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

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

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

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

The genome of eukaryotic species is a complex structure that experience many different interactions within itself and with the surrounding environment. The genetic architecture of a phenotype (that is, the set of genetic elements affecting a trait of the organism) plays a fundamental role in understanding the adaptation process of a species to, for example, different climate environments, or to its interaction with other species. Thus, it is fundamental to study the different aspects of the genetic architecture of the species and its relationship with its surronding environment. Aspects such as modularity (the number of genetic units and the degree to which each unit is affecting a trait of the organism), pleiotropy (the number of different effects that a genetic unit can have on an organism) or linkage (the degree of association between the different genetic units) are essential to understand the genetic architecture and to interpret the effects of selection on the genome. Indeed, the knowledge of the different aspects of the genetic architecture could clarify whether genes are affected by multiple aspects of the environment or, on the contrary, are affected by only specific aspects [1,2].

The work performed by Lotterhos et al. [3] sought to understand the genetic architecture of the adaptation to different environments in lodgepole pine (Pinus contorta), considering as candidate SNPs those previously detected as a result of its extreme association patterns to different environmental variables or to extreme population differentiation. This consideration is very important because the study is only relevant if the studied markers are under the effect of selection. Otherwise, the genetic architecture of the adaptation to different environments would be masked by other (neutral) kind of associations that would be difficult to interpret [4,5]. In order to understand the relationship between genetic architecture and adaptation, it is relevant to detect the association networks of the candidate SNPs with climate variables (a way to measure modularity) and if these SNPs (and loci) are affected by single or multiple environments (a way to measure pleiotropy).

The authors used co-association networks, an innovative approach in this field, to analyse the interaction between the environmental information and the genetic polymorphism of each individual. This methodology is more appropriate than other multivariate methods - such as analysis based on principal components - because it is possible to cluster SNPs based on associations with similar environmental variables. In this sense, the co-association networks allowed to both study the genetic and physical linkage between different co-associations modules but also to compare two different models of evolution: a Modular environmental response architecture (specific genes are affected by specific aspects of the environment) or a Universal pleiotropic environmental response architecture (all genes are affected by all aspects of the environment). The representation of different correlations between allelic frequency and environmental factors (named galaxy biplots) are especially informative to understand the effect of the different clusters on specific aspects of the environment (for example, the co-association network ‘Aridity’ shows strong associations with hot/wet versus cold/dry environments).

The analysis performed by Lotterhos et al. [3], although it has some unavoidable limitations (e.g., only extreme candidate SNPs are selected, limiting the results to the stronger effects; the genetic and physical map is incomplete in this species), includes relevant results and also implements new methodologies in the field. To highlight some of them: the preponderance of a Modular environmental response architecture (evolution in separated modules), the detection of physical linkage among SNPs that are co-associated with different aspects of the environment (which was unexpected a priori), the implementation of co-association networks and galaxy biplots to see the effect of modularity and pleiotropy on different aspects of environment. Finally, this work contains remarkable introductory Figures and Tables explaining unambiguously the main concepts [6] included in this study. This work can be treated as a starting point for many other future studies in the field.

References

[1] Hancock AM, Brachi B, Faure N, Horton MW, Jarymowycz LB, Sperone FG, Toomajian C, Roux F & Bergelson J. 2011. Adaptation to climate across the Arabidopsis thaliana genome. Science 334: 83–86. doi: 10.1126/science.1209244
[2] Wagner GP & Zhang J. The pleiotropic structure of the genotype­phenotype map: the evolvability of complex organisms. Nature Review Genetics 12: 204–213. doi: 10.1038/nrg2949
[3] Lotterhos KE, Yeaman S, Degner J, Aitken S, Hodgins K. 2018. Modularity of genes involved in local adaptation to climate despite physical linkage. bioRxiv 202481, ver. 4 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/202481
[4] Lotterhos KE & Whitlock MC. 2014. Evaluation of demographic history and neutral parameterization on the performance of FST outlier tests. Molecular Ecology 23: 2178–2192. doi: 10.1111/mec.12725
[5] Lotterhos KE & Whitlock MC. 2015. The relative power of genome scans to detect local adaptation depends on sampling design and statistical method. Molecular Ecology 24: 1031–1046. doi: 10.1111/mec.13100
[6] Paaby AB & Rockman MV. 2013. The many faces of pleiotropy. Trends in Genetics 29: 66-73. doi: 10.1016/j.tig.2012.10.010