Pervasive natural selection in the Drosophila genome?

Causes and consequences of a complex recombinational landscape in the ant Cardiocondyla obscurior

Eusocial Hymenoptera have the highest recombination rates among all multicellular animals studied so far, but it is unclear why this is and how this affects the biology of individual species. A high-resolution linkage map for the ant Cardiocondyla obscurior corroborates genome-wide high recombination rates reported for ants (8.1 cM/Mb). However, recombination is locally suppressed in regions that are enriched with TEs, that have strong haplotype divergence, or that show signatures of epistatic selection in C. obscurior The results do not support the hypotheses that high recombination rates are linked to phenotypic plasticity or to modulating selection efficiency. Instead, genetic diversity and the frequency of structural variants correlate positively with local recombination rates, potentially compensating for the low levels of genetic variation expected in haplodiploid social Hymenoptera with low effective population size. Ultimately, the data show that recombination contributes to within-population polymorphism and to the divergence of the lineages within C. obscurior.

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.

Population genetic simulation: Benchmarking frameworks for non-standard models of natural selection

Population genetic simulation has emerged as a common tool for investigating increasingly complex evolutionary and demographic models. Software capable of handling high-level model complexity has recently been developed, and the advancement of tree sequence recording now allows simulations to merge the efficiency and genealogical insight of coalescent simulations with the flexibility of forward simulations. However, frameworks utilizing these features have not yet been compared and benchmarked. Here, we evaluate various simulation workflows using the coalescent simulator msprime and the forward simulator SLiM, to assess resource efficiency and determine an optimal simulation framework. Three aspects were evaluated: (1) the burn-in, to establish an equilibrium level of neutral diversity in the population; (2) the forward simulation, in which temporally fluctuating selection is acting; and (3) the final computation of summary statistics. We provide typical memory and computation time requirements for each step. We find that the fastest framework, a combination of coalescent and forward simulation with tree sequence recording, increases simulation speed by over twenty times compared to classical forward simulations without tree sequence recording, although it does require six times more memory. Overall, using efficient simulation workflows can lead to a substantial improvement when modelling complex evolutionary scenarios-although the optimal framework ultimately depends on the available computational resources.

The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change

Genomic time series from experimental evolution studies and ancient DNA datasets offer us a chance to directly observe the interplay of various evolutionary forces. We show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 y, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide change is due to gene flow. In both cases, after correcting for known major gene flow events, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets.

The impact of non-neutral synonymous mutations when inferring selection on non-synonymous mutations

The distribution of fitness effects (DFE) describes the proportions of new mutations that have different effects on reproductive fitness. Accurate measurements of the DFE are important because the DFE is a fundamental parameter in evolutionary genetics and has implications for our understanding of other phenomena like complex disease or inbreeding depression. Current computational methods to infer the DFE for nonsynonymous mutations from natural variation first estimate demographic parameters from synonymous variants to control for the effects of demography and background selection. Then, conditional on these parameters, the DFE is then inferred for nonsynonymous mutations. This approach relies on the assumption that synonymous variants are neutrally evolving. However, some evidence points toward synonymous mutations having measurable effects on fitness. To test whether selection on synonymous mutations affects inference of the DFE of nonsynonymous mutations, we simulated several possible models of selection on synonymous mutations using SLiM and attempted to recover the DFE of nonsynonymous mutations using Fit∂a∂i, a common method for DFE inference. Our results show that the presence of selection on synonymous variants leads to incorrect inferences of recent population growth. Furthermore, under certain parameter combinations, inferences of the DFE can have an inflated proportion of highly deleterious nonsynonymous mutations. However, this bias can be eliminated if the correct demographic parameters are used for DFE inference instead of the biased ones inferred from synonymous variants. Our work demonstrates how unmodeled selection on synonymous mutations may affect downstream inferences of the DFE.

Moderating the neutralist-selectionist debate: exactly which propositions are we debating, and which arguments are valid?

Half a century after its foundation, the neutral theory of molecular evolution continues to attract controversy. The debate has been hampered by the coexistence of different interpretations of the core proposition of the neutral theory, the 'neutral mutation-random drift' hypothesis. In this review, we trace the origins of these ambiguities and suggest potential solutions. We highlight the difference between the original, the revised and the nearly neutral hypothesis, and re-emphasise that none of them equates to the null hypothesis of strict neutrality. We distinguish the neutral hypothesis of protein evolution, the main focus of the ongoing debate, from the neutral hypotheses of genomic and functional DNA evolution, which for many species are generally accepted. We advocate a further distinction between a narrow and an extended neutral hypothesis (of which the latter posits that random non-conservative amino acid substitutions can cause non-ecological phenotypic divergence), and we discuss the implications for evolutionary biology beyond the domain of molecular evolution. We furthermore point out that the debate has widened from its initial focus on point mutations, and also concerns the fitness effects of large-scale mutations, which can alter the dosage of genes and regulatory sequences. We evaluate the validity of neutralist and selectionist arguments and find that the tested predictions, apart from being sensitive to violation of underlying assumptions, are often derived from the null hypothesis of strict neutrality, or equally consistent with the opposing selectionist hypothesis, except when assuming molecular panselectionism. Our review aims to facilitate a constructive neutralist-selectionist debate, and thereby to contribute to answering a key question of evolutionary biology: what proportions of amino acid and nucleotide substitutions and polymorphisms are adaptive?

Accurate inference of population history in the presence of background selection

All published methods for learning about demographic history make the simplifying assumption that the genome evolves neutrally, and do not seek to account for the effects of natural selection on patterns of variation. This is a major concern, as ample work has demonstrated the pervasive effects of natural selection and in particular background selection (BGS) on patterns of genetic variation in diverse species. Simulations and theoretical work have shown that methods to infer changes in effective population size over time (Ne(t)) become increasingly inaccurate as the strength of linked selection increases. Here, we introduce an extension to the Pairwise Sequentially Markovian Coalescent (PSMC) algorithm, PSMC+, which explicitly co-models demographic history and natural selection. We benchmark our method using forward-in-time simulations with BGS and find that our approach improves the accuracy of effective population size inference. Leveraging a high resolution map of BGS in humans, we infer considerable changes in the magnitude of inferred effective population size relative to previous reports. Finally, we separately infer Ne(t) on the X chromosome and on the autosomes in diverse great apes without making a correction for selection, and find that the inferred ratio fluctuates substantially through time in a way that differs across species, showing that uncorrected selection may be an important driver of signals of genetic difference on the X chromosome and autosomes.

The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change

Genomic time series from experimental evolution studies and ancient DNA datasets offer us a chance to directly observe the interplay of various evolutionary forces. We show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 years, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide change is due to gene flow. In both cases, after correcting for known major gene flow events, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets.

