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06 Mar 2023
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Extrinsic mortality and senescence: a guide for the perplexed

Getting old gracefully, and risk of dying before getting there: a new guide to theory on extrinsic mortality and senescence

Recommended by and based on reviews by Nicole Walasek and 1 anonymous reviewer

Why is there such variation across species and populations in the rate at which individuals show wear and tear as they get older? Several compelling theoretical explanations have been developed on the conditions under which selection allows for or prevents senescence; a notable one being that proposed by George C Williams in 1957 based on the idea of antagonistic pleiotropy (Williams, 1957). One of the testable predictions of this theory is that, in populations where adults experience higher mortality, senescence is expected to be faster. This is one of the most influential predictions of the paper, being intuitive (when individuals are less likely to survive to later age classes, we expect weakened selection on traits that would avoid senescence in these classes), and fitting with ‘live fast, die young’ life history framing. As such, it has been widely incorporated into how we think about the evolution of senescence and has received considerable support in comparative studies across species and populations.  

However, it would be misleading to sit back at this point and think we have ‘solved’ the problem of understanding variation in senescence, and how this is linked with mortality. It turns out that the Williams 1957 paper is hotly contested by theoreticians: for the past 30 years – with increasing focus in the last 4 years – a growing body of models and opinion pieces have proposed flaws in the paper itself and in how it has been interpreted (Abrams, 1993; André and Rousset, 2020; Day and Abrams, 2020; Moorad et al., 2019). Central to several of these critiques is that explicit consideration of density dependence (not considered in Williams’ original paper) changes the conditions under which his predictions hold. A new preprint by de Vries, Gallipaud and Kokko brings further clarity to such critiques of the original paper (Vries et al., 2023). 

Beyond just continuing the tradition of critiquing Williams’ prediction, however, de Vries et al. provide a clear guide that is accessible to non-theoreticians about the issues with William’s prediction, and the way in which density dependence and how it operates can change when we expect senescence to occur. Rather than reiterate their points here, we suggest a close reading of the paper itself, along with an excellent overview of the paper in a recent blog by Daniel Nettle (Nettle, 2022). In brief, the paper starts by synthesizing earlier theoretical and empirical studies on the topic and presenting a very simple model to highlight how – in the absence of density dependence – Williams’ prediction does not hold because of the unregulated population growth, which is necessarily higher when there is low mortality. As a result, for a lineage with low mortality, any fitness advantage of placing offspring into the lineage later (i.e. selection for reduced senescence) is exactly cancelled out by the fact that earlier-produced offspring have higher fitness returns. 

They then present a more complex framework, which incorporates realistic mortality distributions, trade-offs between survival and reproduction, and use a series of 10 scenarios of density dependence (and whether this acts on survival or fecundity, and also whether it depends on a threshold or stochastic, or exerts continuing pressure on the trait) to explore selection on fitness-associated traits with age depending on extrinsic mortality. This then generates a range of results for when the Williams prediction holds, when there is no link between mortality and senescence, and when there is an ‘anti-Williams’ result – i.e., where senescence is slower when there is a high mortality. As has been shown in earlier studies, density dependence and how it operates matters, and Williams’ prediction holds most when density dependence affects juvenile age classes (in their model, when adults are less likely to produce them – i.e. there is density dependence on fecundity; or when there is less recruitment into the adult population due to, for example, competition among juveniles). 

So, perhaps we are now at a point where we can lay to rest the debate on the issues specifically with Williams’ original paper, and instead consider more broadly the key factors to measure when predicting patterns of senescence, and what is tangible for empiricists to quantify in their studies. Here, de Vries et al. provide some helpful insights both into the limitations of their approach and what modelling should be done moving forward, and into how we can link existing studies (for example comparing senescence among populations with varying predation pressure) to the theoretical predictions. At the heart of the latter is understanding the mechanism of density-dependent regulation – does it affect survival or fecundity, which age classes are most sensitive, and how do key traits depend on density? – and this is often difficult to measure in field studies.

And from all this we can learn that even very intuitive and extensively discussed concepts in biology do not always have as firm theoretical underpinnings as assumed, and – as should not be surprising – biology is complex and rather than one clear pattern being predicted, this can depend on a multitude of factors. 

REFERENCES

Abrams PA (1993) Does increased mortality favor the evolution of more rapid senescence? Evolution, 47, 877–887. https://doi.org/10.1111/j.1558-5646.1993.tb01241.x

André J-B, Rousset F (2020) Does extrinsic mortality accelerate the pace of life? A bare-bones approach. Evolution and Human Behavior, 41, 486–492. https://doi.org/10.1016/j.evolhumbehav.2020.03.002

Day T, Abrams PA (2020) Density Dependence, Senescence, and Williams’ Hypothesis. Trends in Ecology & Evolution, 35, 300–302. https://doi.org/10.1016/j.tree.2019.11.005

Moorad J, Promislow D, Silvertown J (2019) Evolutionary Ecology of Senescence and a Reassessment of Williams’ ‘Extrinsic Mortality’ Hypothesis. Trends in Ecology & Evolution, 34, 519–530. https://doi.org/10.1016/j.tree.2019.02.006

Nettle AD (2022) Live fast and die young (maybe). https://www.danielnettle.org.uk/2022/02/18/live-fast-and-die-young-maybe/ (accessed 2.27.23).

de Vries C, Galipaud M, Kokko H (2023) Extrinsic mortality and senescence: a guide for the perplexed. bioRxiv, 2022.01.27.478060, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.01.27.478060

Williams GC (1957) Pleiotropy, natural selection, and the evolution of senescence. Evolution, 11, 398–411. https://doi.org/10.1111/j.1558-5646.1957.tb02911.x

Extrinsic mortality and senescence: a guide for the perplexedCharlotte de Vries, Matthias Galipaud, Hanna Kokko<p style="text-align: justify;">Do environments or species traits that lower the mortality of individuals create selection for delaying senescence? Reading the literature creates an impression that mathematically oriented biologists cannot agree o...Evolutionary Dynamics, Evolutionary Ecology, Evolutionary Theory, Life HistorySinead English2022-08-26 14:30:16 View
20 Nov 2023
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Phenotypic stasis with genetic divergence

Phenotypic stasis despite genetic divergence and differentiation in Caenorhabditis elegans.

