The distribution of fitness effects of new mutations

Evolutionary drivers of reproductive fitness in two endangered forest trees

Population genetics theory predicts a relationship between fitness, genetic diversity (H0) and effective population size (Ne), which is often tested through heterozygosity-fitness correlations (HFCs). We tested whether population and individual fertility and heterozygosity are correlated in two endangered Mexican spruces (Picea martinezii and Picea mexicana) by combining genomic, demographic and reproductive data (seed development and germination traits). For both species, there was a positive correlation between population size and seed development traits, but not germination rate. Individual genome-wide heterozygosity and seed traits were only correlated in P. martinezii (general-effects HFC), and none of the candidate single nucleotide polymorphisms (SNPs) associated with individual fertility showed heterozygote advantage in any species (no local-effects HFC). We observed a single and recent (c. 30 thousand years ago (ka)) population decline for P. martinezii; the collapse of P. mexicana occurred in two phases separated by a long period of stability (c. 800 ka). Recruitment always contributed more to total population census than adult trees in P. mexicana, while this was only the case in the largest populations of P. martinezii. Equating fitness to either H0 or Ne, as traditionally proposed in conservation biology, might not always be adequate, as species-specific evolutionary factors can decouple the expected correlation between these parameters.

Recurrent selection shapes the genomic landscape of differentiation between a pair of host-specialized haplodiploids that diverged with gene flow

Understanding the genetics of adaptation and speciation is critical for a complete picture of how biodiversity is generated and maintained. Heterogeneous genomic differentiation between diverging taxa is commonly documented, with genomic regions of high differentiation interpreted as resulting from differential gene flow, linked selection and reduced recombination rates. Disentangling the roles of each of these non-exclusive processes in shaping genome-wide patterns of divergence is challenging but will enhance our knowledge of the repeatability of genomic landscapes across taxa. Here, we combine whole-genome resequencing and genome feature data to investigate the processes shaping the genomic landscape of differentiation for a sister-species pair of haplodiploid pine sawflies, Neodiprion lecontei and Neodiprion pinetum. We find genome-wide correlations between genome features and summary statistics are consistent with pervasive linked selection, with patterns of diversity and divergence more consistently predicted by exon density and recombination rate than the neutral mutation rate (approximated by dS). We also find that both global and local patterns of FST, dXY and π provide strong support for recurrent selection as the primary selective process shaping variation across pine sawfly genomes, with some contribution from balancing selection and lineage-specific linked selection. Because inheritance patterns for haplodiploid genomes are analogous to those of sex chromosomes, we hypothesize that haplodiploids may be especially prone to recurrent selection, even if gene flow occurred throughout divergence. Overall, our study helps fill an important taxonomic gap in the genomic landscape literature and contributes to our understanding of the processes that shape genome-wide patterns of genetic variation.

Graph-Based Pan-Genome Reveals the Pattern of Deleterious Mutations during the Domestication of Saccharomyces cerevisiae

The "cost of domestication" hypothesis suggests that the domestication of wild species increases the number, frequency, and/or proportion of deleterious genetic variants, potentially reducing their fitness in the wild. While extensively studied in domesticated species, this phenomenon remains understudied in fungi. Here, we used Saccharomyces cerevisiae, the world's oldest domesticated fungus, as a model to investigate the genomic characteristics of deleterious variants arising from fungal domestication. Employing a graph-based pan-genome approach, we identified 1,297,761 single nucleotide polymorphisms (SNPs), 278,147 insertion/deletion events (indels; <30 bp), and 19,967 non-redundant structural variants (SVs; ≥30 bp) across 687 S. cerevisiae isolates. Comparing these variants with synonymous SNPs (sSNPs) as neutral controls, we found that the majority of the derived nonsynonymous SNPs (nSNPs), indels, and SVs were deleterious. Heterozygosity was positively correlated with the impact of deleterious SNPs, suggesting a role of genetic diversity in mitigating their effects. The domesticated isolates exhibited a higher additive burden of deleterious SNPs (dSNPs) than the wild isolates, but a lower burden of indels and SVs. Moreover, the domesticated S. cerevisiae showed reduced rates of adaptive evolution relative to the wild S. cerevisiae. In summary, deleterious variants tend to be heterozygous, which may mitigate their harmful effects, but they also constrain breeding potential. Addressing deleterious alleles and minimizing the genetic load are crucial considerations for future S. cerevisiae breeding efforts.

Competing adaptations maintain nonadaptive variation in a wild cricket population

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

Polygenic dynamics underlying the response of quantitative traits to directional selection

We study the response of a quantitative trait to exponential directional selection in a finite haploid population, both at the genetic and the phenotypic level. We assume an infinite sites model, in which the number of new mutations per generation in the population follows a Poisson distribution (with mean Θ) and each mutation occurs at a new, previously monomorphic site. Mutation effects are beneficial and drawn from a distribution. Sites are unlinked and contribute additively to the trait. Assuming that selection is stronger than random genetic drift, we model the initial phase of the dynamics by a supercritical Galton-Watson process. This enables us to obtain time-dependent results. We show that the copy-number distribution of the mutant in generation n, conditioned on non-extinction until n, is described accurately by the deterministic increase from an initial distribution with mean 1. This distribution is related to the absolutely continuous part W+ of the random variable, typically denoted W, that characterizes the stochasticity accumulating during the mutant's sweep. A suitable transformation yields the approximate dynamics of the mutant frequency distribution in a Wright-Fisher population of size N. Our expression provides a very accurate approximation except when mutant frequencies are close to 1. On this basis, we derive explicitly the (approximate) time dependence of the expected mean and variance of the trait and of the expected number of segregating sites. Unexpectedly, we obtain highly accurate approximations for all times, even for the quasi-stationary phase when the expected per-generation response and the trait variance have equilibrated. The latter refine classical results. In addition, we find that Θ is the main determinant of the pattern of adaptation at the genetic level, i.e., whether the initial allele-frequency dynamics are best described by sweep-like patterns at few loci or small allele-frequency shifts at many. The number of segregating sites is an appropriate indicator for these patterns. The selection strength determines primarily the rate of adaptation. The accuracy of our results is tested by comprehensive simulations in a Wright-Fisher framework. We argue that our results apply to more complex forms of directional selection.

FBXO11 variants are associated with intellectual disability and variable clinical manifestation in Chinese affected individuals

F-box protein 11 (FBXO11) is a member of F-Box protein family, which has recently been proved to be associated with intellectual developmental disorder with dysmorphic facies and behavioral abnormalities (IDDFBA, OMIM: 618089). In this study, 12 intellectual disability individuals from 5 Chinese ID families were collected, and whole exome sequencing (WES), sanger sequencing, and RNA sequencing (RNA-seq) were conducted. Almost all the affected individuals presented with mild to severe intellectual disability (12/12), global developmental delay (10/12), speech and language development delay (8/12) associated with a range of alternate features including increased body weight (7/12), short stature (6/12), seizures (3/12), reduced visual acuity (4/12), hypotonia (1/12), and auditory hallucinations and hallucinations (1/12). Distinguishingly, malformation was not observed in all the affected individuals. WES analysis showed 5 novel FBXO11 variants, which include an inframe deletion variant, a missense variant, two frameshift variants, and a partial deletion of FBXO11 (exon 22-23). RNA-seq indicated that exon 22-23 deletion of FBXO11 results in a new mRNA structure. Conservation and protein structure prediction demonstrated deleterious effect of these variants. The DEGs analysis revealed 148 differentially expressed genes shared among 6 affected individuals, which were mainly associated with genes of muscle and immune system. Our research is the first report of FBXO11-associated IDDFBA in Chinese individuals, which expands the genetic and clinical spectrum of this newly identified NDD/ID syndrome.

