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12 Jun 2018
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Transgenerational cues about local mate competition affect offspring sex ratios in the spider mite Tetranychus urticae

Maternal effects in sex-ratio adjustment

Recommended by based on reviews by 2 anonymous reviewers

Optimal sex ratios have been topic of extensive studies so far. Fisherian 1:1 proportions of males and females are known to be optimal in most (diploid) organisms, but many deviations from this golden rule are observed. These deviations not only attract a lot of attention from evolutionary biologists but also from population ecologists as they eventually determine long-term population growth. Because sex ratios are tightly linked to fitness, they can be under strong selection or plastic in response to changing demographic conditions. Hamilton [1] pointed out that an equality of the sex ratio breaks down when there is local competition for mates. Competition for mates can be considered as a special case of local resource competition. In short, this theory predicts females to adjust their offspring sex ratio conditional on cues indicating the level of local mate competition that their sons will experience. When cues indicate high levels of LMC mothers should invest more resources in the production of daughters to maximise their fitness, while offspring sex ratios should be closer to 50:50 when cues indicate low levels of LMC.
In isolated populations, Macke et al. [2] found sex ratio to evolve fast in response to changes in population sex-structure in the spider mite Tetranychus urticae. Spider mites are becoming top-models in evolutionary biology because of their easy housekeeping, fast generation times and well-studied genome [3]. The species is known to respond fast to changes in relatedness and kin-structure by changing its mating strategy [4], but also dispersal [5]. Sex ratio adjustments are likely mediated by differential investments in egg size, with small eggs possibly experiencing lower chances of fertilization, and thus to develop in haploid males [4].
Alison Duncan and colleagues [6] asked the question whether sex ratios change plastically in response to changes in the local population structure. They additionally questioned whether maternal effects could drive changes in sex-allocation of spider mite mothers. Indeed, theory predicts that if environmental changes are predictable across generations, intergenerational plasticity might be more adaptive than intragenerational plasticity [7]. Especially in spatially structured and highly dynamics populations, female spider mites may experience highly variable demographic conditions from one generation to another. During range expansions, spatial variation in local relatedness and inbreeding are documented to change and to impact eco-evolutionary trajectories as well (e.g. [8]).
Duncan et al. [6] specifically investigate whether the offspring sex ratio of T. urticae females changes in response to 1) the current number of females in the same patch, 2) the number of females in the patches of their mothers and 3) their relatedness to their mate. They surprisingly find the maternal environment to be more important than the actual experienced sex-ratio conditions. These insights thus show the maternal environment to be a reliable predictor of LMC experienced by grand-children. Maternal effects have been found to impact many traits, but this study is the first to convincingly demonstrate maternal effects in sex allocation. It therefore provides an alternative explanation of the apparent fast evolved responses under constant demographic conditions [2], and adds evidence to the importance of non-genetic trait changes for adaptation towards changing demographic and environmental conditions.

References

[1] Hamilton, W. D. (1967). Extraordinary Sex Ratios. Science, 156(3774), 477–488. doi: 10.1126/science.156.3774.477
[2] Macke, E., Magalhães, S., Bach, F., & Olivieri, I. (2011). Experimental evolution of reduced sex ratio adjustment under local mate competition. Science, 334(6059), 1127–1129. doi: 10.1126/science.1212177
[3] Grbić, M., Van Leeuwen, T., Clark, R. M., et al. (2011). The genome of Tetranychus urticae reveals herbivorous pest adaptations. Nature, 479(7374), 487–492. doi: 10.1038/nature10640
[4] Macke, E., Magalhães, S., Bach, F., & Olivieri, I. (2012). Sex-ratio adjustment in response to local mate competition is achieved through an alteration of egg size in a haplodiploid spider mite. Proceedings of the Royal Society B: Biological Sciences, 279(1747), 4634–4642. doi: 10.1098/rspb.2012.1598
[5] Bitume, E. V., Bonte, D., Ronce, O., Bach, F., Flaven, E., Olivieri, I., & Nieberding, C. M. (2013). Density and genetic relatedness increase dispersal distance in a subsocial organism. Ecology Letters, 16(4), 430–437. doi: 10.1111/ele.12057
[6] Duncan, A., Marinosci, C., Devaux, C., Lefèvre, S., Magalhães, S., Griffin, J., Valente, A., Ronce, O., Olivieri, I. (2018). Transgenerational cues about local mate competition affect offspring sex ratios in the spider mite Tetranychus urticae. BioRxiv, 240127, ver. 3. doi: 10.1101/240127
[7] Petegem, K. V., Moerman, F., Dahirel, M., Fronhofer, E. A., Vandegehuchte, M. L., Leeuwen, T. V., Wybouw, N., Stoks, R., Bonte, D. (2018). Kin competition accelerates experimental range expansion in an arthropod herbivore. Ecology Letters, 21(2), 225–234. doi: 10.1111/ele.12887
[8] Marshall, D. J., & Uller, T. (2007). When is a maternal effect adaptive? Oikos, 116(12), 1957–1963. doi: 10.1111/j.2007.0030-1299.16203.x

