TOWARD A SELECTION THEORY OF MOLECULAR EVOLUTION

Rates of evolution differ between cell types identified by single-cell RNAseq in threespine stickleback

Rates of evolutionary change vary by gene. While some broad gene categories are highly conserved with little divergence over time, others undergo continuous selection pressure and are highly divergent. Here, we combine single-cell RNA sequencing (scRNAseq) with evolutionary genomics to understand whether certain cell types exhibit faster evolutionary divergence (using their characteristic genes), than other types of cells. Merging scRNAseq with population genomic data, we show that cell types differ in the rate at which their characteristic genes evolve, as measured by allele frequency divergence among many populations (F ST ) and between species (dN/dS ratios). Neutrophils, B cells, and fibroblasts exhibit elevated F ST at characteristic genes, while eosinophils in the intestine and thrombocytes in the head kidney exhibit lower F ST than the average for 1000 random genes. Gene network centrality also differed between immune- and non-immune-associated genes, and closeness centrality was positively related to gene F ST . These results highlight the value of merging single cell RNA sequencing technology with evolutionary population genomic data, and reveal that genes which define immune cell types exhibit especially rapid evolution.

Genome-wide relaxation of selection and the evolution of the island syndrome in Orkney voles

Island populations often experience different ecological and demographic conditions than their counterparts on the continent, resulting in divergent evolutionary forces affecting their genomes. Random genetic drift and selection both may leave their imprints on island populations, although the relative impact depends strongly on the specific conditions. Here we address their contributions to the island syndrome in a rodent with an unusually clear history of isolation. Common voles (Microtus arvalis) were introduced by humans on the Orkney archipelago north of Scotland >5000 years ago and rapidly evolved to exceptionally large size. Our analyses show that the genomes of Orkney voles were dominated by genetic drift, with extremely low diversity, variable Tajima's D, and very high divergence from continental conspecifics. Increased d N/d S ratios over a wide range of genes in Orkney voles indicated genome-wide relaxation of purifying selection. We found evidence of hard sweeps on key genes of the lipid metabolism pathway only in continental voles. The marked increase of body size in Orkney-a typical phenomenon of the island syndrome-may thus be associated to the relaxation of positive selection on genes related to this pathway. On the other hand, a hard sweep on immune genes of Orkney voles likely reflects the divergent ecological conditions and possibly the history of human introduction. The long-term isolated Orkney voles show that adaptive changes may still impact the evolutionary trajectories of such populations despite the pervasive consequences of genetic drift at the genome level.

An efficient and robust ABC approach to infer the rate and strength of adaptation

Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in nonmodel species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to nonmodel genomes. We apply ABC-MK to the human proteome and a set of known virus interacting proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.

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?

Allelic gene conversion softens selective sweeps

The prominence of positive selection, in which beneficial mutations are favored by natural selection and rapidly increase in frequency, is a subject of intense debate. Positive selection can result in selective sweeps, in which the haplotype(s) bearing the adaptive allele "sweep" through the population, thereby removing much of the genetic diversity from the region surrounding the target of selection. Two models of selective sweeps have been proposed: classical sweeps, or "hard sweeps", in which a single copy of the adaptive allele sweeps to fixation, and "soft sweeps", in which multiple distinct copies of the adaptive allele leave descendants after the sweep. Soft sweeps can be the outcome of recurrent mutation to the adaptive allele, or the presence of standing genetic variation consisting of multiple copies of the adaptive allele prior to the onset of selection. Importantly, soft sweeps will be common when populations can rapidly adapt to novel selective pressures, either because of a high mutation rate or because adaptive alleles are already present. The prevalence of soft sweeps is especially controversial, and it has been noted that selection on standing variation or recurrent mutations may not always produce soft sweeps. Here, we show that the inverse is true: selection on single-origin de novo mutations may often result in an outcome that is indistinguishable from a soft sweep. This is made possible by allelic gene conversion, which "softens" hard sweeps by copying the adaptive allele onto multiple genetic backgrounds, a process we refer to as a "pseudo-soft" sweep. We carried out a simulation study examining the impact of gene conversion on sweeps from a single de novo variant in models of human, Drosophila, and Arabidopsis populations. The fraction of simulations in which gene conversion had produced multiple haplotypes with the adaptive allele upon fixation was appreciable. Indeed, under realistic demographic histories and gene conversion rates, even if selection always acts on a single-origin mutation, sweeps involving multiple haplotypes are more likely than hard sweeps in large populations, especially when selection is not extremely strong. Thus, even when the mutation rate is low or there is no standing variation, hard sweeps are expected to be the exception rather than the rule in large populations. These results also imply that the presence of signatures of soft sweeps does not necessarily mean that adaptation has been especially rapid or is not mutation limited.

