Within-host parasite density is tightly linked to parasite fitness often determining both transmission success and virulence (parasite-induced harm to the host) (Alizon et al., 2009, Anderson & May, 1982). Parasite density may thus be controlled by selection balancing these conflicting pressures. Actual within-host density regulation may be under host or parasite control, or due to other environmental factors (Wale et al., 2019, Vale et al., 2011, Chrostek et al., 2013). Vertically transmitted parasites may also be more vulnerable to drift associated with bottlenecks between generations, which may also determine within-host population size (Mathe-Hubert et al., 2019, Mira & Moran, 2002).

Bénard et al. (2021) use 3 experiments to disentangle the role of drift versus host factors in the control of within-host Wolbachia growth in Drosophila melanogaster. They use the wMelPop Wolbachia strain in which virulence (fly longevity) and within-host growth correlate positively with copy number in the genomic region Octomom (Chrostek et al., 2013, Chrostek & Teixeira, 2015). Octomom copy number can be used as a marker for different genetic lineages within the wMelPop strain.

In a first experiment, they introgressed and backcrossed this Wolbachia strain into 6 different host genetic backgrounds and show striking differences in within-host symbiont densities which correlate positively with Octomom copy number. This is consistent with host genotype selecting different Wolbachia strains, but also with bottlenecks and drift between generations. To distinguish between these possibilities, they perform 2 further experiments. 

A second experiment repeated experiment 1, but this time introgression was into 3 independent lines of the Bolivia and USA Drosophila populations; those that, respectively, exhibited the lowest and highest Wolbachia density and Octomom copy number. In this experiment, growth and Octomom copy number were measured across the 3 lines, for each population, after 1, 13 and 25 generations. Although there were little differences between replicates at generation 1, there were differences at generations 13 and 25 among the replicates of both the Bolivia and USA lines. These results are indicative of parasite control, or drift being responsible for within-host growth rather than host factors. 

A third experiment tested whether Wolbachia density and copy number were under host or parasite control. This was done, again using the USA and Bolivia lines, but this time those from the first experiment, several generations following the initial introgression and backcrossing. The newly introgressed lines were again followed for 25 generations. At generation 1, Wolbachia phenotypes resembled those of the donor parasite population and not the recipient host population indicating a possible maternal effect, but a lack of host control over the parasite. Furthermore, Wolbachia densities and Octomom number differed among replicate lines through time for Bolivia populations and from the donor parasite lines for both populations. These differences among replicate lines that share both host and parasite origins suggest that drift and/or maternal effects are responsible for within-host Wolbachia density and Octomom number. 

These findings indicate that drift appears to play a role in shaping Wolbachia evolution in this system. Nevertheless, completely ruling out the role of the host or parasite in controlling densities will require further study. The findings of Bénard and coworkers (2021) should stimulate future work on the contribution of drift to the evolution of vertically transmitted parasites.

References

Alizon S, Hurford A, Mideo N, Baalen MV (2009) Virulence evolution and the trade-off hypothesis: history, current state of affairs and the future. Journal of Evolutionary Biology, 22, 245–259. https://doi.org/10.1111/j.1420-9101.2008.01658.x

Anderson RM, May RM (1982) Coevolution of hosts and parasites. Parasitology, 85, 411–426. https://doi.org/10.1017/S0031182000055360

Bénard A, Henri H, Noûs C, Vavre F, Kremer N (2021) Wolbachia load variation in Drosophila is more likely caused by drift than by host genetic factors. bioRxiv, 2020.11.29.402545, ver. 4  recommended and peer-reviewed by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2020.11.29.402545

Chrostek E, Marialva MSP, Esteves SS, Weinert LA, Martinez J, Jiggins FM, Teixeira L (2013) Wolbachia Variants Induce Differential Protection to Viruses in Drosophila melanogaster: A Phenotypic and Phylogenomic Analysis. PLOS Genetics, 9, e1003896. https://doi.org/10.1371/journal.pgen.1003896

Chrostek E, Teixeira L (2015) Mutualism Breakdown by Amplification of Wolbachia Genes. PLOS Biology, 13, e1002065. https://doi.org/10.1371/journal.pbio.1002065