Transgenerational cues about local mate competition affect offspring sex ratios in the spider mite Tetranychus urticaeAlison B. Duncan, Cassandra Marinosci, Céline Devaux, Sophie Lefèvre, Sara Magalhães, Joanne Griffin, Adeline Valente, Ophélie Ronce, Isabelle Olivieri<p style="text-align: justify;">In structured populations, competition between closely related males for mates, termed Local Mate Competition (LMC), is expected to select for female-biased offspring sex ratios. However, the cues underlying sex all...Evolutionary Ecology, Life HistoryDries Bonte2017-12-29 16:10:32 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
05 Aug 2020
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Transposable Elements are an evolutionary force shaping genomic plasticity in the parthenogenetic root-knot nematode Meloidogyne incognita

DNA transposons drive genome evolution of the root-knot nematode Meloidogyne incognita

Recommended by ORCID_LOGO based on reviews by Daniel Vitales and 2 anonymous reviewers

Duplications, mutations and recombination may be considered the main sources of genomic variation and evolution. In addition, sexual recombination is essential in purging deleterious mutations and allowing advantageous allelic combinations to occur (Glémin et al. 2019). However, in parthenogenetic asexual organisms, variation cannot be explained by sexual recombination, and other mechanisms must account for it. Although it is known that transposable elements (TE) may influence on genome structure and gene expression patterns, their role as a primary source of genomic variation and rapid adaptability has received less attention. An important role of TE on adaptive genome evolution has been documented for fungal phytopathogens (Faino et al. 2016), suggesting that TE activity might explain the evolutionary dynamics of this type of organisms.
The phytopathogen nematode Meloidogyne incognita is one of the worst agricultural pests in warm climates (Savary et al. 2019). This species, as well as other root-knot nematodes (RKN), shows a wide geographical distribution range infecting diverse groups of plants. Although allopolyploidy may have played an important role on the wide adaptation of this phytopathogen, it may not explain by itself the rapid changes required to overcome plant resistance in a few generations. Paradoxically, M. incognita reproduces asexually via mitotic parthenogenesis (Trudgill and Blok 2001; Castagnone-Sereno and Danchin 2014) and only few single nucleotide variations were identified between different host races isolates (Koutsovoulos et al. 2020). Therefore, this is an interesting model to explore other sources of genomic variation such the TE activity and its role on the success and adaptability of this phytopathogen.
To address these questions, Kozlowski et al. (2020) estimated the TE mobility across 12 geographical isolates that presented phenotypic variations in Meloidogyne incognita, concluding that recent activity of TE in both genic and regulatory regions might have given rise to relevant functional differences between genomes. This was the first estimation of TE activity as a mechanism probably involved in genome plasticity of this root-knot nematode. This study also shed light on evolutionary mechanisms of asexual organisms with an allopolyploid origin. These authors re-annotated the 185 Mb triploid genome of M. incognita for TE content analysis using stringent filters (Kozlowski 2020a), and estimated activity by their distribution using a population genomics approach including isolates from different crops and locations. Canonical TE represented around 4.7% of the M. incognita genome of which mostly correspond to TIR (Terminal Inverted Repeats) and MITEs (Miniature Inverted repeat Transposable Elements) followed by Maverick DNA transposons and LTR (Long Terminal Repeats) retrotransposons. The result that most TE found were represented by DNA transposons is similar to the previous studies with the nematode species model Caenorhabditis elegans (Bessereau 2006; Kozlowski 2020b) and other nematodes as well. Canonical TE annotations were highly similar to their consensus sequences containing transposition machinery when TE are autonomous, whereas no genes involved in transposition were found in non-autonomous ones. These findings suggest recent activity of TE in the M. incognita genome. Other relevant result was the significant variation in TE presence frequencies found in more than 3,500 loci across isolates, following a bimodal distribution within isolates. However, variation in TE frequencies was low to moderate between isolates recapitulating the phylogenetic signal of isolates DNA sequences polymorphisms. A detailed analysis of TE frequencies across isolates allowed identifying polymorphic TE loci, some of which might be neo-insertions mostly of TIRs and MITEs (Kozlowski 2020c). Interestingly, the two thirds of the fixed neo-insertions were located in coding regions or in regulatory regions impacting expression of specific genes in M. incognita. Future research on proteomics is needed to evaluate the functional impact that these insertions have on adaptive evolution in M. incognita. In this line, this pioneer research of Kozlowski et al. (2020) is a first step that is also relevant to remark the role that allopolyploidy and reproduction have had on shaping nematode genomes.

