Jean Cury and colleagues (2021) have developed a protocol to simulate bacterial evolution in SLiM. In contrast to existing methods that depend on the coalescent, SLiM simulates evolution forward in time. SLiM has, up to now, mostly been used to simulate the evolution of eukaryotes (Haller and Messer 2019), but has been adapted here to simulate evolution in bacteria. Forward-in-time simulations are usually computationally very costly. To circumvent this issue, bacterial population sizes are scaled down. One would now expect results to become inaccurate, however, Cury et al. show that scaled-down forwards simulations provide very accurate results (similar to those provided by coalescent simulators) that are consistent with theoretical expectations. Simulations were analyzed and compared to existing methods in simple and slightly more complex scenarios where recombination affects evolution. In all scenarios, simulation results from coalescent methods (fastSimBac (De Maio and Wilson 2017), ms (Hudson 2002)) and scaled-down forwards simulations were very similar, which is very good news indeed.

A biologist not aware of the complexities of forwards, backwards simulations and the coalescent, might now naïvely ask why another simulation method is needed if existing methods perform just as well. To address this question the manuscript closes with a very neat example of what exactly is possible with forwards simulations that cannot be achieved using existing methods. The situation modeled is the growth and evolution of a set of 50 bacteria that are randomly distributed on a petri dish. One side of the petri dish is covered in an antibiotic the other is antibiotic-free. Over time, the bacteria grow and acquire antibiotic resistance mutations until the entire artificial petri dish is covered with a bacterial lawn. This simulation demonstrates that it is possible to simulate extremely complex (e.g. real world) scenarios to, for example, assess whether certain phenomena are expected with our current understanding of bacterial evolution, or whether there are additional forces that need to be taken into account. Hence, forwards simulators could significantly help us to understand what current models can and cannot explain in evolutionary biology.  

References  

Cury J, Haller BC, Achaz G, Jay F (2021) Simulation of bacterial populations with SLiM. bioRxiv, 2020.09.28.316869, version 5 peer-reviewed and recommended by Peer community in Evolutionary Biology.  https://doi.org/10.1101/2020.09.28.316869

De Maio N, Wilson DJ (2017) The Bacterial Sequential Markov Coalescent. Genetics, 206, 333–343. https://doi.org/10.1534/genetics.116.198796

Haller BC, Messer PW (2019) SLiM 3: Forward Genetic Simulations Beyond the Wright–Fisher Model. Molecular Biology and Evolution, 36, 632–637. https://doi.org/10.1093/molbev/msy228

Hudson RR (2002) Generating samples under a Wright–Fisher neutral model of genetic variation. Bioinformatics, 18, 337–338. https://doi.org/10.1093/bioinformatics/18.2.337

In mammals, it is well documented that sexual dimorphism and in particular sex differences in behaviour are fine-tuned by gonadal hormonal profiles. For example, in lemurs, where female social dominance is common, the level of testosterone in females is unusually high compared to that of other primate females (Petty and Drea 2015). 

Recent studies however suggest that gonadal hormones might not be the only biological factor involved in establishing sexual dimorphism, sex chromosomes might also play a role. The four core genotype (FCG) model and other similar systems allowing to decouple phenotypic and genotypic sex in mice have provided very convincing evidence of such a role (Gatewood et al. 2006; Arnold and Chen 2009; Arnold 2020a, 2020b). This however is a new field of research and the role of sex chromosomes in establishing sexually dimorphic behaviours has not been studied very much yet. Moreover, the FCG model has some limits. Sry, the male determinant gene on the mammalian Y chromosome might be involved in some sex differences in neuroanatomy, but Sry is always associated with maleness in the FCG model, and this potential role of Sry cannot be studied using this system.