How chromosomal inversions reorient the evolutionary process

Inversions are structural mutations that reverse the sequence of a chromosome segment and reduce the effective rate of recombination in the heterozygous state. They play a major role in adaptation, as well as in other evolutionary processes such as speciation. Although inversions have been studied since the 1920s, they remain difficult to investigate because the reduced recombination conferred by them strengthens the effects of drift and hitchhiking, which in turn can obscure signatures of selection. Nonetheless, numerous inversions have been found to be under selection. Given recent advances in population genetic theory and empirical study, here we review how different mechanisms of selection affect the evolution of inversions. A key difference between inversions and other mutations, such as single nucleotide variants, is that the fitness of an inversion may be affected by a larger number of frequently interacting processes. This considerably complicates the analysis of the causes underlying the evolution of inversions. We discuss the extent to which these mechanisms can be disentangled, and by which approach.

Quantifying adaptive evolution and the effects of natural selection across the Norway spruce genome

Detecting natural selection is one of the major goals of evolutionary genomics. Here, we sequenced the whole genome of 25 Picea abies individuals and quantified the amount of selection across the genome. Using an estimate of the distribution of fitness effects, we showed that both negative selection and the rate of positively selected substitutions are very limited in coding regions. We found a positive correlation between the rate of adaptive substitutions and recombination rate and a negative correlation between the rate of adaptive substitutions and gene density, suggesting a widespread influence from Hill-Robertson interference on the efficiency of protein adaptation in P. abies. Finally, the distinct population statistics between genomic regions under either positive or balancing selection with that under neutral regions indicated the impact of natural selection on the genomic architecture of Norway spruce. Further gene ontology enrichment analysis for genes located in regions identified as undergoing either positive or long-term balancing selection also highlighted the specific molecular functions and biological processes that appear to be targets of selection in Norway spruce.

Population genomic analysis reveals distinct demographics and recent adaptation in the black flying fox (Pteropus alecto)

As the only mammalian group capable of powered flight, bats have many unique biological traits. Previous comparative genomic studies in bats have focused on long-term evolution. However, the micro-evolutionary processes driving recent evolution are largely under-explored. Using resequencing data from 50 black flying foxes (Pteropus alecto), one of the model species for bats, we find that black flying fox has much higher genetic diversity and lower levels of linkage disequilibrium than most of the mammalian species. Demographic inference reveals strong population fluctuations (>100 fold) coinciding with multiple historical events including the last glacial change and Toba super eruption, suggesting that the black flying fox is a very resilient species with strong recovery abilities. While long-term adaptation in the black flying fox is enriched in metabolic genes, recent adaptation in the black flying fox has a unique landscape where recently selected genes are not strongly enriched in any functional category. The demographic history and mode of adaptation suggest that black flying fox might be a well-adapted species with strong evolutionary resilience. Taken together, this study unravels a vibrant landscape of recent evolution for the black flying fox and sheds light on several unique evolutionary processes for bats comparing to other mammalian groups.

Selection and geography shape male reproductive tract transcriptomes in Drosophila melanogaster

Transcriptome analysis of several animal clades suggests that male reproductive tract gene expression evolves quickly. However, the factors influencing the abundance and distribution of within-species variation, the ultimate source of interspecific divergence, are poorly known. Drosophila melanogaster, an ancestrally African species that has recently spread throughout the world and colonized the Americas in the last roughly 100 years, exhibits phenotypic and genetic latitudinal clines on multiple continents, consistent with a role for spatially varying selection in shaping its biology. Nevertheless, geographic expression variation in the Americas is poorly described, as is its relationship to African expression variation. Here, we investigate these issues through the analysis of two male reproductive tissue transcriptomes [testis and accessory gland (AG)] in samples from Maine (USA), Panama, and Zambia. We find dramatic differences between these tissues in differential expression between Maine and Panama, with the accessory glands exhibiting abundant expression differentiation and the testis exhibiting very little. Latitudinal expression differentiation appears to be influenced by the selection of Panama expression phenotypes. While the testis shows little latitudinal expression differentiation, it exhibits much greater differentiation than the accessory gland in Zambia vs American population comparisons. Expression differentiation for both tissues is non-randomly distributed across the genome on a chromosome arm scale. Interspecific expression divergence between D. melanogaster and D. simulans is discordant with rates of differentiation between D. melanogaster populations. Strongly heterogeneous expression differentiation across tissues and timescales suggests a complex evolutionary process involving major temporal changes in the way selection influences expression evolution in these organs.

Strong, Recent Selective Sweeps Reshape Genetic Diversity in Freshwater Bivalve Megalonaias nervosa

Freshwater Unionid bivalves have recently faced ecological upheaval through pollution, barriers to dispersal, harvesting, and changes in fish-host prevalence. Currently, over 70% of species in North America are threatened, endangered or extinct. To characterize the genetic response to recent selective pressures, we collected population genetic data for one successful bivalve species, Megalonaias nervosa. We identify megabase-sized regions that are nearly monomorphic across the population, signals of strong, recent selection reshaping diversity across 73 Mb total. These signatures of selection are greater than is commonly seen in population genetic models. We observe 102 duplicate genes with high dN/dS on terminal branches among regions with sweeps, suggesting that gene duplication is a causative mechanism of recent adaptation in M. nervosa. Genes in sweeps reflect functional classes important for Unionid survival, including anticoagulation genes important for fish host parasitization, detox genes, mitochondria management, and shell formation. We identify sweeps in regions with no known functional impacts, suggesting mechanisms of adaptation that deserve greater attention in future work on species survival. In contrast, polymorphic transposable elements (TEs) appear to be detrimental and underrepresented among regions with sweeps. TE site frequency spectra are skewed toward singleton variants, and TEs among regions with sweeps are present at low frequency. Our work suggests that duplicate genes are an essential source of genetic novelty that has helped this species succeed in environments where others have struggled. These results suggest that gene duplications deserve greater attention in non-model population genomics, especially in species that have recently faced sudden environmental challenges.

Sweepstakes reproductive success via pervasive and recurrent selective sweeps

Highly fecund natural populations characterized by high early mortality abound, yet our knowledge about their recruitment dynamics is somewhat rudimentary. This knowledge gap has implications for our understanding of genetic variation, population connectivity, local adaptation, and the resilience of highly fecund populations. The concept of sweepstakes reproductive success, which posits a considerable variance and skew in individual reproductive output, is key to understanding the distribution of individual reproductive success. However, it still needs to be determined whether highly fecund organisms reproduce through sweepstakes and, if they do, the relative roles of neutral and selective sweepstakes. Here, we use coalescent-based statistical analysis of population genomic data to show that selective sweepstakes likely explain recruitment dynamics in the highly fecund Atlantic cod. We show that the Kingman coalescent (modelling no sweepstakes) and the Xi-Beta coalescent (modelling random sweepstakes), including complex demography and background selection, do not provide an adequate fit for the data. The Durrett-Schweinsberg coalescent, in which selective sweepstakes result from recurrent and pervasive selective sweeps of new mutations, offers greater explanatory power. Our results show that models of sweepstakes reproduction and multiple-merger coalescents are relevant and necessary for understanding genetic diversity in highly fecund natural populations. These findings have fundamental implications for understanding the recruitment variation of fish stocks and general evolutionary genomics of high-fecundity organisms.