References

[1] Bessereau J-L. 2006. Transposons in C. elegans. WormBook. 10.1895/wormbook.1.70.1
[2] Castagnone-Sereno P, Danchin EGJ. 2014. Parasitic success without sex - the nematode experience. J. Evol. Biol. 27:1323-1333. 10.1111/jeb.12337
[3] Faino L, Seidl MF, Shi-Kunne X, Pauper M, Berg GCM van den, Wittenberg AHJ, Thomma BPHJ. 2016. Transposons passively and actively contribute to evolution of the two-speed genome of a fungal pathogen. Genome Res. 26:1091-1100. 10.1101/gr.204974.116
[4] Glémin S, François CM, Galtier N. 2019. Genome Evolution in Outcrossing vs. Selfing vs. Asexual Species. In: Anisimova M, editor. Evolutionary Genomics: Statistical and Computational Methods. Methods in Molecular Biology. New York, NY: Springer. p. 331-369. 10.1007/978-1-4939-9074-0_11
[5] Koutsovoulos GD, Marques E, Arguel M-J, Duret L, Machado ACZ, Carneiro RMDG, Kozlowski DK, Bailly-Bechet M, Castagnone-Sereno P, Albuquerque EVS, et al. 2020. Population genomics supports clonal reproduction and multiple independent gains and losses of parasitic abilities in the most devastating nematode pest. Evol. Appl. 13:442-457. 10.1111/eva.12881
[6] Kozlowski D. 2020a. Transposable Elements prediction and annotation in the M. incognita genome. Portail Data INRAE. 10.15454/EPTDOS
[7] Kozlowski D. 2020b. Transposable Elements prediction and annotation in the C. elegans genome. Portail Data INRAE. 10.15454/LQCIW0
[8] Kozlowski D. 2020c. TE polymorphisms detection and analysis with PopoolationTE2. Portail Data INRAE. 10.15454/EWJCT8
[9] Kozlowski DK, Hassanaly-Goulamhoussen R, Da Rocha M, Koutsovoulos GD, Bailly-Bechet M, Danchin EG (2020) Transposable Elements are an evolutionary force shaping genomic plasticity in the parthenogenetic root-knot nematode Meloidogyne incognita. bioRxiv, 2020.04.30.069948, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. 10.1101/2020.04.30.069948
[10] Savary S, Willocquet L, Pethybridge SJ, Esker P, McRoberts N, Nelson A. 2019. The global burden of pathogens and pests on major food crops. Nat. Ecol. Evol. 3:430-439. 10.1038/s41559-018-0793-y
[11] Trudgill DL, Blok VC. 2001. Apomictic, polyphagous root-knot nematodes: exceptionally successful and damaging biotrophic root pathogens. Annu Rev Phytopathol 39:53-77. 10.1146/annurev.phyto.39.1.53

Transposable Elements are an evolutionary force shaping genomic plasticity in the parthenogenetic root-knot nematode Meloidogyne incognitaDjampa KL Kozlowski, Rahim Hassanaly-Goulamhoussen, Martine Da Rocha, Georgios D Koutsovoulos, Marc Bailly-Bechet, Etienne GJ Danchin<p>Despite reproducing without sexual recombination, the root-knot nematode Meloidogyne incognita is adaptive and versatile. Indeed, this species displays a global distribution, is able to parasitize a large range of plants and can overcome plant ...Adaptation, Bioinformatics & Computational Biology, Genome Evolution, Molecular Evolution, Population Genetics / Genomics, Reproduction and SexInes Alvarez2020-05-04 11:43:14 View
04 Nov 2020
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Treating symptomatic infections and the co-evolution of virulence and drug resistance

More intense symptoms, more treatment, more drug-resistance: coevolution of virulence and drug-resistance

Recommended by based on reviews by 3 anonymous reviewers

Mathematical models play an essential role in current evolutionary biology, and evolutionary epidemiology is not an exception [1]. While the issues of virulence evolution and drug-resistance evolution resonate in the literature for quite some time [2, 3], the study by Alizon [4] is one of a few that consider co-evolution of both these traits [5]. The idea behind this study is the following: treating individuals with more severe symptoms at a higher rate (which appears to be quite natural) leads to an appearance of virulent drug-resistant strains, via treatment failure. The author then shows that virulence in drug-resistant strains may face different selective pressures than in drug-sensitive strains and hence proceed at different rates. Hence, treatment itself modulates evolution of virulence. As one of the reviewers emphasizes, the present manuscript offers a mathematical view on why the resistant and more virulent strains can be selected in epidemics. Also, we both find important that the author highlights that the topic and results of this study can be attributed to public health policies and development of optimal treatment protocols [6].
Mathematical models are simplified representations of reality, created with a particular purpose. It can be simple as well as complex, but even simple models can produce relatively complex and knitted results. The art of modelling thus lies not only in developing a model, but also in interpreting and unknitting the results. And this is what Alizon [4] indeed does carefully and exhaustively. Using two contrasting theoretical approaches to study co-evolution, the Price equation approach to study short-term evolution and the adaptive dynamics approach to study long-term evolution, Alizon [4] shows that a positive correlation between the rate of treatment and infection severity causes virulence in drug-sensitive strains to decrease. Clearly, no single model can describe and explain an examined system in its entirety, and even this aspect of the work is taken seriously. Many possible extensions of the study are laid out, providing a wide opportunity to pursue this topic even further. Personally, I have had an opportunity to read many Alizon’s papers and use, teach or discuss many of his models and results. All, including the current one, keep high standard and pursue the field of theoretical (evolutionary) epidemiology.