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

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

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

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

References

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

Phenotypic stasis with genetic divergenceFrançois Mallard, Luke Noble, Thiago Guzella, Bruno Afonso, Charles F. Baer, Henrique Teotónio<p style="text-align: justify;">Whether or not genetic divergence in the short-term of tens to hundreds of generations is compatible with phenotypic stasis remains a relatively unexplored problem. We evolved predominantly outcrossing, genetically ...Adaptation, Behavior & Social Evolution, Experimental Evolution, Quantitative GeneticsFrédéric Guillaume2022-09-01 14:32:53 View
02 May 2023
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Durable resistance or efficient disease control? Adult Plant Resistance (APR) at the heart of the dilemma

Plant resistance to pathogens: just you wait?

Recommended by based on reviews by Jean-Paul Soularue and 1 anonymous reviewer

In this preprint, Rimbaud et al. (2023) examine whether Adult Plant Resistance (APR), where plants delay their response to pathogens, is a viable alternative when the solution to evolve complete resistance from the seedling stage exists. At first glance, delaying resistance seems like a counter-intuitive strategy, unless it can result in a weaker selection of the pathogen, and therefore slow down its adaption to plant resistance.

The approach of Rimbaud et al. is to incorporate as much of the mechanisms as possible into a model. By accounting for explicit spatio-temporal dynamics, stochasticity, and the coupling between demography and population genetics, to simulate an agricultural landscape, they reach a nuanced conclusion.

Weaker and delayed activation of genes that confer APR does indeed reduce the selection pressure acting on the pathogen, at the cost of overall less effective protection. The alternative strategy of rapid or complete activation of these genes, although it results in better results in defending against the pathogen, is at risk of being overcome because it introduces a stronger selection pressure.

One important feature of this work is that it accounts for agricultural practices. The landscape that is simulated can account for monoculture, mosaic cultures, mixed cultures, and rotations of crops (with different strategies for resistance). This introduces an interesting element to the conclusion: that human practices will have an impact on the selection pressures acting within the system.

Perhaps the most striking result is that, for the plants, it might be more beneficial to bear the cost of a wild-type pathogen that can benefit from delayed activation of resistance, and therefore exclude the more virulent strains by simply being there first, and essentially buying the plant some time before it activates its resistance more completely. When the landscape is aggregated, even wild-type pathogens can cause severe epidemics; increasing fragmentation, because it enables connectivity between patches of plants with different strategies, allows pathogens to move across cultivars, and reduces the epidemic risk on susceptible plants.

These results should encourage scaling up the perspective on APR, and indeed Rimbaud et al. adopt a landscape-scale perspective, to show that APR genes and genes conferring more complete resistance early on can have synergistic effects. This is, again, both an interesting result for evolutionary biologists, but also a useful way to prioritize different crop management strategies over large spatial scales.

References

Rimbaud, Loup, et al. Durable Resistance or Efficient Disease Control? Adult Plant Resistance (APR) at the Heart of the Dilemma. 2023. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.08.30.505787

Durable resistance or efficient disease control? Adult Plant Resistance (APR) at the heart of the dilemmaLoup Rimbaud, Julien Papaïx, Jean-François Rey, Benoît Moury, Luke G. Barrett, Peter H. Thrall<p style="text-align: justify;">Adult plant resistance (APR) is an incomplete and delayed protection of plants against pathogens. At first glance, such resistance should be less efficient than classical major-effect resistance genes, which confer ...Adaptation, Evolutionary Applications, Evolutionary EpidemiologyTimothée Poisot2022-09-02 16:36:32 View
21 Feb 2023
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Wolbachia genomics reveals a potential for a nutrition-based symbiosis in blood-sucking Triatomine bugs

Nutritional symbioses in triatomines: who is playing?

Recommended by based on reviews by Alejandro Manzano Marín and Olivier Duron

Nearly 8 million people are suffering from Chagas disease in the Americas. The etiological agent, Trypanosoma cruzi, is mainly transmitted by triatomine bugs, also known as kissing or vampire bugs, which suck blood and transmit the parasite through their feces. Among these triatomine species, Rhodnius prolixus is considered the main vector, and many studies have focused on characterizing its biology, physiology, ecology and evolution. 

Interestingly, given that Rhodnius species feed almost exclusively on blood, their diet is unbalanced, and the insects can lack nutrients and vitamins that they cannot synthetize themself, such as B-vitamins. In all insects feeding exclusively on blood, symbioses with microbes producing B-vitamins (mainly biotin, riboflavin and folate) have been widely described (see review in Duron and Gottlieb 2020) and are critical for insect development and reproduction. These co-evolved relationships between blood feeders and nutritional symbionts could now be considered to develop new control methods, by targeting the ‘Achille’s heel’ of the symbiotic association (i.e., transfer of nutrient and / or control of nutritional symbiont density). But for this, it is necessary to better characterize the relationships between triatomines and their symbionts. 

R. prolixus is known to be associated with several symbionts. The extracellular gut symbiont Rhodococcus rhodnii, which reaches high bacterial densities and is almost fixed in R. prolixus populations, appears to be a nutritional symbiont under many blood sources. This symbiont can provide B-vitamins such as biotin (B7), niacin (B3), thiamin (B1), pyridoxin (B6) or riboflavin (B2) and can play an important role in the development and the reproduction of R. prolixus (Pachebat et al. (2013) and see review in Salcedo-Porras et al. (2020)). This symbiont is orally acquired through egg smearing, ensuring the fidelity of transmission of the symbiont from mother to offspring. However, as recently highlighted by Tobias et al. (2020) and Gilliland et al. (2022), other gut microbes could also participate to the provision of B-vitamins, and R. rhodnii could additionally provide metabolites (other than B-vitamins) increasing bug fitness. In the study from Filée et al., the authors focused on Wolbachia, an intracellular, maternally inherited bacterium, known to be a nutritional symbiont in other blood-sucking insects such as bedbugs (Nikoh et al. 2014), and its potential role in vitamin provision in triatomine bugs. 

After screening 17 different triatomine species from the 3 phylogenetic groups prolixus, pallescens and pictipes, they first show that Wolbachia symbionts are widely distributed in the different Rhodnius species. Contrary to R. rhodnii that were detected in all samples, Wolbachia prevalence was patchy and rarely fixed. The authors then sequenced, assembled, and compared 13 Wolbachia genomes from the infected Rhodnius species. They showed that all Wolbachia are phylogenetically positioned in the supergroup F that contains wCle (the Wolbachia from bedbugs). In addition, 8 Wolbachia strains (out of 12) encode a biotin operon under strong purifying selection, suggesting the preservation of the biological function and the metabolic potential of Wolbachia to supplement biotin in their Rhodnius host. From the study of insect genomes, the authors also evidenced several horizontal transfers of genes from Wolbachia to Rhodnius genomes, which suggests a complex evolutionary interplay between vampire bugs and their intracellular symbiont. 