An efficient and robust ABC approach to infer the rate and strength of adaptation

Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in non-model species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to non-model genomes. We apply ABC-MK to the human proteome and a set of known Virus Interacting Proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.

A few essential genetic loci distinguish Penstemon species with flowers adapted to pollination by bees or hummingbirds

In the formation of species, adaptation by natural selection generates distinct combinations of traits that function well together. The maintenance of adaptive trait combinations in the face of gene flow depends on the strength and nature of selection acting on the underlying genetic loci. Floral pollination syndromes exemplify the evolution of trait combinations adaptive for particular pollinators. The North American wildflower genus Penstemon displays remarkable floral syndrome convergence, with at least 20 separate lineages that have evolved from ancestral bee pollination syndrome (wide blue-purple flowers that present a landing platform for bees and small amounts of nectar) to hummingbird pollination syndrome (bright red narrowly tubular flowers offering copious nectar). Related taxa that differ in floral syndrome offer an attractive opportunity to examine the genomic basis of complex trait divergence. In this study, we characterized genomic divergence among 229 individuals from a Penstemon species complex that includes both bee and hummingbird floral syndromes. Field plants are easily classified into species based on phenotypic differences and hybrids displaying intermediate floral syndromes are rare. Despite unambiguous phenotypic differences, genome-wide differentiation between species is minimal. Hummingbird-adapted populations are more genetically similar to nearby bee-adapted populations than to geographically distant hummingbird-adapted populations, in terms of genome-wide dXY. However, a small number of genetic loci are strongly differentiated between species. These approximately 20 "species-diagnostic loci," which appear to have nearly fixed differences between pollination syndromes, are sprinkled throughout the genome in high recombination regions. Several map closely to previously established floral trait quantitative trait loci (QTLs). The striking difference between the diagnostic loci and the genome as whole suggests strong selection to maintain distinct combinations of traits, but with sufficient gene flow to homogenize the genomic background. A surprisingly small number of alleles confer phenotypic differences that form the basis of species identity in this species complex.

Timesweeper: accurately identifying selective sweeps using population genomic time series

Despite decades of research, identifying selective sweeps, the genomic footprints of positive selection, remains a core problem in population genetics. Of the myriad methods that have been developed to tackle this task, few are designed to leverage the potential of genomic time-series data. This is because in most population genetic studies of natural populations, only a single period of time can be sampled. Recent advancements in sequencing technology, including improvements in extracting and sequencing ancient DNA, have made repeated samplings of a population possible, allowing for more direct analysis of recent evolutionary dynamics. Serial sampling of organisms with shorter generation times has also become more feasible due to improvements in the cost and throughput of sequencing. With these advances in mind, here we present Timesweeper, a fast and accurate convolutional neural network-based tool for identifying selective sweeps in data consisting of multiple genomic samplings of a population over time. Timesweeper analyzes population genomic time-series data by first simulating training data under a demographic model appropriate for the data of interest, training a one-dimensional convolutional neural network on said simulations, and inferring which polymorphisms in this serialized data set were the direct target of a completed or ongoing selective sweep. We show that Timesweeper is accurate under multiple simulated demographic and sampling scenarios, identifies selected variants with high resolution, and estimates selection coefficients more accurately than existing methods. In sum, we show that more accurate inferences about natural selection are possible when genomic time-series data are available; such data will continue to proliferate in coming years due to both the sequencing of ancient samples and repeated samplings of extant populations with faster generation times, as well as experimentally evolved populations where time-series data are often generated. Methodological advances such as Timesweeper thus have the potential to help resolve the controversy over the role of positive selection in the genome. We provide Timesweeper as a Python package for use by the community.

On the effects of selection and mutation on species tree inference

The effect of selection acting on regions of the genome on the accuracy of species-level phylogenetic inference using methods that do not explicitly model selection is an open question that is relevant to most, if not all, phylogenomic studies. To address this, we derive a mathematical approximation to the Wright-Fisher model with mutation and selection in the limit as the population size becomes large. In contrast to previous approximations based on diffusion processes, our approximation can be used to study the distribution of coalescent times for an arbitrary number of lineages, allowing calculation of the probability distribution of gene genealogies under the coalescent model. We use these calculations to show that direct selection at strengths typically encountered in practice has only a small effect on the distribution of coalescent times, and hence on the distribution of gene trees. This implies that many coalescent-based methods for estimating the species tree topology will be robust to the presence of selection in a subset of the underlying genes. Selection will, however, bias the estimation of speciation times, causing them to underestimate the true speciation times. Our model captures the effects of selection on the genealogies that generate the observed sequence data, but does not model selective pressures that act only on the subsequent sequences or that negatively impact gene tree estimation.

dN/dS-H, a New Test to Distinguish Different Selection Modes in Protein Evolution and Cancer Evolution

