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03 Aug 2017
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Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradients

What doesn’t kill us makes us stronger: can Fisher’s Geometric model predict antibiotic resistance evolution?

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The increasing number of reported cases of antibiotic resistance is one of today’s major public health concerns. Dealing with this threat involves understanding what drives the evolution of antibiotic resistance and investigating whether we can predict (and subsequently avoid or circumvent) it [1].
One of the most illustrative and common models of adaptation (and, hence, resistance evolution) is Fisher’s Geometric Model (FGM). The original model maps phenotypes to fitness, meaning that each point in the fitness landscape corresponds to a phenotype rather than a genotype. However, it has been shown that when mutations are numerous enough, FGM can also describe adaptive walks in genotype space [2]. Nevertheless, limitations have been highlighted, particularly when trying to study complex scenarios such as antibiotic resistance evolution [3].
Harmand et al. [4] incorporated three extensions to the FGM, which allowed them to match the mutational patterns of antibiotic resistance that they obtained from a screen across a gradient of drug concentrations. The implemented extensions took into account that: 1) only a subset of mutations may contribute to traits under selection, reflecting that not all regions in the genome affect the ability to resist antibiotics; 2) mutations that confer a fitness increase in one environment may not reflect a similar increase in others, if the selective constraints are different; and 3) different antibiotic concentrations may either constrain the maximum fitness that populations can reach (changing the height of the fitness peak) or change the rate of fitness increase with each mutation (changing the width/slope of the peak).
Traditionally, most empirical fitness landscape studies have focused on a subset of mutations obtained after laboratory evolution in specific conditions [5, 6]. The results obtained in Harmand et al. [4] indicate a potential shortcoming of studying these small fitness landscapes: rather than having a constrained evolutionary path to a resistant phenotype, as previously observed, their results suggest that antibiotic resistance can be the product of mutations in different regions of the genome. Returning to the fitness landscape perspective, this indicates that there are many alternative paths that can lead to the evolution of antibiotic resistance. This comparison points at a difficult challenge when aiming at developing a predictive framework for evolution: real-time experiments may indicate that evolution is likely to take similar and predictable paths because the strongest and most frequent mutations dictate the outcome, whereas systematic screens of mutants potentially indicate several paths, that may, however, not be relevant in nature. Only a combination of different experimental approaches with motivated theory as presented in Harmand et al. [4] will allow for a better understanding of where in this continuum evolution is taking place in nature, and to which degree we are able to interfere with it in order to slow down adaptation.

References

[1] Palmer AC, and Kishony R. 2013. Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance. Nature Review Genetics 14: 243—248. doi: 10.1038/nrg3351

[2] Tenaillon O. 2014. The utility of Fisher’s geometric model in evolutionary genetics. Annual Review of Ecology, Evolution and Systematics 45: 179—201. doi: 10.1146/annurev-ecolsys-120213-091846

[3] Blanquart F and Bataillon T. 2016. Epistasis and the structure of fitness landscapes: are experimental fitness landscapes compatible with Fisher’s geometric model? Genetics 203: 847—862. doi: 10.1534/genetics.115.182691

[4] Harmand N, Gallet R, Jabbour-Zahab R, Martin G and Lenormand T. 2017. Fisher’s geometrical model and the mutational patterns of antibiotic resistance across dose gradients. Evolution 71: 23—37. doi: 10.1111/evo.13111

[5] de Visser, JAGM, and Krug J. 2014. Empirical fitness landscapes and the predictability of evolution. Nature 15: 480—490. doi: 10.1038/nrg3744

[6] Palmer AC, Toprak E, Baym M, Kim S, Veres A, Bershtein S and Kishony R. 2015. Delayed commitment to evolutionary fate in antibiotic resistance fitness landscapes. Nature Communications 6: 1—8. doi: 10.1038/ncomms8385

Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradientsNoémie Harmand, Romain Gallet, Roula Jabbour-Zahab, Guillaume Martin, Thomas LenormandFisher's geometrical model (FGM) has been widely used to depict the fitness effects of mutations. It is a general model with few underlying assumptions that gives a large and comprehensive view of adaptive processes. It is thus attractive in sever...AdaptationInês Fragata2017-08-01 16:06:02 View
14 Mar 2017
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Evolution of multiple sensory systems drives novel egg-laying behavior in the fruit pest Drosophila suzukii

A valuable work lying at the crossroad of neuro-ethology, evolution and ecology in the fruit pest Drosophila suzukii