Mathé‐Hubert H, Kaech H, Hertaeg C, Jaenike J, Vorburger C (2019) Nonrandom associations of maternally transmitted symbionts in insects: The roles of drift versus biased cotransmission and selection. Molecular Ecology, 28, 5330–5346. https://doi.org/10.1111/mec.15206

Mira A, Moran NA (2002) Estimating Population Size and Transmission Bottlenecks in Maternally Transmitted Endosymbiotic Bacteria. Microbial Ecology, 44, 137–143. https://doi.org/10.1007/s00248-002-0012-9

Vale PF, Wilson AJ, Best A, Boots M, Little TJ (2011) Epidemiological, Evolutionary, and Coevolutionary Implications of Context-Dependent Parasitism. The American Naturalist, 177, 510–521. https://doi.org/10.1086/659002

Wale N, Jones MJ, Sim DG, Read AF, King AA (2019) The contribution of host cell-directed vs. parasite-directed immunity to the disease and dynamics of malaria infections. Proceedings of the National Academy of Sciences, 116, 22386–22392. https://doi.org/10.1073/pnas.1908147116

Organisms often show robustness to genetic or environmental perturbations. Whether these two components of robustness can evolve separately is the focus of the paper by Le Rouzic [1]. Using theoretical analysis and individual-based computer simulations of a gene regulatory network model, he shows that multiple aspects of robustness can be investigated as a set of pleiotropically linked quantitative traits. While genetically correlated, various robustness components (e.g., mutational, developmental, homeostasis) of gene expression in the regulatory network evolved more or less independently from each other under directional selection. The quantitative approach of Le Rouzic could explain both how unselected robustness components can respond to selection on other components and why various robustness-related features seem to have their own evolutionary history. Moreover, he shows that all components were evolvable, but not all to the same extent. Robustness to environmental disturbances and gene expression stability showed the largest responses while increased robustness to genetic disturbances was slower. Interestingly, all components were positively correlated and remained so after selection for increased or decreased robustness.

This study is an important contribution to the discussion of the evolution of robustness in biological systems. While it has long been recognized that organisms possess the ability to buffer genetic and environmental perturbations to maintain homeostasis (e.g., canalization [2]), the genetic basis and evolutionary routes to robustness and canalization are still not well understood. Models of regulatory gene networks have often been used to address aspects of robustness evolution (e.g., [3]). Le Rouzic [1] used a gene regulatory network model derived from Wagner’s model [4]. The model has as end product the expression level of a set of genes influenced by a set of regulatory elements (e.g., transcription factors). The level and stability of expression are a property of the regulatory interactions in the network.

Le Rouzic made an important contribution to the study of such gene regulation models by using a quantitative genetics approach to the evolution of robustness. He crafted a way to assess the mutational variability and selection response of the components of robustness he was interested in. Le Rouzic’s approach opens avenues to investigate further aspects of gene network evolutionary properties, for instance to understand the evolution of phenotypic plasticity.

Le Rouzic also discusses ways to measure his different robustness components in empirical studies. As the model is about gene expression levels at a set of protein-coding genes influenced by a set of regulatory elements, it naturally points to the possibility of using RNA sequencing to measure the variation of gene expression in know gene networks and assess their robustness. Robustness could then be studied as a multidimensional quantitative trait in an experimental setting.

References

[1] Le Rouzic, A (2022) Gene network robustness as a multivariate character. arXiv: 2101.01564, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://arxiv.org/abs/2101.01564

[2] Waddington CH (1942) Canalization of Development and the Inheritance of Acquired Characters. Nature, 150, 563–565. https://doi.org/10.1038/150563a0

[3] Draghi J, Whitlock M (2015) Robustness to noise in gene expression evolves despite epistatic constraints in a model of gene networks. Evolution, 69, 2345–2358. https://doi.org/10.1111/evo.12732

[4] Wagner A (1994) Evolution of gene networks by gene duplications: a mathematical model and its implications on genome organization. Proceedings of the National Academy of Sciences, 91, 4387–4391. https://doi.org/10.1073/pnas.91.10.4387

Genetic diversity is a key aspect of biodiversity and has important implications for evolutionary potential and thereby the persistence of species. Improving our understanding of the factors that drive genetic structure within and between populations is, therefore, a long-standing goal in evolutionary biology. However, this is a major challenge, because of the complex interplay between genetic drift, migration, and extinction/colonization dynamics on the one hand, and the biology and ecology of species on the other hand (Romiguier et al. 2014, Ellegren and Galtier 2016, Charlesworth 2003). 