Latent mutations in the ancestries of alleles under selection

We consider a single genetic locus with two alleles A1 and A2 in a large haploid population. The locus is subject to selection and two-way, or recurrent, mutation. Assuming the allele frequencies follow a Wright-Fisher diffusion and have reached stationarity, we describe the asymptotic behaviors of the conditional gene genealogy and the latent mutations of a sample with known allele counts, when the count n1 of allele A1 is fixed, and when either or both the sample size n and the selection strength |α| tend to infinity. Our study extends previous work under neutrality to the case of non-neutral rare alleles, asserting that when selection is not too strong relative to the sample size, even if it is strongly positive or strongly negative in the usual sense (α→-∞ or α→+∞), the number of latent mutations of the n1 copies of allele A1 follows the same distribution as the number of alleles in the Ewens sampling formula. On the other hand, very strong positive selection relative to the sample size leads to neutral gene genealogies with a single ancient latent mutation. We also demonstrate robustness of our asymptotic results against changing population sizes, when one of |α| or n is large.

Is biased mutation sufficient to save runaway sexual selection?

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

Modeling biases from low-pass genome sequencing to enable accurate population genetic inferences

Low-pass genome sequencing is cost-effective and enables analysis of large cohorts. However, it introduces biases by reducing heterozygous genotypes and low-frequency alleles, impacting subsequent analyses such as demographic history inference. We developed a probabilistic model of low-pass biases from the Genome Analysis Toolkit (GATK) multi-sample calling pipeline, and we implemented it in the population genomic inference software dadi. We evaluated the model using simulated low-pass datasets and found that it alleviated low-pass biases in inferred demographic parameters. We further validated the model by downsampling 1000 Genomes Project data, demonstrating its effectiveness on real data. Our model is widely applicable and substantially improves model-based inferences from low-pass population genomic data.

Induced genetic diversity through mutagenesis in wheat gene pool and significant use of SCoT markers to underpin key agronomic traits

BACKGROUND

This research explores the efficacy of mutagenesis, specifically using sodium azide (SA) and hydrazine hydrate (HZ) treatments, to introduce genetic diversity and enhance traits in three wheat (Triticum aestivum L.) genotypes. The experiment entails subjecting the seeds to different doses of SA and HZ and cultivating them in the field for two consecutive generations: M1 (first generation) and M2 (second generation). We then employed selective breeding techniques with Start Codon Targeted (SCoT) markers to select traits within the wheat gene pool. Also, the correlation between SCoT markers and specific agronomic traits provides insights into the genetic mechanisms underlying mutagenesis-induced changes in wheat.

RESULTS

In the study, eleven genotypes were derived from parent varieties Sids1, Sids12, and Giza 168, and eight mutant genotypes were selected from the M1 generation and further cultivated to establish the M2 generation. The results revealed that various morphological and agronomical characteristics, such as plant height, spikes per plant, spike length, spikelet per spike, grains per spikelet, and 100-grain weight, showed increases in different genotypes from M1 to M2. SCoT markers were employed to assess genetic diversity among the eleven genotypes. The bioinformatics analysis identified a correlation between SCoT markers and the transcription factors ABSCISIC ACID INSENSITIVE3 (ABI3) and VIVIPAROUS1 (VP1), crucial for plant development, growth, and stress adaptation. A comprehensive examination of genetic distance and the function identification of gene-associated SCoT markers may provide valuable insights into the mechanisms by which SA and HZ act as mutagens, enhancing wheat agronomic qualities.

CONCLUSIONS

This study demonstrates the effective use of SA and HZ treatments to induce gene diversity through mutagenesis in the wheat gene pool, resulting in the enhancement of agronomic traits, as revealed by SCoT markers. The significant improvements in morphological and agronomical characteristics highlight the potential of mutagenesis techniques for crop improvement. These findings offer valuable information for breeders to develop effective breeding programs to enhance wheat quality and resilience through increased genetic diversity.

How should we measure population-level inbreeding depression? Impacts of standing genetic associations between selfing rate and deleterious mutations

Inbreeding depression (ID) is a major selective force during mating system evolution primarily contributed by highly to partially recessive deleterious mutations. Theories suggest that transient genetic association with fitness alleles can be important in affecting the evolution of alleles that modify the selfing rate during its sweep. Nevertheless, empirical tests often focus on the pre-existing genetic association between selfing rate and ID maintained under mutation-selection balance. Therefore, how this standing genetic association is affected by key factors and its impacts on the evolution of selfing remain unclear. I show that as the selection coefficient of deleterious mutations increases, the association between selfing rate and ID declines from positive to negative. These results predict that association between selfing and ID tends to be negative in populations with low selfing rates, while positive in highly selfing populations. Using population genetic and quantitative genetic models, I show that standing genetic associations between selfing rate and fitness alleles can significantly impact the evolution of the mean selfing rate of a population. I present better metrics of population-level ID, which can be calculated based on the correlation coefficient between individual selfing rate and the fitness of selfed and outcrossed offspring.

Fixation times of de novo and standing beneficial variants in subdivided populations

The rate at which beneficial alleles fix in a population depends on the probability of and time to fixation of such alleles. Both of these quantities can be significantly impacted by population subdivision and limited gene flow. Here, we investigate how limited dispersal influences the rate of fixation of beneficial de novo mutations, as well as fixation time from standing genetic variation. We investigate this for a population structured according to the island model of dispersal allowing us to use the diffusion approximation, which we complement with simulations. We find that fixation may take on average fewer generations under limited dispersal than under panmixia when selection is moderate. This is especially the case if adaptation occurs from de novo recessive mutations, and dispersal is not too limited (such that approximately FST<0.2). The reason is that mildly limited dispersal leads to only a moderate increase in effective population size (which slows down fixation), but is sufficient to cause a relative excess of homozygosity due to inbreeding, thereby exposing rare recessive alleles to selection (which accelerates fixation). We also explore the effect of metapopulation dynamics through local extinction followed by recolonization, finding that such dynamics always accelerate fixation from standing genetic variation, while de novo mutations show faster fixation interspersed with longer waiting times. Finally, we discuss the implications of our results for the detection of sweeps, suggesting that limited dispersal mitigates the expected differences between the genetic signatures of sweeps involving recessive and dominant alleles.