One of the most popular measures in the analysis of protein sequence evolution is the ratio of nonsynonymous distance (d_N) to synonymous distance (d_S). Under the assumption that synonymous substitutions in the coding region are selectively neutral, the d_N/d_S ratio can be used to statistically detect the adaptive evolution (or purifying selection) if d_N/d_S > 1 (or d_N/d_S < 1) significantly. However, due to strong structural constraints and/or variable functional constraints imposed on amino acid sites, most encoding genes in most species have demonstrated d_N/d_S < 1. Consequently, the statistical power for testing d_N/d_S = 1 may be insufficient to distinguish between different selection modes. In this paper, we propose a more powerful test, called d_N/d_S-H, in which a new parameter H, a relative measure of rate variation among sites, was introduced. Given the condition of strong purifying selections at some sites, the d_N/d_S-H model predicts d_N/d_S = 1-H for neutral evolution, d_N/d_S < 1-H for nearly neutral selection, and d_N/d_S > 1-H for adaptive evolution. The potential of this new method for resolving the neutral-adaptive debates is illustrated by the protein sequence evolution in vertebrates, Drosophila and yeasts, as well as somatic cancer evolution (specialized as the C_N/C_S-H test).

Strong neutral sweeps occurring during a population contraction

A strong reduction in diversity around a specific locus is often interpreted as a recent rapid fixation of a positively selected allele, a phenomenon called a selective sweep. Rapid fixation of neutral variants can however lead to a similar reduction in local diversity, especially when the population experiences changes in population size, e.g. bottlenecks or range expansions. The fact that demographic processes can lead to signals of nucleotide diversity very similar to signals of selective sweeps is at the core of an ongoing discussion about the roles of demography and natural selection in shaping patterns of neutral variation. Here, we quantitatively investigate the shape of such neutral valleys of diversity under a simple model of a single population size change, and we compare it to signals of a selective sweep. We analytically describe the expected shape of such "neutral sweeps" and show that selective sweep valleys of diversity are, for the same fixation time, wider than neutral valleys. On the other hand, it is always possible to parametrize our model to find a neutral valley that has the same width as a given selected valley. Our findings provide further insight into how simple demographic models can create valleys of genetic diversity similar to those attributed to positive selection.

Population structure and adaptive variation of Helichrysum italicum (Roth) G. Don along eastern Adriatic temperature and precipitation gradient

Immortelle (Helichrysum italicum (Roth) G. Don; Asteraceae) is a perennial plant species native to the Mediterranean region, known for many properties with wide application mainly in perfume and cosmetic industry. A total of 18 wild H. italicum populations systematically sampled along the eastern Adriatic environmental gradient were studied using AFLP markers to determine genetic diversity and structure and to identify loci potentially responsible for adaptive divergence. Results showed higher levels of intrapopulation diversity than interpopulation diversity. Genetic differentiation among populations was significant but low, indicating extensive gene flow between populations. Bayesian analysis of population structure revealed the existence of two genetic clusters. Combining the results of F_ST - outlier analysis (Mcheza and BayeScan) and genome-environment association analysis (Samβada, LFMM) four AFLP loci strongly associated with the bioclimatic variables Bio03 Isothermality, Bio08 Mean temperature of the wettest quarter, Bio15 Precipitation seasonality, and Bio17 Precipitation of driest quarter were found to be the main variables driving potential adaptive genetic variation in H. italicum along the eastern Adriatic environmental gradient. Redundancy analysis revealed that the partitioning of genetic variation was mainly associated with the adaptation to temperature oscillations. The results of the research may contribute to a clearer understanding of the importance of local adaptations for the genetic differentiation of Mediterranean plants and allow the planning of appropriate conservation strategies. However, considering that the identified outlier loci may be linked to genes under selection rather than being the target of natural selection, future studies must aim at their additional analysis.

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.

Random Penetrance of Mutations Among Individuals: A New Type of Genetic Drift in Molecular Evolution

The determinative view of mutation penetrance is a fundamental assumption for the building of molecular evolutionary theory: individuals in the population with the same genotype have the same fitness effect. Since this view has been constantly challenged by experimental evidence, it is desirable to examine to what extent violation of this view could affect our understanding of molecular evolution. To this end, the author formulated a new theory of molecular evolution under a random model of penetrance: for any individual with the same mutational genotype, the coefficient of selection is a random variable. It follows that, in addition to the conventional N _e-genetic drift (N _e is the effective population size), the variance of penetrance among individuals (ε ²) represents a new type of genetic drift, coined by the ε ²-genetic drift. It has been demonstrated that these two genetic drifts together provided new insights on the nearly neutral evolution: the evolutionary rate is inversely related to the log-of-N _e when the ε ²-genetic drift is nontrivial. This log-of-N _e feature of ε ²-genetic drift did explain well why the d _N /d _S ratio (the nonsynonymous rate to the synonymous rate) in humans is only as twofold as that in mice, while the effective population size (N _e) of mice is about two-magnitude larger than that of humans. It was estimated that, for the first time, the variance of random penetrance in mammalian genes was approximately ε ²≈ 5.89 × 10^-3.