Genome-wide analyses of introgression between two sympatric Asian oak species

Introgression can be an important source of new alleles for adaption under rapidly changing environments, perhaps even more important than standing variation. Though introgression has been extensively studied in many plants and animals, key questions on the underlying mechanisms of introgression still remain unanswered. In particular, we are yet to determine the genomic distribution of introgressed regions along the genome; whether the extent and patterns of introgression are influenced by ecological factors; and when and how introgression contributes to adaptation. Here, we generated high-quality genomic resources for two sympatric widespread Asian oak species, Quercus acutissima and Q. variabilis, sampled in multiple forests to study introgression between them. We show that introgressed regions are broadly distributed across the genome. Introgression was affected by genetic divergence between pairs of populations and by the similarity of the environments in which they live-populations occupying similar ecological sites tended to share the same introgressed regions. Introgressed genomic footprints of adaptation were preferentially located in regions with suppressed recombination rate. Introgression probably confers adaptation in these oak populations by introducing allelic variation in cis-regulatory elements, in particular through transposable element insertions, thereby altering the regulation of genes related to stress. Our results provide new avenues of research for uncovering mechanisms of adaptation due to hybridization in sympatric species.

Meiotic, genomic and evolutionary properties of crossover distribution in Drosophila yakuba

The number and location of crossovers across genomes are highly regulated during meiosis, yet the key components controlling them are fast evolving, hindering our understanding of the mechanistic causes and evolutionary consequences of changes in crossover rates. Drosophila melanogaster has been a model species to study meiosis for more than a century, with an available high-resolution crossover map that is, nonetheless, missing for closely related species, thus preventing evolutionary context. Here, we applied a novel and highly efficient approach to generate whole-genome high-resolution crossover maps in D. yakuba to tackle multiple questions that benefit from being addressed collectively within an appropriate phylogenetic framework, in our case the D. melanogaster species subgroup. The genotyping of more than 1,600 individual meiotic events allowed us to identify several key distinct properties relative to D. melanogaster. We show that D. yakuba, in addition to higher crossover rates than D. melanogaster, has a stronger centromere effect and crossover assurance than any Drosophila species analyzed to date. We also report the presence of an active crossover-associated meiotic drive mechanism for the X chromosome that results in the preferential inclusion in oocytes of chromatids with crossovers. Our evolutionary and genomic analyses suggest that the genome-wide landscape of crossover rates in D. yakuba has been fairly stable and captures a significant signal of the ancestral crossover landscape for the whole D. melanogaster subgroup, even informative for the D. melanogaster lineage. Contemporary crossover rates in D. melanogaster, on the other hand, do not recapitulate ancestral crossovers landscapes. As a result, the temporal stability of crossover landscapes observed in D. yakuba makes this species an ideal system for applying population genetic models of selection and linkage, given that these models assume temporal constancy in linkage effects. Our studies emphasize the importance of generating multiple high-resolution crossover rate maps within a coherent phylogenetic context to broaden our understanding of crossover control during meiosis and to improve studies on the evolutionary consequences of variable crossover rates across genomes and time.

Selection on the gametophyte: Modeling alternation of generations in plants

PREMISE

The degree of gametophyte dependence on the sporophyte life stage is a major feature that differentiates the life cycles of land plants, yet the evolutionary consequences of this difference remain poorly understood. Most evolutionary models assume organisms are either haploid or diploid for their entire lifespan, which is not appropriate for simulating plant life cycles. Here, we introduce shadie (Simulating Haploid-Diploid Evolution), a new, simple Python program for implementing simulations with biphasic life cycles and analyzing their results, using SLiM 3 as a simulation back end.

METHODS

We implemented evolutionary simulations under three realistic plant life cycle models supported in shadie, using either standardized or biologically realistic parameter settings to test how variation in plant life cycles and sexual systems affects patterns of genome diversity.

RESULTS

The dynamics of single beneficial mutation fixation did not vary dramatically between different models, but the patterns of spatial variation did differ, demonstrating that different life histories and model parameters affect both genetic diversity and linkage disequilibrium. The rate of linkage disequilibrium decay away from selected sites varied depending on model parameters such as cloning and selfing rates, through their impact on effective population sizes.

DISCUSSION

Evolutionary simulations are an exciting, underutilized approach in evolutionary research and education. shadie can aid plant researchers in developing null hypotheses, examining theory, and designing empirical studies, in order to investigate the role of the gametophyte life stage, and the effects of variation in plant life cycles, on plant genome evolution.

Natural selection drives genome-wide evolution via chance genetic associations

Understanding selection's impact on the genome is a major theme in biology. Functionally neutral genetic regions can be affected indirectly by natural selection, via their statistical association with genes under direct selection. The genomic extent of such indirect selection, particularly across loci not physically linked to those under direct selection, remains poorly understood, as does the time scale at which indirect selection occurs. Here, we use field experiments and genomic data in stick insects, deer mice and stickleback fish to show that widespread statistical associations with genes known to affect fitness cause many genetic loci across the genome to be impacted indirectly by selection. This includes regions physically distant from those directly under selection. Then, focusing on the stick insect system, we show that statistical associations between SNPs and other unknown, causal variants result in additional indirect selection in general and specifically within genomic regions of physically linked loci. This widespread indirect selection necessarily makes aspects of evolution more predictable. Thus, natural selection combines with chance genetic associations to affect genome-wide evolution across linked and unlinked loci and even in modest-sized populations. This process has implications for the application of evolutionary principles in basic and applied science.

Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution

Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer's multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times. Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change. The surprisingly simple use-it or lose-it rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.

Allele frequency divergence reveals ubiquitous influence of positive selection in Drosophila

Resolving the role of natural selection is a basic objective of evolutionary biology. It is generally difficult to detect the influence of selection because ubiquitous non-selective stochastic change in allele frequencies (genetic drift) degrades evidence of selection. As a result, selection scans typically only identify genomic regions that have undergone episodes of intense selection. Yet it seems likely such episodes are the exception; the norm is more likely to involve subtle, concurrent selective changes at a large number of loci. We develop a new theoretical approach that uncovers a previously undocumented genome-wide signature of selection in the collective divergence of allele frequencies over time. Applying our approach to temporally resolved allele frequency measurements from laboratory and wild Drosophila populations, we quantify the selective contribution to allele frequency divergence and find that selection has substantial effects on much of the genome. We further quantify the magnitude of the total selection coefficient (a measure of the combined effects of direct and linked selection) at a typical polymorphic locus, and find this to be large (of order 1%) even though most mutations are not directly under selection. We find that selective allele frequency divergence is substantially elevated at intermediate allele frequencies, which we argue is most parsimoniously explained by positive-not negative-selection. Thus, in these populations most mutations are far from evolving neutrally in the short term (tens of generations), including mutations with neutral fitness effects, and the result cannot be explained simply as an ongoing purging of deleterious mutations.

