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06 Jun 2019
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Multi-model inference of non-random mating from an information theoretic approach

Tell me who you mate with, I’ll tell you what’s going on

Recommended by and based on reviews by Alexandre Courtiol and 2 anonymous reviewers

The study of sexual selection goes as far as Darwin himself. Since then, elaborate theories concerning both intra- and inter-sexual sexual have been developed, and elegant experiments have been designed to test this body of theory. It may thus come as a surprise that the community is still debating on the correct way to measure simple components of sexual selection, such as the Bateman gradient (i.e., the covariance between the number of matings and the number of offspring)[1,2], or to quantify complex behaviours such as mate choice (the non-random choice of individuals with particular characters as mates)[3,4] and their consequences.
One difficulty in the study of sexual selection is evaluating the consequences of non-random mating. Indeed, when non-random mating is observed in a population, it is often difficult to establish whether such mating pattern leads to i) sexual selection per se (selection pressures favouring certain phenotypes), and/or ii) the non-random association of parental genes in their offspring or not. These two processes differ. In particular, assortative (and disassortative) mating can shape genetic covariances without leading to changes in gene frequencies in the population. Their distinction matters because these two processes lead to different evolutionary outcomes, which can have large ripple effects in the evolution of sexual behaviours, sexual ornamentation, and speciation.
In his paper, entitled “Multi-model inference of non-random mating from an information theoretic approach” [5], Carvajal-Rodríguez tackled this issue. The author generated a simple model in which the consequences of non-random mating can be inferred from information on the population frequencies before and after mating. The procedure is as follows: from the initial population frequencies of phenotypes (or genotypes) of both sexes, the model generates predictions on the frequencies after mating, assuming that particular mating patterns have occurred. This leads to different predictions for the phenotypic (or genotypic) frequencies after mating. The particular mating pattern leading to the best fit with the real frequencies is then identified via a model selection procedure (performing model averaging to combine different mating patterns is also possible).
This study builds on a framework introduced by Carvajal-Rodríguez’s colleagues [6] and encompasses later methodological developments involving the author himself [7]. Compared to early work, the new method proposed by the author builds on the relationship between mating pattern and information [8] to distinguish among scenarios that would lead to non-random mating due to different underlying processes, using simple model selection criterion such as the AICc.
The great asset of the proposed method is that it can be applied to the study of natural populations in which the study of mate choice and sexual selection is notoriously difficult. In the manuscript, the procedure is tested on a population of marine gastropods (Littorina saxatilis). This allows the reader to grasp how the method can be applied to a real system. In fact, anyone can try out the method thanks to the freely available software InfoMating programmed by the author. One important assumption underlying the current method is that the frequencies of unmated individuals do not change during the mating season. If this is not the case, the reader may refer to another publication of the same author which relaxes this assumption [9]. These papers are both instrumental for empiricists interested in testing sexual selection theory.

References

[1] Bateman, A. J. (1948). Intra-sexual selection in Drosophila. Heredity, 2(3), 349-368. doi: 10.1038/hdy.1948.21
[2] Jones, A. G. (2009). On the opportunity for sexual selection, the Bateman gradient and the maximum intensity of sexual selection. Evolution: International Journal of Organic Evolution, 63(7), 1673-1684. doi: 10.1111/j.1558-5646.2009.00664.x
[3] Andersson, M., & Simmons, L. W. (2006). Sexual selection and mate choice. Trends in ecology & evolution, 21(6), 296-302. doi: 10.1016/j.tree.2006.03.015
[4] Kuijper, B., Pen, I., & Weissing, F. J. (2012). A guide to sexual selection theory. Annual Review of Ecology, Evolution, and Systematics, 43, 287-311. doi: 10.1146/annurev-ecolsys-110411-160245
[5] Carvajal-Rodríguez, A. (2019). Multi-model inference of non-random mating from an information theoretic approach. bioRxiv, 305730, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/305730
[6] Rolán‐Alvarez, E., & Caballero, A. (2000). Estimating sexual selection and sexual isolation effects from mating frequencies. Evolution, 54(1), 30-36. doi: 10.1111/j.0014-3820.2000.tb00004.x
[7] Carvajal-Rodríguez, A., & Rolan-Alvarez, E. (2006). JMATING: a software for the analysis of sexual selection and sexual isolation effects from mating frequency data. BMC Evolutionary Biology, 6(1), 40. doi: 10.1186/1471-2148-6-40
[8] Carvajal-Rodríguez, A. (2018). Non-random mating and information theory. Theoretical population biology, 120, 103-113. doi: 10.1016/j.tpb.2018.01.003
[9] Carvajal-Rodríguez, A. (2019). A generalization of the informational view of non-random mating: Models with variable population frequencies. Theoretical population biology, 125, 67-74. doi: 10.1016/j.tpb.2018.12.004