This nice piece of work thus provides valuable information to the fields of multiple partners / nutritional symbioses and Wolbachia research. Dual symbioses described in insects feeding on unbalanced diets generally highlight a certain complementarity between symbionts that ensure the whole nutritional complementation. The study presented by Filée et al. leads rather to consider the impact of multiple symbionts with different lifestyles and transmission modes in the provision of a specific nutritional benefit (here, biotin). Because of the low prevalence of Wolbachia in certain species, a “ménage à trois” scenario would rather be replaced by an “open couple”, where the host relationship with new symbiotic partners (more or less stable at the evolutionary timescale) could provide benefits in certain ecological situations. The results also support the potential for Wolbachia to evolve rapidly along a continuum between parasitism and mutualism, by acquiring operons encoding critical pathways of vitamin biosynthesis.

References

Duron O. and Gottlieb Y. (2020) Convergence of Nutritional Symbioses in Obligate Blood Feeders. Trends in Parasitology 36(10):816-825. https://doi.org/10.1016/j.pt.2020.07.007

Filée J., Agésilas-Lequeux K., Lacquehay L., Bérenger J.-M., Dupont L., Mendonça V., Aristeu da Rosa J. and Harry M. (2023) Wolbachia genomics reveals a potential for a nutrition-based symbiosis in blood-sucking Triatomine bugs. bioRxiv, 2022.09.06.506778, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.09.06.506778

Gilliland C.A. et al. (2022) Using axenic and gnotobiotic insects to examine the role of different microbes on the development and reproduction of the kissing bug Rhodnius prolixus (Hemiptera: Reduviidae). Molecular Ecology. https://doi.org/10.1111/mec.16800

Nikoh et al. (2014) Evolutionary origin of insect–Wolbachia nutritional mutualism. PNAS. 111(28):10257-10262. https://doi.org/10.1073/pnas.1409284111

Pachebat, J.A. et al. (2013). Draft genome sequence of Rhodococcus rhodnii strain LMG5362, a symbiont of Rhodnius prolixus (Hemiptera, Reduviidae, Triatominae), the principle vector of Trypanosoma cruzi. Genome Announc. 1(3):e00329-13. https://doi.org/10.1128/genomea.00329-13

Salcedo-Porras N., et al. (2020). The role of bacterial symbionts in Triatomines: an evolutionary perspective. Microorganisms. 8:1438. https://doi.org/10.3390%2Fmicroorganisms8091438

Tobias N.J., Eberhard F.E., Guarneri A.A. (2020) Enzymatic biosynthesis of B-complex vitamins is supplied by diverse microbiota in the Rhodnius prolixus anterior midgut following Trypanosoma cruzi infection. Computational and Structural Biotechnology Journal. 3395-3401. https://doi.org/10.1016/j.csbj.2020.10.031 

Wolbachia genomics reveals a potential for a nutrition-based symbiosis in blood-sucking Triatomine bugsJonathan Filée, Kenny Agésilas-Lequeux, Laurie Lacquehay, Jean Michel Bérenger, Lise Dupont, Vagner Mendonça, João Aristeu da Rosa, Myriam Harry<p>The nutritional symbiosis promoted by bacteria is a key determinant for adaptation and evolution of many insect lineages. A complex form of nutritional mutualism that arose in blood-sucking insects critically depends on diverse bacterial symbio...Genome Evolution, Phylogenetics / Phylogenomics, Species interactionsNatacha Kremer Alejandro Manzano Marín2022-09-13 17:36:46 View
30 May 2023
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slendr: a framework for spatio-temporal population genomic simulations on geographic landscapes

A new powerful tool to easily encode the geo-spatial dimension in population genetics simulations

Recommended by ORCID_LOGO based on reviews by Liisa Loog and 2 anonymous reviewers

Models explaining the evolutionary processes operating in living beings are often impossible to test in the real world. This is mainly because of the long time (i.e., the number of generations) which is necessary for evolution to unfold. In addition, any such experiment would require a large number of individuals and, more importantly, many replicates to account for the inherent variance of the evolutionary processes under investigation. Only organisms with fast generation times and favourable rearing conditions can be used to explicitly test for specific evolutionary hypotheses.

Computer simulations have filled this gap, revolutionising experimental testing in evolutionary biology by integrating genetic models into complex population dynamics, which can be run for (potentially) any length of time. Without going into an extensive description of the many available approaches for population genetics simulations (an exhaustive review can be found in Hoban et al 2012), three main aspects are, in my opinion, important for categorising and choosing one simulation approach over another. The first concerns the basic distinction between coalescent-based and individual-based simulators: the former being an efficient approach, which simulates back in time the coalescence events of a sample of homologous DNA fragments, while the latter is a more computationally intensive approach where all of the individuals (and their underlying genetic/genomic features) in the population are simulated forward-in-time, generation after generation. The second aspect concerns the simulation of natural selection. Although natural selection can be integrated into backward-in-time simulations, it is more realistically implemented as individual-based fitness in forward-in-time simulators. The third point, which has been often overlooked in evolutionary simulations, is about the possibility to design a simulation scenario where individuals and populations can exploit a physical (geographical) space.

Amongst the coalescent-based simulators, SPLATCHE (Currat et al 2004), and its derivatives, is one of the few simulation tools deploying the coalescence process in sub-demes which are all connected by migration, thus getting as close as possible to a spatially-explicit population. On the other hand, individual-based simulators, whose development followed the increasing power of computational machines, offer a great opportunity to include spatio-temporal dynamics within a genomic simulation model. One of the most realistic and efficient individual-based forward-in-time simulators available is SLiM (Haller and Messer 2017), which allows users to implement simulations in arbitrarily complex spaces. Here, the more challenging part is encoding the spatially-explicit scenarios using the SLiM-specific EIDOS language. 

The new R package slendr (Petr et al 2022) offers a practical solution to this issue. By wrapping different tools into a well-known scripting language, slendr allows the design of spatiotemporal simulation scenarios which can be directly executed in the individual-based SLiM simulator, and the output stored with modern tree-sequence analysis tools (tskit; Kellerer et al 2018). Alternatively, simulations of non-spatial models can be run using a coalescent-based algorithm (msprime; Baumdicker et al 2022). The main advantage of slendr is that the whole simulative experiment can be performed entirely in the R environment, taking advantage of the many libraries available for geospatial and genomic data analysis, statistics, and visualisation. The open-source nature of this package, whose main aim is to make complex population genomics modelling more accessible, and the vibrant community of SLiM and tskit users will very likely make slendr widely used amongst the molecular ecology and evolutionary biology communities. 