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

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

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

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

Mutational robustness and the role of buffer genes in evolvability

Organisms rely on mutations to fuel adaptive evolution. However, many mutations impose a negative effect on fitness. Cells may have therefore evolved mechanisms that affect the phenotypic effects of mutations, thus conferring mutational robustness. Specifically, so-called buffer genes are hypothesized to interact directly or indirectly with genetic variation and reduce its effect on fitness. Environmental or genetic perturbations can change the interaction between buffer genes and genetic variation, thereby unmasking the genetic variation's phenotypic effects and thus providing a source of variation for natural selection to act on. This review provides an overview of our understanding of mutational robustness and buffer genes, with the chaperone gene HSP90 as a key example. It discusses whether buffer genes merely affect standing variation or also interact with de novo mutations, how mutational robustness could influence evolution, and whether mutational robustness might be an evolved trait or rather a mere side-effect of complex genetic interactions.

Selection on synonymous sites: the unwanted transcript hypothesis

Although translational selection to favour codons that match the most abundant tRNAs is not readily observed in humans, there is nonetheless selection in humans on synonymous mutations. We hypothesize that much of this synonymous site selection can be explained in terms of protection against unwanted RNAs - spurious transcripts, mis-spliced forms or RNAs derived from transposable elements or viruses. We propose not only that selection on synonymous sites functions to reduce the rate of creation of unwanted transcripts (for example, through selection on exonic splice enhancers and cryptic splice sites) but also that high-GC content (but low-CpG content), together with intron presence and position, is both particular to functional native mRNAs and used to recognize transcripts as native. In support of this hypothesis, transcription, nuclear export, liquid phase condensation and RNA degradation have all recently been shown to promote GC-rich transcripts and suppress AU/CpG-rich ones. With such 'traps' being set against AU/CpG-rich transcripts, the codon usage of native genes has, in turn, evolved to avoid such suppression. That parallel filters against AU/CpG-rich transcripts also affect the endosomal import of RNAs further supports the unwanted transcript hypothesis of synonymous site selection and explains the similar design rules that have enabled the successful use of transgenes and RNA vaccines.

Genetic influences on motor learning and performance and superperforming mutants revealed by random mutational survey of the mouse genome

Evolution depends upon genetic variations that influence physiology. As defined in a genetic screen, phenotypic performance may be enhanced or degraded by such mutations. We set out to detect mutations that influence motor function, including motor learning. Thus, we tested the motor effects of 36,444 non-synonymous coding/splicing mutations induced in the germline of C57BL/6J mice with N-ethyl-N-nitrosourea by measuring changes in the performance of repetitive rotarod trials while blinded to genotype. Automated meiotic mapping was used to implicate individual mutations in causation. In total, 32,726 mice bearing all the variant alleles were screened. This was complemented with the simultaneous testing of 1408 normal mice for reference. In total, 16.3% of autosomal genes were thus rendered detectably hypomorphic or nullified by mutations in homozygosity and motor tested in at least three mice. This approach allowed us to identify superperformance mutations in Rif1, Tk1, Fan1 and Mn1. These genes are primarily related, among other less well-characterized functions, to nucleic acid biology. We also associated distinct motor learning patterns with groups of functionally related genes. These functional sets included, preferentially, histone H3 methyltransferase activity for mice that learnt at an accelerated rate relative to the remaining mutant mice. The results allow for an estimation of the fraction of mutations that can modify a behaviour influential for evolution such as locomotion. They may also enable, once the loci are further validated and the mechanisms elucidated, the harnessing of the activity of the newly identified genes to enhance motor ability or to counterbalance disability or disease. KEY POINTS: We studied the effect of chemically induced random mutations on mouse motor performance. An array of mutations influenced the rate of motor learning. DNA regulation genes predominated among these mutant loci. Several mutations in unsuspected genes led to superperformance. Assuming little-biased mutagenicity, the results allow for an estimation of the probability for any spontaneous mutation to influence a behaviour such as motor learning and ultimate performance.

Effects of urban-induced mutations on ecology, evolution and health

Increasing evidence suggests that urbanization is associated with higher mutation rates, which can affect the health and evolution of organisms that inhabit cities. Elevated pollution levels in urban areas can induce DNA damage, leading to de novo mutations. Studies on mutations induced by urban pollution are most prevalent in humans and microorganisms, whereas studies of non-human eukaryotes are rare, even though increased mutation rates have the potential to affect organisms and their populations in contemporary time. Our Perspective explores how higher mutation rates in urban environments could impact the fitness, ecology and evolution of populations. Most mutations will be neutral or deleterious, and higher mutation rates associated with elevated pollution in urban populations can increase the risk of cancer in humans and potentially other species. We highlight the potential for urban-driven increased deleterious mutational loads in some organisms, which could lead to a decline in population growth of a wide diversity of organisms. Although beneficial mutations are expected to be rare, we argue that higher mutation rates in urban areas could influence adaptive evolution, especially in organisms with short generation times. Finally, we explore avenues for future research to better understand the effects of urban-induced mutations on the fitness, ecology and evolution of city-dwelling organisms.

Identification of the mutual gliding locus as a factor for gut colonization in non-native bee hosts using the ARTP mutagenesis

BACKGROUND

The gut microbiota and their hosts profoundly affect each other's physiology and evolution. Identifying host-selected traits is crucial to understanding the processes that govern the evolving interactions between animals and symbiotic microbes. Current experimental approaches mainly focus on the model bacteria, like hypermutating Escherichia coli or the evolutionary changes of wild stains by host transmissions. A method called atmospheric and room temperature plasma (ARTP) may overcome the bottleneck of low spontaneous mutation rates while maintaining mild conditions for the gut bacteria.

RESULTS

We established an experimental symbiotic system with gnotobiotic bee models to unravel the molecular mechanisms promoting host colonization. By in vivo serial passage, we tracked the genetic changes of ARTP-treated Snodgrassella strains from Bombus terrestris in the non-native honeybee host. We observed that passaged isolates showing genetic changes in the mutual gliding locus have a competitive advantage in the non-native host. Specifically, alleles in the orphan mglB, the GTPase activating protein, promoted colonization potentially by altering the type IV pili-dependent motility of the cells. Finally, competition assays confirmed that the mutations out-competed the ancestral strain in the non-native honeybee gut but not in the native host.

CONCLUSIONS

Using the ARTP mutagenesis to generate a mutation library of gut symbionts, we explored the potential genetic mechanisms for improved gut colonization in non-native hosts. Our findings demonstrate the implication of the cell mutual-gliding motility in host association and provide an experimental system for future study on host-microbe interactions. Video Abstract.