Genealogical structure changes as range expansions transition from pushed to pulled

Range expansions accelerate evolution through multiple mechanisms, including gene surfing and genetic drift. The inference and control of these evolutionary processes ultimately rely on the information contained in genealogical trees. Currently, there are two opposing views on how range expansions shape genealogies. In invasion biology, expansions are typically approximated by a series of population bottlenecks producing genealogies with only pairwise mergers between lineages-a process known as the Kingman coalescent. Conversely, traveling wave models predict a coalescent with multiple mergers, known as the Bolthausen-Sznitman coalescent. Here, we unify these two approaches and show that expansions can generate an entire spectrum of coalescent topologies. Specifically, we show that tree topology is controlled by growth dynamics at the front and exhibits large differences between pulled and pushed expansions. These differences are explained by the fluctuations in the total number of descendants left by the early founders. High growth cooperativity leads to a narrow distribution of reproductive values and the Kingman coalescent. Conversely, low growth cooperativity results in a broad distribution, whose exponent controls the merger sizes in the genealogies. These broad distribution and non-Kingman tree topologies emerge due to the fluctuations in the front shape and position and do not occur in quasi-deterministic simulations. Overall, our results show that range expansions provide a robust mechanism for generating different types of multiple mergers, which could be similar to those observed in populations with strong selection or high fecundity. Thus, caution should be exercised in making inferences about the origin of non-Kingman genealogies.

Quantifying the relationship between genetic diversity and population size suggests natural selection cannot explain Lewontin's Paradox

Neutral theory predicts that genetic diversity increases with population size, yet observed levels of diversity across metazoans vary only two orders of magnitude while population sizes vary over several. This unexpectedly narrow range of diversity is known as Lewontin's Paradox of Variation (1974). While some have suggested selection constrains diversity, tests of this hypothesis seem to fall short. Here, I revisit Lewontin's Paradox to assess whether current models of linked selection are capable of reducing diversity to this extent. To quantify the discrepancy between pairwise diversity and census population sizes across species, I combine previously-published estimates of pairwise diversity from 172 metazoan taxa with newly derived estimates of census sizes. Using phylogenetic comparative methods, I show this relationship is significant accounting for phylogeny, but with high phylogenetic signal and evidence that some lineages experience shifts in the evolutionary rate of diversity deep in the past. Additionally, I find a negative relationship between recombination map length and census size, suggesting abundant species have less recombination and experience greater reductions in diversity due to linked selection. However, I show that even assuming strong and abundant selection, models of linked selection are unlikely to explain the observed relationship between diversity and census sizes across species.

Evidence of Adaptive Evolution in Wolbachia-Regulated Gene DNMT2 and Its Role in the Dipteran Immune Response and Pathogen Blocking

Eukaryotic nucleic acid methyltransferase (MTase) proteins are essential mediators of epigenetic and epitranscriptomic regulation. DNMT2 belongs to a large, conserved family of DNA MTases found in many organisms, including holometabolous insects such as fruit flies and mosquitoes, where it is the lone MTase. Interestingly, despite its nomenclature, DNMT2 is not a DNA MTase, but instead targets and methylates RNA species. A growing body of literature suggests that DNMT2 mediates the host immune response against a wide range of pathogens, including RNA viruses. Curiously, although DNMT2 is antiviral in Drosophila, its expression promotes virus replication in mosquito species. We, therefore, sought to understand the divergent regulation, function, and evolution of these orthologs. We describe the role of the Drosophila-specific host protein IPOD in regulating the expression and function of fruit fly DNMT2. Heterologous expression of these orthologs suggests that DNMT2's role as an antiviral is host-dependent, indicating a requirement for additional host-specific factors. Finally, we identify and describe potential evidence of positive selection at different times throughout DNMT2 evolution within dipteran insects. We identify specific codons within each ortholog that are under positive selection and find that they are restricted to four distinct protein domains, which likely influence substrate binding, target recognition, and adaptation of unique intermolecular interactions. Collectively, our findings highlight the evolution of DNMT2 in Dipteran insects and point to structural, regulatory, and functional differences between mosquito and fruit fly homologs.

Revisiting the Notion of Deleterious Sweeps

It has previously been shown that, conditional on its fixation, the time to fixation of a semi-dominant deleterious autosomal mutation in a randomly mating population is the same as that of an advantageous mutation. This result implies that deleterious mutations could generate selective sweep-like effects. Although their fixation probabilities greatly differ, the much larger input of deleterious relative to beneficial mutations suggests that this phenomenon could be important. We here examine how the fixation of mildly deleterious mutations affects levels and patterns of polymorphism at linked sites - both in the presence and absence of interference amongst deleterious mutations - and how this class of sites may contribute to divergence between-populations and species. We find that, while deleterious fixations are unlikely to represent a significant proportion of outliers in polymorphism-based genomic scans within populations, minor shifts in the frequencies of deleterious mutations can influence the proportions of private variants and the value of FST after a recent population split. As sites subject to deleterious mutations are necessarily found in functional genomic regions, interpretations in terms of recurrent positive selection may require reconsideration.

Detection of hard and soft selective sweeps from Drosophila melanogaster population genomic data

Whether hard sweeps or soft sweeps dominate adaptation has been a matter of much debate. Recently, we developed haplotype homozygosity statistics that (i) can detect both hard and soft sweeps with similar power and (ii) can classify the detected sweeps as hard or soft. The application of our method to population genomic data from a natural population of Drosophila melanogaster (DGRP) allowed us to rediscover three known cases of adaptation at the loci Ace, Cyp6g1, and CHKov1 known to be driven by soft sweeps, and detected additional candidate loci for recent and strong sweeps. Surprisingly, all of the top 50 candidates showed patterns much more consistent with soft rather than hard sweeps. Recently, Harris et al. 2018 criticized this work, suggesting that all the candidate loci detected by our haplotype statistics, including the positive controls, are unlikely to be sweeps at all and that instead these haplotype patterns can be more easily explained by complex neutral demographic models. They also claim that these neutral non-sweeps are likely to be hard instead of soft sweeps. Here, we reanalyze the DGRP data using a range of complex admixture demographic models and reconfirm our original published results suggesting that the majority of recent and strong sweeps in D. melanogaster are first likely to be true sweeps, and second, that they do appear to be soft. Furthermore, we discuss ways to take this work forward given that most demographic models employed in such analyses are necessarily too simple to capture the full demographic complexity, while more realistic models are unlikely to be inferred correctly because they require a large number of free parameters.

Population Genomics on the Fly: Recent Advances in Drosophila

Drosophila melanogaster, a small dipteran of African origin, represents one of the best-studied model organisms. Early work in this system has uniquely shed light on the basic principles of genetics and resulted in a versatile collection of genetic tools that allow to uncover mechanistic links between genotype and phenotype. Moreover, given its worldwide distribution in diverse habitats and its moderate genome-size, Drosophila has proven very powerful for population genetics inference and was one of the first eukaryotes whose genome was fully sequenced. In this book chapter, we provide a brief historical overview of research in Drosophila and then focus on recent advances during the genomic era. After describing different types and sources of genomic data, we discuss mechanisms of neutral evolution including the demographic history of Drosophila and the effects of recombination and biased gene conversion. Then, we review recent advances in detecting genome-wide signals of selection, such as soft and hard selective sweeps. We further provide a brief introduction to background selection, selection of noncoding DNA and codon usage and focus on the role of structural variants, such as transposable elements and chromosomal inversions, during the adaptive process. Finally, we discuss how genomic data helps to dissect neutral and adaptive evolutionary mechanisms that shape genetic and phenotypic variation in natural populations along environmental gradients. In summary, this book chapter serves as a starting point to Drosophila population genomics and provides an introduction to the system and an overview to data sources, important population genetic concepts and recent advances in the field.