Slendr handles real Earth cartographic data where users can design realistic demographic processes which characterise natural populations (i.e., expansions, displacement of large populations, interactions among populations, migrations, population splits, etc.) by changing spatial population boundaries across time and space. All in all, slendr is a very flexible and scalable framework to test the accuracy of spatial models, hypotheses about demography and selection, and interactions between organisms across space and time. 

REFERENCES

Baumdicker, F., Bisschop, G., Goldstein, D., Gower, G., Ragsdale, A. P., Tsambos, G., ... & Kelleher, J. (2022). Efficient ancestry and mutation simulation with msprime 1.0. Genetics, 220(3), iyab229. https://doi.org/10.1093/genetics/iyab229

Currat, M., Ray, N., & Excoffier, L. (2004). SPLATCHE: a program to simulate genetic diversity taking into account environmental heterogeneity. Molecular Ecology Notes, 4(1), 139-142. https://doi.org/10.1046/j.1471-8286.2003.00582.x

Haller, B. C., & Messer, P. W. (2017). SLiM 2: flexible, interactive forward genetic simulations. Molecular biology and evolution, 34(1), 230-240. https://doi.org/10.1093/molbev/msw211

Hoban, S., Bertorelle, G., & Gaggiotti, O. E. (2012). Computer simulations: tools for population and evolutionary genetics. Nature Reviews Genetics, 13(2), 110-122. https://doi.org/10.1038/nrg3130

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

Petr, M., Haller, B. C., Ralph, P. L., & Racimo, F. (2023). slendr: a framework for spatio-temporal population genomic simulations on geographic landscapes. bioRxiv, 2022.03.20.485041, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.03.20.485041

slendr: a framework for spatio-temporal population genomic simulations on geographic landscapesMartin Petr, Benjamin C. Haller, Peter L. Ralph, Fernando Racimo<p style="text-align: justify;">One of the goals of population genetics is to understand how evolutionary forces shape patterns of genetic variation over time. However, because populations evolve across both time and space, most evolutionary proce...Bioinformatics & Computational Biology, Evolutionary Theory, Phylogeography & Biogeography, Population Genetics / GenomicsEmiliano Trucchi2022-09-14 12:57:56 View
16 Mar 2023
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Phylogeographic breaks and how to find them: Separating vicariance from isolation by distance in a lizard with restricted dispersal

The difficult task of partitioning the effects of vicariance and isolation by distance in poor dispersers

Recommended by ORCID_LOGO based on reviews by Kevin Sánchez and Aglaia (Cilia) Antoniou

Partitioning the effects of vicariance and low dispersal has been a long-standing problem in historical biogeography and phylogeography. While the term “vicariance” refers to divergence in allopatry, caused by some physical (geological, geographical) or climatic barriers (e.g. Rosen 1978), isolation by distance refers to the genetic differentiation of remote populations due to the physical distance separating them, when the latter surpasses the scale of dispersal (Wright 1938, 1940, 1943). 

Vicariance and dispersal have long been considered as separate forces leading to separate scenarii of speciation (e.g. reviewed in Hickerson and Meyer 2008). Nevertheless, these two processes are strongly linked, as, for example, vicariance theory relies on the assumption that ancestral lineages were once linked by dispersal prior to physical or climatic isolation (Rosen 1978). Low dispersal and vicariance are not mutually exclusive, and distinguishing these two processes in heterogeneous landscapes, especially for poor dispersers, remains therefore a severe challenge. For example, low dispersal (and/or small population size) can give rise to geographic patterns consistent with a phylogeographic break and be mistaken for geographic isolation (Irwin 2002, Kuo and Avise 2005).

The study of Rancilliac and colleagues (2023) is at the heart of this issue. It focuses on a nominal lizard species, the red-tailed spiny-footed lizard (Acanthodactylus erythrurus, Squamata: Lacertidae), which has a wide spatial distribution (from the Maghreb to the Iberian Peninsula), is found in a variety of different habitats, and has a wide range of morphological traits that do not always correlate with phylogeny. The main question is the following: have “the morphological and ecological diversification of this group been produced by vicariance and lineage diversification, or by local adaptation in the face of historical gene flow?” To tackle this question, the authors used sequence data from multiple mitochondrial and nuclear markers and a nested analysis workflow integrating phylogeography, multiple correspondence analyses and a relatively novel approach to IBD testing (Hausdorf & Henning, 2020). The latter is based on regression analysis and was shown to be less prone to error than the traditional (partial) Mantel test. 

While this set of methods allowed the partitioning of the effect of isolation by distance and vicariance in shaping contemporary genetic diversity in red-tailed spiny-footed lizards, some of the evolutionary history of this species complex remains blurred by ongoing gene flow and admixture, retention of ancestral polymorphism, or selection. The lack of congruence between mitochondrial and nuclear gene trees once again warns us that proposing evolutionary scenarii based on individual gene trees is a risky business. 

References

Hausdorf B, Hennig C (2020) Species delimitation and geography. Molecular Ecology Resources, 20, 950–960. https://doi.org/10.1111/1755-0998.13184

Hickerson MJ, Meyer CP (2008) Testing comparative phylogeographic models of marine vicariance and dispersal using a hierarchical Bayesian approach. BMC Evolutionary Biology, 8, 322. https://doi.org/10.1186/1471-2148-8-322

Irwin DE (2002) Phylogeographic breaks without geographic barriers to gene flow. Evolution, 56, 2383–2394. https://doi.org/10.1111/j.0014-3820.2002.tb00164.x

Kuo C-H, Avise JC (2005) Phylogeographic breaks in low-dispersal species: the emergence of concordance across gene trees. Genetica, 124, 179–186. https://doi.org/10.1007/s10709-005-2095-y

Rancilhac L, Miralles A, Geniez P, Mendez-Aranda D, Beddek M, Brito JC, Leblois R, Crochet P-A (2023) Phylogeographic breaks and how to find them: An empirical attempt at separating vicariance from isolation by distance in a lizard with restricted dispersal. bioRxiv, 2022.09.30.510256, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.09.30.510256

Rosen DE (1978) Vicariant Patterns and Historical Explanation in Biogeography. Systematic Biology, 27, 159–188. https://doi.org/10.2307/2412970

Wright, S (1938) Size of population and breeding structure in relation to evolution. Science 87:430-431.