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Adaptations to a new ecological niche allow species to access new resources and circumvent competitors and are hence obvious pathways of evolutionary success. The evolution of agricultural pest species represents an important case to study how a species adapts, on various timescales, to a novel ecological niche. Among the numerous insects that are agricultural pests, the ability to lay eggs (or oviposit) in ripe fruit appears to be a recurrent scenario. Fruit flies (family Tephritidae) employ this strategy, and include amongst their members some of the most destructive pests (e.g., the olive fruit fly Bactrocera olea or the medfly Ceratitis capitata). In their ms, Karageorgi et al. [1] studied how Drosophila suzukii, a new major agricultural pest species that recently invaded Europe and North America, evolved the novel behavior of laying eggs into undamaged fresh fruit. The close relatives of D. suzukii lay their eggs on decaying plant substrates, and thus this represents a marked change in host use that links to substantial economic losses to the fruit industry. Although a handful of studies have identified genetic changes causing new behaviors in various species, the question of the evolution of behavior remains a largely uncharted territory. The study by Karageorgi et al. [1] represents an original and most welcome contribution in this domain for a non-model species. Using clever behavioral experiments to compare D. suzukii to several related Drosophila species, and complementing those results with neurogenetics and mutant analyses using D. suzukii, the authors nicely dissect the sensory changes at the origin of the new egg-laying behavior. The experiments they describe are easy to follow, richly illustrate through figures and images, and particularly well designed to progressively decipher the sensory bases driving oviposition of D. suzukii on ripe fruit. Altogether, Karageorgi et al.’s [1] results show that the egg-laying substrate preference of D. suzukii has considerably evolved in concert with its morphology (especially its enlarged, serrated ovipositor that enables females to pierce the skin of many ripe fruits). Their observations clearly support the view that the evolution of traits that make D. suzukii an agricultural pest included the modification of several sensory systems (i.e. mechanosensation, gustation and olfaction). These differences between D. suzukii and its close relatives collectively underlie a radical change in oviposition behavior, and were presumably instrumental in the expansion of the ecological niche of the species. The authors tentatively propose a multi-step evolutionary scenario from their results with the emergence of D. suzukii as a pest species as final outcome. Such formalization represents an interesting evolutionary model-framework that obviously would rely upon further data and experiments to confirm and refine some of the evolutionary steps proposed, especially the final and recent transition of D. suzukii from non-invasive to invasive species.

References

[1] Karageorgi M, Bräcker LB, Lebreton S, Minervino C, Cavey M, Siju KP, Grunwald Kadow IC, Gompel N, Prud’homme B. 2017. Evolution of multiple sensory systems drives novel egg-laying behavior in the fruit pest Drosophila suzukii. Current Biology, 27: 1-7. doi: 10.1016/j.cub.2017.01.055

Evolution of multiple sensory systems drives novel egg-laying behavior in the fruit pest Drosophila suzukiiMarianthi Karageorgi, Lasse B. Bräcker, Sébastien Lebreton, Caroline Minervino, Matthieu Cavey, K.P. Siju, Ilona C. Grunwald Kadow, Nicolas Gompel, Benjamin Prud’hommeThe rise of a pest species represents a unique opportunity to address how species evolve new behaviors and adapt to novel ecological niches. We address this question by studying the egg-laying behavior of Drosophila suzukii, an invasive agricultur...Adaptation, Behavior & Social Evolution, Evo-Devo, Evolutionary Applications, Evolutionary Ecology, Expression Studies, Genotype-Phenotype, Macroevolution, Molecular EvolutionArnaud Estoup2017-03-13 17:42:00 View
15 Dec 2016
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Limiting opportunities for cheating stabilizes virulence in insect parasitic nematodes

Application of kin theory to long-standing problem in nematode production for biocontrol

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Much research effort has been extended toward developing systems for managing soil inhabiting insect pests of crops with entomopathogenic nematodes as biocontrol agents. Although small plot or laboratory experiments may suggest a particular insect pest is vulnerable to management in this way, it is often difficult to scale-up nematode production for application at the field- and farm scale to make such a tactic viable. Part of the problem is that entomopathogenic nematode strains must be propagated by serial passage in vivo, because storage by freezing decreases fitness. At the same time, serial propagation results in loss of virulence (ability to infect) over generations in the laboratory, a phenomenon called attenuation.

To probe the underlying reasons for development of attenuation, as a prerequisite to designing strategies to mitigate it, Shapiro-Ilan and Raymond [1] turned to evolutionary theory of social conflict as a possible explanatory framework. Virulence of entomopathogenic nematodes depends on a combination of virulence factors, like various proteases, secreted by both the nematode and symbiotic bacteria to overcome host defenses. Attenuation is characterized in part by a reduced production of these factors. Invasion of a host involves simultaneous attack by a group of nematodes ("cooperators"), which together neutralize host defenses enough to allow individuals to successfully invade. "Cheaters" in the invading population can avoid the metabolic costs of producing virulence factors while reaping the benefits of infecting the host made vulnerable by the cooperators in the population. The authors hypothesize that an increase in frequency of cheaters may contribute to attenuation of virulence during serial propagation in the laboratory. The evolutionary dynamics of cheater frequency in a population have been explored in many contexts as part of kin selection theory. Cheaters can increase in a population by outcompeting cooperators in a host if overall relatedness within the invading population is low. Conversely, frequency of altruism, or costly cooperation, increases in a population if relatedness is high, which is enhanced by low effective dispersal. However, a population that is too isolated can suffer from inbreeding effects, and competition will occur mainly among relatives, which decreases the fitness benefits of altruism.

Shapiro-Ilan and Raymond [1] tested changes in virulence and reproductive output in a serially propagated entomopathogenic nematode, Heterorhabditis floridensis. They compared lines of high or low relatedness, manipulated via multiplicity of infection (MOI) rates (where a low dose of nematodes gives high relatedness and a high dose gives low relatedness); and under global or local competition, manipulated by pooling populations emerging from all or only two host cadavers per generation, respectively. As predicted, treatments of high relatedness (low MOI) and global competition had the greatest level of reproduction, while all lines of low relatedness (high MOI) evolved decreased reproduction and decreased virulence, which led to extinction. The key finding was that lines in the high relatedness (low MOI) and low (local) competition treatment exhibited the most stable virulence through the 12 generations tested. Thus, to minimize attenuation of virulence while maintaining fitness of recently isolated entomopathogenic nematodes, the authors recommend insect hosts be inoculated with low doses of nematodes from inocula pools from as few cadavers as possible.

The application of evolutionary theory, with a clever experimental design, to an important problem in pest management makes this paper particularly noteworthy.