Adaptation, ancestral variation and gene flow in a 'Sky Island' Drosophila species

Over time, populations of species can expand, contract, fragment and become isolated, creating subpopulations that must adapt to local conditions. Understanding how species maintain variation after divergence as well as adapt to these changes in the face of gene flow is of great interest, especially as the current climate crisis has caused range shifts and frequent migrations for many species. Here, we characterize how a mycophageous fly species, Drosophila innubila, came to inhabit and adapt to its current range which includes mountain forests in south-western USA separated by large expanses of desert. Using population genomic data from more than 300 wild-caught individuals, we examine four populations to determine their population history in these mountain forests, looking for signatures of local adaptation. In this first extensive study, establishing D. innubila as a key genomic "Sky Island" model, we find D. innubila spread northwards during the previous glaciation period (30-100 KYA) and have recently expanded even further (0.2-2 KYA). D. innubila shows little evidence of population structure, consistent with a recent establishment and genetic variation maintained since before geographic stratification. We also find some signatures of recent selective sweeps in chorion proteins and population differentiation in antifungal immune genes suggesting differences in the environments to which flies are adapting. However, we find little support for long-term recurrent selection in these genes. In contrast, we find evidence of long-term recurrent positive selection in immune pathways such as the Toll signalling system and the Toll-regulated antimicrobial peptides.

Demography and Natural Selection Have Shaped Genetic Variation in the Widely Distributed Conifer Norway Spruce (Picea abies)

Under the neutral theory, species with larger effective population size are expected to harbor higher genetic diversity. However, across a wide variety of organisms, the range of genetic diversity is orders of magnitude more narrow than the range of effective population size. This observation has become known as Lewontin’s paradox and although aspects of this phenomenon have been extensively studied, the underlying causes for the paradox remain unclear. Norway spruce (Picea abies) is a widely distributed conifer species across the northern hemisphere, and it consequently plays a major role in European forestry. Here, we use whole-genome resequencing data from 35 individuals to perform population genomic analyses in P. abies in an effort to understand what drives genome-wide patterns of variation in this species. Despite having a very wide geographic distribution and an corresponding enormous current population size, our analyses find that genetic diversity of P. abies is low across a number of populations (π = 0.0049 in Central-Europe, π = 0.0063 in Sweden-Norway, π = 0.0063 in Finland). To assess the reasons for the low levels of genetic diversity, we infer the demographic history of the species and find that it is characterized by several reoccurring bottlenecks with concomitant decreases in effective population size can, at least partly, provide an explanation for low polymorphism we observe in P. abies. Further analyses suggest that recurrent natural selection, both purifying and positive selection, can also contribute to the loss of genetic diversity in Norway spruce by reducing genetic diversity at linked sites. Finally, the overall low mutation rates seen in conifers can also help explain the low genetic diversity maintained in Norway spruce.

How Good Are Predictions of the Effects of Selective Sweeps on Levels of Neutral Diversity?

Selective sweeps are thought to play a significant role in shaping patterns of variability across genomes; accurate predictions of their effects are, therefore, important for understanding these patterns. A commonly used model of selective sweeps assumes that alleles sampled at the end of a sweep, and that fail to recombine with wild-type haplotypes during the sweep, coalesce instantaneously, leading to a simple expression for sweep effects on diversity. It is shown here that there can be a significant probability that a pair of alleles sampled at the end of a sweep coalesce during the sweep before a recombination event can occur, reducing their expected coalescent time below that given by the simple approximation. Expressions are derived for the expected reductions in pairwise neutral diversities caused by both single and recurrent sweeps in the presence of such within-sweep coalescence, although the effects of multiple recombination events during a sweep are only treated heuristically. The accuracies of the resulting expressions were checked against the results of simulations. For even moderate ratios of the recombination rate to the selection coefficient, the simple approximation can be substantially inaccurate. The selection model used here can be applied to favorable mutations with arbitrary dominance coefficients, to sex-linked loci with sex-specific selection coefficients, and to inbreeding populations. Using the results from this model, the expected differences between the levels of variability on X chromosomes and autosomes with selection at linked sites are discussed, and compared with data on a population of Drosophila melanogaster.

Greater strength of selection and higher proportion of beneficial amino acid changing mutations in humans compared with mice and Drosophila melanogaster

Quantifying and comparing the amount of adaptive evolution among different species is key to understanding how evolution works. Previous studies have shown differences in adaptive evolution across species; however, their specific causes remain elusive. Here, we use improved modeling of weakly deleterious mutations and the demographic history of the outgroup species and ancestral population and estimate that at least 20% of nonsynonymous substitutions between humans and an outgroup species were fixed by positive selection. This estimate is much higher than previous estimates, which did not correct for the sizes of the outgroup species and ancestral population. Next, we jointly estimate the proportion and selection coefficient (p⁺ and s⁺, respectively) of newly arising beneficial nonsynonymous mutations in humans, mice, and Drosophila melanogaster by examining patterns of polymorphism and divergence. We develop a novel composite likelihood framework to test whether these parameters differ across species. Overall, we reject a model with the same p⁺ and s⁺ of beneficial mutations across species and estimate that humans have a higher p⁺s⁺ compared with that of D. melanogaster and mice. We show that this result cannot be caused by biased gene conversion or hypermutable CpG sites. We discuss possible biological explanations that could generate the observed differences in the amount of adaptive evolution across species.

Genetic adaptation of Tibetan poplar (Populus szechuanica var. tibetica) to high altitudes on the Qinghai-Tibetan Plateau

Plant adaptation to high altitudes has long been a substantial focus of ecological and evolutionary research. However, the genetic mechanisms underlying such adaptation remain poorly understood. Here, we address this issue by sampling, genotyping, and comparing populations of Tibetan poplar, Populus szechuanica var. tibetica, distributed from low (~2,000 m) to high altitudes (~3,000 m) of Sejila Mountain on the Qinghai-Tibet Plateau. Population structure analyses allow clear classification of two groups according to their altitudinal distributions. However, in contrast to the genetic variation within each population, differences between the two populations only explain a small portion of the total genetic variation (3.64%). We identified asymmetrical gene flow from high- to low-altitude populations. Integrating population genomic and landscape genomic analyses, we detected two hotspot regions, one containing four genes associated with altitudinal variation, and the other containing ten genes associated with response to solar radiation. These genes participate in abiotic stress resistance and regulation of reproductive processes. Our results provide insight into the genetic mechanisms underlying high-altitude adaptation in Tibetan poplar.