Wright S (1940) Breeding Structure of Populations in Relation to Speciation. The American Naturalist, 74, 232–248. https://doi.org/10.1086/280891

Wright S (1943) Isolation by distance. Genetics, 28, 114–138. https://doi.org/10.1093/genetics/28.2.114

Phylogeographic breaks and how to find them: Separating vicariance from isolation by distance in a lizard with restricted dispersalLoïs Rancilhac, Aurélien Miralles, Philippe Geniez, Daniel Mendez-Arranda, Menad Beddek, José Carlos Brito, Raphaël Leblois, Pierre-André Crochet<p>Aim</p> <p>Discontinuity in the distribution of genetic diversity (often based on mtDNA) is usually interpreted as evidence for phylogeographic breaks, underlying vicariant units. However, a misleading signal of phylogeographic break can arise...Phylogeography & Biogeography, Population Genetics / Genomics, Speciation, Systematics / TaxonomyEric Pante Kevin Sánchez2022-10-05 13:11:28 View
18 Jan 2023
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The fate of recessive deleterious or overdominant mutations near mating-type loci under partial selfing

Maintenance of deleterious mutations and recombination suppression near mating-type loci under selfing

Recommended by ORCID_LOGO based on reviews by 3 anonymous reviewers

The causes and consequences of the evolution of sexual reproduction are a major topic in evolutionary biology. With advances in sequencing technology, it becomes possible to compare sexual chromosomes across species and infer the neutral and selective processes shaping polymorphism at these chromosomes. Most sex and mating-type chromosomes exhibit an absence of recombination in large genomic regions around the animal, plant or fungal sex-determining genes. This suppression of recombination likely occurred in several time steps generating stepwise increasing genomic regions starting around the sex-determining genes. This mechanism generates so-called evolutionary strata of differentiation between sex chromosomes (Nicolas et al., 2004, Bergero and Charlesworth, 2009, Hartmann et al. 2021). The evolution of extended regions of recombination suppression is also documented on mating-type chromosomes in fungi (Hartmann et al., 2021) and around supergenes (Yan et al., 2020, Jay et al., 2021). The exact reason and evolutionary mechanisms for this phenomenon are still, however, debated.

Two hypotheses are proposed: 1) sexual antagonism (Charlesworth et al., 2005), which, nevertheless, does explain the observed occurrence of the evolutionary strata, and 2) the sheltering of deleterious alleles by inversions carrying a lower load than average in the population (Charlesworth and Wall, 1999, Antonovics and Abrams, 2004). In the latter, the mechanism is as follows. A genetic inversion or a suppressor of recombination in cis may exhibit some overdominance behaviour. The inversion exhibiting less recessive deleterious mutations (compared to others at the same locus) may increase in frequency, before at higher frequency occurring at the homozygous state, expressing its genetic load. However, the inversion may never be at the homozygous state if it is genetically linked to a gene in a permanently heterozygous state. The inversion can then be advantageous and may reach fixation at the sex chromosome (Charlesworth and Wall, 1999, Antonovics and Abrams, 2004, Jay et al., 2022). These selective mechanisms promote thus the suppression of recombination around the sex-determining gene, and recessive deleterious mutations are permanently sheltered. This hypothesis is corroborated by the sheltering of deleterious mutations observed around loci under balancing selection (Llaurens et al. 2009, Lenz et al. 2016) and around mating-type genes in fungi and supergenes (Jay et al. 2021, Jay et al., 2022).

In this present theoretical study, Tezenas et al. (2022) analyse how linkage to a necessarily heterozygous fungal mating type locus influences the persistence/extinction time of a new mutation at a second selected locus. This mutation can either be deleterious and recessive, or overdominant. There is arbitrary linkage between the two loci, and sexual reproduction occurs either between 1) gametes of different individuals (outcrossing), or 2) by selfing with gametes originating from the same (intra-tetrad) or different (inter-tetrad) tetrads produced by that individual. Note, here, that the mating-type gene does not prevent selfing. The authors study the initial stochastic dynamics of the mutation using a multi-type branching process (and simulations when analytical results cannot be obtained) to compute the extinction time of the deleterious mutation. The main result is that the presence of a mating-type locus always decreases the purging probability and increases the purging time of the mutations under selfing. Ultimately, deleterious mutations can indeed accumulate near the mating-type locus over evolutionary time scales. In a nutshell, high selfing or high intra-tetrad mating do increase the sheltering effect of the mating-type locus. In effect, the outcome of sheltering of deleterious mutations depends on two opposing mechanisms: 1) a higher selfing rate induces a greater production of homozygotes and an increased effect of the purging of deleterious mutations, while 2) a higher intra-tetrad selfing rate (or linkage with the mating-type locus) generates heterozygotes which have a small genetic load (and are favoured). The authors also show that rare events of extremely long maintenance of deleterious mutations can occur.

The authors conclude by highlighting the manifold effect of selfing which reduces the effective population size and thus impairs the efficiency of selection and increases the mutational load, while also favouring the purge of deleterious homozygous mutations. Furthermore, this study emphasizes the importance of studying the maintenance and accumulation of deleterious mutations in the vicinity of heterozygous loci (e.g. under balancing selection) in selfing species.

References

Antonovics J, Abrams JY (2004) Intratetrad Mating and the Evolution of Linkage Relationships. Evolution, 58, 702–709. https://doi.org/10.1111/j.0014-3820.2004.tb00403.x

Bergero R, Charlesworth D (2009) The evolution of restricted recombination in sex chromosomes. Trends in Ecology & Evolution, 24, 94–102. https://doi.org/10.1016/j.tree.2008.09.010

Charlesworth D, Morgan MT, Charlesworth B (1990) Inbreeding Depression, Genetic Load, and the Evolution of Outcrossing Rates in a Multilocus System with No Linkage. Evolution, 44, 1469–1489. https://doi.org/10.1111/j.1558-5646.1990.tb03839.x

Charlesworth D, Charlesworth B, Marais G (2005) Steps in the evolution of heteromorphic sex chromosomes. Heredity, 95, 118–128. https://doi.org/10.1038/sj.hdy.6800697

Charlesworth B, Wall JD (1999) Inbreeding, heterozygote advantage and the evolution of neo–X and neo–Y sex chromosomes. Proceedings of the Royal Society of London. Series B: Biological Sciences, 266, 51–56. https://doi.org/10.1098/rspb.1999.0603