Multi-model inference of non-random mating from an information theoretic approachAntonio Carvajal-Rodríguez<p>Non-random mating has a significant impact on the evolution of organisms. Here, I developed a modelling framework for discrete traits (with any number of phenotypes) to explore different models connecting the non-random mating causes (mate comp...Evolutionary Ecology, Evolutionary Theory, Sexual SelectionSara Magalhaes2019-02-08 19:24:03 View
21 Nov 2019
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Environmental specificity in Drosophila-bacteria symbiosis affects host developmental plasticity

Nutrition-dependent effects of gut bacteria on growth plasticity in Drosophila melanogaster

Recommended by based on reviews by Pedro Simões and 1 anonymous reviewer

It is well known that the rearing environment has strong effects on life history and fitness traits of organisms. Microbes are part of every environment and as such likely contribute to such environmental effects. Gut bacteria are a special type of microbe that most animals harbor, and as such they are part of most animals’ environment. Such microbial symbionts therefore likely contribute to local adaptation [1]. The main question underlying the laboratory study by Guilhot et al. [2] was: How much do particular gut bacteria affect the organismal phenotype, in terms of life history and larval foraging traits, of the fruit fly Drosophila melanogaster, a common laboratory model species in biology?
To investigate the above question, the authors isolated 4 taxa of bacteria from the gut of a (randomly picked) Drosophila melanogaster lab strain, and subsequently let Drosophila melanogaster eggs and larvae (stemming from their own, different lab strain) develop both in the typical artificial laboratory medium as well as in grapes, a natural “new” habitat for Drosophila larvae, inoculated with theses bacteria, singly and in combination, also including a bacteria-free control. By investigating various relevant developmental and size traits, the authors found that adding particularly Enterobacteria had some visible effects on several traits, both upward (indicting improvement) and downward (being detrimental) (with three other types of bacteria showing only minor or even no effects). In general, the grape medium reduced performance relative to the standard lab medium. Strongest interactive effects occurred for development time and body size, together making up growth plasticity [3], with lesser such effects on some related behavioral (feeding) traits (Figs. 2,3).
The study premise is interesting, its general objectives are clearly laid out, and the practical work was conducted correctly as far as I can evaluate. The study remains largely descriptive in that no particular a priori hypotheses or predictions in relation to the specific bacteria isolated were formulated, not least because the bacteria were necessarily somewhat arbitrarily chosen and there were apparently no prior studies from which to derive concrete predictions. Overall, the results of this study should be of interest to the community of evolutionary ecologists, especially those working on nutritional and microbiome effects on animal life histories. I consider this work to be primarily ecological, with limited evolutionary content (e.g. no genetics) though some evolutionary implications, as mentioned in the paper’s Conclusions. So this paper would best fit in a microbial or physiological ecology outlet/journal.
The inclusion of a natural medium (grapes) must be commended because this permits inferences and conclusions for at least one natural environment, whereas inferences drawn from laboratory studies in the artificial medium that most Drosophila researchers seem to use are typically limited. Unsurprisingly perhaps, the study showed that Drosophila melanogaster fared generally better in the artificial than the chosen natural medium (grape). Crucially, however, the bacterial symbionts modified both media differentially. Although common bacterial taxa were chosen, the particular bacteria isolated and used remain arbitrary, as there are many. I note that the main and strongest interactive effects between medium and bacterial type are apparent for the Enterobacteria, and they probably also strongly, if not exclusively, mediate the overall effect of the bacterial mixture.
While these specific data are novel, they are not very surprising. If we grow animals in different environments we can expect some detectable effects of these environments, including the bacterial (microbiome) environment, on the hosts life history. The standard and predicted [4] life history response of Drosophila melanogaster (but not all insects [3]) facing stressful nutritional environments, as apparently created by the Enterobacteria, is to extend development but come out smaller in the end. This is what happened here for the laboratory medium ([2]: Fig. 5). The biological interpretation is that individuals have more trouble ingesting and/or digesting the nutrients available (thus prolonging their foraging period and development), yet cannot convert the nutrients effectively into body size increments (hence emerging smaller). This is what the authors here refer to as developmental plasticity, which is ultimately nutritionally mediated. However, interestingly, a signal in the opposite direction was indicated for the bacterial mixture in the grape medium (flies emerging larger after accelerated development: Fig. 5), suggesting some positive effects on growth rate of the natural medium, perhaps related to grapes being a limited resource that needs to be escaped quickly [3]? The reversal of sexual size dimorphism across bacterial treatments in the grape environment detectable in Fig. 4 is interesting, too, though I don’t understand why this happens, and this is not discussed.
In general, more encompassing and increased questions in this context to be researched in the future could be: 1) are these effects predictable (not (yet) at this point, or so it seems); and 2) how strong are these environmental bacterial effects relative to other, more standard effects (e.g. relative to genetic variation, population variation, etc., or relative to other types of environmental effects like, say, temperature)? (3) It could further be asked why not natural but laboratory populations of Drosophila were used for this experiment, if the aim was to draw inferences for the wild situation. (4) Although Genotype x Environment effects are invoked in the Discussion, they were not tested here, lacking genetically different Drosophila families or populations. From an evolutionary standpoint, I consider this the greatest weakness of the study. I was also not too thrilled by the particular statistical analyses employed, though this ultimately does not negate the results. Nevertheless, this work is a good start in this huge field investigating the microbiome. In conclusion, I can recommend this paper after review by PCI Evol Biol.