Evolutionary approach for pollution study: The case of ionizing radiation

Estimating the consequences of environmental changes, specifically in a global change context, is essential for conservation issues. In the case of pollutants, the interest in using an evolutionary approach to investigate their consequences has been emphasized since the 2000s, but these studies remain rare compared to the characterization of direct effects on individual features. We focused on the study case of anthropogenic ionizing radiation because, despite its potential strong impact on evolution, the scarcity of evolutionary approaches to study the biological consequences of this stressor is particularly true. In this study, by investigating some particular features of the biological effects of this stressor, and by reviewing existing studies on evolution under ionizing radiation, we suggest that evolutionary approach may help provide an integrative view on the biological consequences of ionizing radiation. We focused on three topics: (i) the mutagenic properties of ionizing radiation and its disruption of evolutionary processes, (ii) exposures at different time scales, leading to an interaction between past and contemporary evolution, and (iii) the special features of contaminated areas called exclusion zones and how evolution could match field and laboratory observed effects. This approach can contribute to answering several key issues in radioecology: to explain species differences in the sensitivity to ionizing radiation, to improve our estimation of the impacts of ionizing radiation on populations, and to help identify the environmental features impacting organisms (e.g., interaction with other pollution, migration of populations, anthropogenic environmental changes). Evolutionary approach would benefit from being integrated to the ecological risk assessment process.

Hill-Robertson interference may bias the inference of fitness effects of new mutations in highly selfing species

The accurate estimation of the distribution of fitness effects (DFE) of new mutations is critical for population genetic inference but remains a challenging task. While various methods have been developed for DFE inference using the site frequency spectrum of putatively neutral and selected sites, their applicability in species with diverse life history traits and complex demographic scenarios is not well understood. Selfing is common among eukaryotic species and can lead to decreased effective recombination rates, increasing the effects of selection at linked sites, including interference between selected alleles. We employ forward simulations to investigate the limitations of current DFE estimation approaches in the presence of selfing and other model violations, such as linkage, departures from semidominance, population structure, and uneven sampling. We find that distortions of the site frequency spectrum due to Hill-Robertson interference in highly selfing populations lead to mis-inference of the deleterious DFE of new mutations. Specifically, while accounting for the decrease in the effective population size due to linked effects of selection allows an accurate estimation of selection coefficients in moderately selfing populations, this correction is unable to accurately estimate selection coefficients in highly selfing populations when interference between selected alleles is pervasive. In addition, the presence of cryptic population structure with low rates of migration and uneven sampling across subpopulations leads to the false inference of a deleterious DFE skewed towards effectively neutral/mildly deleterious mutations. Finally, the proportion of adaptive substitutions estimated at high rates of selfing is substantially overestimated. Our observations apply broadly to species and genomic regions with little/no recombination and where interference might be pervasive.

Mitochondrial Genomic Evidence of Selective Constraints in Small-Bodied Terrestrial Cetartiodactyla

Body size may drive the molecular evolution of mitochondrial genes in response to changes in energy requirements across species of different sizes. In this study, we perform selection pressure analysis and phylogenetic independent contrasts (PIC) to investigate the association between molecular evolution of mitochondrial genome protein-coding genes (mtDNA PCGs) and body size in terrestrial Cetartiodactyla. Employing selection pressure analysis, we observe that the average non-synonymous/synonymous substitution rate ratio (ω) of mtDNA PCGs is significantly reduced in small-bodied species relative to their medium and large counterparts. PIC analysis further confirms that ω values are positively correlated with body size (R2 = 0.162, p = 0.0016). Our results suggest that mtDNA PCGs of small-bodied species experience much stronger purifying selection as they need to maintain a heightened metabolic rate. On the other hand, larger-bodied species may face less stringent selective pressures on their mtDNA PCGs, potentially due to reduced relative energy expenditure per unit mass. Furthermore, we identify several genes that undergo positive selection, possibly linked to species adaptation to specific environments. Therefore, despite purifying selection being the predominant force in the evolution of mtDNA PCGs, positive selection can also occur during the process of adaptive evolution.

Set2 regulates Ccp1 and Swc2 to ensure centromeric stability by retargeting CENP-A

Precise positioning of the histone-H3 variant, CENP-A, ensures centromere stability and faithful chromosomal segregation. Mislocalization of CENP-A to extra-centromeric loci results in aneuploidy and compromised cell viability associated with formation of ectopic kinetochores. The mechanism that retargets mislocalized CENP-A back to the centromere is unclarified. We show here that the downregulation of the histone H3 lysine 36 (H3K36) methyltransferase Set2 can preserve centromere localization of a temperature-sensitive mutant cnp1-1 Schizosaccharomyces pombe CENP-A (SpCENP-A) protein and reverse aneuploidy by redirecting mislocalized SpCENP-A back to centromere from ribosomal DNA (rDNA) loci, which serves as a sink for the delocalized SpCENP-A. Downregulation of set2 augments Swc2 (SWR1 complex DNA-binding module) expression and releases histone chaperone Ccp1 from the centromeric reservoir. Swc2 and Ccp1 are directed to the rDNA locus to excavate the SpCENP-Acnp1-1, which is relocalized to the centromere in a manner dependent on canonical SpCENP-A loaders, including Mis16, Mis17 and Mis18, thereby conferring cell survival and safeguarding chromosome segregation fidelity. Chromosome missegregation is a severe genetic instability event that compromises cell viability. This mechanism thus promotes CENP-A presence at the centromere to maintain genomic stability.

Targeted accurate RNA consensus sequencing (tARC-seq) reveals mechanisms of replication error affecting SARS-CoV-2 divergence

RNA viruses, like SARS-CoV-2, depend on their RNA-dependent RNA polymerases (RdRp) for replication, which is error prone. Monitoring replication errors is crucial for understanding the virus's evolution. Current methods lack the precision to detect rare de novo RNA mutations, particularly in low-input samples such as those from patients. Here we introduce a targeted accurate RNA consensus sequencing method (tARC-seq) to accurately determine the mutation frequency and types in SARS-CoV-2, both in cell culture and clinical samples. Our findings show an average of 2.68 × 10-5 de novo errors per cycle with a C > T bias that cannot be solely attributed to APOBEC editing. We identified hotspots and cold spots throughout the genome, correlating with high or low GC content, and pinpointed transcription regulatory sites as regions more susceptible to errors. tARC-seq captured template switching events including insertions, deletions and complex mutations. These insights shed light on the genetic diversity generation and evolutionary dynamics of SARS-CoV-2.

Pervasive relaxed selection in termite genomes

Genetic changes that enabled the evolution of eusociality have long captivated biologists. More recently, attention has focussed on the consequences of eusociality on genome evolution. Studies have reported higher molecular evolutionary rates in eusocial hymenopteran insects compared with their solitary relatives. To investigate the genomic consequences of eusociality in termites, we analysed nine genomes, including newly sequenced genomes from three non-eusocial cockroaches. Using a phylogenomic approach, we found that termite genomes have experienced lower rates of synonymous substitutions than those of cockroaches, possibly as a result of longer generation times. We identified higher rates of non-synonymous substitutions in termite genomes than in cockroach genomes, and identified pervasive relaxed selection in the former (24-31% of the genes analysed) compared with the latter (2-4%). We infer that this is due to reductions in effective population size, rather than gene-specific effects (e.g. indirect selection of caste-biased genes). We found no obvious signature of increased genetic load in termites, and postulate efficient purging of deleterious alleles at the colony level. Additionally, we identified genomic adaptations that may underpin caste differentiation, such as genes involved in post-translational modifications. Our results provide insights into the evolution of termites and the genomic consequences of eusociality more broadly.