Heitzmann et al. have used a natural system to approach these questions. They worked on the African Pygmy mouse, Mus minutoides, in which a modified X chromosome called X* can feminize X*Y individuals, which offers a great opportunity for elegant experiments on the effects of sex chromosomes versus hormones on behaviour. They focused on maternal care and compared pup retrieval, nest quality, and mother-pup interactions in XX, X*X and X*Y females. They found that X*Y females are significantly better at retrieving pups than other females. They are also much more aggressive towards the fathers than other females, preventing paternal care. They build nests of poorer quality but have similar interactions with pups compared to other females. Importantly, no significant differences were found between XX and X*X females for these traits, which points to an effect of the Y chromosome in explaining the differences between X*Y and other females (XX, X*X). Also, another work from the same group showed similar gonadal hormone levels in all the females (Veyrunes et al. 2022). 

Heitzmann et al. made a number of predictions based on what is known about the neuroanatomy of rodents which might explain such behaviours. Using cytology, they looked for differences in neuron numbers in the hypothalamus involved in the oxytocin, vasopressin and dopaminergic pathways in XX, X*X and X*Y females, but could not find any significant effects. However, this part of their work relied on very small sample sizes and they used virgin females instead of mothers for ethical reasons, which greatly limited the analysis. 

Interestingly, X*Y females have a higher reproductive performance than XX and X*X ones, which compensate for the cost of producing unviable YY embryos and certainly contribute to maintaining a high frequency of X* in many African pygmy mice populations (Saunders et al. 2014, 2022). X*Y females are probably solitary mothers contrary to other females, and Heitzmann et al. have uncovered a divergent female strategy in this species. Their work points out the role of sex chromosomes in establishing sex differences in behaviours. 

References

Arnold AP (2020a) Sexual differentiation of brain and other tissues: Five questions for the next 50 years. Hormones and Behavior, 120, 104691. https://doi.org/10.1016/j.yhbeh.2020.104691

Arnold AP (2020b) Four Core Genotypes and XY* mouse models: Update on impact on SABV research. Neuroscience & Biobehavioral Reviews, 119, 1–8. https://doi.org/10.1016/j.neubiorev.2020.09.021

Arnold AP, Chen X (2009) What does the “four core genotypes” mouse model tell us about sex differences in the brain and other tissues? Frontiers in Neuroendocrinology, 30, 1–9. https://doi.org/10.1016/j.yfrne.2008.11.001

Gatewood JD, Wills A, Shetty S, Xu J, Arnold AP, Burgoyne PS, Rissman EF (2006) Sex Chromosome Complement and Gonadal Sex Influence Aggressive and Parental Behaviors in Mice. Journal of Neuroscience, 26, 2335–2342. https://doi.org/10.1523/JNEUROSCI.3743-05.2006

Heitzmann LD, Challe M, Perez J, Castell L, Galibert E, Martin A, Valjent E, Veyrunes F (2022) Genotypic sex shapes maternal care in the African Pygmy mouse, Mus minutoides. bioRxiv, 2022.04.05.487174, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.04.05.487174

Petty JMA, Drea CM (2015) Female rule in lemurs is ancestral and hormonally mediated. Scientific Reports, 5, 9631. https://doi.org/10.1038/srep09631

Saunders PA, Perez J, Rahmoun M, Ronce O, Crochet P-A, Veyrunes F (2014) Xy Females Do Better Than the Xx in the African Pygmy Mouse, Mus Minutoides. Evolution, 68, 2119–2127. https://doi.org/10.1111/evo.12387

Saunders PA, Perez J, Ronce O, Veyrunes F (2022) Multiple sex chromosome drivers in a mammal with three sex chromosomes. Current Biology, 32, 2001-2010.e3. https://doi.org/10.1016/j.cub.2022.03.029

Veyrunes F, Perez J, Heitzmann L, Saunders PA, Givalois L (2022) Separating the effects of sex hormones and sex chromosomes on behavior in the African pygmy mouse Mus minutoides, a species with XY female sex reversal. bioRxiv, 2022.07.11.499546. https://doi.org/10.1101/2022.07.11.499546

