Testing the neutral theory of molecular evolution with genomic data from Drosophila

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?

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.

impMKT: the imputed McDonald and Kreitman test, a straightforward correction that significantly increases the evidence of positive selection of the McDonald and Kreitman test at the gene level

The McDonald and Kreitman test is one of the most powerful and widely used methods to detect and quantify recurrent natural selection in DNA sequence data. One of its main limitations is the underestimation of positive selection due to the presence of slightly deleterious variants segregating at low frequencies. Although several approaches have been developed to overcome this limitation, most of them work on gene pooled analyses. Here, we present the imputed McDonald and Kreitman test (impMKT), a new straightforward approach for the detection of positive selection and other selection components of the distribution of fitness effects at the gene level. We compare imputed McDonald and Kreitman test with other widely used McDonald and Kreitman test approaches considering both simulated and empirical data. By applying imputed McDonald and Kreitman test to humans and Drosophila data at the gene level, we substantially increase the statistical evidence of positive selection with respect to previous approaches (e.g. by 50% and 157% compared with the McDonald and Kreitman test in Drosophila and humans, respectively). Finally, we review the minimum number of genes required to obtain a reliable estimation of the proportion of adaptive substitution (α) in gene pooled analyses by using the imputed McDonald and Kreitman test compared with other McDonald and Kreitman test implementations. Because of its simplicity and increased power to detect recurrent positive selection on genes, we propose the imputed McDonald and Kreitman test as the first straightforward approach for testing specific evolutionary hypotheses at the gene level. The software implementation and population genomics data are available at the web-server imkt.uab.cat.

Functional Divergence of the bag-of-marbles Gene in the Drosophila melanogaster Species Group

In Drosophila melanogaster, a key germline stem cell (GSC) differentiation factor, bag of marbles (bam) shows rapid bursts of amino acid fixations between sibling species D. melanogaster and Drosophila simulans, but not in the outgroup species Drosophila ananassae. Here, we test the null hypothesis that bam's differentiation function is conserved between D. melanogaster and four additional Drosophila species in the melanogaster species group spanning approximately 30 million years of divergence. Surprisingly, we demonstrate that bam is not necessary for oogenesis or spermatogenesis in Drosophila teissieri nor is bam necessary for spermatogenesis in D. ananassae. Remarkably bam function may change on a relatively short time scale. We further report tests of neutral sequence evolution at bam in additional species of Drosophila and find a positive, but not perfect, correlation between evidence for positive selection at bam and its essential role in GSC regulation and fertility for both males and females. Further characterization of bam function in more divergent lineages will be necessary to distinguish between bam's critical gametogenesis role being newly derived in D. melanogaster, D. simulans, Drosophila yakuba, and D. ananassae females or it being basal to the genus and subsequently lost in numerous lineages.

Two decades of suspect evidence for adaptive molecular evolution – Negative selection confounding positive selection signals

There has been a large literature in the last two decades affirming adaptive DNA sequence evolution between species. The main lines of evidence are from (i) the McDonald-Kreitman (MK) test, which compares divergence and polymorphism data, and (ii) the phylogenetic analysis by maximum likelihood (PAML) test, which analyzes multispecies divergence data. Here, we apply these two tests concurrently to genomic data of Drosophila and Arabidopsis. To our surprise, the >100 genes identified by the two tests do not overlap beyond random expectation. Because the non-concordance could be due to low powers leading to high false negatives, we merge every 20–30 genes into a ‘supergene’. At the supergene level, the power of detection is large but the calls still do not overlap. We rule out methodological reasons for the non-concordance. In particular, extensive simulations fail to find scenarios whereby positive selection can only be detected by either MK or PAML, but not both. Since molecular evolution is governed by positive and negative selection concurrently, a fundamental assumption for estimating one of these (say, positive selection) is that the other is constant. However, in a broad survey of primates, birds, Drosophila and Arabidopsis, we found that negative selection rarely stays constant for long in evolution. As a consequence, the variation in negative selection is often misconstrued as a signal of positive selection. In conclusion, MK, PAML and any method that examines genomic sequence evolution has to explicitly address the variation in negative selection before estimating positive selection. In a companion study, we propose a possible path forward in two stages—first, by mapping out the changes in negative selection and then using this map to estimate positive selection. For now, the large literature on positive selection between species has to await reassessment.

Polymorphic landscape of SARS-CoV-2 genomes isolated from Indian population in 2020 demonstrates rapid evolution in ORF3a, ORF8, nucleocapsid phosphoprotein and spike glycoprotein

India, with around 15 million COVID-19 cases, recently became the second worst-hit nation by the SARS-CoV-2 pandemic. In this study, we analyzed the mutation and selection landscape of 516 unique and complete genomes of SARS-CoV-2 isolates from India in a 12-month span (from Jan to Dec 2020) to understand how the virus is evolving in this geographical region. We identified 953 genome-wide loci displaying single nucleotide polymorphism (SNP) and the Principal Component Analysis and mutation plots of the datasets indicate an increase in genetic variance with time. The 42% of the polymorphic sites display substitutions in the third nucleotide position of codons indicating that non-synonymous substitutions are more prevalent. These isolates displayed strong evidence of purifying selection in ORF1ab, spike, nucleocapsid, and membrane glycoprotein. We also find some evidence of localized positive selections ORF1ab, spike glycoprotein, and nucleocapsid. The CDSs for ORF3a, ORF8, nucleocapsid phosphoprotein, and spike glycoprotein were found to evolve at rapid rate. This study will be helpful in understanding the dynamics of rapidly evolving SARS-CoV-2.

Identifying loci under selection via explicit demographic models

Adaptive genetic variation is a function of both selective and neutral forces. To accurately identify adaptive loci, it is thus critical to account for demographic history. Theory suggests that signatures of selection can be inferred using the coalescent, following the premise that genealogies of selected loci deviate from neutral expectations. Here, we build on this theory to develop an analytical framework to identify loci under selection via explicit demographic models (LSD). Under this framework, signatures of selection are inferred through deviations in demographic parameters, rather than through summary statistics directly, and demographic history is accounted for explicitly. Leveraging the property of demographic models to incorporate directionality, we show that LSD can provide information on the environment in which selection acts on a population. This can prove useful in elucidating the selective processes underlying local adaptation, by characterizing genetic trade-offs and extending the concepts of antagonistic pleiotropy and conditional neutrality from ecological theory to practical application in genomic data. We implement LSD via approximate Bayesian computation and demonstrate, via simulations, that LSD (a) has high power to identify selected loci across a large range of demographic-selection regimes, (b) outperforms commonly applied genome-scan methods under complex demographies and (c) accurately infers the directionality of selection for identified candidates. Using the same simulations, we further characterize the behaviour of isolation-with-migration models conducive to the study of local adaptation under regimes of selection. Finally, we demonstrate an application of LSD by detecting loci and characterizing genetic trade-offs underlying flower colour in Antirrhinum majus.