Determinants of rapid adaptation in species with large variance in offspring production

The speed of population adaptation to changing biotic and abiotic environments is determined by the interaction between genetic drift, positive selection and linkage effects. Many marine species (fish, crustaceans), invertebrates and pathogens of humans and crops, exhibit sweepstakes reproduction characterized by the production of a very large amount of offspring (fecundity phase) from which only a small fraction may survive to the next generation (viability phase). Using stochastic simulations, we investigate whether the occurrence of sweepstakes reproduction affects the efficiency of a positively selected unlinked locus, and thus, the speed of adaptation since fecundity and/or viability have distinguishable consequences on mutation rate, probability and fixation time of advantageous alleles. We observe that the mean number of mutations at the next generation is always the function of the population size, but the variance increases with stronger sweepstakes reproduction when mutations occur in the parents. On the one hand, stronger sweepstakes reproduction magnifies the effect of genetic drift thus increasing the probability of fixation of neutral allele and decreasing that of selected alleles. On the other hand, the time to fixation of advantageous (as well as neutral) alleles is shortened by stronger sweepstakes reproduction. Importantly, fecundity and viability selection exhibit different probabilities and times to fixation of advantageous alleles under intermediate and weak sweepstakes reproduction. Finally, alleles under both strong fecundity and viability selection display a synergistic efficiency of selection. We conclude that measuring and modelling accurately fecundity and/or viability selection are crucial to predict the adaptive potential of species with sweepstakes reproduction.

The rate of adaptive molecular evolution in wild and domesticated Saccharomyces cerevisiae populations

Through its fermentative capacities, Saccharomyces cerevisiae was central in the development of civilisation during the Neolithic period, and the yeast remains of importance in industry and biotechnology, giving rise to bona fide domesticated populations. Here, we conduct a population genomic study of domesticated and wild populations of S. cerevisiae. Using coalescent analyses, we report that the effective population size of yeast populations decreased since the divergence with S. paradoxus. We fitted models of distributions of fitness effects to infer the rate of adaptive (ω a ) and non-adaptive (ω na ) non-synonymous substitutions in protein-coding genes. We report an overall limited contribution of positive selection to S. cerevisiae protein evolution, albeit with higher rates of adaptive evolution in wild compared to domesticated populations. Our analyses revealed the signature of background selection and possibly Hill-Robertson interference, as recombination was found to be negatively correlated withω na and positively correlated withω a . However, the effect of recombination onω a was found to be labile, as it is only apparent after removing the impact of codon usage bias on the synonymous site frequency spectrum and disappears if we control for the correlation withω na , suggesting that it could be an artefact of the decreasing population size. Furthermore, the rate of adaptive non-synonymous substitutions is significantly correlated with the residue solvent exposure, a relation that cannot be explained by the population's demography. Together, our results provide a detailed characterisation of adaptive mutations in protein-coding genes across S. cerevisiae populations.

Simulating the Effect of Environmental Change on Evolving Populations

This study uses evolutionary simulations to explore the strategies that emerge to enable populations to cope with random environmental changes in situations where lifetime learning approaches are not available to accommodate them. In particular, it investigates how the average magnitude of change per unit time and the persistence of the changes (and hence the resulting autocorrelation of the environmental time series) affect the change tolerances, population diversities, and extinction timescales that emerge. Although it is the change persistence (often discussed in terms of environmental noise color) that has received most attention in the recent literature, other factors, particularly the average change magnitude, interact with this and can be more important drivers of the adaptive strategies that emerge. Moreover, when running simulations, the choice of change representation and normalization can also affect the outcomes. Detailed simulations are presented that are designed to explore all these issues. They also reveal significant dependences on the associated mutation rates and the extent to which they can evolve, and they clarify how evolution often leads populations into strategies with higher risks of extinction. Overall, this study shows how modeling the effect of environmental change requires more care than may have previously been realized.

The distribution of fitness effects during adaptive walks using a simple genetic network

The tempo and mode of adaptation depends on the availability of beneficial alleles. Genetic interactions arising from gene networks can restrict this availability. However, the extent to which networks affect adaptation remains largely unknown. Current models of evolution consider additive genotype-phenotype relationships while often ignoring the contribution of gene interactions to phenotypic variance. In this study, we model a quantitative trait as the product of a simple gene regulatory network, the negative autoregulation motif. Using forward-time genetic simulations, we measure adaptive walks towards a phenotypic optimum in both additive and network models. A key expectation from adaptive walk theory is that the distribution of fitness effects of new beneficial mutations is exponential. We found that both models instead harbored distributions with fewer large-effect beneficial alleles than expected. The network model also had a complex and bimodal distribution of fitness effects among all mutations, with a considerable density at deleterious selection coefficients. This behavior is reminiscent of the cost of complexity, where correlations among traits constrain adaptation. Our results suggest that the interactions emerging from genetic networks can generate complex and multimodal distributions of fitness effects.

Back to the fundamentals: a reply to Basener and Sanford 2018

Fisher's fundamental theorem of natural selection has haunted theoretical population genetic literature since it was proposed in 1930, leading to numerous interpretations. Most of the confusion stemmed from Fisher's own obscure presentation. By the 1970s, a clearer view of Fisher's theorem had been achieved and it was found that, regardless of its utility or significance, it represents a general theorem of evolutionary biology. Basener and Sanford (J Math Biol 76:1589-1622, 2018) writing in JOMB, however, paint a different picture of the fundamental theorem as one hindered by its assumptions and incomplete due to its failure to explicitly incorporate mutational effects. They argue that Fisher saw his theorem as a "mathematical proof of Darwinian evolution". In this reply, we show that, contrary to Basener and Sanford, Fisher's theorem is a general theorem that applies to any evolving population, and that, far from their assertion that it needed to be expanded, the theorem already implicitly incorporates ancestor-descendant variation. We also show that their numerical simulations produce unrealistic results. Lastly, we argue that Basener and Sanford's motivations were in undermining not merely Fisher's theorem, but the concept of universal common descent itself.

The pseudoentropy of allele frequency trajectories, the persistence of variation, and the effective population size

To concisely describe how genetic variation, at individual loci or across whole genomes, changes over time, and to follow transitory allelic changes, we introduce a quantity related to entropy, that we term pseudoentropy. This quantity emerges in a diffusion analysis of the mean time a mutation segregates in a population. For a neutral locus with an arbitrary number of alleles, the mean time of segregation is generally proportional to the pseudoentropy of initial allele frequencies. After the initial time point, pseudoentropy generally decreases, but other behaviours are possible, depending on the genetic diversity and selective forces present. For a biallelic locus, pseudoentropy and entropy coincide, but they are distinct quantities with more than two alleles. Thus for populations with multiple biallelic loci, the language of entropy suffices. Then entropy, combined across loci, serves as a concise description of genetic variation. We used individual based simulations to explore how this entropy behaves under different evolutionary scenarios. In agreement with predictions, the entropy associated with unlinked neutral loci decreases over time. However, deviations from free recombination and neutrality have clear and informative effects on the entropy's behaviour over time. Analysis of publicly available data of a natural D. melanogaster population, that had been sampled over seven years, using a sliding-window approach, yielded considerable variation in entropy trajectories of different genomic regions. These mostly follow a pattern that suggests a substantial effective population size and a limited effect of positive selection on genome-wide diversity over short time scales.