In the 19th century, C. Darwin and F. Delpino engaged in a debate about the success of species with different reproduction modes, with the later favouring the idea that monoecious plants capable of autonomous selfing could spread more easily than dioecious plants (or self-incompatible hermaphroditic plants) if cross-pollination opportunities were limited [1]. Since then, debate has never faded about how natural selection is responsible for transitions to selfing and can explain the diversity and distribution of reproduction modes we observe in the natural world [2, 3].
Explanations for mating systems diversity, and transitions to selfing in particular, generally fall into two categories: either genetic or ecological. On the genetic side, many theoretical works showed a critical role for mutation load and inbreeding depression, transmission advantage and reproductive assurance in the evolution of selfing, e.g. [4]. Many experimental works were conducted to test theoretical hypotheses and predictions, especially regarding the magnitude of inbreeding depression; see [5] for a review. Ecologically, the presence of selfing populations is usually correlated with fragmented and harsh habitats, on the periphery of ancestral outcrossing populations. The cause of this distribution could be that selfers are better dispersers and colonizers than outcrossers, or variations in other life-history traits [6]. Yet, few experiments were run to assess whether selfing species or populations have effectively different ecological characteristics, and even scarcer are experiments evaluating both the roles of mutational load and life-history traits evolution. This is the aim of the present study by X. Yang et al [7].
The study of Yang et al [7], together with that of Petrone Mendoza et al. [8], supervised by S. Glémin and M. Lascoux, is probably one of the first to conduct experiments where the competitive abilities are compared between and within species. Using 4 species of the Capsella genus, annual plants from the mustard family, they tested the theoretical predictions that i) the transition from outcrossing to selfing resulted in reduced competitive ability at higher densities, because of the accumulation of deleterious mutations and/or the evolution of life-history traits in an open habitat and a colonization/dispersal trade-off; ii) that reduced competitive ability of selfers should be less pronounced in polyploid then diploid species because the effect of partially recessive deleterious mutations would be buffered; and iii) that competitive ability of selfers should decline with historical range expansion because of the expansion load [9].
Of the 4 Capsella species studied, only one of them, presumably the ancestral, is a diploid outcrosser with a small distribution but large population sizes. The three other species are selfers, two diploids with independent histories of transitions from outcrossing, and another, tetraploid, resulting from a recent hybridization between one of the diploid selfer and the diploid outcrossing ancestor. Many accessions from each species were sampled and individuals assayed for their competitive ability against a tester species or alone, for vegetative and reproductive traits. The measured vegetative traits (rosette surface at two stages, growth rate and flowering probability) showed no differentiation between selfers and outcrossers. To the contrary, reproductive traits (number of flowers) followed theoretical predictions: selfing species are more sensitive to competition than the outcrossing species, with polyploid selfing species being intermediate between the diploid selfers and the diploid outcrosser, and within the tetraploid selfing species (where sampling was quite significant across a large geographical range) sensitivity to competition increased with range expansion.
The study of Yang et al. [7] suffers from several limitations, such that alternative explanations cannot be discarded in the absence of further experimental data. They nonetheless provide the reader with a nice discussion and prospects on how to untwine the causes and the consequences of transitions to selfing. Their study also brings up to date questions about the joint evolution of mating system and life-history traits, which needs a renewed interest from an empirical and theoretical point of view. The results of Yang et al. raise for instance the question of whether it is indeed expected that only reproductive traits, and not vegetative traits, should evolve with the transition to selfing.
The recommandation and evaluation of this paper have been made in collaboration with Thomas Lesaffre.