Reference

[1] Shapiro-Ilan D, Raymond B. 2016. Limiting opportunities for cheating stabilizes virulence in insect parasitic nematodes. Evolutionary Applications 9:462-470. doi: 10.1111/eva.12348

Limiting opportunities for cheating stabilizes virulence in insect parasitic nematodesShapiro-Ilan D. and B. RaymondCooperative secretion of virulence factors by pathogens can lead to social conflict when cheating mutants exploit collective secretion, but do not contribute to it. If cheats outcompete cooperators within hosts, this can cause loss of virulence....Adaptation, Behavior & Social Evolution, Evolutionary Applications, Evolutionary Dynamics, Evolutionary Ecology, Evolutionary Epidemiology, Evolutionary Theory, Experimental Evolution, Population Genetics / Genomics, Reproduction and SexThomas Sappington2016-12-15 18:33:39 View
18 Nov 2020
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A demogenetic agent based model for the evolution of traits and genome architecture under sexual selection

Sexual selection goes dynamic

Recommended by based on reviews by Frédéric Guillaume and 1 anonymous reviewer

150 years after Darwin published ‘Descent of man and selection in relation to sex’ (Darwin, 1871), the evolutionary mechanism that he laid out in his treatise continues to fascinate us. Sexual selection is responsible for some of the most spectacular traits among animals, and plants, and it appeals to our interest in all things reproductive and sexual (Bell, 1982). In addition, sexual selection poses some of the more intractable problems in evolutionary biology: Its realm encompasses traits that are subject to markedly different selection pressures, particularly when distinct, yet associated, traits tend to be associated with males, e.g. courtship signals, and with females, e.g. preferences (cf. Ah-King & Ahnesjo, 2013). While separate, such traits cannot evolve independently of each other (Arnqvist & Rowe, 2005), and complex feedback loops and correlations between them are predicted (Greenfield et al., 2014). Traditionally, sexual selection has been modelled under simplifying assumptions, and quantitative genetic approaches that avoided evolutionary dynamics have prevailed. New computing methods may be able to free the field from these constraints, and a trio of theoreticians (Chevalier, De Coligny & Labonne 2020) describe here a novel application of a ‘demo-genetic agent (or individual) based model’, a mouthful hereafter termed DG-ABM, for arriving at a holistic picture of the sexual selection trajectory. The application is built on the premise that traits, e.g. courtship, preference, gamete investment, competitiveness for mates, can influence the genetic architecture, e.g. correlations, of those traits. In turn, the genetic architecture can influence the expression and evolvability of the traits. Much of this influence occurs via demographic features, i.e. social environment, generated by behavioral interactions during sexual advertisement, courtship, mate guarding, parental care, post-mating dispersal, etc.
The authors provide a lengthy verbal description of their model, specifying the genomic and behavioral parameters that can be set and how a ‘run’ may be initialized. There is a link to an internet site where users can then enter their own parameter values and begin exploring hypotheses. Back in the article several simulations illustrate simple tests; e.g. how gamete investment and preference jointly evolve given certain survival costs. One obvious test would have been the preference – courtship genetic correlation that represents the core of Fisherian runaway selection, and it is regrettable that it was not examined under a range of demographic parameters. As presented the author’s DG-ABM appears particularly geared toward mating systems in ‘higher’ vertebrates, where couples form during a discrete mating season and are responsible for most reproduction. It is not clear how applicable the model could be to a full range of mating systems and nuances, including those in arthropods and other invertebrates as well as plants.
What is the likely value of the DG-ABM for sexual selection researchers? We will not be able to evaluate its potential impact until readers with specialized understanding of a question and taxon begin exploring and comparing their results with prior expectations. Of course, lack of congruence with earlier predictions would not invalidate the model. Hopefully, some of these specialists will have opportunities for comparing results with pertinent empirical data.

References

Ah-King, M. and Ahnesjo, I. 2013. The ‘sex role’ concept: An overview and evaluation Evolutionary Biology, 40, 461-470. doi: https://doi.org/10.1007/s11692-013-9226-7
Arnqvist, G. and Rowe, L. 2005. Sexual Conflict. Princeton University Press, Princeton. doi: https://doi.org/10.1515/9781400850600
Bell, G. 1982. The Masterpiece of Nature: The Evolution and Genetics of Sexuality. University of California Press, Berkeley.
Chevalier, L., De Coligny, F. and Labonne, J. (2020) A demogenetic individual based model for the evolution of traits and genome architecture under sexual selection. bioRxiv, 2020.04.01.014514, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: https://doi.org/10.1101/2020.04.01.014514
Darwin, C. 1871. The Descent of Man and Selection in Relation to Sex. J. Murray, London.
Greenfield, M.D., Alem, S., Limousin, D. and Bailey, N.W. 2014. The dilemma of Fisherian sexual selection: Mate choice for indirect benefits despite rarity and overall weakness of trait-preference genetic correlation. Evolution, 68, 3524-3536. doi: https://doi.org/10.1111/evo.12542

A demogenetic agent based model for the evolution of traits and genome architecture under sexual selectionLouise Chevalier, François de Coligny, Jacques Labonne<p>Sexual selection has long been known to favor the evolution of mating behaviors such as mate preference and competitiveness, and to affect their genetic architecture, for instance by favoring genetic correlation between some traits. Reciprocall...Adaptation, Behavior & Social Evolution, Evolutionary Dynamics, Evolutionary Theory, Life History, Population Genetics / Genomics, Sexual SelectionMichael D Greenfield2020-04-02 14:44:25 View
20 Nov 2023
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Phenotypic stasis with genetic divergence

Phenotypic stasis despite genetic divergence and differentiation in Caenorhabditis elegans.