References

[1] Kawecki, T. J. and Ebert, D. (2004) Conceptual issues in local adaptation. Ecology Letters 7: 1225-1241. doi: 10.1111/j.1461-0248.2004.00684.x
[2] Guilhot, R., Rombaut, A., Xuéreb, A., Howell, K. and Fellous, S. (2019). Environmental specificity in Drosophila-bacteria symbiosis affects host developmental plasticity. BioRxiv, 717702, v3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/717702
[3] Blanckenhorn, W.U. (1999) Different growth responses to temperature and resource limitation in three fly species with similar life histories. Evolutionary Ecology 13: 395-409. doi: 10.1023/A:1006741222586
[4] Stearns, S. C. and Koella, J. (1986) The evolution of phenotypic plasticity in life history traits: predictions of reaction norms for age and size at maturity. Evolution 40: 893-914. doi: 10.1111/j.1558-5646.1986.tb00560.x

Environmental specificity in Drosophila-bacteria symbiosis affects host developmental plasticityRobin Guilhot, Antoine Rombaut, Anne Xuéreb, Kate Howell, Simon Fellous<p>Environmentally acquired microbial symbionts could contribute to host adaptation to local conditions like vertically transmitted symbionts do. This scenario necessitates symbionts to have different effects in different environments. We investig...Adaptation, Evolutionary Ecology, Phenotypic Plasticity, Species interactionsWolf Blanckenhorn2019-02-13 15:22:23 View
04 Jun 2019
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Thermal regimes, but not mean temperatures, drive patterns of rapid climate adaptation at a continent-scale: evidence from the introduced European earwig across North America

Temperature variance, rather than mean, drives adaptation to local climate

Recommended by based on reviews by Ben Phillips and Eric Gangloff

Climate change is impacting eco-systems worldwide and driving many populations to move, adapt or go extinct. It is increasingly appreciated, for example, that species may adjust their phenology in response to climate change, although empirical data is scarce. In this preprint [1], Tourneur and Meunier report an impressive sampling effort in which life-history traits were measured across introduced populations of earwig in North America. The authors examine whether variation in life-history across populations is correlated with aspects of the thermal climate experienced by each population: mean temperature and seasonality of temperature. They find some fascinating correlations between life-history and thermal climate; correlations with the seasonality of temperature, but not with mean temperature. This study provides relatively uncommon data, in the sense that where most of the literature looking at adaptation in animals in response to climate change has focused on physiological traits [2, 3], this study examines changes in life-history traits with time scales relevant to impending climate change, and provides a reasonable argument that this is adaptation, not just constraint.

References

[1] Tourneur, J.-C. and Meunier, J. (2019). Thermal regimes, but not mean temperatures, drive patterns of rapid climate adaptation at a continent-scale: evidence from the introduced European earwig across North America. BioRxiv, 550319, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/550319
[2] Kellermann, V., Overgaard, J., Hoffmann, A. A., Fløjgaard, C., Svenning, J. C., & Loeschcke, V. (2012). Upper thermal limits of Drosophila are linked to species distributions and strongly constrained phylogenetically. Proceedings of the National Academy of Sciences, 109(40), 16228-16233. doi: 10.1073/pnas.1207553109
[3] Hoffmann, A. A., & Sgro, C. M. (2011). Climate change and evolutionary adaptation. Nature, 470(7335), 479. doi: 10.1038/nature09670

Thermal regimes, but not mean temperatures, drive patterns of rapid climate adaptation at a continent-scale: evidence from the introduced European earwig across North AmericaJean-Claude Tourneur, Joël Meunier<p>The recent development of human societies has led to major, rapid and often inexorable changes in the environment of most animal species. Over the last decades, a growing number of studies formulated predictions on the modalities of animal adap...Adaptation, Evolutionary Ecology, Life HistoryFabien Aubret2019-02-15 09:12:11 View
24 Oct 2019
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Testing host-plant driven speciation in phytophagous insects : a phylogenetic perspective