Jarne et al. (2021) studied whether environmental and demographic factors affect the population genetic structure of four species of hermaphroditic freshwater snails in a similar way, using comparative analyses of neutral genetic microsatellite markers. 

Specifically, they investigated microsatellite variability of Hygrophila in almost 280 sites in Guadeloupe, Lesser Antilles, as part of a long-term survey experiment (Lamy et al. 2013). They then modelled the influence of the mating system, local environmental characteristics and demographic factors on population genetic diversity.

Consistent with theoretical predictions (Charlesworth 2003), they detected higher genetic variation in two outcrossing species than in two selfing species, emphasizing the importance of the mating system in maintaining genetic diversity. The study further identified an important role of site connectivity, through its influences on effective population size and extinction/colonisation events. Finally, the study detects an influence of interspecific interactions caused by an ongoing invasion by one of the studied species on genetic structure, highlighting the indirect effect of changes in community composition and demography on population genetics.

Jarne et al. (2021) could address the extent to which genetic structure is determined by demographic and environmental factors in multiple species given the remarkable sampling available. Additionally, the study system is extremely suitable to address this hypothesis as species’ habitats are defined and delineated. Whilst the authors did attempt to test for across-species correlations, further investigations on this matter are required. Moreover, the effect of interactions between factors should be appropriately considered in any modelling between genetic structure and local environmental or demographic features.

The findings in this study contribute to improving our understanding of factors influencing population genetic diversity, and highlights the complexity of interacting factors, therefore also emphasizing the challenges of drawing general implications, additionally hampered by the relatively limited number of species studied. Jarne et al. (2021) provide an excellent showcase of an empirical framework to test determinants of genetic structure in natural populations. As such, this study can be an example for further attempts of comparative analysis of genetic diversity.

References

Charlesworth, D. (2003) Effects of inbreeding on the genetic diversity of populations. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 358, 1051-1070. doi: https://doi.org/10.1098/rstb.2003.1296

Ellegren, H. and Galtier, N. (2016) Determinants of genetic diversity. Nature Reviews Genetics, 17, 422-433. doi: https://doi.org/10.1038/nrg.2016.58

Jarne, P., Lozano del Campo, A., Lamy, T., Chapuis, E., Dubart, M., Segard, A., Canard, E., Pointier, J.-P. and David, P. (2021) Connectivity and selfing drives population genetic structure in a patchy landscape: a comparative approach of four co-occurring freshwater snail species. HAL, hal-03295242, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://hal.archives-ouvertes.fr/hal-03295242

Lamy, T., Gimenez, O., Pointier, J. P., Jarne, P. and David, P. (2013). Metapopulation dynamics of species with cryptic life stages. The American Naturalist, 181, 479-491. doi: https://doi.org/10.1086/669676

Romiguier, J., Gayral, P., Ballenghien, M. et al. (2014) Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature, 515, 261-263. doi: https://doi.org/10.1038/nature13685

Understanding the mechanisms underlying range expansions is key for predicting species distributions in response to environmental changes (such as global warming) and managing the global expansion of invasive species (Parmesan 2006; Suarez & Tsutsui 2008). Traditionally, two types of ecological processes were studied as essential in shaping range expansion: dispersal and population growth. However, ecology and evolution are intertwined in range expansions, as phenotypic evolution of traits involved in demographic and dispersal patterns and processes can affect and be affected by ecological dynamics, representing a full eco-evolutionary loop (Williams et al. 2019; Miller et al. 2020).

Range expansions can be characterized by the type of population growth and dispersal, divided into pushed or pulled range expansions. Species that have high dispersal and high population growth at low densities present pulled range expansions (pulled by individuals from the edge populations). In contrast, populations presenting increased growth rate at intermediate densities (due to Allee effects - Allee & Bowen 1932; i.e. where growth rate decreases at lower densities) and high dispersal at high densities present pushed range expansions (driven by individuals from core and intermediate populations) (Gandhi et al. 2016). Importantly, the type of expansion is expected to have very different consequences on the genetic (and therefore) phenotypic composition of core and edge populations. Specifically, genetic variability is expected to be lower in populations experiencing pulled expansions and higher in populations involved in pushed expansions (Gandhi et al. 2016; Miller et al. 2020). However, it is not always possible to distinguish between pulled and pushed expansions, as variation in speed and shape can overlap between the two types. In addition, it is difficult to experimentally manipulate the strength of the Allee effect to create pushed versus pulled expansions. Thus, several critical predictions regarding the genetic and phenotypic composition of pulled and pushed expansions are lacking empirical tests (but see Gandhi et al. 2016).