References

[1] Gandon S, Day T, Metcalf JE, Grenfell BT (2016) Forecasting epidemiological and evolutionary dynamics of infectious diseases. Trends Ecol Evol 31: 776-788. doi: https://doi.org/10.1016/j.tree.2016.07.010
[2] Berngruber TW, Froissart R, Choisy M, Gandon S (2013) Evolution of virulence in emerging epidemics. PLoS Pathog 9(3): e1003209. doi: https://doi.org/10.1371/journal.ppat.1003209
[3] Spicknall IH, Foxman B, Marrs CF, Eisenberg JNS (2013) A modeling framework for the evolution and spread of antibiotic resistance: literature review and model categorization. Am J Epidemiol 178: 508-520. doi: https://doi.org/10.1093/aje/kwt017
[4] Alizon S (2020) Treating symptomatic infections and the co-evolution of virulence and drug resistance. bioRxiv, 2020.02.29.970905, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: https://doi.org/10.1101/2020.02.29.970905
[5] Carval D, Ferriere R (2010) A unified model for the coevolution of resistance, tolerance, and virulence. Evolution 64: 2988–3009. doi: https://doi.org/10.1111/j.1558-5646.2010.01035.x
[6] Read AF, T Day, and S Huijben (2011). The evolution of drug resistance and the curious orthodoxy of aggressive chemotherapy. Proc Natl Acad Sci USA 108 Suppl 2, 10871–7. doi: https://doi.org/10.1073/pnas.1100299108

Treating symptomatic infections and the co-evolution of virulence and drug resistanceSamuel Alizon<p>Antimicrobial therapeutic treatments are by definition applied after the onset of symptoms, which tend to correlate with infection severity. Using mathematical epidemiology models, I explore how this link affects the coevolutionary dynamics bet...Evolutionary Applications, Evolutionary Dynamics, Evolutionary Epidemiology, Evolutionary TheoryLudek Berec2020-03-04 10:18:39 View
05 Oct 2017
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Using Connectivity To Identify Climatic Drivers Of Local Adaptation

A new approach to identifying drivers of local adaptation

Recommended by based on reviews by Ruth Arabelle Hufbauer and Thomas Lenormand

Local adaptation, the higher fitness a population achieves in its local “home” environment relative to other environments is a crucial phase in the divergence of populations, and as such both generates and maintains diversity. Local adaptation is enhanced by selection and genetic variation in the relevant traits, and decreased by gene flow and genetic drift.

Demonstrating local adaptation is laborious, and is typically done with a reciprocal transplant design [1], documenting repeated geographic clines [e.g. 2, 3] also provides strong evidence of local adaptation. Even when well documented, it is often unknown which aspects of the environment impose selection. Indeed, differences in environment between different sites that are measured during studies of local adaptation explain little of the variance in the degree of local adaptation [4]. This poses a problem to population management. Given climate change and habitat destruction, understanding the environmental drivers of local adaptation can be crucially important to conducting successful assisted migration or targeted gene flow.

In this manuscript, Macdonald et al. [5] propose a means of identifying which aspects of the environment select for local adaptation without conducting a reciprocal transplant experiment. The idea is that the strength of relationships between traits and environmental variables that are due to plastic responses to the environment will not be influenced by gene flow, but the strength of trait-environment relationships that are due to local adaptation should decrease with gene flow. This then can be used to reduce the somewhat arbitrary list of environmental variables on which data are available down to a targeted list more likely to drive local adaptation in specific traits. To perform such an analysis requires three things: 1) measurements of traits of interest in a species across locations, 2) an estimate of gene flow between locations, which can be replaced with a biologically meaningful estimate of how well connected those locations are from the point of view of the study species, and 3) data on climate and other environmental variables from across a species’ range, many of which are available on line.