Phylogenetic approaches for reconstructing macroevolutionary scenarios of phytophagous insect diversification

Recommended by based on reviews by Brian O'Meara and 1 anonymous reviewer

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

Testing host-plant driven speciation in phytophagous insects : a phylogenetic perspective Emmanuelle Jousselin, Marianne Elias During the last two decades, ecological speciation has been a major research theme in evolutionary biology. Ecological speciation occurs when reproductive isolation between populations evolves as a result of niche differentiation. Phytophagous ins...Macroevolution, Phylogenetics / Phylogenomics, Speciation, Species interactionsHervé Sauquet2019-02-25 17:31:33 View
04 Sep 2019
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The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates

How to estimate clonality from genetic data: use large samples and consider the biology of the species

Recommended by ORCID_LOGO based on reviews by David Macaya-Sanz, Marcela Van Loo and 1 anonymous reviewer

Population geneticists frequently use the genetic and genotypic information of a population sample of individuals to make inferences on the reproductive system of a species. The detection of clones, i.e. individuals with the same genotype, can give information on whether there is clonal (vegetative) reproduction in the species. If clonality is detected, population geneticists typically use genotypic richness R, the number of distinct genotypes relative to the sample size, to estimate the rate of clonality c, which can be defined as the proportion of reproductive events that are clonal. Estimating the rate of clonality based on genotypic richness is however problematic because, to date, there is no analytical, nor simulation-based, characterization of this relationship. Furthermore, the effect of sampling on this relationship has never been critically examined.
The paper by Stoeckel, Porro and Arnaud-Haond [1] contributes significantly to the characterization of the relationship between rate of clonality and genetic and genotypic parameters in a population. The authors use an extensive individual-based simulation approach to assess the effects of rate of clonality (fully sexual, fully clonal and a range of intermediate levels of clonality, i.e., partial clonality) on genetic and genotypic parameters, considering variable population size, sample size, and numbers of generations elapsed since population initiation. Based on their simulations, they derive empirical formulae that link for the first time the rate of clonality to the genotypic richness and to the size distribution of clones (genotypic parameters), as well as to the population inbreeding coefficient and to a metric of linkage disequilibrium (genetic parameters). They then use the simulated data to assess the accuracy of their predictions. In a second phase, the authors use a Bayesian supervised learning algorithm to estimate rates of clonality from the simulated data.
The authors show that the relationship between rate of clonality and genotypic richness is not linear: genotypic richness decreases slowly with increasing clonality, a large drop in genotypic richness is only seen for rates of clonality ≥ 0.90. Genetic parameters are only sensitive to high rates of clonality. The practical implications of these results are that genotypic and genetic parameters can complement each other for the estimation of rates of clonality, with genotypic parameters most useful throughout most of the range of clonality values and with genetic parameters complementing them meaningfully at higher values. The most meaningful practical result of the paper is the demonstration of sampling bias on the estimation of genotypic richness. Commonly used population sample sizes in population genetics studies (n ≤ 50) lead to great overestimation of genotypic richness, which consequently leads to a severe underestimation of the rate of clonality in most systems, irrespectively of whether they have reached stationary equilibrium. Only in small populations, these effects are attenuated.
Biologists interested in the estimation of the rate of clonality will find this paper highly useful to design their sampling, and to choose their statistics for inference in a meaningful way. This paper also calls for a careful reappraisal of previously published works that infer rates of clonality from genetic data, and highlights the prime importance of complementary information on species life history data for a correct understanding of partial clonality.

References

[1] Stoeckel, S., Porro, B., and Arnaud-Haond, S. (2019). The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates. ArXiv:1902.09365 [q-Bio] v4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. Retrieved from http://arxiv.org/abs/1902.09365v4

The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal ratesSolenn Stoeckel, Barbara Porro, Sophie Arnaud-Haond<p>Partial clonality is widespread across the tree of life, but most population genetics models are conceived for exclusively clonal or sexual organisms. This gap hampers our understanding of the influence of clonality on evolutionary trajectories...Population Genetics / Genomics, Reproduction and SexMyriam Heuertz2019-02-28 10:10:56 View
07 Nov 2019
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New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations

Inferring rates of clonal versus sexual reproduction from population genetics data

Recommended by based on reviews by Ludwig TRIEST, Stacy Krueger-Hadfield and 1 anonymous reviewer