The signals of selective constraints on the mitochondrial non-coding control region: insights from comparative mitogenomics of Clupeoid fishes

The vertebrate mitochondrial genome is characterized by an exceptional organization evolving towards a reduced size. However, the persistence of a non-coding and highly variable control region is against this evolutionary trend that is explained by the presence of conserved sequence motifs or binding sites for nuclear-organized proteins that regulate mtDNA maintenance and expression. We performed a comparative mitogenomic investigation of the non-coding control region to understand its evolutionary patterns in Clupeoid fishes which are widely distributed across oceans of the world, exhibiting exemplary evolutionary potential. We confirmed the ability of sequence flanking the conserved sequence motifs in the control region to form stable secondary structures. The existence of evolutionarily conserved secondary structures without primary structure conservation suggested the action of selective constraints towards maintaining the secondary structure. The functional secondary structure is maintained by retaining the frequency of discontinuous AT and TG repeats along with compensatory base substitutions in the stem forming regions which can be considered as a selective constraint. The nucleotide polymorphism along the flanking regions of conserved sequence motifs can be explained as errors during the enzymatic replication of secondary structure-forming repeat elements. The evidence for selective constraints on secondary structures emphasizes the role of the control region in mitogenome function. Maintenance of high frequency of discontinuous repeats can be proposed as a model of adaptive evolution against the mutations that break the secondary structure involved in the efficient regulation of mtDNA functions substantiating the efficient functioning of the control region even in a high nucleotide polymorphism environment.

Genetic-variant hotspots and hotspot clusters in the human genome facilitating adaptation while increasing instability

Background

Genetic variants, underlining phenotypic diversity, are known to distribute unevenly in the human genome. A comprehensive understanding of the distributions of different genetic variants is important for insights into genetic functions and disorders.

Methods

Herein, a sliding-window scan of regional densities of eight kinds of germline genetic variants, including single-nucleotide-polymorphisms (SNPs) and four size-classes of copy-number-variations (CNVs) in the human genome has been performed.

Results

The study has identified 44,379 hotspots with high genetic-variant densities, and 1135 hotspot clusters comprising more than one type of hotspots, accounting for 3.1% and 0.2% of the genome respectively. The hotspots and clusters are found to co-localize with different functional genomic features, as exemplified by the associations of hotspots of middle-size CNVs with histone-modification sites, work with balancing and positive selections to meet the need for diversity in immune proteins, and facilitate the development of sensory-perception and neuroactive ligand-receptor interaction pathways in the function-sparse late-replicating genomic sequences. Genetic variants of different lengths co-localize with retrotransposons of different ages on a “long-with-young” and “short-with-all” basis. Hotspots and clusters are highly associated with tumor suppressor genes and oncogenes (p < 10⁻¹⁰), and enriched with somatic tumor CNVs and the trait- and disease-associated SNPs identified by genome-wise association studies, exceeding tenfold enrichment in clusters comprising SNPs and extra-long CNVs.

Conclusions

In conclusion, the genetic-variant hotspots and clusters represent two-edged swords that spearhead both positive and negative genomic changes. Their strong associations with complex traits and diseases also open up a potential “Common Disease-Hotspot Variant” approach to the missing heritability problem.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00318-3.

A population-genomic approach for estimating selection on polygenic traits in heterogeneous environments

Strong selection can cause rapid evolutionary change, but temporal fluctuations in the form, direction and intensity of selection can limit net evolutionary change over longer time periods. Fluctuating selection could affect molecular diversity levels and the evolution of plasticity and ecological specialization. Nonetheless, this phenomenon remains understudied, in part because of analytical limitations and the general difficulty of detecting selection that does not occur in a consistent manner. Herein, I fill this analytical gap by presenting an approximate Bayesian computation (ABC) method to detect and quantify fluctuating selection on polygenic traits from population genomic time-series data. I propose a model for environment-dependent phenotypic selection. The evolutionary genetic consequences of selection are then modelled based on a genotype-phenotype map. Using simulations, I show that the proposed method generates accurate and precise estimates of selection when the generative model for the data is similar to the model assumed by the method. The performance of the method when applied to an evolve-and-resequence study of host adaptation in the cowpea seed beetle (Callosobruchus maculatus) was more idiosyncratic and depended on specific analytical choices. Despite some limitations, these results suggest the proposed method provides a powerful approach to connect the causes of (variable) selection to traits and genome-wide patterns of evolution. Documentation and open-source computer software (fsabc) implementing this method are available from github (https://github.com/zgompert/fsabc.git).