In a previous study, Dahirel et al. (2021a) combined simulations and experimental evolution of the small wasps Trichogramma brassicae to show that low connectivity led to more pushed expansions, and higher connectivity generated more pulled expansions. In accordance with theoretical predictions, this led to reduced genetic diversity in pulled expansions, and the reverse pattern in pushed expansions. However, the question of how pulled and pushed expansions affect trait evolution remained unanswered.

In this follow-up study, Dahirel et al. (2021b) tackled this issue and linked the changes in connectivity and type of expansion with the phenotypic evolution of several traits using individuals from their previous experiment. Namely, the authors compared core and edge populations with founder strains to test how evolution in pushed vs. pulled expansions affected wasp size, short movement, fecundity, dispersal, and density dependent dispersal. When density dependence was not accounted for, phenotypic changes in edge populations did not match the expectations from changes in expansion dynamics. This could be due to genetic trade-offs between traits that limit phenotypic evolution (Urquhart & Williams 2021). 

However, when accounting for density dependent dispersal, Dahirel et al. (2021b) observed that more connected landscapes (with pulled expansions) showed positive density dispersal in core populations and negative density dispersal in edge populations, similarly to other studies (e.g. Fronhofer et al. 2017). Interestingly, in pushed (with lower connectivity) landscapes, such shift was not observed. Instead, edge populations maintained positive density dispersal even after 14 generations of expansion, whereas core populations showed higher dispersal at lower density. The authors suggest that this seemingly contradictory result is due to a combination of three processes: 1) the expansion reduced positive density dispersal in edge populations; 2) reduced connectivity directly increased dispersal costs, increasing high density dispersal; and 3) reduced connectivity indirectly caused demographic stochasticity (and reduced temporal variability in patches) leading to higher dispersal at low density in core populations. However, these results must be taken with a grain of salt, since only one of the four experimental replicates were used in the density dependent dispersal experiment. In range expansions experiments, replication is fundamental, since stochastic processes (such as gene surfing, where alleles maybe rise in frequency due by chance) are prevalent (Miller et al. 2020), and results are highly dependent on sample size, or number of replicate populations analysed. 

Having said that, results from Dahirel et al. (2021b) highlight the importance to contextualize the management of invasions and species distribution, since it is thought that pulled expansions are more prevalent in nature, but pushed expansions can be more important in scenarios where patchiness is high, such as urban landscapes. Moreover, Dahirel's et al. (2021b) study is a first step showing that accounting for trait density dependence is crucial when following phenotypic evolution during range expansion, and that evolution of density dependent traits may be constrained by landscape conditions. This highlights the need to account for both connectivity and density dependence to draw more accurate predictions on the evolutionary and ecological outcomes of range expansions. 
 
References

Allee WC, Bowen ES (1932) Studies in animal aggregations: Mass protection against colloidal silver among goldfishes. Journal of Experimental Zoology, 61, 185–207. https://doi.org/10.1002/jez.1400610202

Dahirel M, Bertin A, Calcagno V, Duraj C, Fellous S, Groussier G, Lombaert E, Mailleret L, Marchand A, Vercken E (2021a) Landscape connectivity alters the evolution of density-dependent dispersal during pushed range expansions. bioRxiv, 2021.03.03.433752, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.03.03.433752

Dahirel M, Bertin A, Haond M, Blin A, Lombaert E, Calcagno V, Fellous S, Mailleret L, Malausa T, Vercken E (2021b) Shifts from pulled to pushed range expansions caused by reduction of landscape connectivity. Oikos, 130, 708–724. https://doi.org/10.1111/oik.08278

Fronhofer EA, Gut S, Altermatt F (2017) Evolution of density-dependent movement during experimental range expansions. Journal of Evolutionary Biology, 30, 2165–2176. https://doi.org/10.1111/jeb.13182

Gandhi SR, Yurtsev EA, Korolev KS, 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, 6922–6927. https://doi.org/10.1073/pnas.1521056113