Association of genetic and climatic variability in giant sequoia, Sequoiadendron giganteum, reveals signatures of local adaptation along moisture-related gradients

Uncovering the genetic basis of local adaptation is a major goal of evolutionary biology and conservation science alike. In an era of climate change, an understanding of how environmental factors shape adaptive diversity is crucial to predicting species response and directing management. Here, we investigate patterns of genomic variation in giant sequoia, an iconic and ecologically important tree species, using 1,364 bi-allelic single nucleotide polymorphisms (SNPs). We use an F _ST outlier test and two genotype-environment association methods, latent factor mixed models (LFMMs) and redundancy analysis (RDA), to detect complex signatures of local adaptation. Results indicate 79 genomic regions of potential adaptive importance, with limited overlap between the detection methods. Of the 58 loci detected by LFMM, 51 showed strong correlations to a precipitation-driven composite variable and seven to a temperature-related variable. RDA revealed 24 outlier loci with association to climate variables, all of which showed strongest relationship to summer precipitation. Nine candidate loci were indicated by two methods. After correcting for geographic distance, RDA models using climate predictors accounted for 49% of the explained variance and showed significant correlations between SNPs and climatic factors. Here, we present evidence of local adaptation in giant sequoia along gradients of precipitation and provide a first step toward identifying genomic regions of adaptive significance. The results of this study will provide information to guide management strategies that seek to maximize adaptive potential in the face of climate change.

Estimating the genome-wide contribution of selection to temporal allele frequency change

Rapid phenotypic adaptation is often observed in natural populations and selection experiments. However, detecting the genome-wide impact of this selection is difficult since adaptation often proceeds from standing variation and selection on polygenic traits, both of which may leave faint genomic signals indistinguishable from a noisy background of genetic drift. One promising signal comes from the genome-wide covariance between allele frequency changes observable from temporal genomic data (e.g., evolve-and-resequence studies). These temporal covariances reflect how heritable fitness variation in the population leads changes in allele frequencies at one time point to be predictive of the changes at later time points, as alleles are indirectly selected due to remaining associations with selected alleles. Since genetic drift does not lead to temporal covariance, we can use these covariances to estimate what fraction of the variation in allele frequency change through time is driven by linked selection. Here, we reanalyze three selection experiments to quantify the effects of linked selection over short timescales using covariance among time points and across replicates. We estimate that at least 17 to 37% of allele frequency change is driven by selection in these experiments. Against this background of positive genome-wide temporal covariances, we also identify signals of negative temporal covariance corresponding to reversals in the direction of selection for a reasonable proportion of loci over the time course of a selection experiment. Overall, we find that in the three studies we analyzed, linked selection has a large impact on short-term allele frequency dynamics that is readily distinguishable from genetic drift.

Comparative genomics approach to evolutionary process connectivity

The influence of species life history traits and historical demography on contemporary connectivity is still poorly understood. However, these factors partly determine the evolutionary responses of species to anthropogenic landscape alterations. Genetic connectivity and its evolutionary outcomes depend on a variety of spatially dependent evolutionary processes, such as population structure, local adaptation, genetic admixture, and speciation. Over the last years, population genomic studies have been interrogating these processes with increasing resolution, revealing a large diversity of species responses to spatially structured landscapes. In parallel, multispecies meta-analyses usually based on low-genome coverage data have provided fundamental insights into the ecological determinants of genetic connectivity, such as the influence of key life history traits on population structure. However, comparative studies still lack a thorough integration of macro- and micro-evolutionary scales to fully realize their potential. Here, I present how a comparative genomics framework may provide a deeper understanding of evolutionary process connectivity. This framework relies on coupling the inference of long-term demographic and selective history with an assessment of the contemporary consequences of genetic connectivity. Standardizing this approach across several species occupying the same landscape should help understand how spatial environmental heterogeneity has shaped the diversity of historical and contemporary connectivity patterns in different taxa with contrasted life history traits. I will argue that a reasonable amount of genome sequence data can be sufficient to resolve and connect complex macro- and micro-evolutionary histories. Ultimately, implementing this framework in varied taxonomic groups is expected to improve scientific guidelines for conservation and management policies.

A Continuum of Evolving De Novo Genes Drives Protein-Coding Novelty in Drosophila

Orphan genes, lacking detectable homologs in outgroup species, typically represent 10-30% of eukaryotic genomes. Efforts to find the source of these young genes indicate that de novo emergence from non-coding DNA may in part explain their prevalence. Here, we investigate the roots of orphan gene emergence in the Drosophila genus. Across the annotated proteomes of twelve species, we find 6297 orphan genes within 4953 taxon-specific clusters of orthologs. By inferring the ancestral DNA as non-coding for between 550 and 2467 (8.7-39.2%) of these genes, we describe for the first time how de novo emergence contributes to the abundance of clade-specific Drosophila genes. In support of them having functional roles, we show that de novo genes have robust expression and translational support. However, the distinct nucleotide sequences of de novo genes, which have characteristics intermediate between intergenic regions and conserved genes, reflect their recent birth from non-coding DNA. We find that de novo genes encode more disordered proteins than both older genes and intergenic regions. Together, our results suggest that gene emergence from non-coding DNA provides an abundant source of material for the evolution of new proteins. Following gene birth, gradual evolution over large evolutionary timescales moulds sequence properties towards those of conserved genes, resulting in a continuum of properties whose starting points depend on the nucleotide sequences of an initial pool of novel genes.

From Drift to Draft: How Much Do Beneficial Mutations Actually Contribute to Predictions of Ohta's Slightly Deleterious Model of Molecular Evolution?

Since its inception in 1973, the slightly deleterious model of molecular evolution, also known as the nearly neutral theory of molecular evolution, remains a central model to explain the main patterns of DNA polymorphism in natural populations. This is not to say that the quantitative fit to data are perfect. A recent study used polymorphism data from Drosophila melanogaster to test whether, as predicted by the nearly neutral theory, the proportion of effectively neutral mutations depends on the effective population size (Ne ). It showed that a nearly neutral model simply scaling with Ne variation across the genome could not alone explain the data, but that consideration of linked positive selection improves the fit between observations and predictions. In the present article, we extended the work in two main directions. First, we confirmed the observed pattern on a set of 59 species, including high-quality genomic data from 11 animal and plant species with different mating systems and effective population sizes, hence a priori different levels of linked selection. Second, for the 11 species with high-quality genomic data we also estimated the full distribution of fitness effects (DFE) of mutations, and not solely the DFE of deleterious mutations. Both Ne and beneficial mutations contributed to the relationship between the proportion of effectively neutral mutations and local Ne across the genome. In conclusion, the predictions of the slightly deleterious model of molecular evolution hold well for species with small Ne , but for species with large Ne , the fit is improved by incorporating linked positive selection to the model.