References

[1] Darwin, C. R. (1876). The effects of cross and self fertilization in the vegetable kingdom. London: Murray. [2] Stebbins, G. L. (1957). Self fertilization and population variability in the higher plants. The American Naturalist, 91, 337-354. doi: 10.1086/281999
[3] Harder, L.D. & Barrett, S. C. H. (2006). Ecology and evolution of flowers. Oxford: Oxford University Press. [4] Porcher, E. & Lande, R. (2005). The evolution of self-fertilization and inbreeding depression under pollen discounting and pollen limitation. Journal of Evolutionary Biology, 18(3), 497-508. doi: 10.1111/j.1420-9101.2005.00905.x
[5] Winn, A.A., et al. (2011). Analysis of inbreeding depression in mixed-mating plants provides evidence for selective interference and stable mixed mating. Evolution, 65(12), 3339-3359. doi: 10.1111/j.1558-5646.2011.01462.x
[6] Munoz, F., Violle, C. & Cheptou, P.-O. (2016). CSR ecological strategies and plant mating systems: outcrossing increases with competitiveness but stress-tolerance is related to mixed mating. Oikos, 125(9), 1296-1303. doi: 10.1111/oik.02328
[7] Yang, X., Lascoux, M. & Glémin, S (2018). Variation in competitive ability with mating system, ploidy and range expansion in four Capsella species. bioRxiv, 214866, ver. 5 recommended and peer-reviewed by PCI Evol Biol. doi: 10.1101/214866
[8] Petrone Mendoza, S., Lascoux, M. & Glémin, S. (2018). Competitive ability of Capsella species with different mating systems and ploidy levels. Annals of Botany 121(6), 1257-1264. doi: 10.1093/aob/mcy014
[9] Peischl, S. & Excoffier, L. (2015). Expansion load: recessive mutations and the role of standing genetic variation. Molecular Ecology, 24(9): 2084-2094. doi: 10.1111/mec.13154

Assessing population connectivity is central to understanding population dynamics, and is therefore of great importance in evolutionary biology and conservation biology. In the marine realm, the apparent absence of physical barriers, large population sizes and high dispersal capacities of most organisms often result in no detectable structure, thereby hindering inferences of population connectivity. In a review paper, Gagnaire et al. [1] propose several ideas to improve detection of population connectivity. Notably, using simulations they show that under certain circumstances introgression from one species into another may reveal cryptic population structure within that second species.
The isolated Kerguelen archipelago in the south of Indian Ocean represents a typical situation where the structure of coastal marine organisms is expected to be difficult to detect. In an elegant genomic study, Fraïsse et al. [2] take advantage of introgression from foreign lineages to infer fine-grained population structure in a population of mussels around the Kerguelen archipelago, and investigate its association with environmental variables. Using a large panel of genome-wide markers (GBS) and applying a range of methods that unravel patterns of divergence and gene flow among lineages, they first find that the Kerguelen population is highly admixed, with a major genetic background corresponding to the southern mussel lineage Mytilus platensis introgressed by three northern lineages. By selecting a panel of loci enriched in ancestry-informative SNPs (ie, SNPs highly differentiated among northern lineages) they then detect a fine-scale genetic structure around the Kerguelen archipelago, and identify a major connectivity break. They further show an associating between the genetic structure and environmental variables, particularly the presence of Macrocystis kelp, a marker of habitat exposure to waves (a feature repeatedly evidenced to be important for mussels). While such association pattern could lead to the interpretation that differentiated SNPs correspond to loci directly under selection or linked with such loci, and even be considered as support for adaptive introgression, Fraïsse et al. [2] convincingly show by performing simulations that the genetic-environment association detected can be entirely explained by dispersal barriers associated with environmental variables (habitat-associated connectivity). They also explain why the association is better detected by ancestry-informative SNPs as predicted by Gagnaire et al. [1]. In addition, intrinsic genetic incompatibilities, which reduce gene flow, tend to become trapped at ecotones due to ecological selection, even when loci causing genetic incompatibilities are unlinked with loci involved in adaption to local ecological conditions (Bierne et al. [3]’s coupling hypothesis), leading to correlations between environmental variables and loci not involved in local adaptation. Notably, in Fraïsse et al. [2]’s study, the association between the kelp and ancestry-informative alleles is not consistent throughout the archipelago, casting further doubt on the implication of these alleles in local adaptation.
The study of Fraïsse et al. [2] is therefore an important contribution to evolutionary biology because 1) it provides an empirical demonstration that alleles of foreign origin can be pivotal to detect fine-scale connectivity patterns and 2) it represents a test case of Bierne et al. [3]’s coupling hypothesis, whereby introgressed alleles also enhance patterns of genetic-environment associations. Since genomic scan or GWAS approaches fail to clearly reveal loci involved in local adaptation, how can we disentangle environment-driven selection from intrinsic reproductive barriers and habitat-associated connectivity? A related question is whether we can reliably identify cases of adaptive introgression, which have increasingly been put forward as a mechanism involved in adaptation [4]. Unfortunately, there is no easy answer, and the safest way to go is to rely – where possible – on independent information [5], in particular functional studies of the detected loci, as is for example the case in the mimetic butterfly Heliconius literature (e. g., [6]) where several loci controlling colour pattern variation are well characterized.