In partially clonal organisms, genetic markers are often used to characterize the genotypic diversity of populations and infer thereof the relative importance of clonal versus sexual reproduction. Most studies report a measure of genotypic diversity based on a ratio, R, of the number of distinct multilocus genotypes over the sample size, and qualitatively interpret high / low R as indicating the prevalence of sexual / clonal reproduction. However, a theoretical framework allowing to quantify the relative rates of clonal versus sexual reproduction from genotypic diversity is still lacking, except using temporal sampling. Moreover, R is intrinsically highly dependent on sample size and sample design, while alternative measures of genotypic diversity are more robust to sample size, like D*, which is equivalent to the Gini-Simpson diversity index applied to multilocus genotypes. Another potential indicator of reproductive strategies is the inbreeding coefficient, Fis, because population genetics theory predicts that clonal reproduction should lead to negative Fis, at least when the sexual reproduction component occurs through random mating. Taking advantage of this prediction, Arnaud-Haond et al. [1] reanalysed genetic data from 165 populations of four partially clonal seagrass species sampled in a standardized way. They found positive correlations between Fis and both R and D* within each species, reflecting variation in the relative rates of sexual versus clonal reproduction among populations. Moreover, the differences of mean genotypic diversity and Fis values among species were also consistent with their known differences in reproductive strategies. Arnaud-Haond et al. [1] also conclude that previous works based on the interpretation of R generally lead to underestimate the prevalence of clonality in seagrasses. Arnaud-Haond et al. [1] confirm experimentally that Fis merits to be interpreted more properly than usually done when inferring rates of clonal reproduction from population genetics data of species reproducing both sexually and clonally. An advantage of Fis is that it is much less affected by sample size than R, and thus should be more reliable when comparing studies differing in sample design. Hence, when the rate of clonal reproduction becomes significant, we expect Fis < 0 and D* < 1. I expect these two indicators of clonality to be complementary because they rely on different consequences of clonality on pattern of genetic variation. Nevertheless, both measures can be affected by other factors. For example, null alleles, selfing or biparental inbreeding can pull Fis upwards, potentially eliminating the signature of clonal reproduction. Similarly, D* (and other measures of genotypic diversity) can be low because the polymorphism of the genetic markers used is too limited or because sexual reproduction often occurs through selfing, eventually resulting in highly similar homozygous genotypes.
The work of Arnaud-Haond et al. [1] shows that the populations genetics of partially clonal organisms should be better studied, an endeavour encompassed in a companion paper using numerical simulations [2]. A further step that remains to be accomplished is to build a mathematical framework for developing estimators of rates of clonal versus sexual reproduction based on genotypic diversity.

References

[1] Arnaud-Haond, S., Stoeckel, S., and Bailleul, D. (2019). New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations. ArXiv:1902.10240 [q-Bio], v6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. Retrieved from http://arxiv.org/abs/1902.10240
[2] Stoeckel, S., Porro, B., and Arnaud-Haond, S. (2019). The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates. ArXiv:1902.09365 [q-Bio], v4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. Retrieved from http://arxiv.org/abs/1902.09365

New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectationsArnaud-Haond, Sophie, Stoeckel, Solenn, and Bailleul, Diane<p>Seagrass meadows are among the most important coastal ecosystems, in terms of both spatial extent and ecosystem services, but they are also declining worldwide. Understanding the drivers of seagrass meadow dynamics is essential for designing so...Evolutionary Ecology, Population Genetics / Genomics, Reproduction and SexOlivier J Hardy2019-03-01 21:57:34 View
22 Jul 2019
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Transgenerational plasticity of inducible defenses: combined effects of grand-parental, parental and current environments

