traits do not strongly limit the contribution of a locus of large effect to repeated adaptation, particularly under increased migration. These results suggest that repeatability will be more pronounced for local rather than global adaptation. Whereas pleiotropy limits repeatability in a single-population model, when there is local adaptation with gene flow, repeatability can occur if some loci are able to produce alleles of large effect, even when there are pleiotropic trade-offs.

The Ecology of Hybrid Incompatibilities

Ecologically mediated selection against hybrids, caused by hybrid phenotypes fitting poorly into available niches, is typically viewed as distinct from selection caused by epistatic Dobzhansky-Muller hybrid incompatibilities. Here, we show how selection against transgressive phenotypes in hybrids manifests as incompatibility. After outlining our logic, we summarize current approaches for studying ecology-based selection on hybrids. We then quantitatively review QTL-mapping studies and find traits differing between parent taxa are typically polygenic. Next, we describe how verbal models of selection on hybrids translate to phenotypic and genetic fitness landscapes, highlighting emerging approaches for detecting polygenic incompatibilities. Finally, in a synthesis of published data, we report that trait transgression-and thus possibly extrinsic hybrid incompatibility in hybrids-escalates with the phenotypic divergence between parents. We discuss conceptual implications and conclude that studying the ecological basis of hybrid incompatibility will facilitate new discoveries about mechanisms of speciation.

Pleiotropy, epistasis and the genetic architecture of quantitative traits

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

Confronting the Legacy of Eugenics and Ableism: Towards Anti-Ableist Bioscience Education

Society and education are inherently ableist. Disabled people are routinely excluded from education, or have poorer outcomes within educational systems. Improving educational experiences and outcomes for people of color has required educators to design antiracist curricula that explicitly address racial inequality. Here, we explore parallel antiableist approaches to bioscience education in an essay coauthored by a disabled bioscience student and able-bodied faculty member in bioscience. Our work is underpinned by Critical Disability Theory and draws on disability and pedagogical scholarship as well as our own experiences. The biosciences has a unique need to confront its history in the discredited pseudoscience of eugenics, which has led to discrimination and human rights abuses against disabled people. We provide a brief history of the relationship between biological sciences research and eugenics and explore how this legacy impacts bioscience education today. We then present a recommended structure for antiableist biology education. Our approach goes beyond providing disability access, to a model that educates all students about disability issues and empowers them to challenge ableist narratives and practices.

Assessing the opportunity for selection to impact morphological traits in crosses between two Solanum species

Within biology, there have been long-standing goals to understand how traits impact fitness, determine the degree of adaptation, and predict responses to selection. One key step in answering these questions is to study the mode of gene action or genetic architecture of traits. The genetic architecture underlying a trait will ultimately determine whether selection can lead to a change in the phenotype. Theoretical and empirical research have shown that additive architectures are most responsive to selection. The genus Solanum offers a unique system to quantify the genetic architecture of traits. Crosses between Solanum pennellii and S. lycopersicum, which have evolved unique adaptive traits for very different environments, offer an opportunity to investigate the genetic architecture of a variety of morphological traits that often are not variable within species. We generated cohorts between strains of these two Solanum species and collected phenotypic data for eight morphological traits. The genetic architectures underlying these traits were estimated using an information-theoretic approach to line cross analysis. By estimating the genetic architectures of these traits, we were able to show a key role for maternal and epistatic effects and infer the accessibility of these traits to selection.

No evidence that ACE2 or TMPRSS2 drive population disparity in COVID risks

Early in the SARS-CoV2 pandemic, in this journal, Hou et al. (BMC Med 18:216, 2020) interpreted public genotype data, run through functional prediction tools, as suggesting that members of particular human populations carry potentially COVID-risk-increasing variants in genes ACE2 and TMPRSS2 far more often than do members of other populations. Beyond resting on predictions rather than clinical outcomes, and focusing on variants too rare to typify population members even jointly, their claim mistook a well known artifact (that large samples reveal more of a population's variants than do small samples) as if showing real and congruent population differences for the two genes, rather than lopsided population sampling in their shared source data. We explain that artifact, and contrast it with empirical findings, now ample, that other loci shape personal COVID risks far more significantly than do ACE2 and TMPRSS2-and that variation in ACE2 and TMPRSS2 per se unlikely exacerbates any net population disparity in the effects of such more risk-informative loci.

The genetic architecture of repeated local adaptation to climate in distantly related plants

Closely related species often use the same genes to adapt to similar environments. However, we know little about why such genes possess increased adaptive potential and whether this is conserved across deeper evolutionary lineages. Adaptation to climate presents a natural laboratory to test these ideas, as even distantly related species must contend with similar stresses. Here, we re-analyse genomic data from thousands of individuals from 25 plant species as diverged as lodgepole pine and Arabidopsis (~300 Myr). We test for genetic repeatability based on within-species associations between allele frequencies in genes and variation in 21 climate variables. Our results demonstrate significant statistical evidence for genetic repeatability across deep time that is not expected under randomness, identifying a suite of 108 gene families (orthogroups) and gene functions that repeatedly drive local adaptation to climate. This set includes many orthogroups with well-known functions in abiotic stress response. Using gene co-expression networks to quantify pleiotropy, we find that orthogroups with stronger evidence for repeatability exhibit greater network centrality and broader expression across tissues (higher pleiotropy), contrary to the 'cost of complexity' theory. These gene families may be important in helping wild and crop species cope with future climate change, representing important candidates for future study.

Influenza A virus within-host evolution and positive selection in a densely sampled household cohort over three seasons

While influenza A virus (IAV) antigenic drift has been documented globally, in experimental animal infections, and in immunocompromised hosts, positive selection has generally not been detected in acute infections. This is likely due to challenges in distinguishing selected rare mutations from sequencing error, a reliance on cross-sectional sampling, and/or the lack of formal tests of selection for individual sites. Here, we sequenced IAV populations from 346 serial, daily nasal swabs from 143 individuals collected over three influenza seasons in a household cohort. Viruses were sequenced in duplicate, and intrahost single nucleotide variants (iSNV) were identified at a 0.5% frequency threshold. Within-host populations were subject to purifying selection with >75% mutations present at <2% frequency. Children (0-5 years) had marginally higher within-host evolutionary rates than adolescents (6-18 years) and adults (>18 years, 4.4×10-6 vs. 9.42×10-7 and 3.45×10-6, p <0.001). Forty-five iSNV had evidence of parallel evolution, but were not overrepresented in HA and NA. Several increased from minority to consensus level, with strong linkage among iSNV across segments. A Wright Fisher Approximate Bayesian Computational model identified positive selection at 23/256 loci (9%) in A(H3N2) specimens and 19/176 loci (11%) in A(H1N1)pdm09 specimens, and these were infrequently found in circulation. Overall, we found that within-host IAV populations were subject to purifying selection and genetic drift, with only subtle differences across seasons, subtypes, and age strata. Positive selection was rare and inconsistently detected.