Hartmann FE, Duhamel M, Carpentier F, Hood ME, Foulongne-Oriol M, Silar P, Malagnac F, Grognet P, Giraud T (2021) Recombination suppression and evolutionary strata around mating-type loci in fungi: documenting patterns and understanding evolutionary and mechanistic causes. New Phytologist, 229, 2470–2491. https://doi.org/10.1111/nph.17039

Jay P, Chouteau M, Whibley A, Bastide H, Parrinello H, Llaurens V, Joron M (2021) Mutation load at a mimicry supergene sheds new light on the evolution of inversion polymorphisms. Nature Genetics, 53, 288–293. https://doi.org/10.1038/s41588-020-00771-1

Jay P, Tezenas E, Véber A, Giraud T (2022) Sheltering of deleterious mutations explains the stepwise extension of recombination suppression on sex chromosomes and other supergenes. PLOS Biology, 20, e3001698. https://doi.org/10.1371/journal.pbio.3001698

Lenz TL, Spirin V, Jordan DM, Sunyaev SR (2016) Excess of Deleterious Mutations around HLA Genes Reveals Evolutionary Cost of Balancing Selection. Molecular Biology and Evolution, 33, 2555–2564. https://doi.org/10.1093/molbev/msw127

Llaurens V, Gonthier L, Billiard S (2009) The Sheltered Genetic Load Linked to the S Locus in Plants: New Insights From Theoretical and Empirical Approaches in Sporophytic Self-Incompatibility. Genetics, 183, 1105–1118. https://doi.org/10.1534/genetics.109.102707

Nicolas M, Marais G, Hykelova V, Janousek B, Laporte V, Vyskot B, Mouchiroud D, Negrutiu I, Charlesworth D, Monéger F (2004) A Gradual Process of Recombination Restriction in the Evolutionary History of the Sex Chromosomes in Dioecious Plants. PLOS Biology, 3, e4. https://doi.org/10.1371/journal.pbio.0030004

Tezenas E, Giraud T, Véber A, Billiard S (2022) The fate of recessive deleterious or overdominant mutations near mating-type loci under partial selfing. bioRxiv, 2022.10.07.511119, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.10.07.511119

Yan Z, Martin SH, Gotzek D, Arsenault SV, Duchen P, Helleu Q, Riba-Grognuz O, Hunt BG, Salamin N, Shoemaker D, Ross KG, Keller L (2020) Evolution of a supergene that regulates a trans-species social polymorphism. Nature Ecology & Evolution, 4, 240–249. https://doi.org/10.1038/s41559-019-1081-1

The fate of recessive deleterious or overdominant mutations near mating-type loci under partial selfingEmilie Tezenas, Tatiana Giraud, Amandine Veber, Sylvain Billiard<p style="text-align: justify;">Large regions of suppressed recombination having extended over time occur in many organisms around genes involved in mating compatibility (sex-determining or mating-type genes). The sheltering of deleterious alleles...Evolutionary Dynamics, Evolutionary Ecology, Evolutionary Theory, Genome Evolution, Population Genetics / Genomics, Reproduction and SexAurelien Tellier2022-10-10 13:50:30 View
13 Apr 2023
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The landscape of nucleotide diversity in Drosophila melanogaster is shaped by mutation rate variation

An unusual suspect: the mutation landscape as a determinant of local variation in nucleotide diversity

Recommended by based on reviews by David Castellano and 1 anonymous reviewer

Sometimes, important factors for explaining biological processes fall through the cracks, and it is only through careful modeling that their importance eventually comes out to light. In this study, Barroso and Dutheil introduce a new method based on the sequentially Markovian coalescent (SMC, Marjoran and Wall 2006) for jointly estimating local recombination and coalescent rates along a genome. Unlike previous SMC-based methods, however, their method can also co-estimate local patterns of variation in mutation rates. 

This is a powerful improvement which allows them to tackle questions about the reasons for the extensive variation in nucleotide diversity across the chromosomes of a species - a problem that has plagued the minds of population geneticists for decades (Begun and Aquadro 1992, Andolfatto 2007, McVicker et al., 2009, Pouyet and Gilbert 2021). The authors find that variation in de novo mutation rates appears to be the most important factor in determining nucleotide diversity in Drosophila melanogaster. Though seemingly contradicting previous attempts at addressing this problem (Comeron 2014), they take care to investigate and explain why that might be the case.

Barroso and Dutheil have also taken care to carefully explain the details of their new approach and have carried a very thorough set of analyses comparing competing explanations for patterns of nucleotide variation via causal modeling. The reviewers raised several issues involving choices made by the authors in their analysis of variance partitioning, the proper evaluation of the role of linked selection and the recombination rate estimates emerging from their model. These issues have all been extensively addressed by the authors, and their conclusions seem to remain robust. The study illustrates why the mutation landscape should not be ignored as an important determinant of local variation in genetic diversity, and opens up questions about the generalizability of these results to other organisms.

REFERENCES

Andolfatto, P. (2007). Hitchhiking effects of recurrent beneficial amino acid substitutions in the Drosophila melanogaster genome. Genome research, 17(12), 1755-1762. https://doi.org/10.1101/gr.6691007

Barroso, G. V., & Dutheil, J. Y. (2021). The landscape of nucleotide diversity in Drosophila melanogaster is shaped by mutation rate variation. bioRxiv, 2021.09.16.460667, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.09.16.460667

Begun, D. J., & Aquadro, C. F. (1992). Levels of naturally occurring DNA polymorphism correlate with recombination rates in D. melanogaster. Nature, 356(6369), 519-520. https://doi.org/10.1038/356519a0

Comeron, J. M. (2014). Background selection as baseline for nucleotide variation across the Drosophila genome. PLoS Genetics, 10(6), e1004434. https://doi.org/10.1371/journal.pgen.1004434

Marjoram, P., & Wall, J. D. (2006). Fast" coalescent" simulation. BMC genetics, 7, 1-9. https://doi.org/10.1186/1471-2156-7-16

McVicker, G., Gordon, D., Davis, C., & Green, P. (2009). Widespread genomic signatures of natural selection in hominid evolution. PLoS genetics, 5(5), e1000471. https://doi.org/10.1371/journal.pgen.1000471

Pouyet, F., & Gilbert, K. J. (2021). Towards an improved understanding of molecular evolution: the relative roles of selection, drift, and everything in between. Peer Community Journal, 1, e27. https://doi.org/10.24072/pcjournal.16