Macdonald et al. [5] demonstrate their approach using a skink (Lampropholis coggeri). They collected morphological and physiological data on individuals from multiple populations. They estimated connectivity among those locations using information on habitat suitability and dispersal potential [6], and gleaned climatic data from available databases and the literature. They find that two physiological traits, the critical minimum and maximum temperatures, show the strongest signs of local adaptation, specifically local adaptation to annual mean precipitation, precipitation of the driest quarter, and minimum annual temperature. These are then aspects of skink phenotype and skink habitats that could be explored further, or could be used to provide background information if migration efforts, for example for genetic rescue [7] were initiated. The approach laid out has the potential to spark a novel genre of research on local adaptation. It its simplest form, knowing that local adaptation is eroded by gene flow, it is intuitive to consider that if connectivity reduces the strength of the relationship between an environmental variable and a trait, that the trait might be involved in local adaptation. The approach is less intuitive than that, however – it relies not connectivity per-se, but the interaction between connectivity and different environmental variables and how that interaction alters trait-environment relationships. The authors lay out a number of useful caveats and potential areas that could use further development. It will be interesting to see how the community of evolutionary biologists responds.

References

[1] Blanquart F, Kaltz O, Nuismer SL and Gandon S. 2013. A practical guide to measuring local adaptation. Ecology Letters, 16: 1195-1205. doi: 10.1111/ele.12150

[2] Huey RB, Gilchrist GW, Carlson ML, Berrigan D and Serra L. 2000. Rapid evolution of a geographic cline in size in an introduced fly. Science, 287: 308-309. doi: 10.1126/science.287.5451.308

[3] Milesi P, Lenormand T, Lagneau C, Weill M and Labbé P. 2016. Relating fitness to long-term environmental variations in natura. Molecular Ecology, 25: 5483-5499. doi: 10.1111/mec.13855

[4] Hereford, J. 2009. A quantitative survey of local adaptation and fitness trade-offs. The American Naturalist 173: 579-588. doi: 10.1086/597611

[5] Macdonald SL, Llewelyn J and Phillips BL. 2017. Using connectivity to identify climatic drivers of local adaptation. bioRxiv, ver. 4 of October 4, 2017. doi: 10.1101/145169

[6] Macdonald SL, Llewelyn J, Moritz C and Phillips BL. 2017. Peripheral isolates as sources of adaptive diversity under climate change. Frontiers in Ecology and Evolution, 5:88. doi: 10.3389/fevo.2017.00088

[7] Whiteley AR, Fitzpatrick SW, Funk WC and Tallmon DA. 2015. Genetic rescue to the rescue. Trends in Ecology & Evolution, 30: 42-49. doi: 10.1016/j.tree.2014.10.009

Using Connectivity To Identify Climatic Drivers Of Local AdaptationStewart L. Macdonald, John Llewelyn, Ben PhillipsDespite being able to conclusively demonstrate local adaptation, we are still often unable to objectively determine the climatic drivers of local adaptation. Given the rapid rate of global change, understanding the climatic drivers of local adapta...Adaptation, Evolutionary ApplicationsRuth Arabelle Hufbauer Thomas Lenormand2017-06-06 13:06:54 View
06 Jul 2018
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Variation in competitive ability with mating system, ploidy and range expansion in four Capsella species

When ecology meets genetics: Towards an integrated understanding of mating system transitions and diversity

Recommended by and based on reviews by Yaniv Brandvain, Henrique Teotonio and 1 anonymous reviewer

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

References

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

Variation in competitive ability with mating system, ploidy and range expansion in four Capsella speciesXuyue Yang, Martin Lascoux and Sylvain Glémin<p>Self-fertilization is often associated with ecological traits corresponding to the ruderal strategy in Grime’s Competitive-Stress-tolerant-Ruderal (CSR) classification of ecological strategies. Consequently, selfers are expected to be less comp...Evolutionary Ecology, Population Genetics / Genomics, Reproduction and Sex, Species interactionsSylvain Billiard2017-11-06 19:54:52 View
22 May 2023
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Weak seed banks influence the signature and detectability of selective sweeps

New insights into the dynamics of selective sweeps in seed-banked species

Recommended by ORCID_LOGO based on reviews by Guillaume Achaz, Jere Koskela, William Shoemaker and Simon Boitard

Many organisms across the Tree of life have the ability to produce seeds, eggs, cysts, or spores, that can remain dormant for several generations before hatching. This widespread adaptive trait in bacteria, fungi, plants and animals, has a significant impact on the ecology, population dynamics and population genetics of species that express it (Evans and Dennehy 2005).

In population genetics, and despite the recognition of its evolutionary importance in many empirical studies, few theoretical models have been developed to characterize the evolutionary consequences of this trait on the level and distribution of neutral genetic diversity (see, e.g., Kaj et al. 2001; Vitalis et al. 2004), and also on the dynamics of selected alleles (see, e.g., Živković and Tellier 2018). However, due to the complexity of the interactions between evolutionary forces in the presence of dormancy, the fate of selected mutations in their genomic environment is not yet fully understood, even from the most recently developed models.