Genetic background affects the strength of crossover interference in house mice

Meiotic recombination is required for faithful chromosome segregation in most sexually reproducing organisms and shapes the distribution of genetic variation in populations. Both the overall rate and the spatial distribution of crossovers vary within and between species. Adjacent crossovers on the same chromosome tend to be spaced more evenly than expected at random, a phenomenon known as crossover interference. Although interference has been observed in many taxa, the factors that influence the strength of interference are not well understood. We used house mice (Mus musculus), a well-established model system for understanding recombination, to study the effects of genetics and age on recombination rate and interference in the male germline. We analyzed crossover positions in 503 progeny from reciprocal F1 hybrids between inbred strains representing the three major subspecies of house mice. Consistent with previous studies, autosomal alleles from M. m. musculus tend to increase recombination rate, while inheriting a M. m. musculus X chromosome decreases recombination rate. Old males transmit an average of 0.6 more crossovers per meiosis (5.0%) than young males, though the effect varies across genetic backgrounds. We show that the strength of crossover interference depends on genotype, providing a rare demonstration that interference evolves over short timescales. Differences between reciprocal F1s suggest that X-linked factors modulate the strength of interference. Our findings motivate additional comparisons of interference among recently diverged species and further examination of the role of paternal age in determining the number and positioning of crossovers.

Competing adaptations maintain nonadaptive variation in a wild cricket population

How emerging adaptive variants interact is an important factor in the evolution of wild populations, but the opportunity to empirically study this interaction is rare. We recently documented the emergence of an adaptive phenotype "curly-wing" in Hawaiian populations of field crickets (Teleogryllus oceanicus). Curly-wing inhibits males' ability to sing, protecting them from eavesdropping parasitoid flies (Ormia ochracea). Surprisingly, curly-wing co-occurs with similarly protective silent "flatwing" phenotypes in multiple populations, in which neither phenotype has spread to fixation. These two phenotypes are frequently coexpressed, but since either sufficiently reduces song amplitude to evade the fly, their coexpression confers no additional fitness benefit. Numerous "off-target" phenotypic changes are known to accompany flatwing, and we find that curly-wing, too, negatively impacts male courtship ability and affects mass and survival of females under lab conditions. We show through crosses and genomic and mRNA sequencing that curly-wing expression is associated with variation on a single autosome. In parallel analyses of flatwing, our results reinforce previous findings of X-linked single-locus inheritance. By combining insights into the genetic architecture of these alternative phenotypes with simulations and field observations, we show that the co-occurrence of these two adaptations impedes either from fixing, despite extreme fitness benefits, due to fitness epistasis. This co-occurrence of similar adaptive forms in the same populations might be more common than is generally considered and could be an important force inhibiting adaptive evolution in wild populations of sexually reproducing organisms.

Heterosis effect for larval performance of fall armyworm interstrain hybrids

Spodoptera frugiperda, also known as fall armyworm (FAW), is an invasive crop pest that can feed on a variety of host plants, posing a serious threat to food security. There are two sympatric strains of FAW that are morphologically identical but described with different food preferences: the "rice strain" (SfR) and the "corn strain" (SfC). A few genetic loci exist to identify these two strains. Mitochondrial and Z-chromosome-linked haplotypes are the most used, but the biggest part of the genome displays little polymorphism between strains that could explain their adaptation to different plants. We have previously observed consistent transcription differences between the strains in both laboratory and natural populations. Therefore, we wonder if there are effects from host-strain-associated loci, maternally or paternally inherited, on FAW performance that could explain the divergence between the two FAW strains. To test this hypothesis, we first produced two F1 hybrid generations (SfR ♀ × SfC ♂, SfC ♀ × SfR ♂). These reciprocal hybrids should be heterozygous for all chromosomes except for the maternally inherited mitochondrial and sexual W chromosomes. To evaluate whether plant preference is determined by these genetic loci, we cultivated the two hybrids and the two parental strains in triplicate on an artificial diet and recorded several phenotypic traits such as weight over time, survival rate, emerging rate, developmental time, and sex ratio. Then, the same performance experiment was carried out on corn plants. Surprisingly, on the artificial diet, the two hybrid genotypes were both more performant than the two parental strains in terms of survival rate, pupal emerging rate, and developmental time, whereas they were intermediate to the inbred parental strains in pupal weight. On the corn plant diet, both hybrid genotypes outperformed the two parental strains in larval weight. Although these asymmetrical results revealed that mitochondrial or sex-linked haplotypes alone cannot explain the performance differences, they suggested a heterosis effect in FAW. A reduction of the female number for the CR genotype and the decreased F1 offspring reproduction in both hybrids suggested the possibility of Haldane's rule, which might be explained by the dominance model.

Singular effect of linkage on long-term genetic gain in Fisher's infinitesimal model

During the founding of the field of quantitative genetics, Fisher formulated in 1918 his "infinitesimal model" that provided a novel mathematical framework to describe the Mendelian transmission of quantitative traits. If the infinitely many genes in that model are assumed to segregate independently during reproduction, corresponding to having no linkage, directional selection asymptotically leads to a constant genetic gain at each generation. In reality, genes are subject to strong linkage because they lie on chromosomes and thus segregate in a correlated way. Various approximations have been used in the past to study that more realistic case of the infinitesimal model with the expectation that the asymptotic gain per generation is modestly decreased. To treat this system even in the strong linkage limit, we take the genes to lie on continuous chromosomes. Surprisingly, the consequences of genetic linkage are in fact rather singular, changing the nature of the long-term gain per generation: the asymptotic gain vanishes rather than being simply decreased. Nevertheless, the per-generation gain tends to zero sufficiently slowly for the total gain, accumulated over generations, to be unbounded.