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.

A novel family of secreted insect proteins linked to plant gall development

In an elaborate form of inter-species exploitation, many insects hijack plant development to induce novel plant organs called galls that provide the insect with a source of nutrition and a temporary home. Galls result from dramatic reprogramming of plant cell biology driven by insect molecules, but the roles of specific insect molecules in gall development have not yet been determined. Here, we study the aphid Hormaphis cornu, which makes distinctive "cone" galls on leaves of witch hazel Hamamelis virginiana. We found that derived genetic variants in the aphid gene determinant of gall color (dgc) are associated with strong downregulation of dgc transcription in aphid salivary glands, upregulation in galls of seven genes involved in anthocyanin synthesis, and deposition of two red anthocyanins in galls. We hypothesize that aphids inject DGC protein into galls and that this results in differential expression of a small number of plant genes. dgc is a member of a large, diverse family of novel predicted secreted proteins characterized by a pair of widely spaced cysteine-tyrosine-cysteine (CYC) residues, which we named BICYCLE proteins. bicycle genes are most strongly expressed in the salivary glands specifically of galling aphid generations, suggesting that they may regulate many aspects of gall development. bicycle genes have experienced unusually frequent diversifying selection, consistent with their potential role controlling gall development in a molecular arms race between aphids and their host plants.

A novel family of secreted insect proteins linked to plant gall development

In an elaborate form of inter-species exploitation, many insects hijack plant development to induce novel plant organs called galls that provide the insect with a source of nutrition and a temporary home. Galls result from dramatic reprogramming of plant cell biology driven by insect molecules, but the roles of specific insect molecules in gall development have not yet been determined. Here we study the aphidHormaphis cornu, which makes distinctive “cone” galls on leaves of witch hazelHamamelis virginiana. We found that derived genetic variants in the aphid genedeterminant of gall color(dgc) are associated with strong downregulation ofdgctranscription in aphid salivary glands, upregulation in galls of seven genes involved in anthocyanin synthesis, and deposition of two red anthocyanins in galls. We hypothesize that aphids inject DGC protein into galls, and that this results in differential expression of a small number of plant genes.Dgcis a member of a large, diverse family of novel predicted secreted proteins characterized by a pair of widely spaced cysteine-tyrosine-cysteine (CYC) residues, which we named BICYCLE proteins.Bicyclegenes are most strongly expressed in the salivary glands specifically of galling aphid generations, suggesting that they may regulate many aspects of gall development.Bicyclegenes have experienced unusually frequent diversifying selection, consistent with their potential role controlling gall development in a molecular arms race between aphids and their host plants.

One Sentence Summary

Aphidbicyclegenes, which encode diverse secreted proteins, contribute to plant gall development.

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.

Mitogenomics of the endemic Ethiopian rats: looking for footprints of adaptive evolution in sky islands

Organisms living in high altitude must adapt to environmental conditions with hypoxia and low temperature, e.g. by changes in the structure and function of proteins associated with oxidative phosphorylation in mitochondria. Here we analysed the signs of adaptive evolution in 27 mitogenomes of endemic Ethiopian rats (Stenocephalemys), where individual species adapted to different elevation. Significant signals of positive selection were detected in 10 of the 13 mitochondrial protein-coding genes, with a majority of functional substitutions in the NADH dehydrogenase complex. Higher frequency of positively selected sites was found in phylogenetic lineages corresponding to Afroalpine specialists.

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.

Innovation of heterochromatin functions drives rapid evolution of essential ZAD-ZNF genes in Drosophila

Contrary to dogma, evolutionarily young and dynamic genes can encode essential functions. We find that evolutionarily dynamic ZAD-ZNF genes, which encode the most abundant class of insect transcription factors, are more likely to encode essential functions in Drosophila melanogaster than ancient, conserved ZAD-ZNF genes. We focus on the Nicknack ZAD-ZNF gene, which is evolutionarily young, poorly retained in Drosophila species, and evolves under strong positive selection. Yet we find that it is necessary for larval development in D. melanogaster. We show that Nicknack encodes a heterochromatin-localizing protein like its paralog Oddjob, also an evolutionarily dynamic yet essential ZAD-ZNF gene. We find that the divergent D. simulans Nicknack protein can still localize to D. melanogaster heterochromatin and rescue viability of female but not male Nicknack-null D. melanogaster. Our findings suggest that innovation for rapidly changing heterochromatin functions might generally explain the essentiality of many evolutionarily dynamic ZAD-ZNF genes in insects.

Survival of the cheapest: how proteome cost minimization drives evolution

Darwin's theory of evolution emphasized that positive selection of functional proficiency provides the fitness that ultimately determines the structure of life, a view that has dominated biochemical thinking of enzymes as perfectly optimized for their specific functions. The 20th-century modern synthesis, structural biology, and the central dogma explained the machinery of evolution, and nearly neutral theory explained how selection competes with random fixation dynamics that produce molecular clocks essential e.g. for dating evolutionary histories. However, quantitative proteomics revealed that selection pressures not relating to optimal function play much larger roles than previously thought, acting perhaps most importantly via protein expression levels. This paper first summarizes recent progress in the 21st century toward recovering this universal selection pressure. Then, the paper argues that proteome cost minimization is the dominant, underlying 'non-function' selection pressure controlling most of the evolution of already functionally adapted living systems. A theory of proteome cost minimization is described and argued to have consequences for understanding evolutionary trade-offs, aging, cancer, and neurodegenerative protein-misfolding diseases.