In a comprehensive article, Korfmann et al. (2023) aim to fill this gap by investigating the effect of germ banking on the probability of (and time to) fixation of beneficial mutations, as well as on the shape of the selective sweep in their vicinity. To this end, Korfmann et al. (2023) developed and released their own forward-in-time simulator of genome-wide data, including neutral and selected polymorphisms, that makes use of Kelleher et al.’s (2018) tree sequence toolkit to keep track of gene genealogies.

The originality of Korfmann et al.’s (2023) study is to provide new quantitative results for the effect of dormancy on the time to fixation of positively selected mutations, the shape of the genomic landscape in the vicinity of these mutations, and the temporal dynamics of selective sweeps. Their major finding is the prediction that germ banking creates narrower signatures of sweeps around positively selected sites, which are detectable for increased periods of time (as compared to a standard Wright-Fisher population).

The availability of Korfmann et al.’s (2023) code will allow a wider range of parameter values to be explored, to extend their results to the particularities of the biology of many species. However, as they chose to extend the haploid coalescent model of Kaj et al. (2001), further development is needed to confirm the robustness of their results with a more realistic diploid model of seed dormancy.

REFERENCES

Evans, M. E. K., and J. J. Dennehy (2005) Germ banking: bet-hedging and variable release from egg and seed dormancy. The Quarterly Review of Biology, 80(4): 431-451. https://doi.org/10.1086/498282

Kaj, I., S. Krone, and M. Lascoux (2001) Coalescent theory for seed bank models. Journal of Applied Probability, 38(2): 285-300. https://doi.org/10.1239/jap/996986745

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

Korfmann, K., D. Abu Awad, and A. Tellier (2023) Weak seed banks influence the signature and detectability of selective sweeps. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.04.26.489499

Vitalis, R., S. Glémin, and I. Olivieri (2004) When genes go to sleep: the population genetic consequences of seed dormancy and monocarpic perenniality. American Naturalist, 163(2): 295-311. https://doi.org/10.1086/381041

Živković, D., and A. Tellier (2018). All but sleeping? Consequences of soil seed banks on neutral and selective diversity in plant species. Mathematical Modelling in Plant Biology, 195-212. https://doi.org/10.1007/978-3-319-99070-5_10

Weak seed banks influence the signature and detectability of selective sweepsKevin Korfmann, Diala Abu Awad, Aurélien Tellier<p style="text-align: justify;">Seed banking (or dormancy) is a widespread bet-hedging strategy, generating a form of population overlap, which decreases the magnitude of genetic drift. The methodological complexity of integrating this trait impli...Adaptation, Bioinformatics & Computational Biology, Evolutionary Applications, Evolutionary Ecology, Genome Evolution, Life History, Population Genetics / GenomicsRenaud Vitalis2022-05-23 13:01:57 View
03 May 2020
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When does gene flow facilitate evolutionary rescue?

Reconciling the upsides and downsides of migration for evolutionary rescue

Recommended by based on reviews by 3 anonymous reviewers

The evolutionary response of populations to changing or novel environments is a topic that unites the interests of evolutionary biologists, ecologists, and biomedical researchers [1]. A prominent phenomenon in this research area is evolutionary rescue, whereby a population that is otherwise doomed to extinction survives due to the spread of new or pre-existing mutations that are beneficial in the new environment. Scenarios of evolutionary rescue require a specific set of parameters: the absolute growth rate has to be negative before the rescue mechanism spreads, upon which the growth rate becomes positive. However, potential examples of its relevance exist (e.g., [2]). From a theoretical point of view, the technical challenge but also the beauty of evolutionary rescue models is that they combine the study of population dynamics (i.e., changes in the size of populations) and population genetics (i.e., changes in the frequencies in the population). Together, the potential relevance of evolutionary rescue in nature and the models' theoretical appeal has resulted in a suite of modeling studies on the subject in recent years.
In this manuscript [3], Tomasini and Peischl address a question that has been contentiously discussed in the literature: when does migration favor evolutionary rescue? They expand on past work (specifically, [4, 5]) by studying the influence of the interaction of the speed and severity of environmental change and the amount of dispersal on the probability of evolutionary rescue. They develop simple analytical results (complemented by simulations) for a haploid one-locus model of two populations connected by gene flow, where both populations deteriorate successively such that evolutionary rescue is required for the metapopulation to survive. For example, the authors derive a simple analytical condition demonstrating that migration between the subpopulations favors evolutionary rescue if environmental change occurs slowly across the two populations (which leaves time for the second population to serve as an immigration source), if the new environment is very harsh and/or if rescue mutations are strongly beneficial in the new environment. The latter conditions ensure that the rescue mutations can spread easily in the new environment without much competition with immigrating, maladapted, genotypes. This result is intuitive and connects between traditional single and multiple-deme models.
Altogether, Tomasini and Peischl present an extensive theoretical study and address also the effect of various tweaks to the model assumptions, such as asymmetries in gene flow and/or carrying capacities, and the effects of different density regulation and local growth rates. They successfully made an effort to explain and interpret their results for a general audience, such that also non-theoreticians should not be afraid to take a look at this manuscript.