Recommended by ORCID_LOGO based on reviews by Benoit Pujol and Pedro Simões

Explaining long periods of evolutionary stasis, the absence of change in trait means over geological times, despite the existence of abundant genetic variation in most traits has challenged evolutionary theory since Darwin's theory of evolution by gradual modification (Estes & Arnold 2007). Stasis observed in contemporary populations is even more daunting since ample genetic variation is usually coupled with the detection of selection differentials (Kruuk et al. 2002, Morrissey et al. 2010). Moreover, rapid adaptation to environmental changes in contemporary populations, fuelled by standing genetic variation provides evidence that populations can quickly respond to an adaptive challenge. Explanations for evolutionary stasis usually invoke stabilizing selection as a main actor, whereby optimal trait values remain roughly constant over long periods of time despite small-scale environmental fluctuations. Genetic correlation among traits may also play a significant role in constraining evolutionary changes over long timescales (Schluter 1996). Yet, genetic constraints are rarely so strong as to completely annihilate genetic changes, and they may evolve. Patterns of genetic correlations among traits, as captured in estimates of the G-matrix of additive genetic co-variation, are subject to changes over generations under the action of drift, migration, or selection, among other causes (Arnold et al. 2008). Therefore, under the assumption of stabilizing selection on a set of traits, phenotypic stasis and genetic divergence in patterns of trait correlations may both be observed when selection on trait correlations is weak relative to its effect on trait means.

Mallard et al. (2023) set out to test whether selection or drift may explain the divergence in genetic correlation among traits in experimental lines of the nematode Caenorhabditis elegans and whether stabilizing selection may be a driver of phenotypic stasis. To do so, they analyzed the evolution of locomotion behavior traits over 100 generations of lab evolution in a constant and homogeneous environment after 140 generations of domestication from a largely differentiated set of founder populations. The locomotion traits were transition rates between movement states and direction (still, forward or backward movement). They could estimate the traits' broad-sense G-matrix in three populations at two generations (50 and 100), and in the ancestral mixed population. Similarly, they estimated the shape of the selection surface by regressing locomotion behavior on fertility. Armed with both G-matrix and surface estimates, they could test whether the G's orientation matched selection's orientation and whether changes in G were constrained by selection. They found stasis in trait mean over 100 generations but divergence in the amount and orientation of the genetic variation of the traits relative to the ancestral population. The selected populations changed orientation of their G-matrices and lost genetic variation during the experiment in agreement with a model of genetic drift on quantitative traits. Their estimates of selection also point to mostly stabilizing selection on trait combinations with weak evidence of disruptive selection, suggesting a saddle-shaped selection surface. The evolutionary responses of the experimental populations were mostly consistent with small differentiation in the shape of G-matrices during the 100 generations of stabilizing selection.

Mallard et al. (2023) conclude that phenotypic stasis was maintained by stabilizing selection and drift in their experiment. They argue that their findings are consistent with a "table-top mountain" model of stabilizing selection, whereby the population is allowed some wiggle room around the trait optimum, leaving space for random fluctuations of trait variation, and especially trait co-variation. The model is an interesting solution that might explain how stasis can be maintained over contemporary times while allowing for random differentiation of trait genetic co-variation. Whether such differentiation can then lead to future evolutionary divergence once replicated populations adapt to a new environment is an interesting idea to follow.

References

Arnold, S. J., Bürger, R., Hohenlohe, P. A., Ajie, B. C. and Jones, A. G. 2008. Understanding the evolution and stability of the G-matrix. Evolution 62(10): 2451-2461. 
https://doi.org/10.1111/j.1558-5646.2008.00472.x
 
Estes, S. and Arnold, S. J. 2007. Resolving the Paradox of Stasis: Models with Stabilizing Selection Explain Evolutionary Divergence on All Timescales.. Am. Nat. 169(2): 227-244.
https://doi.org/10.1086/510633
 
Kruuk, L. E. B., Slate, J., Pemberton, J. M., Brotherstone, S., Guinness, F. and Clutton-Brock, T. 2002. Antler size in red deer: Heritability and selection but no evolution. Evolution 56(8): 1683-1695.
https://doi.org/10.1111/j.0014-3820.2002.tb01480.x
 
Mallard, F., Noble, L., Guzella, T., Afonso, B., Baer, C. F., Teotónio, H. 2023. Phenotypic stasis with genetic divergence. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology.
https://doi.org/10.1101/2022.05.28.493856
 
Morrissey, M. B., Kruuk, L. E. B. and Wilson, A. J. 2010. The danger of applying the breeder's equation in observational studies of natural populations. J Evolution Biol 23(11): 2277-2288. 
https://doi.org/10.1111/j.1420-9101.2010.02084.x
 
Schluter, D. 1996. Adaptive radiation along genetic lines of least resistance. Evolution 50(5): 1766-1774. 
https://doi.org/10.1111/j.1558-5646.1996.tb03563.x

Phenotypic stasis with genetic divergenceFrançois Mallard, Luke Noble, Thiago Guzella, Bruno Afonso, Charles F. Baer, Henrique Teotónio<p style="text-align: justify;">Whether or not genetic divergence in the short-term of tens to hundreds of generations is compatible with phenotypic stasis remains a relatively unexplored problem. We evolved predominantly outcrossing, genetically ...Adaptation, Behavior & Social Evolution, Experimental Evolution, Quantitative GeneticsFrédéric Guillaume2022-09-01 14:32:53 View
13 Dec 2018
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A behavior-manipulating virus relative as a source of adaptive genes for parasitoid wasps