Molecular Evolution in Large Steps-Codon Substitutions under Positive Selection

Molecular evolution is believed to proceed in small steps. The step size can be defined by a distance reflecting physico-chemical disparities between amino acid (AA) pairs that can be exchanged by single 1-bp mutations. We show that AA substitution rates are strongly and negatively correlated with this distance but only when positive selection is relatively weak. We use the McDonald and Kreitman test to separate the influences of positive and negative selection. While negative selection is indeed stronger on AA substitutions generating larger changes in chemical properties of AAs, positive selection operates by different rules. For 65 of the 75 possible pairs, positive selection is comparable in strength regardless of AA distance. However, the ten pairs under the strongest positive selection all exhibit large leaps in chemical properties. Five of the ten pairs are shared between Drosophila and Hominoids, thus hinting at a common but modest biochemical basis of adaptation across taxa. The hypothesis that adaptive changes often take large functional steps will need to be extensively tested. If validated, molecular models will need to better integrate positive and negative selection in the search for adaptive signal.

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.

Identifying Lineage-Specific Targets of Natural Selection by a Bayesian Analysis of Genomic Polymorphisms and Divergence from Multiple Species

We present a method that jointly analyzes the polymorphism and divergence sites in genomic sequences of multiple species to identify the genes under natural selection and pinpoint the occurrence time of selection to a specific lineage of the species phylogeny. This method integrates population genetics models using a Bayesian Poisson random field framework and combines information over all gene loci to boost the power for detecting selection. The method provides posterior distributions of the fitness effects of each gene along with parameters associated with the evolutionary history, including the species divergence time and effective population size of external species. The results of simulations demonstrate that our method achieves a high power to identify genes under positive selection for a wide range of selection intensity and provides reasonably accurate estimates of the population genetic parameters. The proposed method is applied to genomic sequences of humans, chimpanzees, gorillas, and orangutans and identifies a list of lineage-specific targets of positive selection. The positively selected genes in the human lineage are enriched in pathways of gene expression regulation, immune system and metabolism, etc. Our analysis provides insights into natural evolution in the coding regions of humans and great apes and thus serves as a basis for further molecular and functional studies.

Exploiting selection at linked sites to infer the rate and strength of adaptation

Genomic data encodes past evolutionary events and has the potential to reveal the strength, rate, and biological drivers of adaptation. However, jointly estimating adaptation rate (a) and adaptation strength remains challenging because evolutionary processes such as demography, linkage, and non-neutral polymorphism can confound inference. Here, we exploit the influence of background selection to reduce the fixation rate of weakly-beneficial alleles to jointly infer the strength and rate of adaptation. We develop an MK-based method (ABC-MK) to infer adaptation rate and strength, and estimate α = 0.135 in human protein-coding sequences, 72% of which is contributed by weakly-adaptive variants. We show that in this adaptation regime α is reduced ≈ 25% by linkage genome-wide. Moreover, we show that virus-interacting proteins (VIPs) undergo adaptation that is both stronger and nearly twice as frequent as the genome average (α = 0.224, 56% due to strongly-beneficial alleles). Our results suggest that while most adaptation in human proteins is weakly-beneficial, adaptation to viruses is often strongly-beneficial. Our method provides a robust framework for estimating adaptation rate and strength across species.

Family quarrels in seeds and rapid adaptive evolution in Arabidopsis

Evolutionary conflict can drive rapid adaptive evolution, sometimes called an arms race, because each party needs to respond continually to the adaptations of the other. Evidence for such arms races can sometimes be seen in morphology, in behavior, or in the genes underlying sexual interactions of host-pathogen interactions, but is rarely predicted a priori. Kin selection theory predicts that conflicts of interest should usually be reduced but not eliminated among genetic relatives, but there is little evidence as to whether conflict within families can drive rapid adaptation. Here we test multiple predictions about how conflict over the amount of resources an offspring receives from its parent would drive rapid molecular evolution in seed tissues of the flowering plant Arabidopsis As predicted, there is more adaptive evolution in genes expressed in Arabidopsis seeds than in other specialized organs, more in endosperms and maternal tissues than in embryos, and more in the specific subtissues involved in nutrient transfer. In the absence of credible alternative hypotheses, these results suggest that kin selection and conflict are important in plants, that the conflict includes not just the mother and offspring but also the triploid endosperm, and that, despite the conflict-reducing role of kinship, family members can engage in slow but steady tortoise-like arms races.

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.

Inferring the distribution of selective effects from a time inhomogeneous model

We have developed a Poisson random field model for estimating the distribution of selective effects of newly arisen nonsynonymous mutations that could be observed as polymorphism or divergence in samples of two related species under the assumption that the two species populations are not at mutation-selection-drift equilibrium. The model is applied to 91Drosophila genes by comparing levels of polymorphism in an African population of D. melanogaster with divergence to a reference strain of D. simulans. Based on the difference of gene expression level between testes and ovaries, the 91 genes were classified as 33 male-biased, 28 female-biased, and 30 sex-unbiased genes. Under a Bayesian framework, Markov chain Monte Carlo simulations are implemented to the model in which the distribution of selective effects is assumed to be Gaussian with a mean that may differ from one gene to the other to sample key parameters. Based on our estimates, the majority of newly-arisen nonsynonymous mutations that could contribute to polymorphism or divergence in Drosophila species are mildly deleterious with a mean scaled selection coefficient of -2.81, while almost 86% of the fixed differences between species are driven by positive selection. There are only 16.6% of the nonsynonymous mutations observed in sex-unbiased genes that are under positive selection in comparison to 30% of male-biased and 46% of female-biased genes that are beneficial. We also estimated that D. melanogaster and D. simulans may have diverged 1.72 million years ago.

A Large Panel of Drosophila simulans Reveals an Abundance of Common Variants

The rapidly expanding availability of large NGS data sets provides an opportunity to investigate population genetics at an unprecedented scale. Drosophila simulans is the sister species of the model organism Drosophila melanogaster, and is often presumed to share similar demographic history. However, previous population genetic and ecological work suggests very different signatures of selection and demography. Here, we sequence a new panel of 170 inbred genotypes of a North American population of D. simulans, a valuable complement to the DGRP and other D. melanogaster panels. We find some unexpected signatures of demography, in the form of excess intermediate frequency polymorphisms. Simulations suggest that this is possibly due to a recent population contraction and selection. We examine the outliers in the D. simulans genome determined by a haplotype test to attempt to parse the contribution of demography and selection to the patterns observed in this population. Untangling the relative contribution of demography and selection to genomic patterns of variation is challenging, however, it is clear that although D. melanogaster was thought to share demographic history with D. simulans different forces are at work in shaping genomic variation in this population of D. simulans.