References

[1] Bell, G. (2017). Evolutionary Rescue. Annual Review of Ecology, Evolution, and Systematics 48(1), 605-627. doi: 10.1146/annurev-ecolsys-110316-023011
[2] Oziolor, E. M., Reid, N. M., Yair, S. et al. (2019). Adaptive introgression enables evolutionary rescue from extreme environmental pollution. Science, 364(6439), 455-457. doi: 10.1126/science.aav4155
[3] Tomasini, M. and Peischl, S. (2020) When does gene flow facilitate evolutionary rescue? bioRxiv, 622142, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/622142
[4] Uecker, H., Otto, S. P., and Hermisson, J. (2014). Evolutionary rescue in structured populations. The American Naturalist, 183(1), E17-E35. doi: 10.1086/673914
[5] Tomasini, M., and Peischl, S. (2018). Establishment of locally adapted mutations under divergent selection. Genetics, 209(3), 885-895. doi: 10.1534/genetics.118.301104

When does gene flow facilitate evolutionary rescue?Matteo Tomasini, Stephan Peischl<p>Experimental and theoretical studies have highlighted the impact of gene flow on the probability of evolutionary rescue in structured habitats. Mathematical modelling and simulations of evolutionary rescue in spatially or otherwise structured p...Evolutionary Dynamics, Evolutionary Theory, Population Genetics / GenomicsClaudia Bank2019-05-22 11:12:13 View
06 May 2019
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When sinks become sources: adaptive colonization in asexuals

Fisher to the rescue

Recommended by and based on reviews by 3 anonymous reviewers

The ability of a population to adapt to a new niche is an important phenomenon in evolutionary biology. The colonisation of a new volcanic island by plant species; the colonisation of a host treated by antibiotics by a-resistant strain; the Ebola virus transmitting from bats to humans and spreading epidemically in Western Africa, are all examples of a population invading a new niche, adapting and eventually establishing in this new environment.

Adaptation to a new niche can be studied using source-sink models. In the original environment —the “source”—, the population enjoys a positive growth-rate and is self-sustaining, while in the new environment —the “sink”— the population has a negative growth rate and is able to sustain only by the continuous influx of migrants from the source. Understanding the dynamics of adaptation to the sink environment is challenging from a theoretical standpoint, because it requires modelling the demography of the sink as well as the transient dynamics of adaptation. Moreover, local selection in the sink and immigration from the source create distributions of genotypes that complicate the use of many common mathematical approaches.

In their paper, Lavigne et al. [1], develop a new deterministic model of adaptation to a harsh sink environment in an asexual species. The fitness of an individual is maximal when a number of phenotypes are tuned to an optimal value, and declines monotonously as phenotypes are further away from this optimum. This model —called Fisher’s Geometric Model— generates a GxE interaction for fitness because the phenotypic optimum in the sink environment is distinct from that in the source environment [2]. The authors circumvent mathematical difficulties by developing an original approach based on tracking the deterministic dynamics of the cumulant generating function of the fitness distribution in the sink. They derive a number of important results on the dynamics of adaptation to the sink:

  • From the point where immigration from the source to the sink starts, four phases of adaptation are observed. After a short transient phase (phase 1), a migration-selection balance is reached in the sink (phase 2). After a while, thanks to the immigration of rare adapted migrants and mutation in the sink, a small fraction of the sink population exhibits a close-to-optimal phenotype. This small adapted fraction grows in frequency and mean fitness rapidly increases in the sink (phase 3). Finally, the population settles around the sink optimum (phase 4) and, hurray, the sink is now a source!

  • Interestingly, in this model the evolutionary dynamics do not depend on the immigration rate. In other words, adaptation will proceed at the same rate regardless of how many immigrants invade the sink. This is because the impact of immigration on adaptation depends on the rate of immigration relative to the sink density. This ratio is actually independent of immigration in a model where the sink is initially empty, migration from the sink back to the source is negligible and without density-dependence in the sink.

  • In this model, mutation is a double-edged sword. Adapted phenotypes emerge from new mutations, and under this effect alone a higher mutation rate would translate into a shorter time to establishment in the sink. However, mutations may also have deleterious effects by displacing the phenotype away from the optimum. This mutation load will be greater when individuals need to simultaneously tune a large number of phenotypes. As a consequence of these two effects of mutations, time to establishment is minimal for an intermediate mutation rate. This result emerges from Fisher’s Geometric Model, but may hold more generally for biologically plausible fitness landscapes where mutations generates both beneficial (allowing adaptation to the sink) and deleterious genotypes.