The Temporal Dynamics of Background Selection in Nonequilibrium Populations

Neutral genetic diversity across the genome is determined by the complex interplay of mutation, demographic history, and natural selection. While the direct action of natural selection is limited to functional loci across the genome, its impact can have effects on nearby neutral loci due to genetic linkage. These effects of selection at linked sites, referred to as genetic hitchhiking and background selection (BGS), are pervasive across natural populations. However, only recently has there been a focus on the joint consequences of demography and selection at linked sites, and some empirical studies have come to apparently contradictory conclusions as to their combined effects. To understand the relationship between demography and selection at linked sites, we conducted an extensive forward simulation study of BGS under a range of demographic models. We found that the relative levels of diversity in BGS and neutral regions vary over time and that the initial dynamics after a population size change are often in the opposite direction of the long-term expected trajectory. Our detailed observations of the temporal dynamics of neutral diversity in the context of selection at linked sites in nonequilibrium populations provide new intuition about why patterns of diversity under BGS vary through time in natural populations and help reconcile previously contradictory observations. Most notably, our results highlight that classical models of BGS are poorly suited for predicting diversity in nonequilibrium populations.

Contingent Convergence: The Ability To Detect Convergent Genomic Evolution Is Dependent on Population Size and Migration

Outlier scans, in which the genome is scanned for signatures of selection, have become a prominent tool in studies of local adaptation, and more recently studies of genetic convergence in natural populations. However, such methods have the potential to be confounded by features of demographic history, such as population size and migration, which are considerably varied across natural populations. In this study, we use forward-simulations to investigate and illustrate how several measures of genetic differentiation commonly used in outlier scans (FST, DXY and Δπ) are influenced by demographic variation across multiple sampling generations. In a factorial design with 16 treatments, we manipulate the presence/absence of founding bottlenecks (N of founding individuals), prolonged bottlenecks (proportional size of diverging population) and migration rate between two populations with ancestral and diverged phenotypic optima. Our results illustrate known constraints of individual measures associated with reduced population size and a lack of migration; but notably we demonstrate how relationships between measures are similarly dependent on these features of demography. We find that false-positive signals of convergent evolution (the same simulated outliers detected in independent treatments) are attainable as a product of similar population size and migration treatments (particularly for DXY), and that outliers across different measures (for e.g., FST and DXY) can occur with little influence of selection. Taken together, we show how underappreciated, yet quantifiable measures of demographic history can influence commonly employed methods for detecting selection.

Global evaluation of taxonomic relationships and admixture within the Culex pipiens complex of mosquitoes

BACKGROUND

Within the Culex pipiens mosquito complex, there are six contemporarily recognized taxa: Cx. quinquefasciatus, Cx. pipiens f. pipiens, Cx. pipiens f. molestus, Cx. pipiens pallens, Cx. australicus and Cx. globocoxitus. Many phylogenetic aspects within this complex have eluded resolution, such as the relationship of the two Australian endemic taxa to the other four members, as well as the evolutionary origins and taxonomic status of Cx. pipiens pallens and Cx. pipiens f. molestus. Ultimately, insights into lineage relationships within the complex will facilitate a better understanding of differential disease transmission by these mosquitoes. To this end, we have combined publicly available data with our own sequencing efforts to examine these questions.

RESULTS

We found that the two Australian endemic complex members, Cx. australicus and Cx. globocoxitus, comprise a monophyletic group, are genetically distinct, and are most closely related to the cosmopolitan Cx. quinquefasciatus. Our results also show that Cx. pipiens pallens is genetically distinct, but may have arisen from past hybridization. Lastly, we observed complicated patterns of genetic differentiation within and between Cx. pipiens f. pipiens and Cx. pipiens f. molestus.

CONCLUSIONS

Two Australian endemic Culex taxa, Cx. australicus and Cx. globocoxitus, belong within the Cx. pipiens complex, but have a relatively older evolutionary origin. They likely diverged from Cx. quinquefasciatus after its colonization of Australia. The taxon Cx. pipiens pallens is a distinct evolutionary entity that likely arose from past hybridization between Cx. quinquefasciatus and Cx. pipiens f. pipiens/Cx. pipiens f. molestus. Our results do not suggest it derives from ongoing hybridization. Finally, genetic differentiation within the Cx. pipiens f. pipiens and Cx. pipiens f. molestus samples suggests that they collectively form two separate geographic clades, one in North America and one in Europe and the Mediterranean. This may indicate that the Cx. pipiens f. molestus form has two distinct origins, arising from Cx. pipiens f. pipiens in each region. However, ongoing genetic exchange within and between these taxa have obscured their evolutionary histories, and could also explain the absence of monophyly among our samples. Overall, this work suggests many avenues that warrant further investigation.

Variation of the adaptive substitution rate between species and within genomes

The importance of adaptive mutations in molecular evolution is extensively debated. Recent developments in population genomics allow inferring rates of adaptive mutations by fitting a distribution of fitness effects to the observed patterns of polymorphism and divergence at sites under selection and sites assumed to evolve neutrally. Here, we summarize the current state-of-the-art of these methods and review the factors that affect the molecular rate of adaptation. Several studies have reported extensive cross-species variation in the proportion of adaptive amino-acid substitutions (α) and predicted that species with larger effective population sizes undergo less genetic drift and higher rates of adaptation. Disentangling the rates of positive and negative selection, however, revealed that mutations with deleterious effects are the main driver of this population size effect and that adaptive substitution rates vary comparatively little across species. Conversely, rates of adaptive substitution have been documented to vary substantially within genomes. On a genome-wide scale, gene density, recombination and mutation rate were observed to play a role in shaping molecular rates of adaptation, as predicted under models of linked selection. At the gene level, it has been reported that the gene functional category and the macromolecular structure substantially impact the rate of adaptive mutations. Here, we deliver a comprehensive review of methods used to infer the molecular adaptive rate, the potential drivers of adaptive evolution and how positive selection shapes molecular evolution within genes, across genes within species and between species.

The Linked Selection Signature of Rapid Adaptation in Temporal Genomic Data

The majority of empirical population genetic studies have tried to understand the evolutionary processes that have shaped genetic variation in a single sample taken from a present-day population. However, genomic data collected over tens of generations in both natural and laboratory populations are increasingly used to find selected loci underpinning adaptation over these short timescales. Although these studies have been quite successful in detecting selection on large-effect loci, the fitness differences between individuals are often polygenic, such that selection leads to allele frequency changes that are difficult to distinguish from genetic drift. However, one promising signal comes from polygenic selection's effect on neutral sites that become stochastically associated with the genetic backgrounds that lead to fitness differences between individuals. Previous theoretical work has established that the random associations between a neutral allele and heritable fitness backgrounds act to reduce the effective population size experienced by this neutral allele. These associations perturb neutral allele frequency trajectories, creating autocovariance in the allele frequency changes across generations. Here, we show how temporal genomic data allow us to measure the temporal autocovariance in allele frequency changes and characterize the genome-wide impact of polygenic selection. We develop expressions for these temporal autocovariances, showing that their magnitude is determined by the level of additive genetic variation, recombination, and linkage disequilibria in a region. Furthermore, by using analytic expressions for the temporal variances and autocovariances in allele frequency, we demonstrate that one can estimate the additive genetic variation for fitness and the drift-effective population size from temporal genomic data. We also show how the proportion of total variation in allele frequency change due to linked selection can be estimated from temporal data. Overall, we demonstrate that temporal genomic data offer opportunities to identify the role of linked selection on genome-wide diversity over short timescales, and can help bridge population genetic and quantitative genetic studies of adaptation.