Transgenerational plasticity through three generations

Recommended by based on reviews by Stewart Plaistow and 1 anonymous reviewer

Organisms very often display phenotypic plasticity, whereby the expression of trait (or suite of traits) changes in a consistent way as a function of some environmental variable. Sometimes this plastic response remains labile and so the trait continues to respond to the environment throughout an organism’s life, but there are also many examples in which environmental conditions during a critical developmental window irreversibly set the stage for how a trait will be expressed later in life.
Traditionally, most studies of phenotypic plasticity have considered how an organism’s phenotype is altered by the environment that it experiences (called within-generation plasticity) but there is growing interest in how an organism’s phenotype is altered by the environment experienced by its ancestors (called transgenerational plasticity) [1]. In the simplest cases an organism’s phenotype might be affected by the environmental conditions experienced by its parents. There are several examples of this phenomenon as well, including interesting cases where predator cues experiences by an organism’s parents dictate the extent to which it displays a defensive phenotype.
Tariel et al. [2] present a study that takes these ideas to the next logical step and examines transgenerational plasticity through three generations. They used a well-studied system of snails (Physa acuta) that display inducible defences in response to predator (crayfish) cues. The authors exposed three generations of snails to one of two treatments: the presence or absence of predator cues, and then examined a suite of behavioural and morphological traits associated with predator defence. This allowed them to determine if and how offspring, parental, and grandparental environment influence offspring phenotype.
Interestingly, their results do show that transgenerational plasticity can act across multiple generations. The patterns found were complex though and it is difficult at this stage to assess how likely it is that these responses are adaptive. For example, a behavioural trait appears to respond to grandparental but not parental environment, shell thickness responds to both, and snail weight and a composite index of morphology respond to neither. Exactly what this means in terms of an offspring’s fitness, however, is unclear. It is also not immediately clear from the study how predictive a grandparent’s environment is of the conditions likely to be faced by an individual. Further work will be needed on these issues to better interpret what this transgenerational plasticity means and to assess if it might be an evolved response to cope with varying predation pressure. It would also be useful to delve more deeply into the developmental mechanisms throughout which this plasticity occurs. Irrespective of these issues, however, the study does reveal that transgenerational plasticity across multiple generations can indeed occur and so cannot be ignored as a source of phenotypic variation.

References

[1] West-Eberhard, M. J. (2003). Developmental plasticity and evolution. Oxford University Press.
[2] Tariel, J., Plenet, S., and Luquet, E. (2019). Transgenerational plasticity of inducible defenses: combined effects of grand-parental, parental and current environments. bioRxiv, 589945, ver. 3, peer-reviewed and recommended by Peer Community in Evolutionary Biology. doi: 10.1101/589945

Transgenerational plasticity of inducible defenses: combined effects of grand-parental, parental and current environmentsJuliette Tariel; Sandrine Plénet; Emilien Luquet<p>While an increasing number of studies highlights that parental environment shapes offspring phenotype (transgenerational plasticity TGP), TGP beyond the parental generation has received less attention. Studies suggest that TGP impacts populatio...Adaptation, Evolutionary Ecology, Non Genetic Inheritance, Phenotypic PlasticityTroy Day2019-03-29 09:31:53 View
22 Mar 2022
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Substantial genetic mixing among sexual and androgenetic lineages within the clam genus Corbicula

Strange reproductive modes and population genetics

Recommended by based on reviews by Arnaud Estoup, Simon Henry Martin and 2 anonymous reviewers

There are many organisms that are asexual or have unusual modes of reproduction. One such quasi-sexual reproductive mode is androgenesis, in which the offspring, after fertilization, inherits only the entire paternal nuclear genome. The maternal genome is ditched along the way. One group of organisms which shows this mode of reproduction are clams in the genus Corbicula, some of which are androecious, while others are dioecious and sexual. The study by Vastrade et al. (2022) describes population genetic patterns in these clams, using both nuclear and mitochondrial sequence markers.

In contrast to what might be expected for an asexual lineage, there is evidence for significant genetic mixing between populations. In addition, there is high heterozygosity and evidence for polyploidy in some lineages. Overall, the picture is complicated! However, what is clear is that there is far more genetic mixing than expected. One possible mechanism by which this could occur is 'nuclear capture' where there is a mixing of maternal and paternal lineages after fertilization. This can sometimes occur as a result of hybridization between 'species', leading to further mixing of divergent lineages. Thus the group is clearly far from an ancient asexual lineage - recombination and mixing occur with some regularity.

The study also analyzed recent invasive populations in Europe and America. These had reduced genetic diversity, but also showed complex patterns of allele sharing suggesting a complex origin of the invasive lineages.

In the future, it will be exciting to apply whole genome sequencing approaches to systems such as this. There are challenges in interpreting a handful of sequenced markers especially in a system with polyploidy and considerable complexity, and whole-genome sequencing could clarify some of the outstanding questions,

Overall, this paper highlights the complex genetic patterns that can result through unusual reproductive modes, which provides a challenge for the field of population genetics and for the recognition of species boundaries. 