Establishing large mammal population trends from heterogeneous count data

Monitoring population trends is pivotal to effective wildlife conservation and management. However, wildlife managers often face many challenges when analyzing time series of census data due to heterogeneities in sampling methodology, strategy, or frequency. We present a three-step method for modeling trends from time series of count data obtained through multiple census methods (aerial or ground census and expert estimates). First, we design a heuristic for constructing credible intervals for all types of animal counts including those which come with no precision measure. Then, we define conversion factors for rendering aerial and ground counts comparable and provide values for broad classes of animals from an extant series of parallel aerial and ground censuses. Lastly, we construct a Bayesian model that takes the reconciled counts as input and estimates the relative growth rates between successive dates while accounting for their precisions. Importantly, we bound the rate of increase to account for the demographic potential of a species. We propose a flow chart for constructing credible intervals for various types of animal counts. We provide estimates of conversion factors for 5 broad classes of species. We describe the Bayesian model for calculating trends, annual rates of population increase, and the associated credible intervals. We develop a bespoke R CRAN package, popbayes, for implementing all the calculations that take the raw counts as input. It produces consistent and reliable estimates of population trends and annual rates of increase. Several examples from real populations of large African mammals illustrate the different features of our method. The approach is well-suited for analyzing population trends for heterogeneous time series and allows a principled use of all the available historical census data. The method is general and flexible and applicable to various other animal species besides African large mammals. It can readily be adapted to test predictions of various hypotheses about drivers of rates of population increase.

Meta-analytical evidence for frequency-dependent selection across the tree of life

Explaining the maintenance of genetic variation in fitness-related traits within populations is a fundamental challenge in ecology and evolutionary biology. Frequency-dependent selection (FDS) is one mechanism that can maintain such variation, especially when selection favours rare variants (negative FDS). However, our general knowledge about the occurrence of FDS, its strength and direction remain fragmented, limiting general inferences about this important evolutionary process. We systematically reviewed the published literature on FDS and assembled a database of 747 effect sizes from 101 studies to analyse the occurrence, strength, and direction of FDS, and the factors that could explain heterogeneity in FDS. Using a meta-analysis, we found that overall, FDS is more commonly negative, although not significantly when accounting for phylogeny. An analysis of absolute values of effect sizes, however, revealed the widespread occurrence of modest FDS. However, negative FDS was only significant in laboratory experiments and non-significant in mesocosms and field-based studies. Moreover, negative FDS was stronger in studies measuring fecundity and involving resource competition over studies using other fitness components or focused on other ecological interactions. Our study unveils key general patterns of FDS and points in future promising research directions that can help us understand a long-standing fundamental problem in evolutionary biology and its consequences for demography and ecological dynamics.

Why are triploid quaking aspen (Populus tremuloides) common?

PREMISE

Quaking aspen is a clonal tree species that has mixed ploidy, often with high relative abundance of both diploids and triploids but no haploids or tetraploids. Triploids typically have low fertility, leaving their occurrence apparently unlikely from an evolutionary perspective, unless they provide a "triploid bridge" to generating higher-fitness tetraploids-which are not observed in this species. This study focused on how triploidy can be maintained in quaking aspen.

METHODS

A computational model was used to simulate gamete production, sexual reproduction, asexual reproduction, parent survival, and offspring survival in a population. All parameters were assumed to be cytotype-dependent and environment-independent. Sampling methods were used to identify parameter combinations consistent with observed cytotype frequencies.

RESULTS

Many processes and parameter values were sufficient to yield a moderate frequency of triploids, and very few were necessary. The most plausible route involved higher triploid survival at the parent or offspring stage and limited unreduced gamete production by either diploid or triploid parents. Triploid fertility was helpful but not necessary.

CONCLUSIONS

The coexistence of diploids and triploids in quaking aspen is statistically likely and promoted by the existence of commonly observed, long-lived triploid clones. However, other mechanisms not captured by the model related to environmental variation could also occur. Further empirical data or more complex but difficult-to-parameterize models are needed to gain further insight.

The neurodevelopmental genes alan shepard and Neuroglian contribute to female mate preference in African Drosophila melanogaster

Mate choice is a key trait that determines fitness for most sexually reproducing organisms, with females often being the choosy sex. Female preference often results in strong selection on male traits that can drive rapid divergence of traits and preferences between lineages, leading to reproductive isolation. Despite this fundamental property of female mate choice, very few loci have been identified that contribute to mate choice and reproductive isolation. We used a combination of population genetics, quantitative complementation tests, and behavioural assays to demonstrate that alan shepard and Neuroglian contribute to female mate choice, and could contribute to partial reproductive isolation between populations of Drosophila melanogaster. Our study is among the first to identify genes that contribute to female mate preference in this historically important system, where female preference is an active premating barrier to reproduction. The identification of loci that are primarily known for their roles in neurodevelopment provides intriguing questions of how female mate preference evolves in populations via changes in sensory system and higher learning brain centres.

Is biased mutation sufficient to save runaway sexual selection?

In the 1980s, groundbreaking theoretical studies showed that ornaments displayed during courtship can coevolve with preferences for such ornaments, leading to extreme exaggeration of both traits. Later models cast doubt on such "runaway" sexual selection, showing that even a small cost of preferences can prevent exaggerated ornaments from persisting long-term. It was subsequently shown that if mutations acting on the ornament are biased-tending to produce smaller rather than larger ornaments-then exaggeration can persist even in the presence of preference costs, seemingly vindicating the original models. Here, we unpack an implicit assumption of these "biased mutation" models: Mutations are assumed to lead, on average, to both smaller and less costly ornaments. Biased mutation consequently generates both a fitness cost (due to reduced mating success) and a fitness benefit (due to increased survival). We lift this assumption by separating an individual's investment in an ornament from their efficiency in converting such investment into ornament size. We assume that biased mutation acts only on efficiency but not on investment, and discuss the plausibility of this alternative assumption. Our model predicts that exaggerated ornaments and preferences can persist stably once they arise, but that strong initial preferences are needed to kick-start the runaway process. Consequently, biased mutation alone may not always be sufficient to save runaway sexual selection.

A suite of selective pressures supports the maintenance of alleles of a Drosophila immune peptide

The innate immune system provides hosts with a crucial first line of defense against pathogens. While immune genes are often among the fastest evolving genes in the genome, in Drosophila , antimicrobial peptides (AMPs) are notable exceptions. Instead, AMPs may be under balancing selection, such that over evolutionary timescales multiple alleles are maintained in populations. In this study, we focus on the Drosophila antimicrobial peptide Diptericin A, which has a segregating amino acid polymorphism associated with differential survival after infection with the Gram-negative bacteria Providencia rettgeri . Diptericin A also helps control opportunistic gut infections by common Drosophila gut microbes, especially those of Lactobacillus plantarum . In addition to genotypic effects on gut immunity, we also see strong sex-specific effects that are most prominent in flies without functional diptericin A . To further characterize differences in microbiomes between different diptericin genotypes, we used 16S metagenomics to look at the microbiome composition. We used both lab reared and wild caught flies for our sequencing and looked at overall composition as well as the differential abundance of individual bacterial families. Overall, we find flies that are homozygous for one allele of diptericin A are better equipped to survive a systemic infection from P. rettgeri , but in general have a shorter lifespans after being fed common gut commensals. Our results suggest a possible mechanism for the maintenance of genetic variation of diptericin A through the complex interactions of sex, systemic immunity, and the maintenance of the gut microbiome.

