Plant-animal interactions have long been identified as a major driving force in evolution. However, only in the last two decades have rigorous macroevolutionary studies of the topic been made possible, thanks to the increasing availability of densely sampled molecular phylogenies and the substantial development of comparative methods. In this extensive and thoughtful perspective [1], Jousselin and Elias thoroughly review current hypotheses, data, and available macroevolutionary methods to understand how plant-insect interactions may have shaped the diversification of phytophagous insects. First, the authors review three main hypotheses that have been proposed to lead to host-plant driven speciation in phytophagous insects: the ‘escape and radiate’, ‘oscillation’, and ‘musical chairs’ scenarios, each with their own set of predictions. Jousselin and Elias then synthesize a vast core of recent studies on different clades of insects, where explicit phylogenetic approaches have been used. In doing so, they highlight heterogeneity in both the methods being used and predictions being tested across these studies and warn against the risk of subjective interpretation of the results. Lastly, they advocate for standardization of phylogenetic approaches and propose a series of simple tests for the predictions of host-driven speciation scenarios, including the characterization of host-plant range history and host breadth history, and diversification rate analyses. This helpful review will likely become a new point of reference in the field and undoubtedly help many researchers formalize and frame questions of plant-insect diversification in future studies of phytophagous insects.

References

[1] Jousselin, E., Elias, M. (2019). Testing Host-Plant Driven Speciation in Phytophagous Insects: A Phylogenetic Perspective. arXiv, 1910.09510, ver. 1 peer-reviewed and recommended by PCI Evol Biol. https://arxiv.org/abs/1910.09510v1

Many emerging diseases arise by parasites switching to new host species, while other parasites seem to remain with same host lineage for very long periods of time, even over timescales where an ancestral host species splits into two or more new species. The ability to understand these dynamics would form an important part of our understanding of infectious disease.

Experiments are clearly important for understanding these processes, but so are comparative studies, investigating the variation that we find in nature. Such comparative data do show strong signs of non-randomness, and this suggests that the epidemiological and ecological processes might be predictable, at least in part. For example, when we map patterns of parasite presence/absence onto host phylogenies, we often find that certain host clades harbour many more parasites than expected, or that closely-related hosts harbour closely-related parasites. Nevertheless, it remains difficult to interpret these patterns to make inferences about ecological and epidemiological processes. This is partly because non-random associations can arise in multiple ways. For example, parasites might be inherited from the common ancestor of related hosts, or might switch to new hosts, but preferentially establish on novel hosts that are closely related to their existing host. Infection might also influence the shape of host phylogeny, either by increasing the rate of host extinction or, conversely, increasing the rate of speciation (as with manipulative symbionts that might induce reproductive isolation).

These various processes have, by and large, been studied in isolation, but the model introduced by Engelstädter and Fortuna [1], makes an important first step towards studying them together. Without such combined analyses, we will not be able to tell if the processes have their own unique signatures, or whether the same sort of non-randomness can arise in multiple ways.

A major finding of the work is that the size of a host clade can be an important determinant of its overall infection level. This had been shown in previous work, assuming that the host phylogeny was fixed, but the current paper shows that it extends also to situations where host extinction and speciation takes place at a comparable rate to host shifting. This finding, then, calls into question the natural assumption that a clade of host species that is highly parasite ridden, must have some genetic or ecological characteristic that makes them particularly prone to infection, arguing that the clade size, rather than any characteristic of the clade members, might be the important factor. It will be interesting to see whether this prediction about clade size is borne out with comparative studies.

Another feature of the study is that the framework is naturally extendable, to include further processes, such as the influence of parasite presence on extinction or speciation rates. No doubt extensions of this kind will form the basis of important future work.

References

[1] Engelstädter J and Fortuna NZ. 2018. The dynamics of preferential host switching: host phylogeny as a key predictor of parasite prevalence and distribution. bioRxiv 209254 ver. 5 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/209254

Plastic responses of organisms to their environment may be maladaptive in particular when organisms are exposed to new environments. Phenotypic plasticity may also have opposite effects on the adaptive response of organisms to environmental changes: whether phenotypic plasticity favors or hinders such adaptation depends on a balance between the ability of the population to respond to the change non-genetically in the short term, and the weakened genetic response to environmental change. These topics have received continued attention, particularly in the context of climate change (e.g., Chevin et al. 2013, Duputié et al., 2015, Vinton et al . 2022).