Retrotransposons and the Evolution of Genome Size in Pisum

Here we investigate the plant population genetics of retrotransposon insertion sites in pea to find out whether genetic drift and the neutral theory of molecular evolution can account for their abundance in the pea genome. (1) We asked whether two contrasting types of pea LTR-containing retrotransposons have the frequency and age distributions consistent with the behavior of neutral alleles and whether these parameters can explain the rate of change of genome size in legumes. (2) We used the recently assembled v1a pea genome sequence to obtain data on LTR-LTR divergence from which their age can be estimated. We coupled these data to prior information on the distribution of insertion site alleles. (3) We found that the age and frequency distribution data are consistent with the neutral theory. (4) We concluded that demographic processes are the underlying cause of genome size variation in legumes.

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.

The evolution of metabolism: How to test evolutionary hypotheses at the genomic level

The origin of primordial metabolism and its expansion to form the metabolic networks extant today represent excellent systems to study the impact of natural selection and the potential adaptive role of novel compounds. Here we present the current hypotheses made on the origin of life and ancestral metabolism and present the theories and mechanisms by which the large chemical diversity of plants might have emerged along evolution. In particular, we provide a survey of statistical methods that can be used to detect signatures of selection at the gene and population level, and discuss potential and limits of these methods for investigating patterns of molecular adaptation in plant metabolism.

Molecular Evolution of the Glutathione S-Transferase Family in the Bemisia tabaci Species Complex

The glutathione S-transferase (GST) family plays an important role in the adaptation of herbivorous insects to new host plants and other environmental constrains. The family codes for enzymes that neutralize reactive oxygen species and phytotoxins through the conjugation of reduced glutathione. Here, we studied the molecular evolution of the GST family in Bemisia tabaci, a complex of >35 sibling species, differing in their geographic and host ranges. We tested if some enzymes evolved different functionality, by comparing their sequences in six species, representing five of the six major genetic clades in the complex. Comparisons of the nonsynonymous to synonymous substitution ratios detected positive selection events in 11 codons of 5 cytosolic GSTs. Ten of them are located in the periphery of the GST dimer, suggesting a putative involvement in interactions with other proteins. Modeling the tertiary structure of orthologous enzymes, identified additional 19 mutations in 9 GSTs, likely affecting the enzymes' functionality. Most of the mutation events were found in the environmentally responsive classes Delta and Sigma, indicating a slightly different delta/sigma tool box in each species. At a broader genomic perspective, our analyses indicated a significant expansion of the Delta GST class in B. tabaci and a general association between the diet breadth of hemipteran species and their total number of GST genes. We raise the possibility that at least some of the identified changes improve the fitness of the B. tabaci species carrying them, leading to their better adaptation to specific environments.

Divergent selection and genetic structure of Sideritis scardica populations from southern Balkan Peninsula as revealed by AFLP fingerprinting

Sideritis scardica Giseb. is a subalpine/alpine plant species endemic to the central part of the Balkan Peninsula. In this study, we combined Amplified Fragment Length Polymorphism (AFLP) and environmental data to examine the adaptive genetic variations in S. scardica natural populations sampled in contrasting environments. A total of 226 AFLP loci were genotyped in 166 individuals from nine populations. The results demonstrated low gene diversity, ranging from 0.095 to 0.133 and significant genetic differentiation ranging from 0.115 to 0.408. Seven genetic clusters were revealed by Bayesian clustering methods as well as by Discriminant Analysis of Principal Components and each population formed its respective cluster. The exception were populations P02 Mt. Shara and P07 Mt. Vermio, that were admixed between two clusters. Both landscape genetic methods Mcheza and BayeScan identified a total of seven (3.10%) markers exhibiting higher levels of genetic differentiation among populations. The spatial analysis method Samβada detected 50 individual markers (22.12%) associated with bioclimatic variables, among them seven were identified by both Mcheza and BayeScan as being under directional selection. Four bioclimatic variables associated with five out of seven outliers were related to precipitation, suggesting that this variable is the key factor affecting the adaptive variation of S. scardica.

Selection, Linkage, and Population Structure Interact To Shape Genetic Variation Among Threespine Stickleback Genomes

The outcome of selection on genetic variation depends on the geographic organization of individuals and populations as well as the organization of loci within the genome. Spatially variable selection between marine and freshwater habitats has had a significant and heterogeneous impact on patterns of genetic variation across the genome of threespine stickleback fish. When marine stickleback invade freshwater habitats, more than a quarter of the genome can respond to divergent selection, even in as little as 50 years. This process largely uses standing genetic variation that can be found ubiquitously at low frequency in marine populations, can be millions of years old, and is likely maintained by significant bidirectional gene flow. Here, we combine population genomic data of marine and freshwater stickleback from Cook Inlet, Alaska, with genetic maps of stickleback fish derived from those same populations to examine how linkage to loci under selection affects genetic variation across the stickleback genome. Divergent selection has had opposing effects on linked genetic variation on chromosomes from marine and freshwater stickleback populations: near loci under selection, marine chromosomes are depauperate of variation, while these same regions among freshwater genomes are the most genetically diverse. Forward genetic simulations recapitulate this pattern when different selective environments also differ in population structure. Lastly, dense genetic maps demonstrate that the interaction between selection and population structure may impact large stretches of the stickleback genome. These findings advance our understanding of how the structuring of populations across geography influences the outcomes of selection, and how the recombination landscape broadens the genomic reach of selection.