Understanding evolutionary rescue and parallelism in response to environmental stress

Evolutionary rescue, the process by which populations facing environmental stress avoid extinction through genetic adaptation, is a critical area of study in evolutionary biology. The order in which mutations arise and get established will be relevant to the population's rescue. This study investigates the degree of parallel evolution at the genotypic level between independent populations facing environmental stress and subject to different demographic regimes. Under density regulation, 2 regimes exist: In the first, the population can restore positive growth rates by adjusting its population size or through adaptive mutations, whereas in the second regime, the population is doomed to extinction unless a rescue mutation occurs. Analytical approximations for the likelihood of evolutionary rescue are obtained and contrasted with simulation results. We show that the initial level of maladaptation and the demographic regime significantly affect the level of parallelism. There is an evident transition between these 2 regimes. Whereas in the first regime, parallelism decreases with the level of maladaptation, it displays the opposite behavior in the rescue/extinction regime. These findings have important implications for understanding population persistence and the degree of parallelism in evolutionary responses as they integrate demographic effects and evolutionary processes.

The role of epistasis in evolutionary rescue

The process by which adaptive evolution preserves a population threatened with extinction due to environmental changes is known as evolutionary rescue. Several factors determine the fate of those populations, including demography and genetic factors, such as standing genetic variation, gene flow, availability of de novo mutations, and so on. Despite the extensive debate about evolutionary rescue in the current literature, a study about the role of epistasis and the topography of the fitness landscape on the fate of dwindling populations is missing. In the current work, we aim to fill this gap and study the influence of epistasis on the probability of extinction of populations. We present simulation results, and analytical approximations are derived. Counterintuitively, we show that the likelihood of extinction is smaller when the degree of epistasis is higher. The reason underneath is twofold: first, higher epistasis can promote mutations of more significant phenotypic effects, but also, the incongruence between the maps genotype-phenotype and phenotype-fitness turns the fitness landscape at low epistasis more rugged, thus curbing some of its advantages.

Effective population size in field pea

BACKGROUND

Effective population size (Ne) is a pivotal parameter in population genetics as it can provide information on the rate of inbreeding and the contemporary status of genetic diversity in breeding populations. The population with smaller Ne can lead to faster inbreeding, with little potential for genetic gain making selections ineffective. The importance of Ne has become increasingly recognized in plant breeding, which can help breeders monitor and enhance the genetic variability or redesign their selection protocols. Here, we present the first Ne estimates based on linkage disequilibrium (LD) in the pea genome.

RESULTS

We calculated and compared Ne using SNP markers from North Dakota State University (NDSU) modern breeding lines and United States Department of Agriculture (USDA) diversity panel. The extent of LD was highly variable not only between populations but also among different regions and chromosomes of the genome. Overall, NDSU had a higher and longer-range LD than the USDA that could extend up to 500 Kb, with a genome-wide average r2 of 0.57 (vs 0.34), likely due to its lower recombination rates and the selection background. The estimated Ne for the USDA was nearly three-fold higher (Ne = 174) than NDSU (Ne = 64), which can be confounded by a high degree of population structure due to the selfing nature of pea.

CONCLUSIONS

Our results provided insights into the genetic diversity of the germplasm studied, which can guide plant breeders to actively monitor Ne in successive cycles of breeding to sustain viability of the breeding efforts in the long term.

Synthesis of sexual selection: a systematic map of meta-analyses with bibliometric analysis

Sexual selection has been a popular subject within evolutionary biology because of its central role in explaining odd and counterintuitive traits observed in nature. Consequently, the literature associated with this field of study became vast. Meta-analytical studies attempting to draw inferences from this literature have now accumulated, varying in scope and quality, thus calling for a synthesis of these syntheses. We conducted a systematic literature search to create a systematic map with a report appraisal of meta-analyses on topics associated with sexual selection, aiming to identify the conceptual and methodological gaps in this secondary literature. We also conducted bibliometric analyses to explore whether these gaps are associated with the gender and origin of the authors of these meta-analyses. We included 152 meta-analytical studies in our systematic map. We found that most meta-analyses focused on males and on certain animal groups (e.g. birds), indicating severe sex and taxonomic biases. The topics in these studies varied greatly, from proximate (e.g. relationship of ornaments with other traits) to ultimate questions (e.g. formal estimates of sexual selection strength), although the former were more common. We also observed several common methodological issues in these studies, such as lack of detailed information regarding searches, screening, and analyses, which ultimately impairs the reliability of many of these meta-analyses. In addition, most of the meta-analyses' authors were men affiliated to institutions from developed countries, pointing to both gender and geographical authorship biases. Most importantly, we found that certain authorship aspects were associated with conceptual and methodological issues in meta-analytical studies. Many of our findings might simply reflect patterns in the current state of the primary literature and academia, suggesting that our study can serve as an indicator of issues within the field of sexual selection at large. Based on our findings, we provide both conceptual and analytical recommendations to improve future studies in the field of sexual selection.

Allele frequency dynamics under sex-biased demography and sex-specific inheritance in a pedigreed jay population

Sex-biased demography, including sex-biased survival or migration, can alter allele frequency changes across the genome. In particular, we can expect different patterns of genetic variation on autosomes and sex chromosomes due to sex-specific differences in life histories, as well as differences in effective population size, transmission modes, and the strength and mode of selection. Here, we demonstrate the role that sex differences in life history played in shaping short-term evolutionary dynamics across the genome. We used a 25-year pedigree and genomic dataset from a long-studied population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of sex-biased demography and inheritance in shaping genome-wide allele frequency trajectories. We used gene dropping simulations to estimate individual genetic contributions to future generations and to model drift and immigration on the known pedigree. We quantified differential expected genetic contributions of males and females over time, showing the impact of sex-biased dispersal in a monogamous system. Due to female-biased dispersal, more autosomal variation is introduced by female immigrants. However, due to male-biased transmission, more Z variation is introduced by male immigrants. Finally, we partitioned the proportion of variance in allele frequency change through time due to male and female contributions. Overall, most allele frequency change is due to variance in survival and births. Males and females make similar contributions to autosomal allele frequency change, but males make higher contributions to allele frequency change on the Z chromosome. Our work shows the importance of understanding sex-specific demographic processes in characterizing genome-wide allele frequency change in wild populations.