Genetic intimacy of filamentous viruses and endoparasitoid wasps

Recommended by based on reviews by Alejandro Manzano Marín and 1 anonymous reviewer

Viruses establish intimate relationships with the cells they infect. The virocell is a novel entity, different from the original host cell and beyond the mere combination of viral and cellular genetic material. In these close encounters, viral and cellular genomes often hybridise, combine, recombine, merge and excise. Such chemical promiscuity leaves genomics scars that can be passed on to descent, in the form of deletions or duplications and, importantly, insertions and back and forth exchange of genetic material between viruses and their hosts.
In this preprint [1], Di Giovanni and coworkers report the identification of 13 genes present in the extant genomes of members of the Leptopilina wasp genus, bearing sound signatures of having been horizontally acquired from an ancestral virus. Importantly the authors identify Leptopilina boulardi filamentous virus (LbFV) as an extant relative of the ancestral virus that served as donor for the thirteen horizontally transferred genes. While pinpointing genes with a likely possible viral origin in eukaryotic genomes is only relatively rare, identifying an extant viral lineage related to the ancestral virus that continues to infect an extant relative of the ancestral host is remarkable. But the amazing evolutionary history of the Leptopilina hosts and these filamentous viruses goes beyond this shared genes. These wasps are endoparasitoids of Drosophila larvae, the female wasp laying the eggs inside the larvae and simultaneously injecting venom that hinders the immune response. The composition of the venoms is complex, varies between wasp species and also between individuals within a species, but a central component of all these venoms are spiked structures that vary in morphology, symmetry and size, often referred to as virus-like particles (VLPs).
In this preprint, the authors convincingly show that the expression pattern in the Leptopilina wasps of the thirteen genes identified to have been horizontally acquired from the LbFV ancestor coincides with that of the production of VLPs in the female wasp venom gland. Based on this spatio-temporal match, the authors propose that these VLPs have a viral origin. The data presented in this preprint will undoubtedly stimulate further research on the composition, function, origin, evolution and diversity of these VLP structures, which are highly debated (see for instance [2] and [3]).

References

[1] Di Giovanni, D., Lepetit, D., Boulesteix, M., Ravallec, M., & Varaldi, J. (2018). A behavior-manipulating virus relative as a source of adaptive genes for parasitoid wasps. bioRxiv, 342758, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/342758
[2] Poirié, M., Colinet, D., & Gatti, J. L. (2014). Insights into function and evolution of parasitoid wasp venoms. Current Opinion in Insect Science, 6, 52-60. doi: 10.1016/j.cois.2014.10.004
[3] Heavner, M. E., Ramroop, J., Gueguen, G., Ramrattan, G., Dolios, G., Scarpati, M., ... & Govind, S. (2017). Novel organelles with elements of bacterial and eukaryotic secretion systems weaponize parasites of Drosophila. Current Biology, 27(18), 2869-2877. doi: 10.1016/j.cub.2017.08.019

A behavior-manipulating virus relative as a source of adaptive genes for parasitoid waspsD. Di Giovanni, D. Lepetit, M. Boulesteix, M. Ravallec, J. Varaldi<p>To circumvent host immune response, numerous hymenopteran endo-parasitoid species produce virus-like structures in their reproductive apparatus that are injected into the host together with the eggs. These viral-like structures are absolutely n...Adaptation, Behavior & Social Evolution, Genetic conflicts, Genome EvolutionIgnacio Bravo2018-07-18 15:59:14 View
13 Dec 2016
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Structural genomic changes underlie alternative reproductive strategies in the ruff (Philomachus pugnax)

Supergene Control of a Reproductive Polymorphism

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Two back-to-back papers published earlier this year in Nature Genetics provide compelling evidence for the control of a male reproductive polymorphism in a wading bird by a "supergene", a cluster of tightly linked genes [1-2]. The bird in question, the ruff (Philomachus pugnax), has a rather unusual reproductive system that consists of three distinct types of males ("reproductive morphs"): aggressive "independents" who represent the majority of males; a smaller fraction of non-territorial "satellites" who are submissive towards "independents"; and "faeders" who mimic females and are rare. Previous work has shown that the male morphs differ in major aspects of mating and aggression behavior, plumage coloration and body size, and that – intriguingly – this complex multi-trait polymorphism is apparently controlled by a single autosomal Mendelian locus with three alleles [3]. To uncover the genetic control of this polymorphism two independent teams, led by Terry Burke [1] and Leif Andersson [2], have set out to analyze the genomes of male ruffs. Using a combination of genomics and genetics, both groups managed to pin down the supergene locus and map it to a non-recombining, 4.5 Mb large inversion which arose 3.8 million years ago. While "independents" are homozygous for the ancestral uninverted sequence, "satellites" and "faeders" carry evolutionarily divergent, dominant alternative haplotypes of the inversion. Thus, as in several other notable cases, for example the supergene control of disassortative mating, aggressiveness and plumage color in white-throated sparrows [4], of mimicry in Heliconius and Papilio butterflies [5-6], or of social structure in ants [7], an inversion – behaving as a single "locus" – underpins the mechanistic basis of the supergene. More generally, and beyond inversions, a growing number of studies now shows that selection can favor the evolution of suppressed recombination, thereby leading to the emergence of clusters of tightly linked loci which can then control – presumably due to polygenic gene action – a suite of complex phenotypes [8-10]. A largely unresolved question in this field concerns the identity of the causative alleles and loci within a given supergene. Recent progress on this question has been made for example in Papilio polytes butterflies where a mimicry supergene has been found to involve – surprisingly – only a single but large gene: multiple mimicry alleles in the doublesex gene are maintained in strong linkage disequilibrium via an inversion. It will clearly be of great interest to see future examples of such a fine-scale genetic dissection of supergenes. In conclusion, we were impressed by the data and analyses of Küpper et al. [1] and Lamichhaney et al. [2]: both papers beautifully illustrate how genomics and evolutionary ecology can be combined to make new, exciting discoveries. Both papers will appeal to readers with an interest in supergenes, inversions, the interplay of selection and recombination, or the genetic control of complex phenotypes.