Population genetic analysis of autophagy and phagocytosis genes in Drosophila melanogaster and D. simulans

Autophagy and phagocytosis are cellular immune mechanisms for internalization and elimination of intracellular and extracellular pathogens. Some pathogens have evolved the ability to inhibit or manipulate these processes, raising the prospect of adaptive reciprocal co-evolution by the host. We performed population genetic analyses on phagocytosis and autophagy genes in Drosophila melanogaster and D. simulans to test for molecular evolutionary signatures of immune adaptation. We found that phagocytosis and autophagy genes as a whole exhibited an elevated level of haplotype homozygosity in both species. In addition, we detected signatures of recent selection, notably in the Atg14 and Ykt6 genes in D. melanogaster and a pattern of elevated sequence divergence in the genderblind (gb) gene on the D. simulans lineage. These results suggest that the evolution of the host cellular immune system as a whole may be shaped by a dynamic conflict between Drosophila and its pathogens even without pervasive evidence of strong adaptive evolution at the individual gene level.

Genome-wide maps of ribosomal occupancy provide insights into adaptive evolution and regulatory roles of uORFs during Drosophila development

Upstream open reading frames (uORFs) play important roles in regulating the main coding DNA sequences (CDSs) via translational repression. Despite their prevalence in the genomes, uORFs are overall discriminated against by natural selection. However, it remains unclear why in the genomes there are so many uORFs more conserved than expected under the assumption of neutral evolution. Here, we generated genome-wide maps of translational efficiency (TE) at the codon level throughout the life cycle of Drosophila melanogaster. We identified 35,735 uORFs that were expressed, and 32,224 (90.2%) of them showed evidence of ribosome occupancy during Drosophila development. The ribosome occupancy of uORFs is determined by genomic features, such as optimized sequence contexts around their start codons, a shorter distance to CDSs, and higher coding potentials. Our population genomic analysis suggests the segregating mutations that create or disrupt uORFs are overall deleterious in D. melanogaster. However, we found for the first time that many (68.3% of) newly fixed uORFs that are associated with ribosomes in D. melanogaster are driven by positive Darwinian selection. Our findings also suggest that uORFs play a vital role in controlling the translational program in Drosophila. Moreover, we found that many uORFs are transcribed or translated in a developmental stage-, sex-, or tissue-specific manner, suggesting that selective transcription or translation of uORFs could potentially modulate the TE of the downstream CDSs during Drosophila development.

Upstream open reading frames (uORFs) in the 5′ untranslated regions (UTRs) of messenger RNAs can potentially inhibit translation of the downstream regions that encode proteins by sequestering protein-making machinery the ribosome. Moreover, mutations that destroy existing uORFs or create new ones are known to cause human disease. Although mutations that create new uORFs are generally deleterious and are selected against, many uORFs are evolutionarily conserved across eukaryotic species. To resolve this dilemma, we used extensive mRNA-Seq and ribosome profiling to generate high-resolution genome-wide maps of ribosome occupancy and translational efficiency (TE) during the life cycle of the fruit fly D. melanogaster. This allowed us to identify the sequence features of uORFs that influence their ability to associate with ribosomes. We demonstrate for the first time that the majority of the newly fixed uORFs in D. melanogaster, especially the translated ones, are under positive Darwinian selection. We also show that uORFs exert widespread repressive effects on the translation of the downstream protein-coding region. We find that many uORFs are transcribed or translated in a developmental stage-, sex-, or tissue-specific manner. Our results suggest that during Drosophila development, changes in the TE of uORFs, as well as the inclusion/exclusion of uORFs, are frequently exploited to inversely influence the translation of the downstream protein-coding regions. Our study provides novel insights into the molecular mechanisms and functional consequences of uORF-mediated regulation.

Faster-X evolution: Theory and evidence from Drosophila

A faster rate of adaptive evolution of X-linked genes compared with autosomal genes can be caused by the fixation of recessive or partially recessive advantageous mutations, due to the full expression of X-linked mutations in hemizygous males. Other processes, including recombination rate and mutation rate differences between X chromosomes and autosomes, may also cause faster evolution of X-linked genes. We review population genetics theory concerning the expected relative values of variability and rates of evolution of X-linked and autosomal DNA sequences. The theoretical predictions are compared with data from population genomic studies of several species of Drosophila. We conclude that there is evidence for adaptive faster-X evolution of several classes of functionally significant nucleotides. We also find evidence for potential differences in mutation rates between X-linked and autosomal genes, due to differences in mutational bias towards GC to AT mutations. Many aspects of the data are consistent with the male hemizygosity model, although not all possible confounding factors can be excluded.

RNA-Interference Pathways Display High Rates of Adaptive Protein Evolution in Multiple Invertebrates

Conflict between organisms can lead to a reciprocal adaptation that manifests as an increased evolutionary rate in genes mediating the conflict. This adaptive signature has been observed in RNA-interference (RNAi) pathway genes involved in the suppression of viruses and transposable elements in Drosophila melanogaster, suggesting that a subset of Drosophila RNAi genes may be locked in an arms race with these parasites. However, it is not known whether rapid evolution of RNAi genes is a general phenomenon across invertebrates, or which RNAi genes generally evolve adaptively. Here we use population genomic data from eight invertebrate species to infer rates of adaptive sequence evolution, and to test for past and ongoing selective sweeps in RNAi genes. We assess rates of adaptive protein evolution across species using a formal meta-analytic framework to combine data across species and by implementing a multispecies generalized linear mixed model of mutation counts. Across species, we find that RNAi genes display a greater rate of adaptive protein substitution than other genes, and that this is primarily mediated by positive selection acting on the genes most likely to defend against viruses and transposable elements. In contrast, evidence for recent selective sweeps is broadly spread across functional classes of RNAi genes and differs substantially among species. Finally, we identify genes that exhibit elevated adaptive evolution across the analyzed insect species, perhaps due to concurrent parasite-mediated arms races.