Gene Protein Sequence Evolution Can Predict the Rapid Divergence of Ovariole Numbers in the Drosophila melanogaster Subgroup

Ovaries play key roles in fitness and evolution: they are essential female reproductive structures that develop and house the eggs in sexually reproducing animals. In Drosophila, the mature ovary contains multiple tubular egg-producing structures known as ovarioles. Ovarioles arise from somatic cellular structures in the larval ovary called terminal filaments (TFs), formed by TF cells and subsequently enclosed by sheath (SH) cells. As in many other insects, ovariole number per female varies extensively in Drosophila. At present, however, there is a striking gap of information on genetic mechanisms and evolutionary forces that shape the well-documented rapid interspecies divergence of ovariole numbers. To address this gap, here we studied genes associated with Drosophila melanogaster ovariole number or functions based on recent experimental and transcriptional datasets from larval ovaries, including TFs and SH cells, and assessed their rates and patterns of molecular evolution in five closely related species of the melanogaster subgroup that exhibit species-specific differences in ovariole numbers. From comprehensive analyses of protein sequence evolution (dN/dS), branch-site positive selection, expression specificity (tau), and phylogenetic regressions (phylogenetic generalized least squares), we report evidence of 42 genes that showed signs of playing roles in the genetic basis of interspecies evolutionary change of Drosophila ovariole number. These included the signaling genes upd2 and Ilp5 and extracellular matrix genes vkg and Col4a1, whose dN/dS predicted ovariole numbers among species. Together, we propose a model whereby a set of ovariole-involved gene proteins have an enhanced evolvability, including adaptive evolution, facilitating rapid shifts in ovariole number among Drosophila species.

Rewinding the Ratchet: Rare Recombination Locally Rescues Neo-W Degeneration and Generates Plateaus of Sex-Chromosome Divergence

Natural selection is less efficient in the absence of recombination. As a result, nonrecombining sequences, such as sex chromosomes, tend to degenerate over time. Although the outcomes of recombination arrest are typically observed after many millions of generations, recent neo-sex chromosomes can give insight into the early stages of this process. Here, we investigate the evolution of neo-sex chromosomes in the Spanish marbled white butterfly, Melanargia ines, where a Z-autosome fusion has turned the homologous autosome into a nonrecombining neo-W chromosome. We show that these neo-sex chromosomes are likely limited to the Iberian population of M. ines, and that they arose around the time when this population split from North-African populations, around 1.5 million years ago. Recombination arrest of the neo-W chromosome has led to an excess of premature stop-codons and frame-shift mutations, and reduced gene expression compared to the neo-Z chromosome. Surprisingly, we identified two regions of ∼1 Mb at one end of the neo-W that are both less diverged from the neo-Z and less degraded than the rest of the chromosome, suggesting a history of rare but repeated genetic exchange between the two neo-sex chromosomes. These plateaus of neo-sex chromosome divergence suggest that neo-W degradation can be locally reversed by rare recombination between neo-W and neo-Z chromosomes.

Biases in ARG-Based Inference of Historical Population Size in Populations Experiencing Selection

Inferring the demographic history of populations provides fundamental insights into species dynamics and is essential for developing a null model to accurately study selective processes. However, background selection and selective sweeps can produce genomic signatures at linked sites that mimic or mask signals associated with historical population size change. While the theoretical biases introduced by the linked effects of selection have been well established, it is unclear whether ancestral recombination graph (ARG)-based approaches to demographic inference in typical empirical analyses are susceptible to misinference due to these effects. To address this, we developed highly realistic forward simulations of human and Drosophila melanogaster populations, including empirically estimated variability of gene density, mutation rates, recombination rates, purifying, and positive selection, across different historical demographic scenarios, to broadly assess the impact of selection on demographic inference using a genealogy-based approach. Our results indicate that the linked effects of selection minimally impact demographic inference for human populations, although it could cause misinference in populations with similar genome architecture and population parameters experiencing more frequent recurrent sweeps. We found that accurate demographic inference of D. melanogaster populations by ARG-based methods is compromised by the presence of pervasive background selection alone, leading to spurious inferences of recent population expansion, which may be further worsened by recurrent sweeps, depending on the proportion and strength of beneficial mutations. Caution and additional testing with species-specific simulations are needed when inferring population history with non-human populations using ARG-based approaches to avoid misinference due to the linked effects of selection.

Understanding the Genetic Basis of Variation in Meiotic Recombination: Past, Present, and Future

Meiotic recombination is a fundamental feature of sexually reproducing species. It is often required for proper chromosome segregation and plays important role in adaptation and the maintenance of genetic diversity. The molecular mechanisms of recombination are remarkably conserved across eukaryotes, yet meiotic genes and proteins show substantial variation in their sequence and function, even between closely related species. Furthermore, the rate and distribution of recombination shows a huge diversity within and between chromosomes, individuals, sexes, populations, and species. This variation has implications for many molecular and evolutionary processes, yet how and why this diversity has evolved is not well understood. A key step in understanding trait evolution is to determine its genetic basis-that is, the number, effect sizes, and distribution of loci underpinning variation. In this perspective, I discuss past and current knowledge on the genetic basis of variation in recombination rate and distribution, explore its evolutionary implications, and present open questions for future research.

Fisher's Geometric Model as a Tool to Study Speciation

Interactions between alleles and across environments play an important role in the fitness of hybrids and are at the heart of the speciation process. Fitness landscapes capture these interactions and can be used to model hybrid fitness, helping us to interpret empirical observations and clarify verbal models. Here, we review recent progress in understanding hybridization outcomes through Fisher's geometric model, an intuitive and analytically tractable fitness landscape that captures many fitness patterns observed across taxa. We use case studies to show how the model parameters can be estimated from different types of data and discuss how these estimates can be used to make inferences about the divergence history and genetic architecture. We also highlight some areas where the model's predictions differ from alternative incompatibility-based models, such as the snowball effect and outlier patterns in genome scans.