References

[1] Küpper C, Stocks M, Risse JE, dos Remedios N, Farrell LL, McRae SB, Morgan TC, Karlionova N, Pinchuk P, Verkuil YI, et al. 2016. A supergene determines highly divergent male reproductive morphs in the ruff. Nature Genetics 48:79-83. doi: 10.1038/ng.3443

[2] Lamichhaney S, Fan G, Widemo F, Gunnarsson U, Thalmann DS, Hoeppner MP, Kerje S, Gustafson U, Shi C, Zhang H, et al. 2016. Structural genomic changes underlie alternative reproductive strategies in the ruff (Philomachus pugnax). Nature Genetics 48:84-88. doi: 10.1038/ng.3430

[3] Lank DB, Smith CM, Hanotte O, Burke T, Cooke F. 1995. Genetic polymorphism for alternative mating behaviour in lekking male ruff Philomachus pugnax. Nature 378:59-62. doi: 10.1038/378059a0

[4] Tuttle Elaina M, Bergland Alan O, Korody Marisa L, Brewer Michael S, Newhouse Daniel J, Minx P, Stager M, Betuel A, Cheviron Zachary A, Warren Wesley C, et al. 2016. Divergence and Functional Degradation of a Sex Chromosome-like Supergene. Current Biology 26:344-350. doi: 10.1016/j.cub.2015.11.069

[5] Joron M, Frezal L, Jones RT, Chamberlain NL, Lee SF, Haag CR, Whibley A, Becuwe M, Baxter SW, Ferguson L, et al. 2011. Chromosomal rearrangements maintain a polymorphic supergene controlling butterfly mimicry. Nature 477:203-206. doi: 10.1038/nature10341

[6] Kunte K, Zhang W, Tenger-Trolander A, Palmer DH, Martin A, Reed RD, Mullen SP, Kronforst MR. 2014. doublesex is a mimicry supergene. Nature 507:229-232. doi: 10.1038/nature13112

[7] Wang J, Wurm Y, Nipitwattanaphon M, Riba-Grognuz O, Huang Y-C, Shoemaker D, Keller L. 2013. A Y-like social chromosome causes alternative colony organization in fire ants. Nature 493:664-668. doi: 10.1038/nature11832

[8] Thompson MJ, Jiggins CD. 2014. Supergenes and their role in evolution. Heredity 113:1-8. doi: 10.1038/hdy.2014.20

[9] Schwander T, Libbrecht R, Keller L. 2014. Supergenes and Complex Phenotypes. Current Biology 24:R288-R294. doi: 10.1016/j.cub.2014.01.056

[10] Charlesworth D. 2015. The status of supergenes in the 21st century: recombination suppression in Batesian mimicry and sex chromosomes and other complex adaptations. Evolutionary Applications 9:74-90. doi: 10.1111/eva.12291

Structural genomic changes underlie alternative reproductive strategies in the ruff (Philomachus pugnax)Lamichhaney S, Fan G, Widemo F, Gunnarsson U, Thalmann DS, Hoeppner MP, Kerje S, Gustafson U, Shi C, Zhang H, et al.The ruff is a Palearctic wader with a spectacular lekking behavior where highly ornamented males compete for females1, 2, 3, 4. This bird has one of the most remarkable mating systems in the animal kingdom, comprising three different male morphs (...Adaptation, Behavior & Social Evolution, Genotype-Phenotype, Life History, Population Genetics / Genomics, Quantitative Genetics, Reproduction and SexThomas Flatt2016-12-13 17:46:54 View
16 Nov 2022
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Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice

Tinder in mice: A match made with the sense of smell

Recommended by ORCID_LOGO based on reviews by Angeles de Cara, Ludovic Claude Maisonneuve and 1 anonymous reviewer

Differentiation-based genome scans lie at the core of speciation and adaptation genomics research. Dating back to Lewontin & Krakauer (1973), they have become very popular with the advent of genomics to identify genome regions of enhanced differentiation relative to neutral expectations. These regions may represent genetic barriers between divergent lineages and are key for studying reproductive isolation. However, genome scan methods can generate a high rate of false positives, primarily if the neutral population structure is not accounted for (Bierne et al. 2013). Moreover, interpreting genome scans can be challenging in the context of secondary contacts between diverging lineages (Bierne et al. 2011), because the coupling between different components of reproductive isolation (local adaptation, intrinsic incompatibilities, mating preferences, etc.) can occur readily, thus preventing the causes of differentiation from being determined.

Smadja and collaborators (2022) applied a sophisticated genome scan for trait association (BAYPASS, Gautier 2015) to underlie the genetic basis of a polygenetic behaviour: assortative mating in hybridizing mice. My interest in this neat study mainly relies on two reasons. First, the authors used an ingenious geographical setting (replicate pairs of “Choosy” versus “Non-Choosy” populations) with multi-way comparisons to narrow down the list of candidate regions resulting from BAYPASS. The latter corrects for population structure, handles cost-effective pool-seq data and allows for gene-based analyses that aggregate SNP signals within a gene. These features reinforce the set of outlier genes detected; however, not all are expected to be associated with mating preference. 