Testing the neutral hypothesis of phenotypic evolution

Although evolution by natural selection is widely regarded as the most important principle of biology, it is unknown whether phenotypic variations within and between species are mostly adaptive or neutral due to the lack of relevant studies of large, unbiased samples of phenotypic traits. Here, we examine 210 yeast morphological traits chosen because of experimental feasibility irrespective of their potential adaptive values. Our analysis is based on the premise that, under neutrality, the rate of phenotypic evolution measured in the unit of mutational size declines as the trait becomes more important to fitness, analogous to the neutral paradigm that functional genes evolve more slowly than functionless pseudogenes. However, we find faster evolution of more important morphological traits within and between species, rejecting the neutral hypothesis. By contrast, an analysis of 3,466 gene expression traits fails to refute neutrality. Thus, at least in yeast, morphological evolution appears largely adaptive, but the same may not apply to other classes of phenotypes. Our neutrality test is applicable to other species, especially genetic model organisms, for which estimations of mutational size and trait importance are relatively straightforward.

A Direct Test of Selection in Cell Populations Using the Diversity in Gene Expression within Tumors

Although intratumor diversity driven by selection has been the prevailing view in cancer biology, recent population genetic analyses have been unable to reject the neutral interpretation. As the power to reject neutrality in tumors is often low, it will be desirable to have an alternative means to test selection directly. Here, we utilize gene expression data as a surrogate for functional significance in intra- and intertumor comparisons. The expression divergence between samples known to be driven by selection (e.g., between tumor and normal tissues) is always higher than the divergence between normal samples, which should be close to the neutral level of divergence. In contrast, the expression differentiation between regions of the same tumor, being lower than the neutral divergence, is incompatible with the hypothesis of selectively driven divergence. To further test the hypothesis of neutral evolution, we select a hepatocellular carcinoma tumor that has large intratumor SNV and CNV (single nucleotide variation and copy number variation, respectively) diversity. This tumor enables us to calibrate the level of expression divergence against that of genetic divergence. We observe that intratumor divergence in gene expression profile lags far behind genetic divergence, indicating insufficient phenotypic differences for selection to operate. All these expression analyses corroborate that natural selection does not operate effectively within tumors, supporting recent interpretations of within-tumor diversity. As the expected level of genetic diversity, hence the potential for drug resistance, would be much higher under neutrality than under selection, the issue is of both theoretical and clinical significance.

Genomics of parallel adaptation at two timescales in Drosophila

Two interesting unanswered questions are the extent to which both the broad patterns and genetic details of adaptive divergence are repeatable across species, and the timescales over which parallel adaptation may be observed. Drosophila melanogaster is a key model system for population and evolutionary genomics. Findings from genetics and genomics suggest that recent adaptation to latitudinal environmental variation (on the timescale of hundreds or thousands of years) associated with Out-of-Africa colonization plays an important role in maintaining biological variation in the species. Additionally, studies of interspecific differences between D. melanogaster and its sister species D. simulans have revealed that a substantial proportion of proteins and amino acid residues exhibit adaptive divergence on a roughly few million years long timescale. Here we use population genomic approaches to attack the problem of parallelism between D. melanogaster and a highly diverged conger, D. hydei, on two timescales. D. hydei, a member of the repleta group of Drosophila, is similar to D. melanogaster, in that it too appears to be a recently cosmopolitan species and recent colonizer of high latitude environments. We observed parallelism both for genes exhibiting latitudinal allele frequency differentiation within species and for genes exhibiting recurrent adaptive protein divergence between species. Greater parallelism was observed for long-term adaptive protein evolution and this parallelism includes not only the specific genes/proteins that exhibit adaptive evolution, but extends even to the magnitudes of the selective effects on interspecific protein differences. Thus, despite the roughly 50 million years of time separating D. melanogaster and D. hydei, and despite their considerably divergent biology, they exhibit substantial parallelism, suggesting the existence of a fundamental predictability of adaptive evolution in the genus.

Both local adaptation on short timescales and the long-term accumulation of adaptive differences between species have recently been investigated using comparative genomic and population genomic approaches in several species. However, the repeatability of adaptive evolution at the genetic level is poorly understood. Here we attack this problem by comparing patterns of long and short-term adaptation in Drosophila melanogaster to patterns of adaptation on two timescales in a highly diverged congener, Drosophila hydei. We found, despite the fact that these species diverged from a common ancestor roughly 50 million years ago, the population genomics of latitudinal allele frequency differentiation shows that there is a substantial shared set of genes likely playing a role in the short term adaptive divergence of populations in both species. Analyses of longer-term adaptive protein divergence for the D. hydei-D. mojavensis and D. melanogaster-D. simulans clades reveal a striking level of parallel adaptation. This parallelism includes not only the specific genes/proteins that exhibit adaptive evolution, but extends even to the magnitudes of the selective effects on interspecific protein differences.

Determining the factors driving selective effects of new nonsynonymous mutations

The distribution of fitness effects (DFE) of new mutations plays a fundamental role in evolutionary genetics. However, the extent to which the DFE differs across species has yet to be systematically investigated. Furthermore, the biological mechanisms determining the DFE in natural populations remain unclear. Here, we show that theoretical models emphasizing different biological factors at determining the DFE, such as protein stability, back-mutations, species complexity, and mutational robustness make distinct predictions about how the DFE will differ between species. Analyzing amino acid-changing variants from natural populations in a comparative population genomic framework, we find that humans have a higher proportion of strongly deleterious mutations than Drosophila melanogaster. Furthermore, when comparing the DFE across yeast, Drosophila, mice, and humans, the average selection coefficient becomes more deleterious with increasing species complexity. Last, pleiotropic genes have a DFE that is less variable than that of nonpleiotropic genes. Comparing four categories of theoretical models, only Fisher's geometrical model (FGM) is consistent with our findings. FGM assumes that multiple phenotypes are under stabilizing selection, with the number of phenotypes defining the complexity of the organism. Our results suggest that long-term population size and cost of complexity drive the evolution of the DFE, with many implications for evolutionary and medical genomics.

Population genomics reveals that an anthropophilic population of Aedes aegypti mosquitoes in West Africa recently gave rise to American and Asian populations of this major disease vector

BACKGROUND

The mosquito Aedes aegypti is the main vector of dengue, Zika, chikungunya and yellow fever viruses. This major disease vector is thought to have arisen when the African subspecies Ae. aegypti formosus evolved from being zoophilic and living in forest habitats into a form that specialises on humans and resides near human population centres. The resulting domestic subspecies, Ae. aegypti aegypti, is found throughout the tropics and largely blood-feeds on humans.