Simulation of functional additive and non-additive genetic effects using statistical estimates from quantitative genetic models

Stochastic simulation software is commonly used to aid breeders designing cost-effective breeding programs and to validate statistical models used in genetic evaluation. An essential feature of the software is the ability to simulate populations with desired genetic and non-genetic parameters. However, this feature often fails when non-additive effects due to dominance or epistasis are modeled, as the desired properties of simulated populations are estimated from classical quantitative genetic statistical models formulated at the population level. The software simulates underlying functional effects for genotypic values at the individual level, which are not necessarily the same as effects from statistical models in which dominance and epistasis are included. This paper provides the theoretical basis and mathematical formulas for the transformation between functional and statistical effects in such simulations. The transformation is demonstrated with two statistical models analyzing individual phenotypes in a single population (common in animal breeding) and plot phenotypes of three-way hybrids involving two inbred populations (observed in some crop breeding programs). We also describe different methods for the simulation of functional effects for additive genetics, dominance, and epistasis to achieve the desired levels of variance components in classical statistical models used in quantitative genetics.

Predictable and Divergent Change in the Multivariate Matrix during Parallel Adaptation

AbstractAdaptation to replicated environmental conditions can be remarkably predictable, suggesting that parallel evolution may be a common feature of adaptive radiation. An open question, however, is how phenotypic variation itself evolves during repeated adaptation. Here, we use a dataset of morphological measurements from 35 populations of threespine stickleback, consisting of 16 parapatric lake-stream pairs and three marine populations, to understand how phenotypic variation has evolved during transitions from marine to freshwater environments and during subsequent diversification across the lake-stream boundary. We find statistical support for divergent phenotypic covariance (P) across populations, with most diversification of P occurring among freshwater populations. Despite a close correspondence between within-population phenotypic variation and among-population divergence, we find that variation in P is unrelated to total variation in population means across the set of populations. For lake-stream pairs, we find that theoretical predictions for microevolutionary change can explain more than 30% of divergence in P matrices across the habitat boundary. Together, our results indicate that divergence in variance structure occurs primarily in dimensions of trait space with low phenotypic integration, correlated with disparate lake and stream environments. Our findings illustrate how conserved and divergent features of multivariate variation can underlie adaptive radiation.

On the resolution of sexual conflict over shared traits

Anisogamy, different-sized male and female gametes, sits at the heart of sexual selection and conflict between the sexes. Sperm producers (males) and egg producers (females) of the same species generally share most, if not all, of the same genome, but selection frequently favours different trait values in each sex for traits common to both. The extent to which this conflict might be resolved, and the potential mechanisms by which this can occur, have been widely debated. Here, we summarize recent findings and emphasize that once the sexes evolve, sexual selection is ongoing, and therefore new conflict is always possible. In addition, sexual conflict is largely a multivariate problem, involving trait combinations underpinned by networks of interconnected genes. Although these complexities can hinder conflict resolution, they also provide multiple possible routes to decouple male and female phenotypes and permit sex-specific evolution. Finally, we highlight difficulty in the study of sexual conflict over shared traits and promising directions for future research.

Limits to species' range: the tension between local and global adaptation

We know that heritable variation is abundant, and that selection causes all but the smallest populations to rapidly shift beyond their original trait distribution. So then, what limits the range of a species? There are physical constraints and also population genetic limits to the effectiveness of selection, ultimately set by population size. Global adaptation, where the same genotype is favoured over the whole range, is most efficient when based on a multitude of weakly selected alleles and is effective even when local demes are small, provided that there is some gene flow. In contrast, local adaptation is sensitive to gene flow and may require alleles with substantial effect. How can populations combine the advantages of large effective size with the ability to specialise into local niches? To what extent does reproductive isolation help resolve this tension? I address these questions using eco-evolutionary models of polygenic adaptation, contrasting discrete demes with continuousspace.

Patterns and effects of gene flow on adaptation across spatial scales: implications for management

Gene flow can have rapid effects on adaptation and is an important evolutionary tool available when undertaking biological conservation and restoration. This tool is underused partly because of the perceived risk of outbreeding depression and loss of mean fitness when different populations are crossed. In this article, we briefly review some theory and empirical findings on how genetic variation is distributed across species ranges, describe known patterns of gene flow in nature with respect to environmental gradients, and highlight the effects of gene flow on adaptation in small or stressed populations in challenging environments (e.g., at species range limits). We then present a case study involving crosses at varying spatial scales among mountain populations of a trigger plant (Stylidium armeria: Stylidiaceae) in the Australian Alps to highlight how some issues around gene flow effects can be evaluated. We found evidence of outbreeding depression in seed production at greater geographic distances. Nevertheless, we found no evidence of maladaptive gene flow effects in likelihood of germination, plant performance (size), and performance variance, suggesting that gene flow at all spatial scales produces offspring with high adaptive potential. This case study demonstrates a path to evaluating how increasing sources of gene flow in managed wild and restored populations could identify some offspring with high fitness that could bolster the ability of populations to adapt to future environmental changes. We suggest further ways in which managers and researchers can act to understand and consider adaptive gene flow in natural and conservation contexts under rapidly changing conditions.

Variation in season length and development time is sufficient to drive the emergence and coexistence of social and solitary behavioral strategies

Season length and its associated variables can influence the expression of social behaviors, including the occurrence of eusociality in insects. Eusociality can vary widely across environmental gradients, both within and between different species. Numerous theoretical models have been developed to examine the life history traits that underlie the emergence and maintenance of eusociality, yet the impact of seasonality on this process is largely uncharacterized. Here, we present a theoretical model that incorporates season length and offspring development time into a single, individual-focused model to examine how these factors can shape the costs and benefits of social living. We find that longer season lengths and faster brood development times are sufficient to favor the emergence and maintenance of a social strategy, while shorter seasons favor a solitary one. We also identify a range of season lengths where social and solitary strategies can coexist. Moreover, our theoretical predictions are well-matched to the natural history and behavior of two flexibly-eusocial bee species, suggesting our model can make realistic predictions about the evolution of different social strategies. Broadly, this work reveals the crucial role that environmental conditions can have in shaping social behavior and its evolution and underscores the need for further models that explicitly incorporate such variation to study evolutionary trajectories of eusociality.