Miller TEX, Angert AL, Brown CD, Lee-Yaw JA, Lewis M, Lutscher F, Marculis NG, Melbourne BA, Shaw AK, Szűcs M, Tabares O, Usui T, Weiss-Lehman C, Williams JL (2020) Eco-evolutionary dynamics of range expansion. Ecology, 101, e03139. https://doi.org/10.1002/ecy.3139

Parmesan C (2006) Ecological and Evolutionary Responses to Recent Climate Change. Annual Review of Ecology, Evolution, and Systematics, 37, 637–669.  https://doi.org/10.1146/annurev.ecolsys.37.091305.110100

Suarez AV, Tsutsui ND (2008) The evolutionary consequences of biological invasions. Molecular Ecology, 17, 351–360. https://doi.org/10.1111/j.1365-294X.2007.03456.x

Urquhart CA, Williams JL (2021) Trait correlations and landscape fragmentation jointly alter expansion speed via evolution at the leading edge in simulated range expansions. Theoretical Ecology. https://doi.org/10.1007/s12080-021-00503-z

Williams JL, Hufbauer RA, Miller TEX (2019) How Evolution Modifies the Variability of Range Expansion. Trends in Ecology & Evolution, 34, 903–913. https://doi.org/10.1016/j.tree.2019.05.012

An individual’s sexual phenotype is determined during development. Understanding which pathways are activated or repressed during the developmental stages leading to a sexually mature individual, for example by studying gene expression and how its level is biased between sexes, allows us to understand the functional aspects of dimorphic phenotypes between the sexes.

Several studies have quantified the differences in transcription between the sexes in mature individuals, showing the extent of this sex-bias and which functions are affected. There is, however, less data available on what occurs during the different phases of development leading to this phenotype, especially in species with specific developmental strategies, such as hemimetabolous insects. While many well-studied insects such as the honey bee, drosophila, and butterflies, exhibit an holometabolous development ("holo" meaning "complete" in reference to their drastic metamorphosis from the juvenile to the adult stage), hemimetabolous insects have juvenile stages that look similar to the adult stage (the hemi prefix meaning "half", referring to the more tissue-specific changes during development), as seen in crickets, cockroaches, and stick insects. Learning more about what happens during development in terms of the identity of genes that are sex-biased (are they the same genes at different developmental stages? What are their function? Do they exhibit specific sequence evolution rates? Is one sex over-represented in the sex-biased genes?) and their quantity over developmental time (gradual or abrupt increase in number, if any?) would allow us to better understand the evolution of sexual dimorphism at the gene expression level and how it relates to dimorphism at the organismic level.

Djordjevic et al (2021) studied the transcriptome during development in an hemimetabolous stick insect, to improve our knowledge of this type of development, where the organismic phenotype is already mostly present in the early life stages. To do this, they quantified whole-genome gene expression levels in whole insects, using RNA-seq at three different developmental stages. One of the interesting results presented by Djordjevic and colleagues is that the increase in the number of genes that were sex-biased in expression is gradual over the three stages of development studied and it is mostly the same genes that stay sex-biased over time, reflecting the gradual change in phenotypes between hatchlings, juveniles and adults. Furthermore, male-biased genes had faster sequence divergence rates than unbiased genes and that female-biased genes.

This new information of sex-bias in gene expression in an hemimetabolous insect allowed the authors to do a comparison of sex-biased genes with what has been found in a well-studied holometabolous insect, Drosophila. The gene expression patterns showed that four times more genes were sex-biased in expression in that species than in stick insects. Furthermore, the increase in the number of sex-biased genes during development was quite abrupt and clearly distinct in the adult stage, a pattern that was not seen in stick insects. As pointed out by the authors, this pattern of a "burst" of sex-biased genes at maturity is more common than the gradual increase seen in stick insects.

With this study, we now know more about the evolution of sex-biased gene expression in an hemimetabolous insect and how it relates to their phenotypic dimorphism. Clearly, the next step will be to sample more hemimetabolous species at different life stages, to see how this pattern is widespread or not in this mode of development in insects.

References

Djordjevic J, Dumas Z, Robinson-Rechavi M, Schwander T, Parker DJ (2021) Dynamics of sex-biased gene expression during development in the stick insect Timema californicum. bioRxiv, 2021.01.23.427895, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.01.23.427895