The second reason why this study is valuable to me is that Smadja et al. (2022) complemented the population genomic approach with functional predictions to validate the genetic signal. In line with previous behavioural and chemical assays on the proximal mechanisms of mating preferences, they identified multiple olfactory and vomeronasal receptor genes as highly significant candidates. Therefore, combining genomic signals with functional analyses is a clever way to provide insights into the causes of reproductive isolation, especially when multiple barriers are involved. This is typically true for reinforcement (Butlin & Smadja 2018), suspected to occur in these mice because, in that case, assortative mating (a prezygotic barrier) evolves in response to the cost of hybridization (for example, due to hybrid inviability). 

As advocated by the authors, their study paves the way for future work addressing the genetic basis of reinforcement, a trait of major evolutionary importance for which we lack empirical data. They also make a compelling case using complementary approaches that olfactory and vomeronasal receptors have a central role in mammal speciation.


References:

Bierne N, Welch J, Loire E, Bonhomme F, David P (2011) The coupling hypothesis: why genome scans may fail to map local adaptation genes. Mol Ecol 20: 2044–2072. https://doi.org/10.1111/j.1365-294X.2011.05080.x

Bierne N, Roze D, Welch JJ (2013) Pervasive selection or is it…? why are FST outliers sometimes so frequent? Mol Ecol 22: 2061–2064. https://doi.org/10.1111/mec.12241 

Butlin RK, Smadja CM (2018) Coupling, Reinforcement, and Speciation. Am Nat 191:155–172. https://doi.org/10.1086/695136 

Gautier M (2015) Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates. Genetics 201:1555–1579. https://doi.org/10.1534/genetics.115.181453 

Lewontin RC, Krakauer J (1973) Distribution of gene frequency as a test of the theory of selective neutrality of polymorphisms. Genetics 74: 175–195. https://doi.org/10.1093/genetics/74.1.175 

Smadja CM, Loire E, Caminade P, Severac D, Gautier M, Ganem G (2022) Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice. bioRxiv, 2022.07.21.500634, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.07.21.500634

Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in miceCarole M. Smadja, Etienne Loire, Pierre Caminade, Dany Severac, Mathieu Gautier, Guila Ganem<p>Deciphering the genetic bases of behavioural traits is essential to understanding how they evolve and contribute to adaptation and biological diversification, but it remains a substantial challenge, especially for behavioural traits with polyge...Adaptation, Behavior & Social Evolution, Genotype-Phenotype, SpeciationChristelle Fraïsse2022-07-25 11:54:52 View
22 May 2023
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Weak seed banks influence the signature and detectability of selective sweeps

New insights into the dynamics of selective sweeps in seed-banked species

Recommended by ORCID_LOGO based on reviews by Guillaume Achaz, Jere Koskela, William Shoemaker and Simon Boitard

Many organisms across the Tree of life have the ability to produce seeds, eggs, cysts, or spores, that can remain dormant for several generations before hatching. This widespread adaptive trait in bacteria, fungi, plants and animals, has a significant impact on the ecology, population dynamics and population genetics of species that express it (Evans and Dennehy 2005).

In population genetics, and despite the recognition of its evolutionary importance in many empirical studies, few theoretical models have been developed to characterize the evolutionary consequences of this trait on the level and distribution of neutral genetic diversity (see, e.g., Kaj et al. 2001; Vitalis et al. 2004), and also on the dynamics of selected alleles (see, e.g., Živković and Tellier 2018). However, due to the complexity of the interactions between evolutionary forces in the presence of dormancy, the fate of selected mutations in their genomic environment is not yet fully understood, even from the most recently developed models.

In a comprehensive article, Korfmann et al. (2023) aim to fill this gap by investigating the effect of germ banking on the probability of (and time to) fixation of beneficial mutations, as well as on the shape of the selective sweep in their vicinity. To this end, Korfmann et al. (2023) developed and released their own forward-in-time simulator of genome-wide data, including neutral and selected polymorphisms, that makes use of Kelleher et al.’s (2018) tree sequence toolkit to keep track of gene genealogies.

The originality of Korfmann et al.’s (2023) study is to provide new quantitative results for the effect of dormancy on the time to fixation of positively selected mutations, the shape of the genomic landscape in the vicinity of these mutations, and the temporal dynamics of selective sweeps. Their major finding is the prediction that germ banking creates narrower signatures of sweeps around positively selected sites, which are detectable for increased periods of time (as compared to a standard Wright-Fisher population).

The availability of Korfmann et al.’s (2023) code will allow a wider range of parameter values to be explored, to extend their results to the particularities of the biology of many species. However, as they chose to extend the haploid coalescent model of Kaj et al. (2001), further development is needed to confirm the robustness of their results with a more realistic diploid model of seed dormancy.