Widespread selection and gene flow shape the genomic landscape during a radiation of monkeyflowers

Speciation genomic studies aim to interpret patterns of genome-wide variation in light of the processes that give rise to new species. However, interpreting the genomic "landscape" of speciation is difficult, because many evolutionary processes can impact levels of variation. Facilitated by the first chromosome-level assembly for the group, we use whole-genome sequencing and simulations to shed light on the processes that have shaped the genomic landscape during a radiation of monkeyflowers. After inferring the phylogenetic relationships among the 9 taxa in this radiation, we show that highly similar diversity (π) and differentiation (FST) landscapes have emerged across the group. Variation in these landscapes was strongly predicted by the local density of functional elements and the recombination rate, suggesting that the landscapes have been shaped by widespread natural selection. Using the varying divergence times between pairs of taxa, we show that the correlations between FST and genome features arose almost immediately after a population split and have become stronger over time. Simulations of genomic landscape evolution suggest that background selection (BGS; i.e., selection against deleterious mutations) alone is too subtle to generate the observed patterns, but scenarios that involve positive selection and genetic incompatibilities are plausible alternative explanations. Finally, tests for introgression among these taxa reveal widespread evidence of heterogeneous selection against gene flow during this radiation. Combined with previous evidence for adaptation in this system, we conclude that the correlation in FST among these taxa informs us about the processes contributing to adaptation and speciation during a rapid radiation.

Lipidome Evolution in Mammalian Tissues

Lipids are essential structural and functional components of cells. Little is known, however, about the evolution of lipid composition in different tissues. Here, we report a large-scale analysis of the lipidome evolution in six tissues of 32 species representing primates, rodents, and bats. While changes in genes’ sequence and expression accumulate proportionally to the phylogenetic distances, <2% of the lipidome evolves this way. Yet, lipids constituting this 2% cluster in specific functions shared among all tissues. Among species, human show the largest amount of species-specific lipidome differences. Many of the uniquely human lipidome features localize in the brain cortex and cluster in specific pathways implicated in cognitive disorders.

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.

Effects of life history and ecology on virus evolutionary potential

The life history traits of viruses pose many consequences for viral population structure. In turn, population structure may influence the evolutionary trajectory of a virus. Here we review factors that affect the evolutionary potential of viruses, including rates of mutation and recombination, bottlenecks, selection pressure, and ecological factors such as the requirement for hosts and vectors. Mutation, while supplying a pool of raw genetic material, also results in the generation of numerous unfit mutants. The infection of multiple host species may expand a virus' ecological niche, although it may come at a cost to genetic diversity. Vector-borne viruses often experience a diminished frequency of positive selection and exhibit little diversity, and resistance against vector-borne viruses may thus be more durable than against non-vectored viruses. Evidence indicates that adaptation to a vector is more evolutionarily difficult than adaptation to a host. Overall, a better understanding of how various factors influence viral dynamics in both plant and animal pathosystems will lead to more effective anti-viral treatments and countermeasures.

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.

Random Genetic Drift and Selective Pressures Shaping the Blattabacterium Genome

Estimates suggest that at least half of all extant insect genera harbor obligate bacterial mutualists. Whereas an endosymbiotic relationship imparts many benefits upon host and symbiont alike, the intracellular lifestyle has profound effects on the bacterial genome. The obligate endosymbiont genome is a product of opposing forces: genes important to host survival are maintained through physiological constraint, contrasted by the fixation of deleterious mutations and genome erosion through random genetic drift. The obligate cockroach endosymbiont, Blattabacterium - providing nutritional augmentation to its host in the form of amino acid synthesis - displays radical genome alterations when compared to its most recent free-living relative Flavobacterium. To date, eight Blattabacterium genomes have been published, affording an unparalleled opportunity to examine the direction and magnitude of selective forces acting upon this group of symbionts. Here, we find that the Blattabacterium genome is experiencing a 10-fold increase in selection rate compared to Flavobacteria. Additionally, the proportion of selection events is largely negative in direction, with only a handful of loci exhibiting signatures of positive selection. These findings suggest that the Blattabacterium genome will continue to erode, potentially resulting in an endosymbiont with an even further reduced genome, as seen in other insect groups such as Hemiptera.