RESULTS

To understand this transition, we have sequenced the exomes of mosquitoes collected from five populations from around the world. We found that Ae. aegypti specimens from an urban population in Senegal in West Africa were more closely related to populations in Mexico and Sri Lanka than they were to a nearby forest population. We estimate that the populations in Senegal and Mexico split just a few hundred years ago, and we found no evidence of Ae. aegypti aegypti mosquitoes migrating back to Africa from elsewhere in the tropics. The out-of-Africa migration was accompanied by a dramatic reduction in effective population size, resulting in a loss of genetic diversity and rare genetic variants.

CONCLUSIONS

We conclude that a domestic population of Ae. aegypti in Senegal and domestic populations on other continents are more closely related to each other than to other African populations. This suggests that an ancestral population of Ae. aegypti evolved to become a human specialist in Africa, giving rise to the subspecies Ae. aegypti aegypti. The descendants of this population are still found in West Africa today, and the rest of the world was colonised when mosquitoes from this population migrated out of Africa. This is the first report of an African population of Ae. aegypti aegypti mosquitoes that is closely related to Asian and American populations. As the two subspecies differ in their ability to vector disease, their existence side by side in West Africa may have important implications for disease transmission.

Animal breeding in the (post-) genomic era

One of the benefits of the genomics revolution for animal production will be knowledge of genes that can be used to select more profitable livestock. Although it is possible to use genetic markers linked to genes of economic importance, tests for the genes themselves will be much more successful. Consequently finding genes of economic importance to livestock will be a major research aim for the future. Most traits of economic importance are quantitative traits affected by many genes. Mutations at many genes (e.g. 500) and at many positions within a gene (e.g. 1000 coding and non-coding bases) can affect a typical quantitative trait. The effect of these mutations on phenotype is usually small (e.g. 0·1 standard deviation) but occasionally large. Many mutations are lost from the population through genetic drift and selection, so that polymorphisms exist at only a subset of the relevant genes (e.g. 100 genes). Finding these genes, that have relatively small effects, is more difficult than finding genes for a classical Mendellian trait but, as the genomic tools become more powerful, it is becoming feasible and some successes have already occurred. The standard approach is to map a quantitative trait loci (QTL) to a chromosome region using linkage and linkage disequilibrium. Then test polymorphisms in positional candidate genes for an effect on the trait. Tools such as genomic sequence, EST collections and comparative maps make this approach feasible. Candidate genes can be selected based on functional data such as gene expression obtained from microarrays. At present the gain in rate of genetic improvement from use of DNA-based tests for QTL is small, because selection without them is already quite accurate, not enough QTL have been identified and genotyping is too expensive. However, in the future, with many QTL identified and inexpensive genotyping combined with decreased generation intervals, large gains are possible.

A Genomic Map of the Effects of Linked Selection in Drosophila

Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of "linked selection" on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from 125 lines in Drosophila melanogaster and reliably predict diversity levels at the 1Mb scale. Our results corroborate estimates of a high fraction of beneficial substitutions in proteins and untranslated regions (UTR). They allow us to distinguish between the contribution of sweeps and other modes of selection around amino acid substitutions and to uncover evidence for pervasive sweeps in untranslated regions (UTRs). Our inference further suggests a substantial effect of other modes of linked selection and of adaptation in particular. More generally, we demonstrate that linked selection has had a larger effect in reducing diversity levels and increasing their variance in D. melanogaster than previously appreciated.

Inferring the Frequency Spectrum of Derived Variants to Quantify Adaptive Molecular Evolution in Protein-Coding Genes of Drosophila melanogaster

Many approaches for inferring adaptive molecular evolution analyze the unfolded site frequency spectrum (SFS), a vector of counts of sites with different numbers of copies of derived alleles in a sample of alleles from a population. Accurate inference of the high-copy-number elements of the SFS is difficult, however, because of misassignment of alleles as derived vs. ancestral. This is a known problem with parsimony using outgroup species. Here we show that the problem is particularly serious if there is variation in the substitution rate among sites brought about by variation in selective constraint levels. We present a new method for inferring the SFS using one or two outgroups that attempts to overcome the problem of misassignment. We show that two outgroups are required for accurate estimation of the SFS if there is substantial variation in selective constraints, which is expected to be the case for nonsynonymous sites in protein-coding genes. We apply the method to estimate unfolded SFSs for synonymous and nonsynonymous sites in a population of Drosophila melanogaster from phase 2 of the Drosophila Population Genomics Project. We use the unfolded spectra to estimate the frequency and strength of advantageous and deleterious mutations and estimate that ∼50% of amino acid substitutions are positively selected but that <0.5% of new amino acid mutations are beneficial, with a scaled selection strength of Nes ≈ 12.

Elevated Linkage Disequilibrium and Signatures of Soft Sweeps Are Common in Drosophila melanogaster

The extent to which selection and demography impact patterns of genetic diversity in natural populations of Drosophila melanogaster is yet to be fully understood. We previously observed that linkage disequilibrium (LD) at scales of ∼10 kb in the Drosophila Genetic Reference Panel (DGRP), consisting of 145 inbred strains from Raleigh, North Carolina, measured both between pairs of sites and as haplotype homozygosity, is elevated above neutral demographic expectations. We also demonstrated that signatures of strong and recent soft sweeps are abundant. However, the extent to which these patterns are specific to this derived and admixed population is unknown. It is also unclear whether these patterns are a consequence of the extensive inbreeding performed to generate the DGRP data. Here we analyze LD statistics in a sample of >100 fully-sequenced strains from Zambia; an ancestral population to the Raleigh population that has experienced little to no admixture and was generated by sequencing haploid embryos rather than inbred strains. We find an elevation in long-range LD and haplotype homozygosity compared to neutral expectations in the Zambian sample, thus showing the elevation in LD is not specific to the DGRP data set. This elevation in LD and haplotype structure remains even after controlling for possible confounders including genomic inversions, admixture, population substructure, close relatedness of individual strains, and recombination rate variation. Furthermore, signatures of partial soft sweeps similar to those found in the DGRP as well as partial hard sweeps are common in Zambia. These results suggest that while the selective forces and sources of adaptive mutations may differ in Zambia and Raleigh, elevated long-range LD and signatures of soft sweeps are generic in D. melanogaster.