In their work, Ledru et al. focus on the adaptive nature of plastic behavior and on its consequences in a consumer-resource ecosystem. As they emphasize, previous works have found that plastic foraging promotes community stability, but these did not consider plasticity as an evolving trait, so Ledru et al. set out to test whether this conclusion holds when both plastic foraging and niche traits of consumers and resources evolve (though ultimately, their new conclusions may not all depend on plasticity evolving). Along the way, they first seek to clarify when such plasticity will evolve, and how it affects the evolution of the niche diversity of consumers and resources, before turning to the question of consumer persistence. 

The model is rather complex, as three traits are allowed to evolve, and the resource uptake expressed through plastic behavior has its own dynamics affected by some form of social learning. Classically, in models of niche evolution, a consumer's efficiency in exploiting a resource characterized by a trait y (here, the resource's individual niche trait), has been described in terms of location-scale (typically Gaussian) kernels, with mean x (the consumer's individual niche trait) specifying the most efficiently exploited resource, and with variance characterizing individual niche breadth. The evolution of the variance has been considered in some previous models but is assumed to be fixed here.  Rather, the new model considers the evolution of the distribution of resource traits, of the consumer's individual niche trait (which is not plastic), and of a "plastic foraging trait" that controls the relative time spent foraging plastically versus foraging randomly. When foraging plastically, the consumers modify their foraging effort towards the type of resource that maximizes their energy intake. in some previous models, the effect of variation in the extent of plastic foraging was already considered, but the evolution of allocation to a plastic foraging strategy versus random foraging was not considered. The model is formulated through reaction-diffusion equations, and its dynamics is investigated by numerical integration.

Foraging plasticity readily evolves, when resources vary widely enough, competition for resources is strong, and the cost of plasticity is weak. This means in particular that a large individual niche width of consumers selects for increased plastic foraging, as the evolution of plastic foraging leads to reduced niche overlap between consumers. The evolution of plastic foraging itself generally, though not always, favors the diversification of the niche traits of consumers and of resources. There is thus a positive feedback loop between plastic foraging and resource diversity. Ledru et al. conclude that the total niche width of the consumer population should also correlate with the evolution of plastic foraging, an implication which they relate to the so-called niche variation hypothesis and to empirical tests of it. 

The joint evolution of the consumer's individual niche trait and plastic foraging trait generates a striking pattern within populations: consumers whose individual niche trait is at an edge of the resource distribution forage more plastically. The authors observe that this relatively simple prediction has not been subjected to any empirical test. 

Returning to the question of consumer persistence, Ledru et al. evaluate this persistence when consumer mortality increases, and in response to either gradual or sudden environmental changes. These different perturbations all reduce the benefits of plastic foraging. The effect of plastic foraging on stability are complex, being negative or positive effect depending on the type of disturbance, and in particular the ecosystem has a lower sustainable rate of environmental change in the presence of plastic foraging. However, allowing the evolutionary regression of plastic foraging then has a comparatively positive effect on persistence.

Despite the substantial effort devoted to analyzing this complex model, relaxing some of its assumptions would likely reveal further complexities. Notably, the overall effect of plasticity on consumer persistence depends on effects already encountered in models of the adaptive response of single species to environmental change: a fast non-genetic response in the short term versus a weakened genetic response in the longer term. The overall balance between these opposite effects on adaptation may be difficult to predict robustly. In the case of a constant rate of environmental change, the results of the present model depend on a lag load between the trait changes of consumer and resource populations, and the extent of the lag may also depend on many factors, such as the extent of genetic variation (e.g., Bürger & Lynch, 1995) for niche traits in consumers and resources. Here, the same variance of mutational effects was assumed for all three evolving traits. Further, spatial environmental variation, a central issue in studies of adaptive responses to environmental changes (e.g., Parmesan, 2006, Zhu et al., 2012), was not considered. Finally, the rate of adjustment of effort by consumers with given niche trait and plastic foraging trait values was assumed proportional to the density of consumers with such trait values. This was justified as a way of accounting for the use of social cues during foraging, but to the extent that they occur, social effects could manifest themselves through other learning dynamics. 

In conclusion, Ledru et al. have addressed a broad range of questions, suggesting new empirical tests of behavioural patterns on one side, and recovering in the context of community response to environmental changes a complexity that could be expected from earlier works on adaptive responses of organisms but that has been overlooked by previous works on community effects of phenotypic plasticity.