The landscape of nucleotide diversity in Drosophila melanogaster is shaped by mutation rate variationGustavo V Barroso, Julien Y Dutheil<p style="text-align: justify;">What shapes the distribution of nucleotide diversity along the genome? Attempts to answer this question have sparked debate about the roles of neutral stochastic processes and natural selection in molecular evolutio...Bioinformatics & Computational Biology, Population Genetics / GenomicsFernando Racimo2022-10-30 07:52:07 View
02 Feb 2023
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Heterogeneities in infection outcomes across species: sex and tissue differences in virus susceptibility

Susceptibility to infection is not explained by sex or differences in tissue tropism across different species of Drosophila

Recommended by based on reviews by Greg Hurst and 1 anonymous reviewer

Understanding factors explaining both intra and interspecific variation in susceptibility to infection by parasites remains a key question in evolutionary biology. Within a species variation in susceptibility is often explained by differences in behaviour affecting exposure to infection and/or resistance affecting the degree by which parasite growth is controlled (Roy & Kirchner, 2000, Behringer et al., 2000). This can vary between the sexes (Kelly et al., 2018) and may be explained by the ability of a parasite to attack different organs or tissues (Brierley et al., 2019). However, what goes on within one species is not always relevant to another, making it unclear when patterns can be scaled up and generalised across species. This is also important to understand when parasites may jump hosts, or identify species that may be susceptible to a host jump (Longdon et al., 2015). Phylogenetic distance between hosts is often an important factor explaining susceptibility to a particular parasite in plant and animal hosts (Gilbert & Webb, 2007, Faria et al., 2013). 

In two separate experiments, Roberts and Longdon (Roberts & Longdon, 2022) investigated how sex and tissue tropism affected variation in the load of Drosophila C Virus (DCV) across multiple Drosophila species. DCV load has been shown to correlate positively with mortality (Longdon et al., 2015). Overall, they found that load did not vary between the sexes; within a species males and females had similar DCV loads for 31 different species. There was some variation in levels of DCV growth in different tissue types, but these too were consistent across males for 7 species of Drosophila. Instead, in both experiments, host phylogeny or interspecific variation, explained differences in DCV load with some species being more infected than others. 

This study is neat in that it incorporates and explores simultaneously both intra and interspecific variation in infection-related life-history traits which is not often done (but see (Longdon et al., 2015, Imrie et al., 2021, Longdon et al., 2011, Johnson et al., 2012). Indeed, most studies to date explore either inter-specific differences in susceptibility to a parasite (it can or can’t infect a given species) (Davies & Pedersen, 2008, Pfenning-Butterworth et al., 2021) or intra-specific variability in infection-related traits (infectivity, resistance etc.) due to factors such as sex, genotype and environment (Vale et al., 2008, Lambrechts et al., 2006). This work thus advances on previous studies, while at the same time showing that sex differences in parasite load are not necessarily pervasive. 

References

Behringer DC, Butler MJ, Shields JD (2006) Avoidance of disease by social lobsters. Nature, 441, 421–421. https://doi.org/10.1038/441421a

Brierley L, Pedersen AB, Woolhouse MEJ (2019) Tissue tropism and transmission ecology predict virulence of human RNA viruses. PLOS Biology, 17, e3000206. https://doi.org/10.1371/journal.pbio.3000206

Davies TJ, Pedersen AB (2008) Phylogeny and geography predict pathogen community similarity in wild primates and humans. Proceedings of the Royal Society B: Biological Sciences, 275, 1695–1701. https://doi.org/10.1098/rspb.2008.0284

Faria NR, Suchard MA, Rambaut A, Streicker DG, Lemey P (2013) Simultaneously reconstructing viral cross-species transmission history and identifying the underlying constraints. Philosophical Transactions of the Royal Society B: Biological Sciences, 368, 20120196. https://doi.org/10.1098/rstb.2012.0196

Gilbert GS, Webb CO (2007) Phylogenetic signal in plant pathogen–host range. Proceedings of the National Academy of Sciences, 104, 4979–4983. https://doi.org/10.1073/pnas.0607968104

Imrie RM, Roberts KE, Longdon B (2021) Between virus correlations in the outcome of infection across host species: Evidence of virus by host species interactions. Evolution Letters, 5, 472–483. https://doi.org/10.1002/evl3.247

Johnson PTJ, Rohr JR, Hoverman JT, Kellermanns E, Bowerman J, Lunde KB (2012) Living fast and dying of infection: host life history drives interspecific variation in infection and disease risk. Ecology Letters, 15, 235–242. https://doi.org/10.1111/j.1461-0248.2011.01730.x

Kelly CD, Stoehr AM, Nunn C, Smyth KN, Prokop ZM (2018) Sexual dimorphism in immunity across animals: a meta-analysis. Ecology Letters, 21, 1885–1894. https://doi.org/10.1111/ele.13164

Lambrechts L, Chavatte J-M, Snounou G, Koella JC (2006) Environmental influence on the genetic basis of mosquito resistance to malaria parasites. Proceedings of the Royal Society B: Biological Sciences, 273, 1501–1506. https://doi.org/10.1098/rspb.2006.3483

Longdon B, Hadfield JD, Day JP, Smith SCL, McGonigle JE, Cogni R, Cao C, Jiggins FM (2015) The Causes and Consequences of Changes in Virulence following Pathogen Host Shifts. PLOS Pathogens, 11, e1004728. https://doi.org/10.1371/journal.ppat.1004728

Longdon B, Hadfield JD, Webster CL, Obbard DJ, Jiggins FM (2011) Host Phylogeny Determines Viral Persistence and Replication in Novel Hosts. PLOS Pathogens, 7, e1002260. https://doi.org/10.1371/journal.ppat.1002260

Pfenning-Butterworth AC, Davies TJ, Cressler CE (2021) Identifying co-phylogenetic hotspots for zoonotic disease. Philosophical Transactions of the Royal Society B: Biological Sciences, 376, 20200363. https://doi.org/10.1098/rstb.2020.0363

Roberts KE, Longdon B (2023) Heterogeneities in infection outcomes across species: examining sex and tissue differences in virus susceptibility. bioRxiv 2022.11.01.514663, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.11.01.514663 

Roy BA, Kirchner JW (2000) Evolutionary Dynamics of Pathogen Resistance and Tolerance. Evolution, 54, 51–63. https://doi.org/10.1111/j.0014-3820.2000.tb00007.x

Vale PF, Stjernman M, Little TJ (2008) Temperature-dependent costs of parasitism and maintenance of polymorphism under genotype-by-environment interactions. Journal of Evolutionary Biology, 21, 1418–1427. https://doi.org/10.1111/j.1420-9101.2008.01555.x