REFERENCES

Evans, M. E. K., and J. J. Dennehy (2005) Germ banking: bet-hedging and variable release from egg and seed dormancy. The Quarterly Review of Biology, 80(4): 431-451. https://doi.org/10.1086/498282

Kaj, I., S. Krone, and M. Lascoux (2001) Coalescent theory for seed bank models. Journal of Applied Probability, 38(2): 285-300. https://doi.org/10.1239/jap/996986745

Kelleher, J., K. R. Thornton, J. Ashander, and P. L. Ralph (2018) Efficient pedigree recording for fast population genetics simulation. PLoS Computational Biology, 14(11): e1006581. https://doi.org/10.1371/journal.pcbi.1006581

Korfmann, K., D. Abu Awad, and A. Tellier (2023) Weak seed banks influence the signature and detectability of selective sweeps. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.04.26.489499

Vitalis, R., S. Glémin, and I. Olivieri (2004) When genes go to sleep: the population genetic consequences of seed dormancy and monocarpic perenniality. American Naturalist, 163(2): 295-311. https://doi.org/10.1086/381041

Živković, D., and A. Tellier (2018). All but sleeping? Consequences of soil seed banks on neutral and selective diversity in plant species. Mathematical Modelling in Plant Biology, 195-212. https://doi.org/10.1007/978-3-319-99070-5_10

Weak seed banks influence the signature and detectability of selective sweepsKevin Korfmann, Diala Abu Awad, Aurélien Tellier<p style="text-align: justify;">Seed banking (or dormancy) is a widespread bet-hedging strategy, generating a form of population overlap, which decreases the magnitude of genetic drift. The methodological complexity of integrating this trait impli...Adaptation, Bioinformatics & Computational Biology, Evolutionary Applications, Evolutionary Ecology, Genome Evolution, Life History, Population Genetics / GenomicsRenaud Vitalis2022-05-23 13:01:57 View
04 Mar 2024
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Simultaneous Inference of Past Demography and Selection from the Ancestral Recombination Graph under the Beta Coalescent

Beyond the standard coalescent: demographic inference with complete genomes and graph neural networks under the beta coalescent

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

Modelling the evolution of complete genome sequences in populations requires accounting for the recombination process, as a single tree can no longer describe the underlying genealogy. The sequentially Markov coalescent (SMC, McVean and Cardin 2005; Marjoram and Wall 2006) approximates the standard coalescent with recombination process and permits estimating population genetic parameters (e.g., population sizes, recombination rates) using population genomic datasets. As such datasets become available for an increasing number of species, more fine-tuned models are needed to encompass the diversity of life cycles of organisms beyond the model species on which most methods have been benchmarked.

The work by Korfmann et al. (Korfmann et al. 2024) represents a significant step forward as it accounts for multiple mergers in SMC models. Multiple merger models account for simultaneous coalescence events so that more than two lineages find a common ancestor in a given generation. This feature is not allowed in standard coalescent models and may result from selection or skewed offspring distributions, conditions likely met by a broad range of species, particularly microbial.

Yet, this work goes beyond extending the SMC, as it introduces several methodological innovations. The "classical" SMC-based inference approaches rely on hidden Markov models to compute the likelihood of the data while efficiently integrating over the possible ancestral recombination graphs (ARG). Following other recent works (e.g. Gattepaille et al. 2016), Korfmann et al. propose to separate the ARG inference from model parameter estimation under maximum likelihood (ML). They introduce a procedure where the ARG is first reconstructed from the data and then taken as input in the model fitting step. While this approach does not permit accounting for the uncertainty in the ARG reconstruction (which is typically large), it potentially allows for the extraction of more information from the ARG, such as the occurrence of multiple merging events. Going away from maximum likelihood inference, the authors trained a graph neural network (GNN) on simulated ARGs, introducing a new, flexible way to estimate population genomic parameters.

The authors used simulations under a beta-coalescent model with diverse demographic scenarios and showed that the ML and GNN approaches introduced can reliably recover the simulated parameter values. They further show that when the true ARG is given as input, the GNN outperforms the ML approach, demonstrating its promising power as ARG reconstruction methods improve. In particular, they showed that trained GNNs can disentangle the effects of selective sweeps and skewed offspring distributions while inferring past population size changes.

This work paves the way for new, exciting applications, though many questions must be answered. How frequent are multiple mergers? As the authors showed that these events "erase" the record of past demographic events, how many genomes are needed to conduct reliable inference, and can the methods computationally cope with the resulting (potentially large) amounts of required data? This is particularly intriguing as micro-organisms, prone to strong selection and skewed offspring distributions, also tend to carry smaller genomes.

References

Gattepaille L, Günther T, Jakobsson M. 2016. Inferring Past Effective Population Size from Distributions of Coalescent Times. Genetics 204:1191-1206.
https://doi.org/10.1534/genetics.115.185058
 
Korfmann K, Sellinger T, Freund F, Fumagalli M, Tellier A. 2024. Simultaneous Inference of Past Demography and Selection from the Ancestral Recombination Graph under the Beta Coalescent. bioRxiv, 2022.09.28.508873. ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.09.28.508873
 
Marjoram P, Wall JD. 2006. Fast "coalescent" simulation. BMC Genet. 7:16.
https://doi.org/10.1186/1471-2156-7-16
 
McVean GAT, Cardin NJ. 2005. Approximating the coalescent with recombination. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 360:1387-1393.
https://doi.org/10.1098/rstb.2005.1673

Simultaneous Inference of Past Demography and Selection from the Ancestral Recombination Graph under the Beta CoalescentKevin Korfmann, Thibaut Sellinger, Fabian Freund, Matteo Fumagalli, Aurélien Tellier<p style="text-align: justify;">The reproductive mechanism of a species is a key driver of genome evolution. The standard Wright-Fisher model for the reproduction of individuals in a population assumes that each individual produces a number of off...Adaptation, Bioinformatics & Computational Biology, Evolutionary Applications, Evolutionary Theory, Life History, Population Genetics / GenomicsJulien Yann Dutheil2023-07-31 13:11:22 View