References

Bürger, R. and Lynch, M. (1995), Evolution and extinction in a changing environment: a quantitative-genetic analysis. Evolution, 49: 151-163. https://doi.org/10.1111/j.1558-5646.1995.tb05967.x

Chevin, L.-M., Collins, S. and Lefèvre, F. (2013), Phenotypic plasticity and evolutionary demographic responses to climate change: taking theory out to the field. Funct Ecol, 27: 967-979. https://doi.org/10.1111/j.1365-2435.2012.02043.x

Duputié, A., Rutschmann, A., Ronce, O. and Chuine, I. (2015), Phenological plasticity will not help all species adapt to climate change. Glob Change Biol, 21: 3062-3073. https://doi-org.inee.bib.cnrs.fr/10.1111/gcb.12914

Ledru, L., Garnier, J., Guillot, O., Faou, E., & Ibanez, S. (2023). The evolutionary dynamics of plastic foraging and its ecological consequences: a resource-consumer model. EcoEvoRxiv, ver. 4 peer-reviewed and recommended by Peer Community In Evolutionary Biology. https://doi.org/10.32942/X2QG7M

Parmesan, C. (2006) Ecological and evolutionary responses to recent climate change
Annual Review of Ecology, Evolution, and Systematics 2006 37:1, 637-669. https://doi.org/10.1146/annurev.ecolsys.37.091305.110100

Vinton, A.C., Gascoigne, S.J.L., Sepil, I., Salguero-Gómez, R., (2022) Plasticity’s role in adaptive evolution depends on environmental change components. Trends in Ecology & Evolution, 37: 1067-1078.
https://doi.org/10.1016/j.tree.2022.08.008

Zhu, K., Woodall, C.W. and Clark, J.S. (2012), Failure to migrate: lack of tree range expansion in response to climate change. Glob Change Biol, 18: 1042-1052. https://doi.org/10.1111/j.1365-2486.2011.02571.x

Natural landscapes are often composite, with spatial variation in environmental factors being the norm rather than exception. Adaptation to such variation is a major driver of diversity at all levels of biological organization, from genes to phenotypes, species and ultimately ecosystems. While natural selection favours traits that show a better fit to local conditions, the genomic response to such selection is not necessarily straightforward. This is because many quantitative traits are complex and the product of many loci, each with a small to moderate phenotypic contribution. Adapting to environmental challenges that occur in narrow ranges may thus prove difficult as each individual locus is easily swamped by alleles favoured across the rest of the population range. 

To better understand whether and how evolution overcomes such a hurdle, Laroche and Lenormand [1]  combine quantitative genetics and population genetic modelling to track genomic changes that underpin a trait whose fitness optimum differs between a certain spatial range, referred to as a “pocket”, and the rest of the habitat. As it turns out from their analysis, one critical and probably underappreciated factor in determining the type of genetic architecture that evolves is how fitness declines away from phenotypic optima. One classical and popular model of fitness landscape that relates trait value to reproductive success is Gaussian, whereby small trait variations away from the optimum result in even smaller variations in fitness. This facilitates local adaptation via the invasion of alleles of small effects as carriers inside the pocket show a better fit while those outside the pocket only suffer a weak fitness cost. By contrast, when the fitness landscape is more peaked around the optimum, for instance where the decline is linear, adaptation through weak effect alleles is less likely, requiring larger pockets that are less easily swamped by alleles selected in the rest of the range.  

In addition to mathematically investigating the initial emergence of local adaptation, Laroche and Lenormand use computer simulations to look at its long-term maintenance. In principle, selection should favour a genetic architecture that consolidates the phenotype and increases its heritability, for instance by grouping several alleles of large effects close to one another on a chromosome to avoid being broken down by meiotic recombination. Whether or not this occurs also depends on the fitness landscape. When the landscape is Gaussian, the genetic architecture of the trait eventually consists of tightly linked alleles of large effects. The replacement of small effects by large effects loci is here again promoted by the slow fitness decline around the optimum. This is because any shift in architecture in an adapted population requires initially crossing a fitness valley. With a Gaussian landscape, this valley is shallow enough to be crossed, facilitated by a bit of genetic drift. By contrast, when fitness declines linearly around the optimum, genetic architecture is much less evolutionarily labile as any architecture change initially entails a fitness cost that is too high to bear.     

Overall, Laroche and Lenormand provide a careful and thought-provoking analysis of a classical problem in population genetics. In addition to questioning some longstanding modelling assumptions, their results may help understand why differentiated populations are sometimes characterized by “genomic islands” of divergence, and sometimes not. 