Codon Usage Selection Can Bias Estimation of the Fraction of Adaptive Amino Acid Fixations

A growing number of molecular evolutionary studies are estimating the proportion of adaptive amino acid substitutions (α) from comparisons of ratios of polymorphic and fixed DNA mutations. Here, we examine how violations of two of the model assumptions, neutral evolution of synonymous mutations and stationary base composition, affect α estimation. We simulated the evolution of coding sequences assuming weak selection on synonymous codon usage bias and neutral protein evolution, α = 0. We show that weak selection on synonymous mutations can give polymorphism/divergence ratios that yield α-hat (estimated α) considerably larger than its true value. Nonstationary evolution (changes in population size, selection, or mutation) can exacerbate such biases or, in some scenarios, give biases in the opposite direction, α-hat < α. These results demonstrate that two factors that appear to be prevalent among taxa, weak selection on synonymous mutations and non-steady-state nucleotide composition, should be considered when estimating α. Estimates of the proportion of adaptive amino acid fixations from large-scale analyses of Drosophila melanogaster polymorphism and divergence data are positively correlated with codon usage bias. Such patterns are consistent with α-hat inflation from weak selection on synonymous mutations and/or mutational changes within the examined gene trees.

Targeted capture in evolutionary and ecological genomics

The rapid expansion of next-generation sequencing has yielded a powerful array of tools to address fundamental biological questions at a scale that was inconceivable just a few years ago. Various genome-partitioning strategies to sequence select subsets of the genome have emerged as powerful alternatives to whole-genome sequencing in ecological and evolutionary genomic studies. High-throughput targeted capture is one such strategy that involves the parallel enrichment of preselected genomic regions of interest. The growing use of targeted capture demonstrates its potential power to address a range of research questions, yet these approaches have yet to expand broadly across laboratories focused on evolutionary and ecological genomics. In part, the use of targeted capture has been hindered by the logistics of capture design and implementation in species without established reference genomes. Here we aim to (i) increase the accessibility of targeted capture to researchers working in nonmodel taxa by discussing capture methods that circumvent the need of a reference genome, (ii) highlight the evolutionary and ecological applications where this approach is emerging as a powerful sequencing strategy and (iii) discuss the future of targeted capture and other genome-partitioning approaches in the light of the increasing accessibility of whole-genome sequencing. Given the practical advantages and increasing feasibility of high-throughput targeted capture, we anticipate an ongoing expansion of capture-based approaches in evolutionary and ecological research, synergistic with an expansion of whole-genome sequencing.

The population genetics of drug resistance evolution in natural populations of viral, bacterial and eukaryotic pathogens

Drug resistance is a costly consequence of pathogen evolution and a major concern in public health. In this review, we show how population genetics can be used to study the evolution of drug resistance and also how drug resistance evolution is informative as an evolutionary model system. We highlight five examples from diverse organisms with particular focus on: (i) identifying drug resistance loci in the malaria parasite Plasmodium falciparum using the genomic signatures of selective sweeps, (ii) determining the role of epistasis in drug resistance evolution in influenza, (iii) quantifying the role of standing genetic variation in the evolution of drug resistance in HIV, (iv) using drug resistance mutations to study clonal interference dynamics in tuberculosis and (v) analysing the population structure of the core and accessory genome of Staphylococcus aureus to understand the spread of methicillin resistance. Throughout this review, we discuss the uses of sequence data and population genetic theory in studying the evolution of drug resistance.

Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution

The prevailing view that the evolution of cells in a tumor is driven by Darwinian selection has never been rigorously tested. Because selection greatly affects the level of intratumor genetic diversity, it is important to assess whether intratumor evolution follows the Darwinian or the non-Darwinian mode of evolution. To provide the statistical power, many regions in a single tumor need to be sampled and analyzed much more extensively than has been attempted in previous intratumor studies. Here, from a hepatocellular carcinoma (HCC) tumor, we evaluated multiregional samples from the tumor, using either whole-exome sequencing (WES) (n = 23 samples) or genotyping (n = 286) under both the infinite-site and infinite-allele models of population genetics. In addition to the many single-nucleotide variations (SNVs) present in all samples, there were 35 "polymorphic" SNVs among samples. High genetic diversity was evident as the 23 WES samples defined 20 unique cell clones. With all 286 samples genotyped, clonal diversity agreed well with the non-Darwinian model with no evidence of positive Darwinian selection. Under the non-Darwinian model, MALL (the number of coding region mutations in the entire tumor) was estimated to be greater than 100 million in this tumor. DNA sequences reveal local diversities in small patches of cells and validate the estimation. In contrast, the genetic diversity under a Darwinian model would generally be orders of magnitude smaller. Because the level of genetic diversity will have implications on therapeutic resistance, non-Darwinian evolution should be heeded in cancer treatments even for microscopic tumors.

Inference of Evolutionary Forces Acting on Human Biological Pathways

Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald-Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects and evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their two-dimensional null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of nonsynonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures.

Inferring natural selection signals in Plasmodium vivax-encoded proteins having a potential role in merozoite invasion

Detecting natural selection signals in Plasmodium parasites antigens might be used for identifying potential new vaccine candidates. Fifty-nine Plasmodium vivax-Sal-I genes encoding proteins having a potential role in invasion were used as query for identifying them in recent P. vivax strain genome sequences and two closely-related Plasmodium species. Several measures of DNA sequence variation were then calculated and selection signatures were detected by using different approaches. Our results may be used for determining which genes expressed during P. vivax merozoite stage could be prioritised for further population genetics or functional studies for designing a P. vivax vaccine which would avoid allele-specific immune responses.