Modeling the mosaic structure of bacterial genomes to infer their evolutionary history

The chronology and phylogeny of bacterial evolution are difficult to reconstruct due to a scarce fossil record. The analysis of bacterial genomes remains challenging because of large sequence divergence, the plasticity of bacterial genomes due to frequent gene loss, horizontal gene transfer, and differences in selective pressure from one locus to another. Therefore, taking advantage of the rich and rapidly accumulating genomic data requires accurate modeling of genome evolution. An important technical consideration is that loci with high effective mutation rates may diverge beyond the detection limit of the alignment algorithms used, biasing the genome-wide divergence estimates toward smaller divergences. In this article, we propose a novel method to gain insight into bacterial evolution based on statistical properties of genome comparisons. We find that the length distribution of sequence matches is shaped by the effective mutation rates of different loci, by the horizontal transfers, and by the aligner sensitivity. Based on these inputs, we build a model and show that it accounts for the empirically observed distributions, taking the Enterobacteriaceae family as an example. Our method allows to distinguish segments of vertical and horizontal origins and to estimate the time divergence and exchange rate between any pair of taxa from genome-wide alignments. Based on the estimated time divergences, we construct a time-calibrated phylogenetic tree to demonstrate the accuracy of the method.

Rolling with the punches: Organism-environment interactions shape spatial pattern of adaptive differentiation in the widespread mantis shrimp Oratosquilla oratoria

Investigating spatial pattern of adaptive variation and its underlying processes can inform the adaptive potential distributed within species ranges, which is increasingly important in the context of a changing climate. A correct interpretation of adaptive variation pattern requires that population history and the ensuing population genetic structure are taken into account. Here we carried out such a study by integrating population genomic analyses, demographic model testing and species distribution modeling to investigate patterns and causes of adaptive differentiation in a widespread mantis shrimp, Oratosquilla oratoria, along a replicated, broad-scale temperature gradient in the northwestern Pacific (NWP). Our results supported a strong hierarchical ecogeographic structure dominated by habitat-linked divergence among O. oratoria populations accompanied with introgressive hybridization. A combined FST outlier and environmental correlation analyses revealed remarkable temperature-associated clines in allele frequency across paired North-South populations on Chinese and Japanese coasts, and identified a suite of loci associated with temperature adaptation. Further demographic model testing revealed the observed clinal variation derived partly from Pleistocene divergence followed by recent secondary contact. More importantly, the likelihood of hybridization is predicted to increase as climate change progresses, which would break barriers to gene flow and enable the spread of adaptive genetic variation. These results support that not only is temperature-driven adaptive differentiation occurs in O. oratoria but that such pattern is likely attributed to ancient adaptive variation, sustained by contemporary ocean conditions and a semi-permeable barrier to gene flow maintained by selection. They moreover provide genomic insights into the distribution of adaptive potential across O. oratoria' s species range. This work can serve as a case study to characterize adaptive diversity of marine species in the NWP by integrating environmental and genetic data at temporal and spatial scales in a population genomic framework, which would improve management and conservation actions under climate change.

Self-replicating artificial neural networks give rise to universal evolutionary dynamics

In evolutionary models, mutations are exogenously introduced by the modeler, rather than endogenously introduced by the replicator itself. We present a new deep-learning based computational model, the self-replicating artificial neural network (SeRANN). We train it to (i) copy its own genotype, like a biological organism, which introduces endogenous spontaneous mutations; and (ii) simultaneously perform a classification task that determines its fertility. Evolving 1,000 SeRANNs for 6,000 generations, we observed various evolutionary phenomena such as adaptation, clonal interference, epistasis, and evolution of both the mutation rate and the distribution of fitness effects of new mutations. Our results demonstrate that universal evolutionary phenomena can naturally emerge in a self-replicator model when both selection and mutation are implicit and endogenous. We therefore suggest that SeRANN can be applied to explore and test various evolutionary dynamics and hypotheses.

Within-host evolution of SARS-CoV-2: how often are de novo mutations transmitted from symptomatic infections?

Despite a relatively low mutation rate, the large number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as within-host parameter estimates for symptomatic SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of de novo SARS-CoV-2 mutations as a function of bottleneck size and selection coefficient. For narrow bottlenecks, we find that mutations affecting per-target-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding) have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion). We further find that mutations affecting the eclipse rate (with phenotypes associated with reorganization of cellular metabolic processes and synthesis of viral budding precursor material) are highly favoured relative to all other traits examined. We find that mutations leading to reduced removal rates of infected cells (with phenotypes associated with innate immune evasion) have limited transmission advantage relative to mutations leading to humoral evasion. Predicted transmission probabilities, however, for mutations affecting innate immune evasion are more consistent with the range of clinically estimated household transmission probabilities for de novo mutations. This result suggests that although mutations affecting humoral evasion are more easily transmitted when they occur, mutations affecting innate immune evasion may occur more readily. We examine our predictions in the context of a number of previously characterized mutations in circulating strains of SARS-CoV-2. Our work offers both a null model for SARS-CoV-2 mutation rates and predicts which aspects of viral life history are most likely to successfully evolve, despite low mutation rates and repeated transmission bottlenecks.

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

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

Reduction of genetic diversity in 'Alalā (Hawaiian crow; Corvus hawaiiensis) between the late 1800s and the late 1900s

Genetic and genomic data are increasingly used to aid conservation management of endangered species by providing insights into evolutionary histories, factors associated with extinction risks, and potential for future adaptation. For the 'Alalā, or Hawaiian crow (Corvus hawaiiensis), genetic concerns include negative correlations between inbreeding and hatching success. However, it is unclear if low genetic diversity and inbreeding depression are consequences of a historical population bottleneck, or if 'Alalā had historically low genetic diversity that predated human influence, perhaps as a result of earlier declines or founding events. In this study, we applied a hybridization-based sequence capture to generate a genome-wide single nucleotide polymorphism (SNP) dataset for comparing historical specimens collected in the 1890s, when 'Alalā were more numerous, to samples taken between 1973 and 1998, when 'Alalā population densities were near the lowest documented levels in the wild, prior to all individuals being collected for captive rearing. We found low genome-wide diversity in both sample groups, however, the modern sample group (1973 to 1998 cohort) exhibited relatively fewer polymorphic alleles, a lower proportion of polymorphic loci, and lower observed heterozygosity, consistent with a population decline and potential bottleneck effects. These results combined with a current low population size highlight the importance of continued efforts by conservation managers to mitigate inbreeding and maintain founder representation to preserve what genetic diversity remains.