Mutations in the albinism gene oca2 alter vision-dependent prey capture behavior in the Mexican tetra

Understanding the phenotypic consequences of naturally occurring genetic changes, as well as their impact on fitness, is fundamental to understanding how organisms adapt to an environment. This is critical when genetic variants have pleiotropic effects, as determining how each phenotype impacted by a gene contributes to fitness is essential to understand how and why traits have evolved. A striking example of a pleiotropic gene contributing to trait evolution is the oca2 gene, coding mutations in which underlie albinism and reductions of sleep in the blind Mexican cavefish, Astyanax mexicanus. Here, we characterize the effects of mutations in the oca2 gene on larval prey capture. We find that when conspecific surface fish with engineered mutations in the oca2 allele are hunting, they use cave-like, wide angle strikes to capture prey. However, unlike cavefish or surface fish in the dark, which rely on lateral line mediated hunting, oca2 mutant surface fish use vision when striking at prey from wide angles. Finally, we find that while oca2 mutant surface fish do not outcompete pigmented surface siblings in the dark, pigmented fish outcompete albino fish in the light. This raises the possibility that albinism is detrimental to larval feeding in a surface-like lighted environment, but does not have negative consequences for fish in cave-like, dark environments. Together, these results demonstrate that oca2 plays a role in larval feeding behavior in A. mexicanus. Further, they expand our understanding of the pleiotropic phenotypic consequences of oca2 in cavefish evolution.

Temporal genomics in Hawaiian crickets reveals compensatory intragenomic coadaptation during adaptive evolution

Theory predicts that compensatory genetic changes reduce negative indirect effects of selected variants during adaptive evolution, but evidence is scarce. Here, we test this in a wild population of Hawaiian crickets using temporal genomics and a high-quality chromosome-level cricket genome. In this population, a mutation, flatwing, silences males and rapidly spread due to an acoustically-orienting parasitoid. Our sampling spanned a social transition during which flatwing fixed and the population went silent. We find long-range linkage disequilibrium around the putative flatwing locus was maintained over time, and hitchhiking genes had functions related to negative flatwing-associated effects. We develop a combinatorial enrichment approach using transcriptome data to test for compensatory, intragenomic coevolution. Temporal changes in genomic selection were distributed genome-wide and functionally associated with the population's transition to silence, particularly behavioural responses to silent environments. Our results demonstrate how 'adaptation begets adaptation'; changes to the sociogenetic environment accompanying rapid trait evolution can generate selection provoking further, compensatory adaptation.

Biology and life table parameters of Paralobesia viteana (Lepidoptera: Tortricidae), grown on different grape cultivars

The grape berry moth, Paralobesia viteana (Clemens), is an important pest of cultivated grapes in eastern North America. Damage is caused directly by larval feeding of grape clusters and indirectly by increasing fruit susceptibility to fungal and bacterial pathogens. Despite the impact of grape berry moth on grapes being widely recognized, there is a lack of understanding of the influence that different grape cultivars may have on grape berry moth development, reproduction, and population dynamics. In this study, we constructed age-stage 2-sex life tables for grape berry moth fed on 5 grape cultivars: Concord, Niagara, Riesling, Chambourcin, and Vidal, to examine the effects of diet on insect population development, survival, reproduction, and demographic parameters such as net reproductive rate, intrinsic rate of increase, finite rate of increase, and mean generation time. Our findings reveal that grape cultivar significantly influenced the neonate wandering period, larval developmental time, adult and female longevity, pupal weight, adult preoviposition period, oviposition period, mean generation time, age-stage-specific life expectancy, and reproductive value of P. viteana. However, diet type did not affect grape berry moth total fecundity or other demographic parameters. The highest female reproductive value was observed at 30-40 days of age, indicating that control tactics implemented during this time frame would have the greatest impact on reducing population increase. This study provides critical information on the effects of different grape cultivars on grape berry moth development, reproduction, and demography. These insights could lead to the development of management strategies that improve pest control and reduce economic losses in vineyards.

Effects of selection stringency on the outcomes of directed evolution

Directed evolution makes mutant lineages compete in climbing complicated sequence-function landscapes. Given this underlying complexity it is unclear how selection stringency, a ubiquitous parameter of directed evolution, impacts the outcome. Here we approach this question in terms of the fitnesses of the candidate variants at each round and the heterogeneity of their distributions of fitness effects. We show that even if the fittest mutant is most likely to yield the fittest mutants in the next round of selection, diversification can improve outcomes by sampling a larger variety of fitness effects. We find that heterogeneity in fitness effects between variants, larger population sizes, and evolution over a greater number of rounds all encourage diversification.

The distribution of beneficial mutational effects between two sister yeast species poorly explains natural outcomes of vineyard adaptation

Domesticated strains of Saccharomyces cerevisiae have adapted to resist copper and sulfite, two chemical stressors commonly used in winemaking. S. paradoxus, has not adapted to these chemicals despite being consistently present in sympatry with S. cerevisiae in vineyards. This contrast represents a case of apparent evolutionary constraints favoring greater adaptive capacity in S. cerevisiae. In this study, we used a comparative mutagenesis approach to test whether S. paradoxus is mutationally constrained with respect to acquiring greater copper and sulfite resistance. For both species, we assayed the rate, effect size, and pleiotropic costs of resistance mutations and sequenced a subset of 150 mutants isolated from our screen. We found that the distributions of mutational effects displayed by the two species were very similar and poorly explained the natural pattern. We also found that chromosome VIII aneuploidy and loss of function mutations in PMA1 confer copper resistance in both species, whereas loss of function mutations in REG1 were only a viable route to copper resistance in S. cerevisiae. We also observed a single de novo duplication of the CUP1 gene in S. paradoxus but none in S. cerevisiae. For sulfite, loss of function mutations in RTS1 and KSP1 confer resistance in both species, but mutations in RTS1 have larger average effects in S. paradoxus. Our results show that even when the distributions of mutational effects are largely similar, species can differ in the adaptive paths available to them. They also demonstrate that assays of the distribution of mutational effects may lack predictive insight concerning adaptive outcomes.

Behavioral selection in structured populations

The multilevel model of behavioral selection (MLBS) by Borgstede and Eggert (Behav Process 186:104370. 10.1016/j.beproc.2021.104370 , 2021) provides a formal framework that integrates reinforcement learning with natural selection using an extended Price equation. However, the MLBS is so far only formulated for homogeneous populations, thereby excluding all sources of variation between individuals. This limitation is of primary theoretical concern because any application of the MLBS to real data requires to account for variation between individuals. In this paper, I extend the MLBS to account for inter-individual variation by dividing the population into homogeneous sub-populations and including class-specific reproductive values as weighting factors for an individual's evolutionary fitness. The resulting formalism closes the gap between the theoretical underpinnings of behavioral selection and the application of the theory to empirical data, which naturally includes inter-individual variation. Furthermore, the extended MLBS is used to establish an explicit connection between the dynamics of learning and the maximization of individual fitness. These results expand the scope of the MLBS as a general theoretical framework for the quantitative analysis of learning and evolution.