References

[1] Laroche F, Lenormand T (2022) The genetic architecture of local adaptation in a cline. bioRxiv, 2022.06.30.498280, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.06.30.498280

Not all genetic elements composing genomes are there for the benefit of their carrier. Many have no consequences on fitness, or too mild ones to be eliminated by selection, and thus stem from neutral processes. Many others are indeed the product of selection, but one acting at a different level, increasing the fitness of some elements of the genome only, at the expense of the “organism” as a whole. These can be called selfish genetic elements, and come into a wide variety of flavours [1], illustrating many possible means to cheat with “fair” reproductive processes such as meiosis, and thus get overrepresented in the offspring of their hosts. Producing copies of itself through transposition is one such strategy; a very successful one indeed, explaining a large part of the genomic content of many organisms. Killing non carrier gametes following meiosis in heterozygous carriers is another one. Less know and less common is the ability of some elements to turn heterozygous carriers into homozygous ones, that will thus transmit the selfish elements to all offspring instead of half. This is achieved by nucleic sequences encoding so-called “Homing endonucleases” (HEs). These proteins tend to induce double strand breaks of DNA specifically in regions homologous to their own insertion sites. The recombination machinery is such that the intact homologous region, that is, the one carrying the HE sequence, is then used as a template for the reparation of the break, resulting in the effective conversion of a non-carrier allele into a carrier allele. Such elements can also occur in the mitochondrial genomes of organisms where mitochondria are not strictly transmitted by one parent only, offering mitochondrial HEs some opportunities for “homing” into new non carrier genomes. This is the case in yeasts, where HEs were first reported [2,3].
In this new study, based on genomic experimental data from the fungal maize pathogen Ustilago maydis, Julien Dutheil and colleagues [4] document one possible evolutionary pathway for which little evidence existed before: the passage of a mitochondrial HE into the nuclear genome. The GC content of this region leaves little doubt on its mitochondrial origin, and homologs can indeed be found in the mitochondrial genomes of close relatives. Strangely enough, U. maydis itself does not appear to carry this selfish element in its own mitochondria, suggesting it may have been acquired from a different species, or be subject to a sufficiently rapid turnover to have been recently lost.
Many elements of the story uncovered by this study remain mysterious. How, in the first place, was this HE gene inserted in a nuclear genomic region that shows no apparent homology with its original insertion site, making typical “homing” a not-so-likely explanation? This question may in fact be generalised to many HE systems: is the first insertion into a homing site always the product of a typical homing event, which implies the presence of an homologous template DNA fragment, or can HE genes insert through other means? But then, why specifically in regions that would be targeted by the nuclease they encode? What is the evolutionary fate of this newly inserted element? The new gene may well be on its way to pseudogenisation, as suggested by the truncation of its upper part, precluding its functioning as a HE, and the lack of evidence of selective constraints through dN/dS analysis; but the mutation generated by the insertion event may have phenotypic implications, possibly through the partial truncation of another gene, encoding a helicase. How old is this insertion? The fact that it has accumulated some mutations makes a very recent event rather unlikely, but this insertion has been detected in only one isolate of U. maydis, suggesting it is not so frequent in natural populations.
Whatever the answers to these open questions, that will hopefully be addressed by further work on this system, the present study has revealed that horizontal transmission enlarges the scope of possible evolutionary consequences of HE genes, that may move not only between mitochondrial genomes, but also occasionally into a nucleus.

References

[1] Burt, A., and Trivers, R. (2006). Genes in Conflict: The Biology of Selfish Genetic Elements. Belknap Press.
[2] Coen, D., Deutch, J., Netter, P., Petrochillo, E., and Slonimski, P. (1970). Mitochondrial genetics. I. Methodology and phenomenology. Symposia of the Society for Experimental Biology, 24, 449-496.
[3] Colleaux, L., D’Auriol, L., Betermier, M., Cottarel, G., Jacquier, A., Galibert, F., and Dujon, B. (1986). Universal code equivalent of a yeast mitochondrial intron reading frame is expressed into E. coli as a specific double strand endonuclease. Cell, 44, 521–533. doi: 10.1016/0092-8674(86)90262-X
[4] Dutheil, J. Y., Münch, K., Schotanus, K., Stukenbrock, E. H., and Kahmann, R. (2020). The insertion of a mitochondrial selfish element into the nuclear genome and its consequences. bioRxiv, 787044, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/787044