Investigating low frequency somatic mutations in Arabidopsis with Duplex Sequencing

Mutations are the source of novel genetic diversity but can also lead to disease and maladaptation. The conventional view is that mutations occur randomly with respect to their environment-specific fitness consequences. However, intragenomic mutation rates can vary dramatically due to transcription coupled repair and based on local epigenomic modifications, which are non-uniformly distributed across genomes. One sequence feature associated with decreased mutation is higher expression level, which can vary depending on environmental cues. To understand whether the association between expression level and mutation rate creates a systematic relationship with environment-specific fitness effects, we perturbed expression through a heat treatment in Arabidopsis thaliana. We quantified gene expression to identify differentially expressed genes, which we then targeted for mutation detection using Duplex Sequencing. This approach provided a highly accurate measurement of the frequency of rare somatic mutations in vegetative plant tissues, which has been a recent source of uncertainty in plant mutation research. We included mutant lines lacking mismatch repair (MMR) and base excision repair (BER) capabilities to understand how repair mechanisms may drive biased mutation accumulation. We found wild type (WT) and BER mutant mutation frequencies to be very low (mean variant frequency 1.8×10-8 and 2.6×10-8, respectively), while MMR mutant frequencies were significantly elevated (1.13×10-6). These results show that somatic variant frequencies are extremely low in WT plants, indicating that larger datasets will be needed to address the fundamental evolutionary question as to whether environmental change leads to gene-specific changes in mutation rate.

Mutation and evolution: Conceptual possibilities

Although random mutation is central to models of evolutionary change, a lack of clarity remains regarding the conceptual possibilities for thinking about the nature and role of mutation in evolution. We distinguish several claims at the intersection of mutation, evolution, and directionality and then characterize a previously unrecognized category: complex conditioned mutation. Empirical evidence in support of this category suggests that the historically famous fluctuation test should be revisited, and new experiments should be undertaken with emerging experimental techniques to facilitate detecting mutation rates within specific loci at an ultra-high, individual base pair resolution.

Phased genome assemblies reveal haplotype-specific genetic load in the critically endangered Chinese Bahaba (Teleostei, Sciaenidae)

While haplotype-specific genetic load shapes the evolutionary trajectory of natural and captive populations, mixed-haplotype assembly and genotyping hindered its characterization in diploids. Herein, we produced two phased genome assemblies of the critically endangered fish Chinese Bahaba (Bahaba taipingensis, Sciaenidae, Teleostei) and resequenced 20 whole genomes to quantify population genetic load at a haplotype level. We identified frame-shifting variants as the most deleterious type, followed by mutations in the 5'-UTR, 3'-UTR and missense mutations at conserved amino acids. Phased haplotypes revealed gene deletions and high-impact deleterious variants. We estimated ~1.12% of genes missing or interrupted per haplotype, with a significant overlap of disrupted genes (30.35%) between haplotype sets. Relative proportions of deleterious variant categories differed significantly between haplotypes. Simulations suggested that purifying selection struggled to purge slightly deleterious genetic load in captive breeding compared to genotyping interventions, and that higher inter-haplotypic variance of genetic load predicted more efficient purging by artificial selection. Combining the knowledge of haplotype-resolved genetic load with predictive modelling will be immensely useful for understanding the evolution of deleterious variants and guiding conservation planning.

A dynamical limit to evolutionary adaptation

Natural selection makes evolutionary adaptation possible even if the overwhelming majority of new mutations are deleterious. However, in rapidly evolving populations where numerous linked mutations occur and segregate simultaneously, clonal interference and genetic hitchhiking can limit the efficiency of selection, allowing deleterious mutations to accumulate over time. This can in principle overwhelm the fitness increases provided by beneficial mutations, leading to an overall fitness decline. Here, we analyze the conditions under which evolution will tend to drive populations to higher versus lower fitness. Our analysis focuses on quantifying the boundary between these two regimes, as a function of parameters such as population size, mutation rates, and selection pressures. This boundary represents a state in which adaptation is precisely balanced by Muller's ratchet, and we show that it can be characterized by rapid molecular evolution without any net fitness change. Finally, we consider the implications of global fitness-mediated epistasis and find that under some circumstances, this can drive populations toward the boundary state, which can thus represent a long-term evolutionary attractor.

Antibiotic dose and nutrient availability differentially drive the evolution of antibiotic resistance and persistence

Effective treatment of bacterial infections proves increasingly challenging due to the emergence of bacterial variants that endure antibiotic exposure. Antibiotic resistance and persistence have been identified as two major bacterial survival mechanisms, and several studies have shown a rapid and strong selection of resistance or persistence mutants under repeated drug treatment. Yet, little is known about the impact of the environmental conditions on resistance and persistence evolution and the potential interplay between both phenotypes. Based on the distinct growth and survival characteristics of resistance and persistence mutants, we hypothesized that the antibiotic dose and availability of nutrients during treatment might play a key role in the evolutionary adaptation to antibiotic stress. To test this hypothesis, we combined high-throughput experimental evolution with a mathematical model of bacterial evolution under intermittent antibiotic exposure. We show that high nutrient levels during antibiotic treatment promote selection of high-level resistance, but that resistance mainly emerges independently of persistence when the antibiotic concentration is sufficiently low. At higher doses, resistance evolution is facilitated by the preceding or concurrent selection of persistence mutants, which ensures survival of populations in harsh conditions. Collectively, our experimental data and mathematical model elucidate the evolutionary routes toward increased bacterial survival under different antibiotic treatment schedules, which is key to designing effective antibiotic therapies.

Genome sequences and population genomics provide insights into the demographic history, inbreeding, and mutation load of two 'living fossil' tree species of Dipteronia

'Living fossils', that is, ancient lineages of low taxonomic diversity, represent an exceptional evolutionary heritage, yet we know little about how demographic history and deleterious mutation load have affected their long-term survival and extinction risk. We performed whole-genome sequencing and population genomic analyses on Dipteronia sinensis and D. dyeriana, two East Asian Tertiary relict trees. We found large-scale genome reorganizations and identified species-specific genes under positive selection that are likely involved in adaptation. Our demographic analyses suggest that the wider-ranged D. sinensis repeatedly recovered from population bottlenecks over late Tertiary/Quaternary periods of adverse climate conditions, while the population size of the narrow-ranged D. dyeriana steadily decreased since the late Miocene, especially after the Last Glacial Maximum (LGM). We conclude that the efficient purging of deleterious mutations in D. sinensis facilitated its survival and repeated demographic recovery. By contrast, in D. dyeriana, increased genetic drift and reduced selection efficacy, due to recent severe population bottlenecks and a likely preponderance of vegetative propagation, resulted in fixation of strongly deleterious mutations, reduced fitness, and continuous population decline, with likely detrimental consequences for the species' future viability and adaptive potential. Overall, our findings highlight the significant impact of demographic history on levels of accumulation and purging of putatively deleterious mutations that likely determine the long-term survival and extinction risk of Tertiary relict trees.