Repeated Selection of Alternatively Adapted Haplotypes Creates Sweeping Genomic Remodeling in Stickleback

Heterogeneous genetic divergence can accumulate across the genome when populations adapt to different habitats while still exchanging alleles. How long does diversification take and how much of the genome is affected? When divergence occurs in parallel from standing genetic variation, how often are the same haplotypes involved? We explore these questions using restriction site-associated DNA sequencing genotyping data and show that broad-scale genomic repatterning, fueled by copious standing variation, can emerge in just dozens of generations in replicate natural populations of threespine stickleback fish (Gasterosteus aculeatus). After the catastrophic 1964 Alaskan earthquake, marine stickleback colonized newly created ponds on seismically uplifted islands. We find that freshwater fish in these young ponds differ from their marine ancestors across the same genomic segments previously shown to have diverged in much older lake populations. Outside of these core divergent regions the genome shows no population structure across the ocean-freshwater divide, consistent with strong local selection acting in alternative environments on stickleback populations still connected by significant gene flow. Reinforcing this inference, a majority of divergent haplotypes that are at high frequency in ponds are detectable in the sea, even across great geographic distances. Building upon previous population genomics work in this model species, our data suggest that a long history of divergent selection and gene flow among stickleback populations in oceanic and freshwater habitats has maintained polymorphisms of alternatively adapted DNA sequences that facilitate parallel evolution.

Habitat Association Predicts Genetic Diversity and Population Divergence in Amazonian Birds

The ecological traits of organisms may predict their genetic diversity and population genetic structure and mediate the action of evolutionary processes important for speciation and adaptation. Making these ecological-evolutionary links is difficult because it requires comparable genetic estimates from many species with differing ecologies. In Amazonian birds, habitat association is an important component of ecological diversity. Here, we examine the link between habitat association and genetic parameters using 20 pairs of closely related Amazonian bird species in which one member of the pair occurs primarily in forest edge and floodplains and the other occurs in upland forest interior. We use standardized geographic sampling and data from 2,416 genomic markers to estimate genetic diversity, population genetic structure, and statistics reflecting demographic and evolutionary processes. We find that species of upland forest have greater genetic diversity and divergence across the landscape as well as signatures of older histories and less gene flow than floodplain species. Our results reveal that species ecology in the form of habitat association is an important predictor of genetic diversity and population divergence and suggest that differences in diversity between floodplain and upland avifaunas in the Amazon may be driven by differences in the demographic and evolutionary processes at work in the two habitats.

Extreme Mitogenomic Variation in Natural Populations of Chaetognaths

The extent of within-species genetic variation across the diversity of animal life is an underexplored problem in ecology and evolution. Although neutral genetic variation should scale positively with population size, mitochondrial diversity levels are believed to show little variation across animal species. Here, we report an unprecedented case of extreme mitochondrial diversity within natural populations of two morphospecies of chaetognaths (arrow worms). We determine that this diversity is composed of deep sympatric mitochondrial lineages, which are in some cases as divergent as human and platypus. Additionally, based on 54 complete mitogenomes, we observed mitochondrial gene order differences between several of these lineages. We examined nuclear divergence patterns (18S, 28S, and an intron) to determine the possible origin of these lineages, but did not find congruent patterns between mitochondrial and nuclear markers. We also show that extreme mitochondrial divergence in chaetognaths is not driven by positive selection. Hence, we propose that the extreme levels of mitochondrial variation could be the result of either a complex scenario of reproductive isolation, or a combination of large population size and accelerated mitochondrial mutation rate. These findings emphasize the importance of characterizing genome-wide levels of nuclear variation in these species and promote chaetognaths as a remarkable model to study mitochondrial evolution.

Contrasting patterns of nucleotide polymorphism suggest different selective regimes within different parts of the PgiC1 gene in Festuca ovina L

Background

Phosphoglucose isomerase (PGI, EC 5.3.1.9) is an essential metabolic enzyme in all eukaryotes. An earlier study of the PgiC1 gene, which encodes cytosolic PGI in the grass Festuca ovina L., revealed a marked difference in the levels of nucleotide polymorphism between the 5’ and 3’ portions of the gene.

Methods

In the present study, we characterized the sequence polymorphism in F. ovina PgiC1 in more detail and examined possible explanations for the non-uniform pattern of nucleotide polymorphism across the gene.

Results

Our study confirms that the two portions of the PgiC1 gene show substantially different levels of DNA polymorphism and also suggests that the peptide encoded by the 3’ portion of PgiC1 is functionally and structurally more important than that encoded by the 5’ portion. Although there was some evidence of purifying selection (d_N/d_S test) on the 5’ portion of the gene, the signature of purifying selection was considerably stronger on the 3’ portion of the gene (d_N/d_S and McDonald–Kreitman tests). Several tests support the action of balancing selection within the 5’ portion of the gene. Wall’s B and Q tests were significant only for the 5’ portion of the gene. There were also marked peaks of nucleotide diversity, Tajima’s D and the d_N/d_S ratio at or around a PgiC1 codon site (within the 5’ portion of the gene) that a previous study had suggested was subject to positive diversifying selection.