References

Vastrade M, Etoundi E, Bournonville T, Colinet M, Debortoli N, Hedtke SM, Nicolas E, Pigneur L-M, Virgo J, Flot J-F, Marescaux J, Doninck KV (2022) Substantial genetic mixing among sexual and androgenetic lineages within the clam genus Corbicula. bioRxiv, 590836, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/590836

Substantial genetic mixing among sexual and androgenetic lineages within the clam genus CorbiculaVastrade M., Etoundi E., Bournonville T., Colinet M., Debortoli N., Hedtke S.M., Nicolas E., Pigneur L.-M., Virgo J., Flot J.-F., Marescaux J. and Van Doninck K.<p style="text-align: justify;">“Occasional” sexuality occurs when a species combines clonal reproduction and genetic mixing. This strategy is predicted to combine the advantages of both asexuality and sexuality, but its actual consequences on the...Evolutionary Ecology, Hybridization / Introgression, Phylogeography & BiogeographyChris Jiggins2019-03-29 15:42:56 View
20 Nov 2019
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Distribution of iridescent colours in hummingbird communities results from the interplay between selection for camouflage and communication

Feathers iridescence sheds light on the assembly rules of humingbirds communities

Recommended by based on reviews by 2 anonymous reviewers

Ecology needs rules stipulating how species distributions and ecological communities should be assembled along environmental gradients, but few rules have yet emerged in the ecological literature. The search of ecogeographical rules governing the spatial variation of birds colours has recently known an upsurge of interest in the litterature [1]. Most studies have, however, looked at pigmentary colours and not structural colours (e.g. iridescence), although it is know that color perception by animals (both birds and their predators) can be strongly influenced by light diffraction causing iridescence patterns on feathers.
In the present study [2], the authors study ca. 190 ecological communities of hummingbirds as a function of their iridescent colors, in a large study zone spanning varied habitats across Ecuador. They show that colour composition of local hummingbirds communities are shaped by two main processes :
(i) phenotyping clustering of birds with similar dorsal colours, due to local selection of species with similar camouflages against predators (i.e. some sort of mimetic circles).
(ii) phenotypic overdispersion of birds with distinct facial and ventral colours, resulting from character displacement and limiting reproductive interference.
I found this second result particularly interesting because it adds to the mounting evidence that character displacement (also for songs or olfactory signaling) allow local coexistence between closely-related bird species once they have reached secondary sympatry. It is important to note that not all color patches though to be involved in sexual selection followed this overdispersion rule -- throat and crown color patches were not found overdispersed. This suggests that further investigation is needed to determine how color variation shape the structure of hummingbird communities, or bird communities in general.
Another notable quality of the present study is that it is making extensive use of museum specimens and thus shows that very innovative research can be performed with museum collections.

References

[1] Delhey, K. (2019). A review of Gloger’s rule, an ecogeographical rule of colour: definitions, interpretations and evidence. Biological Reviews, 94(4), 1294–1316. doi: 10.1111/brv.12503
[2] Gruson, H., Elias, M., Parra, J. L., Andraud, C., Berthier, S., Doutrelant, C., & Gomez, D. (2019). Distribution of iridescent colours in hummingbird communities results from the interplay between selection for camouflage and communication. BioRxiv, 586362, v5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/586362

Distribution of iridescent colours in hummingbird communities results from the interplay between selection for camouflage and communicationHugo Gruson, Marianne Elias, Juan L. Parra, Christine Andraud, Serge Berthier, Claire Doutrelant, Doris Gomez<p>Identification errors between closely related, co-occurring, species may lead to misdirected social interactions such as costly interbreeding or misdirected aggression. This selects for divergence in traits involved in species identification am...Evolutionary Ecology, Macroevolution, Phylogeography & Biogeography, Sexual Selection, Species interactionsSébastien Lavergne2019-03-29 17:23:20 View
05 May 2020
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Meta-population structure and the evolutionary transition to multicellularity