Understanding the Factors That Shape Patterns of Nucleotide Diversity in the House Mouse Genome

A major goal of population genetics has been to determine the extent by which selection at linked sites influences patterns of neutral nucleotide diversity in the genome. Multiple lines of evidence suggest that diversity is influenced by both positive and negative selection. For example, in many species there are troughs in diversity surrounding functional genomic elements, consistent with the action of either background selection (BGS) or selective sweeps. In this study, we investigated the causes of the diversity troughs that are observed in the wild house mouse genome. Using the unfolded site frequency spectrum, we estimated the strength and frequencies of deleterious and advantageous mutations occurring in different functional elements in the genome. We then used these estimates to parameterize forward-in-time simulations of chromosomes, using realistic distributions of functional elements and recombination rate variation in order to determine whether selection at linked sites can explain the observed patterns of nucleotide diversity. The simulations suggest that BGS alone cannot explain the dips in diversity around either exons or conserved noncoding elements. A combination of BGS and selective sweeps produces deeper dips in diversity than BGS alone, but the inferred parameters of selection cannot fully explain the patterns observed in the genome. Our results provide evidence of sweeps shaping patterns of nucleotide diversity across the mouse genome and also suggest that infrequent, strongly advantageous mutations play an important role in this. The limitations of using the unfolded site frequency spectrum for inferring the frequency and effects of advantageous mutations are discussed.

Do estimates of contemporary effective population size tell us what we want to know?

Estimation of effective population size (N_e) from genetic marker data is a major focus for biodiversity conservation because it is essential to know at what rates inbreeding is increasing and additive genetic variation is lost. But are these the rates assessed when applying commonly used N_e estimation techniques? Here we use recently developed analytical tools and demonstrate that in the case of substructured populations the answer is no. This is because the following: Genetic change can be quantified in several ways reflecting different types of N_e such as inbreeding (N_eI), variance (N_eV), additive genetic variance (N_eAV), linkage disequilibrium equilibrium (N_eLD), eigenvalue (N_eE) and coalescence (N_eCo) effective size. They are all the same for an isolated population of constant size, but the realized values of these effective sizes can differ dramatically in populations under migration. Commonly applied N_e‐estimators target N_eV or N_eLD of individual subpopulations. While such estimates are safe proxies for the rates of inbreeding and loss of additive genetic variation under isolation, we show that they are poor indicators of these rates in populations affected by migration. In fact, both the local and global inbreeding (N_eI) and additive genetic variance (N_eAV) effective sizes are consistently underestimated in a subdivided population. This is serious because these are the effective sizes that are relevant to the widely accepted 50/500 rule for short and long term genetic conservation.  The bias can be infinitely large and is due to inappropriate parameters being estimated when applying theory for isolated populations to subdivided ones.

The Effects on Neutral Variability of Recurrent Selective Sweeps and Background Selection

Levels of variability and rates of adaptive evolution may be affected by hitchhiking, the effect of selection on evolution at linked sites. Hitchhiking can be caused either by "selective sweeps" or by background selection, involving the spread of new favorable alleles or the elimination of deleterious mutations, respectively. Recent analyses of population genomic data have fitted models where both these processes act simultaneously, to infer the parameters of selection. Here, we investigate the consequences of relaxing a key assumption of some of these studies, that the time occupied by a selective sweep is negligible compared with the neutral coalescent time. We derive a new expression for the expected level of neutral variability in the presence of recurrent selective sweeps and background selection. We also derive approximate integral expressions for the effects of recurrent selective sweeps. The accuracy of the theoretical predictions was tested against multilocus simulations, with selection, recombination, and mutation parameters that are realistic for Drosophila melanogaster In the presence of crossing over, there is approximate agreement between the theoretical and simulation results. We show that the observed relationships between the rate of crossing over, and the level of synonymous site diversity and rate of adaptive evolution in Drosophila are probably mainly caused by background selection, whereas selective sweeps and population size changes are needed to produce the observed distortions of the site frequency spectrum.

The Neutral Theory in Light of Natural Selection

In this perspective, we evaluate the explanatory power of the neutral theory of molecular evolution, 50 years after its introduction by Kimura. We argue that the neutral theory was supported by unreliable theoretical and empirical evidence from the beginning, and that in light of modern, genome-scale data, we can firmly reject its universality. The ubiquity of adaptive variation both within and between species means that a more comprehensive theory of molecular evolution must be sought.

The importance of the Neutral Theory in 1968 and 50 years on: A response to Kern and Hahn 2018

A recent article reassessing the Neutral Theory of Molecular Evolution claims that it is no longer as important as is widely believed. The authors argue that "the neutral theory was supported by unreliable theoretical and empirical evidence from the beginning, and that in light of modern, genome-scale data, we can firmly reject its universality." Claiming that "the neutral theory has been overwhelmingly rejected," they propose instead that natural selection is the major force shaping both between-species divergence and within-species variation. Although this is probably a minority view, it is important to evaluate such claims carefully in the context of current knowledge, as inaccuracies can sometimes morph into an accepted narrative for those not familiar with the underlying science. We here critically examine and ultimately reject Kern and Hahn's arguments and assessment, and instead propose that it is now abundantly clear that the foundational ideas presented five decades ago by Kimura and Ohta are indeed correct.

Determinants of the Efficacy of Natural Selection on Coding and Noncoding Variability in Two Passerine Species

Population genetic theory predicts that selection should be more effective when the effective population size (N_e) is larger, and that the efficacy of selection should correlate positively with recombination rate. Here, we analyzed the genomes of ten great tits and ten zebra finches. Nucleotide diversity at 4-fold degenerate sites indicates that zebra finches have a 2.83-fold larger N_e. We obtained clear evidence that purifying selection is more effective in zebra finches. The proportion of substitutions at 0-fold degenerate sites fixed by positive selection (α) is high in both species (great tit 48%; zebra finch 64%) and is significantly higher in zebra finches. When α was estimated on GC-conservative changes (i.e., between A and T and between G and C), the estimates reduced in both species (great tit 22%; zebra finch 53%). A theoretical model presented herein suggests that failing to control for the effects of GC-biased gene conversion (gBGC) is potentially a contributor to the overestimation of α, and that this effect cannot be alleviated by first fitting a demographic model to neutral variants. We present the first estimates in birds for α in the untranslated regions, and found evidence for substantial adaptive changes. Finally, although purifying selection is stronger in high-recombination regions, we obtained mixed evidence for α increasing with recombination rate, especially after accounting for gBGC. These results highlight that it is important to consider the potential confounding effects of gBGC when quantifying selection and that our understanding of what determines the efficacy of selection is incomplete.