Pervasive selective sweeps across human gut microbiomes

The human gut microbiome is composed of a highly diverse consortia of species which are continually evolving within and across hosts. The ability to identify adaptations common to many host gut microbiomes would not only reveal shared selection pressures across hosts, but also key drivers of functional differentiation of the microbiome that may affect community structure and host traits. However, to date there has not been a systematic scan for adaptations that have spread across host microbiomes. Here, we develop a novel selection scan statistic, named the integrated linkage disequilibrium score (iLDS), that can detect the spread of adaptive haplotypes across host microbiomes via migration and horizontal gene transfer. Specifically, iLDS leverages signals of hitchhiking of deleterious variants with the beneficial variant, a common feature of adaptive evolution. We find that iLDS is capable of detecting simulated and known cases of selection, and moreover is robust to potential confounders that can also elevate LD. Application of the statistic to ~20 common commensal gut species from a large cohort of healthy, Western adults reveals pervasive spread of selected alleles across human microbiomes mediated by horizontal gene transfer. Among the candidate selective sweeps recovered by iLDS is an enrichment for genes involved in the metabolism of maltodextrin, a synthetic starch that has recently become a widespread component of Western diets. In summary, we demonstrate that selective sweeps across host microbiomes are a common feature of the evolution of the human gut microbiome.

Motifs in SARS-CoV-2 evolution

We present a novel framework enhancing the prediction of whether novel lineage poses the threat of eventually dominating the viral population. The framework is based purely on genomic sequence data, without requiring prior established biological analysis. Its building blocks are sets of coevolving sites in the alignment (motifs), identified via coevolutionary signals. The collection of such motifs forms a relational structure over the polymorphic sites. Motifs are constructed using distances quantifying the coevolutionary coupling of pairs and manifest as coevolving clusters of sites. We present an approach to genomic surveillance based on this notion of relational structure. Our system will issue an alert regarding a lineage, based on its contribution to drastic changes in the relational structure. We then conduct a comprehensive retrospective analysis of the COVID-19 pandemic based on SARS-CoV-2 genomic sequence data in GISAID from October 2020 to September 2022, across 21 lineages and 27 countries with weekly resolution. We investigate the performance of this surveillance system in terms of its accuracy, timeliness, and robustness. Lastly, we study how well each lineage is classified by such a system.

Schrödinger's yeast: the challenge of using transformation to compare fitness among Saccharomyces cerevisiae that differ in ploidy or zygosity

How the number of genome copies modifies the effect of random mutations remains poorly known. In yeast, researchers have investigated these effects for knock-out or other large-effect mutations, but have not accounted for differences at the mating-type locus. We set out to compare fitness differences among strains that differ in ploidy and/or zygosity using a panel of spontaneously arising mutations acquired in haploid yeast from a previous study. To ensure no genetic differences, even at the mating-type locus, we embarked on a series of transformations, which first sterilized and then temporarily introduced plasmid-borne mating types. Despite these attempts to equalize the haplotypes, fitness variation introduced during transformation swamped the differences among the original mutation-accumulation lines. While colony size looked normal, we observed a bi-modality in the maximum growth rate of our transformed yeast and determined that many of the slow growing lines were respiratory deficient ("petite"). Not previously reported, we found that yeast that were TID1/RDH54 knockouts were less likely to become petite. Even for lines with the same petite status, however, we found no correlation in fitness between the two replicate transformations performed. These results pose a challenge for any study using transformation to measure the fitness effect of genetic differences among strains. By attempting to hold haplotypes constant, we introduced more mutations that overwhelmed our ability to measure fitness differences between the genetic states. In this study, we transformed over one hundred different lines of yeast, using two independent transformations, and found that this common laboratory procedure can cause large changes to the microbe studied. Our study provides a cautionary tale of the need to use multiple transformants in fitness assays.

The effects of sex on extinction dynamics of Chlamydomonas reinhardtii depend on the rate of environmental change

The continued existence of sex, despite many the costs it entails, still lacks an adequate explanation, as previous studies demonstrated that the effects of sex are environment-dependent: sex enhances the rate of adaptation in changing environments, but the benefits level off in benign conditions. To the best of our knowledge, the potential impact of different patterns of environmental change on the magnitude of these benefits received less attention in theoretical studies. In this paper, we begin to explore this issue by examining the effect of the rate of environmental deterioration (negatively correlated with population survival rate), on the benefits of sex. To investigate the interplay of sex and the rate of environmental deterioration, we carried out a long-term selection experiment with a unicellular alga (Chlamydomonas reinhardtii), by manipulating mode of reproduction (asexual, facultative or obligate sexual) and the rate of environmental deterioration (an increase of salt concentration). We monitored both the population size and extinction dynamics. The results revealed that the relative advantage of sex increased at the intermediate rate and plateaued at the highest rate of environmental deterioration. Obligate sexual populations had the slowest extinction rate under the intermediate rate of environmental deterioration, while facultative sexuality was favoured under the high rate-treatment. To the best of our knowledge, our study is the first to demonstrate that the interplay of sex and the rate of environmental deterioration affects the probability of survival, which indicates that mode of reproduction may be an important determinant of survival of the anthropogenic-induced environmental change.

Deleterious and Adaptive Mutations in Plant Germplasm Conserved Ex Situ

Conserving more than 7 million plant germplasm accessions in 1,750 genebanks worldwide raises the hope of securing the food supply for humanity for future generations. However, there is a genetic cost for such long-term germplasm conservation, which has been largely unaccounted for before. We investigated the extent and variation of deleterious and adaptive mutations in 490 individual plants representing barley, wheat, oat, soybean, maize, rapa, and sunflower collections in a seed genebank using RNA-Seq technology. These collections were found to have a range of deleterious mutations detected from 125 (maize) to 83,695 (oat) with a mean of 13,537 and of the averaged sample-wise mutation burden per deleterious locus from 0.069 to 0.357 with a mean of 0.200. Soybean and sunflower collections showed that accessions acquired earlier had increased mutation burdens. The germplasm with more years of storage in several collections carried more deleterious and fewer adaptive mutations. The samples with more cycles of germplasm regeneration revealed fewer deleterious and more adaptive mutations. These findings are significant for understanding mutational dynamics and genetic cost in conserved germplasm and have implications for long-term germplasm management and conservation.

Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations

AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).

Mutualism reduces the severity of gene disruptions in predictable ways across microbial communities

Predicting evolution in microbial communities is critical for problems from human health to global nutrient cycling. Understanding how species interactions impact the distribution of fitness effects for a focal population would enhance our ability to predict evolution. Specifically, does the type of ecological interaction, such as mutualism or competition, change the average effect of a mutation (i.e., the mean of the distribution of fitness effects)? Furthermore, how often does increasing community complexity alter the impact of species interactions on mutant fitness? To address these questions, we created a transposon mutant library in Salmonella enterica and measured the fitness of loss of function mutations in 3,550 genes when grown alone versus competitive co-culture or mutualistic co-culture with Escherichia coli and Methylorubrum extorquens. We found that mutualism reduces the average impact of mutations, while competition had no effect. Additionally, mutant fitness in the 3-species communities can be predicted by averaging the fitness in each 2-species community. Finally, we discovered that in the mutualism S. enterica obtained vitamins and more amino acids than previously known. Our results suggest that species interactions can predictably impact fitness effect distributions, in turn suggesting that evolution may ultimately be predictable in multi-species communities.