Heterogeneities in infection outcomes across species: sex and tissue differences in virus susceptibilityKatherine E Roberts, Ben Longdon<p style="text-align: justify;">Species vary in their susceptibility to pathogens, and this can alter the ability of a pathogen to infect a novel host. However, many factors can generate heterogeneity in infection outcomes, obscuring our ability t...Evolutionary EcologyAlison DuncanAnonymous, Greg Hurst2022-11-03 11:17:42 View
04 Aug 2023
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Sensitive windows for within- and trans-generational plasticity of anti-predator defences

Sensitive windows for phenotypic plasticity within and across generations; where empirical results do not meet the theory but open a world of possibilities

Recommended by ORCID_LOGO based on reviews by David Murray-Stoker, Timothée Bonnet and Willem Frankenhuis

It is easy to define phenotypic plasticity as a mechanism by which traits change in response to a modification of the environment. Many complex mechanisms are nevertheless involved with plastic responses, their strength, and stability (e.g., reliability of cues, type of exposure, genetic expression, epigenetics). It is rather intuitive to think that environmental cues perceived at different stages of development will logically drive different phenotypic responses (Fawcett and Frankenhuis 2015). However, it has proven challenging to try and explain, or model how and why different effects are caused by similar cues experienced at different developmental or life stages (Walasek et al. 2022). The impact of these ‘sensitive windows’ on the stability of plastic responses within or across generations remains unclear. In their paper entitled “Sensitive windows for within- and trans-generational plasticity of anti-predator defences”, Tariel-Adam (2023) address this question.

In this paper, Tariel et al. acknowledge the current state of the art, i.e., that some traits influenced by the environment at early life stages become fixed later in life (Snell-Rood et al. 2015) and that sensitive windows are therefore more likely to be observed during early stages of development. Constructive exchanges with the reviewers illustrated that Tariel et al. presented a clear picture of the knowledge on sensitive windows from a conceptual and a mechanistic perspective, thereby providing their study with a strong and elegant rationale. Tariel et al. outlined that little is known about the significance of this scenario when it comes to transgenerational plasticity. Theory predicts that exposure late in the life of parents should be more likely to drive transgenerational plasticity because the cue perceived by parents is more likely to be reliable if time between parental exposure and offspring expression is short (McNamara et al. 2016). I would argue that although sensible, this scenario is likely oversimplifying the complexity of evolutionary, ecological, and inheritance mechanisms at play (Danchin et al. 2018). Tariel-Adam et al. (2023) point out in their paper how the absence of experimental results limits our understanding of the evolutionary and adaptive significance of transgenerational plasticity and decided to address this broad question.

Tariel-Adam et al. (2023) used the context of predator-prey interactions, which is a powerful framework to evaluate the temporality of predator cues and prey responses within and across generations (Sentis et al. 2018). They conducted a very elegant experiment whereby two generations of freshwater snails Physa acuta were exposed to crayfish predator cues at different developmental windows. They triggered the within-generation phenotypic plastic response of inducible defences (e.g., shell thickness) and identified sensitive windows as to evaluate their role in within-generation phenotypic plasticity versus transgenerational plasticity. They used different linear models, which lead to constructive exchanges with reviewers, and between reviewers, well trained on these approaches, in particular on effect sizes, that improved the paper by pushing the discussion all the way towards a consensus. 

Tariel-Adam et al. (2023) results showed that the phenotypic plastic response of different traits was associated with different sensitive windows. Although early-life development was confirmed to be a sensitive window, it was far from being the only developmental stage driving within-generation plastic responses of defence traits. This finding contributes to change our views on plasticity because where theoretical models predict early- and late-life sensitive windows, empirical results gathered here present a more continuous opportunity for sensitive windows over the lifetime of freshwater snails. This is likely because multifactorial mechanisms drive the reliability and adaptive significance of predator cues. To me, this paper most original contribution lies probably in the empirical investigation of sensitive windows underlying transgenerational plasticity. Their finding implies mechanistic ties between sensitive windows driving within-generation and transgenerational plasticity for some traits, but they also shed light on the possible independence of these processes. Although one may be disheartened by these findings illustrating the ability of nature to combine complex mechanisms in order to produce somewhat unpredictable scenarios, one can only find that this unlimited range of phenotypic plasticity scenarios is a wonder to investigate because much remains to be understood. As mentioned in the conclusion of the paper, the opportunity for sensitive windows to drive such a range of plastic responses may also be an opportunity for organisms to adapt to a wide range of environmental demands. 

References

Danchin E, A Pocheville, O Rey, B Pujol, and S Blanchet (2019). Epigenetically facilitated mutational assimilation: epigenetics as a hub within the inclusive evolutionary synthesis. Biological Reviews, 94: 259-282. https://doi.org/10.1111/brv.12453

Fawcett TW, and WE Frankenhuis (2015). Adaptive Explanations for Sensitive Windows in Development. Frontiers in Zoology 12, S3. https://doi.org/10.1186/1742-9994-12-S1-S3 

McNamara JM, SRX Dall, P Hammerstein, and O Leimar (2016). Detection vs. Selection: Integration of Genetic, Epigenetic and Environmental Cues in Fluctuating Environments. Ecology Letters 19, 1267–1276. https://doi.org/10.1111/ele.12663

Sentis A, R Bertram, N Dardenne, et al. (2018). Evolution without standing genetic variation: change in transgenerational plastic response under persistent predation pressure. Heredity 121, 266–281. https://doi.org/10.1038/s41437-018-0108-8 

Snell-Rood EC, EM Swanson, and RL Young (2015). Life History as a Constraint on Plasticity: Developmental Timing Is Correlated with Phenotypic Variation in Birds. Heredity 115, 379–388. https://doi.org/10.1038/hdy.2015.47

Tariel-Adam J, E Luquet, and S Plénet (2023). Sensitive windows for within- and trans-generational plasticity of anti-predator defences. OSF preprints, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.31219/osf.io/mr8hu

Walasek N, WE Frankenhuis, and K Panchanathan (2022). An Evolutionary Model of Sensitive Periods When the Reliability of Cues Varies across Ontogeny. Behavioral Ecology 33, 101–114. https://doi.org/10.1093/beheco/arab113

Sensitive windows for within- and trans-generational plasticity of anti-predator defencesJuliette Tariel-Adam; Émilien Luquet; Sandrine Plénet<p>Transgenerational plasticity could be an important mechanism for adaptation to variable environments in addition to within-generational plasticity. But its potential for adaptation may be restricted to specific developmental windows that are hi...Adaptation, Evolutionary Ecology, Phenotypic PlasticityBenoit Pujol2022-11-14 08:08:27 View