References

[1] Gagnaire, P.-A., Broquet, T., Aurelle, D., Viard, F., Souissi, A., Bonhomme, F., Arnaud-Haond, S., & Bierne, N. (2015). Using neutral, selected, and hitchhiker loci to assess connectivity of marine populations in the genomic era. Evolutionary Applications, 8, 769–786. doi: 10.1111/eva.12288
[2] Fraïsse, C., Haguenauer, A., Gerard, K., Weber, A. A.-T., Bierne, N., & Chenuil, A. (2018). Fine-grained habitat-associated genetic connectivity in an admixed population of mussels in the small isolated Kerguelen Islands. bioRxiv, 239244, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/239244
[3] Bierne, N., Welch, J., Loire, E., Bonhomme, F., & David, P. (2011). The coupling hypothesis: why genome scans may fail to map local adaptation genes. Molecular Ecology, 20, 2044–2072. doi: 10.1111/j.1365-294X.2011.05080.x
[4] Hedrick, P. W. (2013). Adaptive introgression in animals: examples and comparison to new mutation and standing variation as sources of adaptive variation. Molecular Ecology, 22, 4606–4618. doi: 10.1111/mec.12415
[5] Ravinet, M., Faria, R., Butlin, R. K., Galindo, J., Bierne, N., Rafajlović, M., Noor, M. A. F., Mehlig, B., & Westram, A. M. (2017). Interpreting the genomic landscape of speciation: a road map for finding barriers to gene flow. Journal of Evolutionary Biology, 30, 1450–1477. doi: 10.1111/jeb.13047.
[6] Jay, P., Whibley, A., Frézal, L., Rodríguez de Cara, M. A., Nowell, R. W., Mallet, J., Dasmahapatra, K. K., & Joron, M. (2018). Supergene evolution triggered by the introgression of a chromosomal inversion. Current Biology, 28, 1839–1845.e3. doi: 10.1016/j.cub.2018.04.072