Developmental noise and phenotypic plasticity are correlated in Drosophila simulans

Non-genetic variation is the phenotypic variation induced by the differential expression of a genotype in response to varying environmental cues and is broadly categorized into two types: phenotypic plasticity and developmental noise. These aspects of variation have been suggested to play an important role in adaptive evolution. However, the mechanisms by which these two types of non-genetic variations influence the evolutionary process are currently poorly understood. Using a machine-learning-based phenotyping tool, we independently quantified phenotypic plasticity and developmental noise in the wing morphological traits of the fruit fly Drosophila simulans. Utilizing a rearing experiment, we demonstrated plastic responses in both wing size and shape as well as non-zero heritability of both phenotypic plasticity and developmental noise, which suggests that adaptive phenotypic plasticity can evolve via genetic accommodation in the wing morphology of D. simulans. We found a positive correlation between phenotypic plasticity and developmental noise, while the correlation between the plastic response to three kinds of environmental factors that were examined (nutrient condition, temperature, and light-dark cycle) was poor. These results suggest that phenotypic plasticity and developmental noise contribute to evolvability in a similar manner, however, the mechanisms that underlie the correspondence between these two types of variation remain to be elucidated.

Mutations in yeast are deleterious on average regardless of the degree of adaptation to the testing environment

The role of spontaneous mutations in evolution depends on the distribution of their effects on fitness. Despite a general consensus that new mutations are deleterious on average, a handful of mutation accumulation experiments in diverse organisms instead suggest that beneficial and deleterious mutations can have comparable fitness impacts, i.e. the product of their respective rates and effects can be roughly equal. We currently lack a general framework for predicting when such a pattern will occur. One idea is that beneficial mutations will be more evident in genotypes that are not well adapted to the testing environment. We tested this prediction experimentally in the laboratory yeast Saccharomyces cerevisiae by allowing nine replicate populations to adapt to novel environments with complex sets of stressors. After >1000 asexual generations interspersed with 41 rounds of sexual reproduction, we assessed the mean effect of induced mutations on yeast growth in both the environment to which they had been adapting and the alternative novel environment. The mutations were deleterious on average, with the severity depending on the testing environment. However, we found no evidence that the adaptive match between genotype and environment is predictive of mutational fitness effects.

Evolutionary rescue in resistance to pesticides

Evolutionary rescue occurs when the genetic evolution of adaptation saves a population from decline or extinction after environmental change. The evolution of resistance to pesticides is a special scenario of abrupt environmental change, where rescue occurs under (very) strong selection for one or a few de novo resistance mutations of large effect. Here, a population genetic model of evolutionary rescue with density-dependent population change is developed, with a focus on deriving results that are important to resistance management. Massive stochastic simulations are used to generate observations, which are accurately predicted using analytical approximations. Key results include the probability density function for the time to resistance and the probability of population extinction. The distribution of resistance times shows a lag period, a narrow peak and a long tail. Surprisingly, the mean time to resistance can increase with the strength of selection because, if a mutation does not occur early on, then its emergence is delayed by the pesticide reducing the population size. The probability of population extinction shows a sharp transition, in that when extinction is possible, it is also highly likely. Consequently, population suppression and (local) eradication can be theoretically achievable goals, as novel strategies to delay resistance evolution.

Fitness as the organismal performance measure guiding adaptive evolution

A long-standing problem in evolutionary theory is to clarify in what sense (if any) natural selection cumulatively improves the design of organisms. Various concepts, such as fitness and inclusive fitness, have been proposed to resolve this problem. In addition, there have been attempts to replace the original problem with more tractable questions, such as whether a given gene or trait is favored by selection. Here, we ask what theoretical properties the concept fitness should possess to encapsulate the improvement criterion required to talk meaningfully about adaptive evolution. We argue that natural selection tends to shape phenotypes based on the causal properties of individuals and that this tendency is, therefore, best captured by a fitness concept that focuses on these properties. We highlight a fitness concept that meets this role under broad conditions but requires adjustments in our conceptual understanding of adaptive evolution. These adjustments combine elements of Dawkinsian gene selectionism and Egbert Leigh's "parliament of genes."

Recombinant inbred line panels inform the genetic architecture and interactions of adaptive traits in Drosophila melanogaster

The distribution of allelic effects on traits, along with their gene-by-gene and gene-by-environment interactions, contributes to the phenotypes available for selection and the trajectories of adaptive variants. Nonetheless, uncertainty persists regarding the effect sizes underlying adaptations and the importance of genetic interactions. Herein, we aimed to investigate the genetic architecture and the epistatic and environmental interactions involving loci that contribute to multiple adaptive traits using two new panels of Drosophila melanogaster recombinant inbred lines (RILs). To better fit our data, we re-implemented functions from R/qtl (Broman et al. 2003) using additive genetic models. We found 14 quantitative trait loci (QTL) underlying melanism, wing size, song pattern, and ethanol resistance. By combining our mapping results with population genetic statistics, we identified potential new genes related to these traits. None of the detected QTLs showed clear evidence of epistasis, and our power analysis indicated that we should have seen at least one significant interaction if sign epistasis or strong positive epistasis played a pervasive role in trait evolution. In contrast, we did find roles for gene-by-environment interactions involving pigmentation traits. Overall, our data suggest that the genetic architecture of adaptive traits often involves alleles of detectable effect, that strong epistasis does not always play a role in adaptation, and that environmental interactions can modulate the effect size of adaptive alleles.

Limits on the evolutionary rates of biological traits

This paper focuses on the maximum speed at which biological evolution can occur. I derive inequalities that limit the rate of evolutionary processes driven by natural selection, mutations, or genetic drift. These rate limits link the variability in a population to evolutionary rates. In particular, high variances in the fitness of a population and of a quantitative trait allow for fast changes in the trait's average. In contrast, low variability makes a trait less susceptible to random changes due to genetic drift. The results in this article generalize Fisher's fundamental theorem of natural selection to dynamics that allow for mutations and genetic drift, via trade-off relations that constrain the evolutionary rates of arbitrary traits. The rate limits can be used to probe questions in various evolutionary biology and ecology settings. They apply, for instance, to trait dynamics within or across species or to the evolution of bacteria strains. They apply to any quantitative trait, e.g., from species' weights to the lengths of DNA strands.