  • Lastly, in Fisher’s Geometric Model, the time to establishment increases superlinearly with harshness of the sink when the sink is too harsh, and establishment may occur only after a very long time. In these harsh sinks, the adapted genotypes are very few and increase very slowly in frequency, making the second phase of adaptation much longer. Thus, and as a direct consequence of Fisher’s Geometric Model, adding a “stepping stone” intermediate environment would allow faster adaptation to the extreme environment.

In conclusion, this theoretical work presents a method based on Fisher’s Geometric Model and the use of cumulant generating functions to resolve some aspects of adaptation to a sink environment. It generates a number of theoretical predictions for the adaptive colonisation of a sink by an asexual species with some standing genetic variation. It will be a fascinating task to examine whether these predictions hold in experimental evolution systems: will we observe the four phases of the dynamics of mean fitness in the sink environment? Will the rate of adaptation indeed be independent of the immigration rate? Is there an optimal rate of mutation for adaptation to the sink? Such critical tests of the theory will greatly improve our understanding of adaptation to novel environments.

References

[1] Lavigne, F., Martin, G., Anciaux, Y., Papaïx, J., and Roques, L. (2019). When sinks become sources: adaptive colonization in asexuals. bioRxiv, 433235, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/433235
[2] Martin, G., and Lenormand, T. (2006). A general multivariate extension of Fisher's geometrical model and the distribution of mutation fitness effects across species. Evolution, 60, 893-907. doi: 10.1111/j.0014-3820.2006.tb01169.x

When sinks become sources: adaptive colonization in asexualsFlorian Lavigne, Guillaume Martin, Yoann Anciaux, Julien Papaïx, Lionel Roques<p>The successful establishment of a population into a new empty habitat outside of its initial niche is a phenomenon akin to evolutionary rescue in the presence of immigration. It underlies a wide range of processes, such as biological invasions ...Adaptation, Evolutionary Applications, Evolutionary Dynamics, Evolutionary EcologyFrançois Blanquart2018-10-03 20:59:16 View
13 Jan 2019
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Why cooperation is not running away

A nice twist on partner choice theory

Recommended by based on reviews by 2 anonymous reviewers

In this paper, Geoffroy et al. [1] deal with partner choice as a mechanism of maintaining cooperation, and argues that rather than being unequivocally a force towards improved payoffs to everyone through cooperation, partner choice can lead to “over-cooperation” where individuals can evolve to invest so much in cooperation that the costs of cooperating partially or fully negate the benefits from it. This happens when partner choice is consequential and effective, i.e., when interactions are long (so each decision to accept or reject a partner is a bigger stake) and when meeting new partners is frequent when unpaired (so that when one leaves an interaction one can find a new partner quickly). Geoffroy et al. [1] show that this tendency to select for overcooperation under such regimes can be counteracted if individuals base their acceptance-rejection of partners not just on the partner cooperativeness, but also on their own. By using tools from matching theory in economics, they show that plastic partner choice generates positive assortment between cooperativeness of the partners, and in the extreme case of perfectly assortative pairings, makes the pair the unit of selection, which selects for maximum total payoff.
This study is a nice contribution to the literature that illustrates potential complexities with partner choice as a mechanism for cooperation, including how the proximate mechanisms of partner choice can significantly alter the evolutionary trajectory of cooperation. Modeling choice as a reaction norm that depends on one’s own traits also adds a layer of realism to partner choice theory.
The authors are also to be commended for the revisions they made through the review process. Earlier versions of the model somewhat overstated the tendency for fixed partner choice strategies to lead to over cooperation, missing some of the important features in previous models, notably McNamara et al. [2] that can counter this tendency. In this version, the authors acknowledge these factors, mainly, mortality during partner choice (which increases the opportunity cost of forgoing a current partner) and also the fact that endogenous distribution of alternative partners (which will tend to be worse than the overall population distribution, because more cooperative types spend more time attached and less cooperative types more time unattached). These two factors can constrain cooperation from “running away” as the authors put it, but the main point of Geoffroy et al. [1] that plastic choice can create selection against inefficient cooperation stands.
I think the paper will be very stimulating to theoretical and empirical researchers working on partner choice and social behaviors, and happy to recommend it.

References

[1] Geoffroy, F., Baumard, N., & Andre, J.-B. (2019). Why cooperation is not running away. bioRxiv, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/316117
[2] McNamara, J. M., Barta, Z., Fromhage, L., & Houston, A. I. (2008). The coevolution of choosiness and cooperation. Nature, 451, 189–192. doi: 10.1038/nature06455

Why cooperation is not running awayFélix Geoffroy, Nicolas Baumard, Jean-Baptiste André<p>A growing number of experimental and theoretical studies show the importance of partner choice as a mechanism to promote the evolution of cooperation, especially in humans. In this paper, we focus on the question of the precise quantitative lev...Behavior & Social Evolution, Evolutionary TheoryErol Akcay2018-05-15 10:32:51 View