Exciting times are afoot for those of us interested in the ecology and evolution of invasive populations. Recent years have seen evolutionary process woven firmly into our understanding of invasions (Miller et al. 2020). This integration has inspired a welter of empirical and theoretical work. We have moved from field observations and verbal models to replicate experiments and sophisticated mathematical models. Progress has been rapid, and we have seen science at its best; an intimate discussion between theory and data.
An area currently under very active development is our understanding of pushed invasions. Here a population spreads through space driven, not by dispersal and growth originating at the leading tip of the invasion, but by dispersal and growth originating deeper in the bulk of the population. These pushed invasions may be quite common – they result when per capita growth and dispersal rates are higher in the bulk of the wave than at the leading tip. They result from a range of well-known phenomena, including Allee effects and density-dependent dispersal (Gandhi et al. 2016; Bîrzu et al. 2019). Pushed invasions travel faster than we would expect given growth and dispersal rates on the leading tip, and they lose genetic diversity more slowly than classical pulled invasions (Roques et al. 2012; Haond et al. 2018; Bîrzu et al. 2019).
Well… in theory, anyway. The theory on pushed waves has momentarily streaked ahead of the empirical work, because empirical systems for studying pushed invasions are rare (though see Gandhi et al. 2016; Gandhi, Korolev, and Gore 2019). In this paper, Dahirel and colleagues (2020) make the argument that we may be able to generate pushed invasions in laboratory systems simply by reducing the connectedness of our experimental landscapes. If true, we might have a simple tool for turning many of our established experimental systems into systems for studying pushed dynamics.
It’s a nice idea, and the paper goes to careful lengths to explore the possibility in their lab system (a parasitoid wasp, Trichogramma). They run experiments on replicate wasp populations comparing strongly- v poorly-connected arrays, and estimate the resulting invasion speeds and rate of diversity loss. They also build a simulation model of the system, allowing them to explore in-silico a range of possible processes underlying their results.
As well as developing these parallel systems, Dahirel and colleagues (2020) go to careful lengths to develop statistical analyses that allow inference on key parameters, and they apply these analyses to both the experimental and simulation data. They have been motivated to apply methods that might be used in both laboratory and field settings to help classify invasions.
Ultimately, they found reasonable evidence that their poorly-connected habitat did induce a pushed dynamic. Their poorly connected invasions travelled faster than they should have if they were pulled, they lost diversity more slowly than the highly connected habitat, and replicates with a higher carrying capacity tended to have higher invasion speeds. All in line with expectations of a pushed dynamic. Interestingly, however, their simulation results suggest that they probably got this perfect result for unexpected reasons. The strong hint is that their poorly-connected habitat induced density dependent dispersal in the wasps. Without this effect, their simulations suggest they should have seen diversity decreasing much more rapidly than it did.
There is a nuanced, thoughtful, and carefully argued discussion about all this in the paper, and it is worth reading. There is much of value in this paper. Theirs is not a perfect empirical system in which all the model assumptions are met and in which huge population sizes make stochastic effects negligible. Here is a system one step closer to the messy reality of biology. The struggle to align this system with new theory has been worth the effort. Not only does it give us hope that we might usefully be able to discriminate between classes of invasions using real-world data, but it hints at a rule that Tolstoy might have expressed this way: all pulled invasions are alike, each pushed invasion is pushed in its own way.

References

Bîrzu, G., Matin, S., Hallatschek, O., and Korolev, K. S. (2019). Genetic drift in range expansions is very sensitive to density dependence in dispersal and growth. Ecology Letters, 22(11), 1817-1827. doi: https://doi.org/10.1111/ele.13364
Dahirel, M., Bertin, A., Haond, M., Blin, A., Lombaert, E., Calcagno, V., Fellous, S., Mailleret, L., Malausa, T., and Vercken, E. (2020). Shifts from pulled to pushed range expansions caused by reduction of landscape connectivity. bioRxiv, 2020.05.13.092775, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. https://doi.org/10.1101/2020.05.13.092775
Gandhi, S. R., Korolev, K. S., and Gore, J. (2019). Cooperation mitigates diversity loss in a spatially expanding microbial population. Proceedings of the National Academy of Sciences, 116(47), 23582-23587. doi: https://doi.org/10.1073/pnas.1910075116
Gandhi, S. R., Yurtsev, E. A., Korolev, K. S., and Gore, J. (2016). Range expansions transition from pulled to pushed waves as growth becomes more cooperative in an experimental microbial population. Proceedings of the National Academy of Sciences, 113(25), 6922-6927. doi: https://doi.org/10.1073/pnas.1521056113
Haond, M., Morel-Journel, T., Lombaert, E., Vercken, E., Mailleret, L. and Roques, L. (2018). When higher carrying capacities lead to faster propagation (2018), bioRxiv, 307322, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/307322
Miller et al. (2020). Eco‐evolutionary dynamics of range expansion. Ecology, 101(10), e03139. doi: https://doi.org/10.1002/ecy.3139
Roques, L., Garnier, J., Hamel, F., and Klein, E. K. (2012). Allee effect promotes diversity in traveling waves of colonization. Proceedings of the National Academy of Sciences, 109(23), 8828-8833. doi: https://doi.org/10.1073/pnas.1201695109