The ecology of evolutionary transitions to multicellularity

Recommended by based on reviews by 2 anonymous reviewers

The evolutionary transition to multicellular life from free-living, single-celled ancestors has occurred independently in multiple lineages [1-5]. This evolutionary transition to cooperative group living can be difficult to explain given the fitness advantages enjoyed by the non-cooperative, single-celled organisms that still numerically dominate life on earth [1,6,7]. Although several hypotheses have been proposed to explain the transition to multicellularity, a common theme is the abatement of the efficacy of natural selection among the single cells during the free-living stage and the promotion of the efficacy of selection among groups of cells during the cooperative stage, an argument reminiscent of those from George Williams’ seminal book [8,9]. The evolution of life cycles appears to be a key step in the transition to multicellularity as it can align fitness advantages of the single-celled 'reproductive' stage with that of the cooperative 'organismal' stage [9-12]. That is, the evolution of life cycles allows natural selection to operate over timescales longer than that of the doubling time of the free-living cells [13]. Despite the importance of this issue, identifying the range of ecological conditions that reduce the importance of natural selection at the single-celled, free-living stage and increase the importance of selection among groups of cooperating cells has not been addressed empirically.
Rose et al [14] addressed this issue in a series of real time evolution experiments with bacteria in which they varied the intensity of between-group versus individual-level selection. Central to the experiment is an ecological scaffold that requires lineages to switch between free-living (reproductive) and group-living (organismal) life-stages. One ecological scenario severely limited natural selection at the single-celled, free-living stage by maintaining separation among the reproductive propagules originating from different organisms (groups of cells derived from a single ancestral cell). A second ecological scenario mixed the reproductive propagules from different organisms, leading to severe competition between single cells derived from both the same and other 'organisms'. These ecological scenarios lead to very different evolutionary outcomes. Limiting competition, and thus natural selection, at the reproductive propagule stage promoted traits that favored organismal fitness at the expense of cell division, while competition among single-cells favored traits that promote cell-level traits at the expense of group-level traits. The authors investigate a range of measures of cell and group-level performance in order to understand the mechanisms favoring organismal versus single-cell fitness. Importantly, an evolutionary trade-off between traits promoting organismal fitness and single-cell fitness appears to constrain maximizing fitness of both phases, especially when strong natural selection acts on the single-cell stage.
This article is incredibly thorough and utilizes multiple experiments and levels of argument in order to support the conclusions. The authors include considerable discussion of broader topics surrounding the immediate hypotheses throughout the article, which add both clarity and complexity. The complexity of the experiments, results, and the topic itself lead to a thought-heavy article in a throwback to the monographs of old; expect to read each section multiple times.

References

[1] Maynard Smith, J. and Szathmáry, E. (1995). The Major Transitions in Evolution. Oxford, UK: Freeman. p 346.
[2] Bonner, J. T. (1998). The origins of multicellularity. Integrative Biology: Issues, News, and Reviews: Published in Association with The Society for Integrative and Comparative Biology, 1(1), 27-36. doi: 10.1002/(SICI)1520-6602(1998)1:1<27::AID-INBI4>3.0.CO;2-6
[3] Kaiser, D. (2001). Building a multicellular organism. Annual review of genetics, 35(1), 103-123. doi: 10.1146/annurev.genet.35.102401.090145
[4] Medina, M., Collins, A. G., Taylor, J. W., Valentine, J. W., Lipps, J. H., Amaral-Zettler, L., and Sogin, M. L. (2003). Phylogeny of Opisthokonta and the evolution of multicellularity and complexity in Fungi and Metazoa. International Journal of Astrobiology, 2(3), 203-211. doi: 10.1017/S1473550403001551
[5] King, N. (2004). The unicellular ancestry of animal development. Developmental cell, 7(3), 313-325. doi: 10.1016/j.devcel.2004.08.010
[6] Michod R. E. (1999). Darwinian Dynamics. Evolutionary Transitions in Fitness and Individuality. Princeton, NJ: Princeton Univ. Press. p 262.
[7] Lynch, M. (2007). The frailty of adaptive hypotheses for the origins of organismal complexity. Proceedings of the National Academy of Sciences, 104(suppl 1), 8597-8604. doi: 10.1073/pnas.0702207104
[8] Williams, G. C. (1996). Adaptation and Natural Selection, Reprint edition. Princeton, NJ: Princeton Univ. Press.
[9] Grosberg, R. K., and Strathmann, R. R. (2007). The evolution of multicellularity: a minor major transition?. Annu. Rev. Ecol. Evol. Syst., 38, 621-654. doi: 10.1146/annurev.ecolsys.36.102403.114735
[10] Buss, L. W. (1987). The Evolution of Individuality. Princeton, NJ: Princeton Univ. Press.
[11] Godfrey-Smith, P. (2009). Darwinian Populations and Natural Selection. Oxford University Press, USA.
[12] Van Gestel, J., and Tarnita, C. E. (2017). On the origin of biological construction, with a focus on multicellularity. Proceedings of the National Academy of Sciences, 114(42), 11018-11026. doi: 10.1073/pnas.1704631114
[13] Black, A. J., Bourrat, P., and Rainey, P. B. (2020). Ecological scaffolding and the evolution of individuality. Nature Ecology & Evolution, 4(3), 426-436. doi: 10.1038/s41559-019-1086-9
[14] Rose, C. J., Hammerschmidt, K., Pichugin, Y. and Rainey, P. B. (2020). Meta-population structure and the evolutionary transition to multicellularity. bioRxiv, 407163, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/407163

Meta-population structure and the evolutionary transition to multicellularityCaroline J Rose, Katrin Hammerschmidt, Yuriy Pichugin and Paul B Rainey<p>The evolutionary transition to multicellularity has occurred on numerous occasions, but transitions to complex life forms are rare. While the reasons are unclear, relevant factors include the intensity of within- versus between-group selection ...Adaptation, Evolutionary Dynamics, Experimental EvolutionDustin Brisson2019-04-04 12:26:36 View