Soft shoulders ahead: spurious signatures of soft and partial selective sweeps result from linked hard sweeps

Characterizing the nature of the adaptive process at the genetic level is a central goal for population genetics. In particular, we know little about the sources of adaptive substitution or about the number of adaptive variants currently segregating in nature. Historically, population geneticists have focused attention on the hard-sweep model of adaptation in which a de novo beneficial mutation arises and rapidly fixes in a population. Recently more attention has been given to soft-sweep models, in which alleles that were previously neutral, or nearly so, drift until such a time as the environment shifts and their selection coefficient changes to become beneficial. It remains an active and difficult problem, however, to tease apart the telltale signatures of hard vs. soft sweeps in genomic polymorphism data. Through extensive simulations of hard- and soft-sweep models, here we show that indeed the two might not be separable through the use of simple summary statistics. In particular, it seems that recombination in regions linked to, but distant from, sites of hard sweeps can create patterns of polymorphism that closely mirror what is expected to be found near soft sweeps. We find that a very similar situation arises when using haplotype-based statistics that are aimed at detecting partial or ongoing selective sweeps, such that it is difficult to distinguish the shoulder of a hard sweep from the center of a partial sweep. While knowing the location of the selected site mitigates this problem slightly, we show that stochasticity in signatures of natural selection will frequently cause the signal to reach its zenith far from this site and that this effect is more severe for soft sweeps; thus inferences of the target as well as the mode of positive selection may be inaccurate. In addition, both the time since a sweep ends and biologically realistic levels of allelic gene conversion lead to errors in the classification and identification of selective sweeps. This general problem of "soft shoulders" underscores the difficulty in differentiating soft and partial sweeps from hard-sweep scenarios in molecular population genomics data. The soft-shoulder effect also implies that the more common hard sweeps have been in recent evolutionary history, the more prevalent spurious signatures of soft or partial sweeps may appear in some genome-wide scans.

Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps

Adaptation from standing genetic variation or recurrent de novo mutation in large populations should commonly generate soft rather than hard selective sweeps. In contrast to a hard selective sweep, in which a single adaptive haplotype rises to high population frequency, in a soft selective sweep multiple adaptive haplotypes sweep through the population simultaneously, producing distinct patterns of genetic variation in the vicinity of the adaptive site. Current statistical methods were expressly designed to detect hard sweeps and most lack power to detect soft sweeps. This is particularly unfortunate for the study of adaptation in species such as Drosophila melanogaster, where all three confirmed cases of recent adaptation resulted in soft selective sweeps and where there is evidence that the effective population size relevant for recent and strong adaptation is large enough to generate soft sweeps even when adaptation requires mutation at a specific single site at a locus. Here, we develop a statistical test based on a measure of haplotype homozygosity (H12) that is capable of detecting both hard and soft sweeps with similar power. We use H12 to identify multiple genomic regions that have undergone recent and strong adaptation in a large population sample of fully sequenced Drosophila melanogaster strains from the Drosophila Genetic Reference Panel (DGRP). Visual inspection of the top 50 candidates reveals that in all cases multiple haplotypes are present at high frequencies, consistent with signatures of soft sweeps. We further develop a second haplotype homozygosity statistic (H2/H1) that, in combination with H12, is capable of differentiating hard from soft sweeps. Surprisingly, we find that the H12 and H2/H1 values for all top 50 peaks are much more easily generated by soft rather than hard sweeps. We discuss the implications of these results for the study of adaptation in Drosophila and in species with large census population sizes.

Evolutionary adaptation is a process in which beneficial mutations increase in frequency in response to selective pressures. If these mutations were previously rare or absent from the population, adaptation should generate a characteristic signature in the genetic diversity around the adaptive locus, known as a selective sweep. Such selective sweeps can be distinguished into hard selective sweeps, where only a single adaptive mutation rises in frequency, or soft selective sweeps, where multiple adaptive mutations at the same locus sweep through the population simultaneously. Here we design a new statistical method that can identify both hard and soft sweeps in population genomic data and apply this method to a Drosophila melanogaster population genomic dataset consisting of 145 sequenced strains collected in North Carolina. We find that selective sweeps were abundant in the recent history of this population. Interestingly, we also find that practically all of the strongest and most recent sweeps show patterns that are more consistent with soft rather than hard sweeps. We discuss the implications of these findings for the discovery and quantification of adaptation from population genomic data in Drosophila and other species with large population sizes.

Decelerated genome evolution in modern vertebrates revealed by analysis of multiple lancelet genomes

Vertebrates diverged from other chordates ~500 Myr ago and experienced successful innovations and adaptations, but the genomic basis underlying vertebrate origins are not fully understood. Here we suggest, through comparison with multiple lancelet (amphioxus) genomes, that ancient vertebrates experienced high rates of protein evolution, genome rearrangement and domain shuffling and that these rates greatly slowed down after the divergence of jawed and jawless vertebrates. Compared with lancelets, modern vertebrates retain, at least relatively, less protein diversity, fewer nucleotide polymorphisms, domain combinations and conserved non-coding elements (CNE). Modern vertebrates also lost substantial transposable element (TE) diversity, whereas lancelets preserve high TE diversity that includes even the long-sought RAG transposon. Lancelets also exhibit rapid gene turnover, pervasive transcription, fastest exon shuffling in metazoans and substantial TE methylation not observed in other invertebrates. These new lancelet genome sequences provide new insights into the chordate ancestral state and the vertebrate evolution.

The lancelet, or amphioxus, is an extant basal chordate that diverged from other chordate lineages about 550 million years ago. Here the authors sequence and assemble the diploid genome of a male adult of the Chinese lancelet, B. belcheri, and highlight genomic features that may have played an important role in the origin and evolution of vertebrates.

Faster-X effects in two Drosophila lineages

Under certain circumstances, X-linked loci are expected to experience more adaptive substitutions than similar autosomal loci. To look for evidence of faster-X evolution, we analyzed the evolutionary rates of coding sequences in two sets of Drosophila species, the melanogaster and pseudoobscura clades, using whole-genome sequences. One of these, the pseudoobscura clade, contains a centric fusion between the ancestral X chromosome and the autosomal arm homologous to 3L in D. melanogaster. This offers an opportunity to study the same loci in both an X-linked and an autosomal context, and to compare these loci with those that are only X-linked or only autosomal. We therefore investigated these clades for evidence of faster-X evolution with respect to nonsynonymous substitutions, finding mixed results. Overall, there was consistent evidence for a faster-X effect in the melanogaster clade, but not in the pseudoobscura clade, except for the comparison between D. pseudoobscura and its close relative, Drosophila persimilis. An analysis of polymorphism data on a set of genes from D. pseudoobscura that evolve rapidly with respect to their protein sequences revealed no evidence for a faster-X effect with respect to adaptive protein sequence evolution; their rapid evolution is instead largely attributable to lower selective constraints. Faster-X evolution in the melanogaster clade was not related to male-biased gene expression; surprisingly, however, female-biased genes showed evidence for faster-X effects, perhaps due to their sexually antagonistic effects in males.