Conclusions

Our results suggest that the two portions of the gene have been subject to different selective regimes. Purifying selection appears to have been the main force contributing to the relatively low level of polymorphism within the 3’ portion of the sequence. In contrast, it is possible that balancing selection has contributed to the maintenance of the polymorphism within the 5’ portion of the gene.

Electronic supplementary material

The online version of this article (doi:10.1186/s41065-017-0032-6) contains supplementary material, which is available to authorized users.

Molecular Population Genetics

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data.

The Selective Maintenance of Allelic Variation Under Generalized Dominance

Simple models of viability selection acting on variation at a single diploid locus only maintain multiple alleles for very restricted sets of fitnesses. Most of these models assume that fitnesses are independent, even if the genotypes share alleles. Here, we extend this result to a model with generalized dominance interactions, in which fitnesses are strongly affected by what we call the “primary effects” of the genotype’s component alleles, so that genotypes with shared alleles have correlated fitnesses. Nevertheless, in keeping with previously reported results, we also show that such fitness sets are easily constructed over time if recurrent mutation is occurring simultaneously. We find that such models maintain less variation over time than do (previous) models with independently sampled fitnesses, especially when the effects of genetic drift are taken into account. We also show that there is a weak tendency for greater weighting of primary effects to evolve over time.

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

The availability of large-scale population genomic sequence data has resulted in an explosion in efforts to infer the demographic histories of natural populations across a broad range of organisms. As demographic events alter coalescent genealogies, they leave detectable signatures in patterns of genetic variation within and between populations. Accordingly, a variety of approaches have been designed to leverage population genetic data to uncover the footprints of demographic change in the genome. The vast majority of these methods make the simplifying assumption that the measures of genetic variation used as their input are unaffected by natural selection. However, natural selection can dramatically skew patterns of variation not only at selected sites, but at linked, neutral loci as well. Here we assess the impact of recent positive selection on demographic inference by characterizing the performance of three popular methods through extensive simulation of data sets with varying numbers of linked selective sweeps. In particular, we examined three different demographic models relevant to a number of species, finding that positive selection can bias parameter estimates of each of these models-often severely. We find that selection can lead to incorrect inferences of population size changes when none have occurred. Moreover, we show that linked selection can lead to incorrect demographic model selection, when multiple demographic scenarios are compared. We argue that natural populations may experience the amount of recent positive selection required to skew inferences. These results suggest that demographic studies conducted in many species to date may have exaggerated the extent and frequency of population size changes.

A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations

Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20) SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure), particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur) and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among chromosomes in the Uyghur, with a large region of excess French ancestry harboring a gene with a known disease association. Similar variation was detected in the mouse hybrid zone, with notable constancy in regions of excess ancestry among admixed populations. By filling what has been an analytical gap, the proposed method should be a useful tool for many biologists. A computer program (popanc), written in C++, has been developed based on the proposed method and is available on-line at http://sourceforge.net/projects/popanc/.

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.

Detecting spatial genetic signatures of local adaptation in heterogeneous landscapes

The spatial structure of the environment (e.g. the configuration of habitat patches) may play an important role in determining the strength of local adaptation. However, previous studies of habitat heterogeneity and local adaptation have largely been limited to simple landscapes, which poorly represent the multiscale habitat structure common in nature. Here, we use simulations to pursue two goals: (i) we explore how landscape heterogeneity, dispersal ability and selection affect the strength of local adaptation, and (ii) we evaluate the performance of several genotype-environment association (GEA) methods for detecting loci involved in local adaptation. We found that the strength of local adaptation increased in spatially aggregated selection regimes, but remained strong in patchy landscapes when selection was moderate to strong. Weak selection resulted in weak local adaptation that was relatively unaffected by landscape heterogeneity. In general, the power of detection methods closely reflected levels of local adaptation. False-positive rates (FPRs), however, showed distinct differences across GEA methods based on levels of population structure. The univariate GEA approach had high FPRs (up to 55%) under limited dispersal scenarios, due to strong isolation by distance. By contrast, multivariate, ordination-based methods had uniformly low FPRs (0-2%), suggesting these approaches can effectively control for population structure. Specifically, constrained ordinations had the best balance of high detection and low FPRs and will be a useful addition to the GEA toolkit. Our results provide both theoretical and practical insights into the conditions that shape local adaptation and how these conditions impact our ability to detect selection.

Bayesian inference of selection in a heterogeneous environment from genetic time-series data

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild.