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07 Jul 2017
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Negative frequency-dependent selection is frequently confounding

Unmasking the delusive appearance of negative frequency-dependent selection

Recommended by based on reviews by David Baltrus and 2 anonymous reviewers

Explaining the processes that maintain polymorphisms in a population has been a fundamental line of research in evolutionary biology. One of the main mechanisms identified that preserves genetic diversity is negative frequency-dependent selection (NFDS), which constitutes a powerful framework for interpreting the presence of persistent polymorphisms. Nevertheless, a number of patterns that are often explained by invoking NFDS may also be compatible with, and possibly more easily explained by, different processes.
In the present manuscript [1], Brisson acknowledges first that genuine NFDS has been instrumental for our understanding on the dynamics that perpetuate polymorphisms, and that the power and importance of NFDS cannot be disregarded. Second, the author aims at identifying certain of the processes that may result in maintenance of genetic diversity, and whose outcome may be mistaken for NFDS, namely directional selection in changing environments, density-dependent fitness, multiple niche selection and community diversity. The author claims that systematic resort to NFDS as explanatory device may have lead to its application to systems where it does not apply or that do not fulfil the basic assumptions of NFDS. The author struggles in the text to provide with a precise, verbal definition of NFDS, and the exchanges with the reviewers during the recommendation process show that agreeing on such a verbal definition of NFDS is not trivial. Probably a profound mathematical formulation of the varying value of a genotype’s fitness relative to other competing ones as a function of their frequency (developing further the synthesis by Heino [2]) may still be wanting. Indeed, the text is intended for a broad audience of evolutionary biologists with operational mathematical knowledge and interest in models, rather than for modellers or biomathematicians. Nevertheless, the manuscript is rich in references to original literature, elaborates on interesting lines of thought and discussion and will hopefully trigger novel experimental and formal research to clarify the role of NFDS and to discern between alternative mechanisms that may render similar patterns of maintenance of genetic diversity.

References

[1] Brisson D. 2017. Negative frequency-dependent selection is frequently confounding. bioRxiv 113324, ver. 3 of 20th June 2017. doi: 10.1101/113324

[2] Heino M, Metz JAJ and Kaitala V. 1998. The enigma of frequency-dependent selection. Trends in Ecology & Evolution 13: 367-370. doi: 1016/S0169-5347(98)01380-9

Negative frequency-dependent selection is frequently confoundingDustin BrissonThe existence of persistent genetic variation within natural populations presents an evolutionary problem as natural selection and genetic drift tend to erode genetic diversity. Models of balancing selection were developed to account for the high ...Evolutionary Applications, Evolutionary Theory, Population Genetics / GenomicsIgnacio Bravo2017-03-03 18:46:42 View
19 Mar 2018
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Natural selection on plasticity of thermal traits in a highly seasonal environment

Is thermal plasticity itself shaped by natural selection? An assessment with desert frogs

Recommended by based on reviews by Dries Bonte, Wolf Blanckenhorn and Nadia Aubin-Horth

It is well known that climatic factors – most notably temperature, season length, insolation and humidity – shape the thermal niche of organisms on earth through the action of natural selection. But how is this achieved precisely? Much of thermal tolerance is actually mediated by phenotypic plasticity (as opposed to genetic adaptation). A prominent expectation is that environments with greater (daily and/or annual) thermal variability select for greater plasticity, i.e. better acclimation capacity. Thus, plasticity might be selected per se.

A Chilean group around Leonardo Bacigalupe assessed natural selection in the wild in one marginal (and extreme) population of the four-eyed frog Pleurodema thaul (Anura: Leptodactylidae) in an isolated oasis in the Atacama Desert, permitting estimation of mortality without much potential of confounding it with migration [1]. Several thermal traits were considered: CTmax – the critical maximal temperature; CTmin – the critical minimum temperature; Tpref – preferred temperature; Q10 – thermal sensitivity of metabolism; and body mass. Animals were captured in the wild and subsequently assessed for thermal traits in the laboratory at two acclimation temperatures (10° & 20°C), defining the plasticity in all traits as the difference between the traits at the two acclimation temperatures. Thereafter the animals were released again in their natural habitat and their survival was monitored over the subsequent 1.5 years, covering two breeding seasons, to estimate viability selection in the wild. The authors found and conclude that, aside from larger body size increasing survival (an unsurprising result), plasticity does not seem to be systematically selected directly, while some of the individual traits show weak signs of selection.

Despite limited sample size (ca. 80 frogs) investigated in only one marginal but very seasonal population, this study is interesting because selection on plasticity in physiological thermal traits, as opposed to selection on the thermal traits themselves, is rarely investigated. The study thus also addressed the old but important question of whether plasticity (i.e. CTmax-CTmin) is a trait by itself or an epiphenomenon defined by the actual traits (CTmax and CTmin) [2-5]. Given negative results, the main question could not be ultimately solved here, so more similar studies should be performed.

References

[1] Bacigalupe LD, Gaitan-Espitia, JD, Barria AM, Gonzalez-Mendez A, Ruiz-Aravena M, Trinder M & Sinervo B. 2018. Natural selection on plasticity of thermal traits in a highly seasonal environment. bioRxiv 191825, ver. 5 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/191825
[2] Scheiner SM. 1993. Genetics and evolution of phenotypic plasticity. Annual Review in Ecology and Systematics 24: 35–68. doi: 10.1146/annurev.es.24.110193.000343
[3] Scheiner SM. 1993. Plasticity as a selectable trait: Reply to Via. The American Naturalist. 142: 371–373. doi: 10.1086/285544
[4] Via S. 1993. Adaptive phenotypic plasticity - Target or by-product of selection in a variable environment? The American Naturalist. 142: 352–365. doi: 10.1086/285542
[5] Via S. 1993. Regulatory genes and reaction norms. The American Naturalist. 142: 374–378. doi: 10.1086/285542

Natural selection on plasticity of thermal traits in a highly seasonal environmentLeonardo Bacigalupe, Juan Diego Gaitan-Espitia, Aura M Barria, Avia Gonzalez-Mendez, Manuel Ruiz-Aravena, Mark Trinder, Barry Sinervo<p>For ectothermic species with broad geographical distributions, latitudinal/altitudinal variation in environmental temperatures (averages and extremes) are expected to shape the evolution of physiological tolerances and the acclimation capacity ...Adaptation, Evolutionary Ecology, Phenotypic PlasticityWolf Blanckenhorn2017-09-22 23:17:40 View
11 Jul 2022
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Mutualists construct the ecological conditions that trigger the transition from parasitism

Give them some space: how spatial structure affects the evolutionary transition towards mutualistic symbiosis

Recommended by ORCID_LOGO based on reviews by Eva Kisdi and 3 anonymous reviewers

The evolution of mutualistic symbiosis is a puzzle that has fascinated evolutionary ecologist for quite a while. Data on transitions between symbiotic bacterial ways of life has evidenced shifts from mutualism towards parasitism and vice versa (Sachs et al., 2011), so there does not seem to be a strong determinism on those transitions. From the host’s perspective, mutualistic symbiosis implies at the very least some form of immune tolerance, which can be costly (e.g. Sorci, 2013). Empirical approaches thus raise very important questions: How can symbiosis turn from parasitism into mutualism when it seemingly needs such a strong alignment of selective pressures on both the host and the symbiont? And yet why is mutualistic symbiosis so widespread and so important to the evolution of macro-organisms (Margulis, 1998)?

While much of the theoretical literature on the evolution of symbiosis and mutualism has focused on either the stability of such relationships when non-mutualists can invade the host-symbiont system (e.g. Ferrière et al., 2007) or the effect of the mode of symbiont transmission on the evolutionary dynamics of mutualism (e.g. Genkai-Kato and Yamamura, 1999), the question remains whether and under which conditions parasitic symbiosis can turn into mutualism in the first place. Earlier results suggested that spatial demographic heterogeneity between host populations could be the leading determinant of evolution towards mutualism or parasitism (Hochberg et al., 2000). Here, Ledru et al. (2022) investigate this question in an innovative way by simulating host-symbiont evolutionary dynamics in a spatially explicit context. Their hypothesis is intuitive but its plausibility is difficult to gauge without a model: Does the evolution towards mutualism depend on the ability of the host and symbiont to evolve towards close-range dispersal in order to maintain clusters of efficient host-symbiont associations, thus outcompeting non-mutualists?

I strongly recommend reading this paper as the results obtained by the authors are very clear: competition strength and the cost of dispersal both affect the likelihood of the transition from parasitism to mutualism, and once mutualism has set in, symbiont trait values clearly segregate between highly dispersive parasites and philopatric mutualists. The demonstration of the plausibility of their hypothesis is accomplished with brio and thoroughness as the authors also examine the conditions under which the transition can be reversed, the impact of the spatial range of competition and the effect of mortality. Since high dispersal cost and strong, long-range competition appear to be the main factors driving the evolutionary transition towards mutualistic symbiosis, now is the time for empiricists to start investigating this question with spatial structure in mind.

References

Ferrière, R., Gauduchon, M. and Bronstein, J. L. (2007) Evolution and persistence of obligate mutualists and exploiters: competition for partners and evolutionary immunization. Ecology Letters, 10, 115-126. https://doi.org/10.1111/j.1461-0248.2006.01008.x

Genkai-Kato, M. and Yamamura, N. (1999) Evolution of mutualistic symbiosis without vertical transmission. Theoretical Population Biology, 55, 309-323. https://doi.org/10.1006/tpbi.1998.1407

Hochberg, M. E., Gomulkiewicz, R., Holt, R. D. and Thompson, J. N. (2000) Weak sinks could cradle mutualistic symbioses - strong sources should harbour parasitic symbioses. Journal of Evolutionary Biology, 13, 213-222. https://doi.org/10.1046/j.1420-9101.2000.00157.x

Ledru L, Garnier J, Rohr M, Noûs C and Ibanez S (2022) Mutualists construct the ecological conditions that trigger the transition from parasitism. bioRxiv, 2021.08.18.456759, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.08.18.456759

Margulis, L. (1998) Symbiotic planet: a new look at evolution, Basic Books, Amherst.

Sachs, J. L., Skophammer, R. G. and Regus, J. U. (2011) Evolutionary transitions in bacterial symbiosis. Proceedings of the National Academy of Sciences, 108, 10800-10807. https://doi.org/10.1073/pnas.1100304108

Sorci, G. (2013) Immunity, resistance and tolerance in bird–parasite interactions. Parasite Immunology, 35, 350-361. https://doi.org/10.1111/pim.12047

Mutualists construct the ecological conditions that trigger the transition from parasitismLeo Ledru, Jimmy Garnier, Matthias Rohr, Camille Nous, Sebastien Ibanez<p>The evolution of mutualism between hosts and initially parasitic symbionts represents a major transition in evolution. Although vertical transmission of symbionts during host reproduction and partner control both favour the stability of mutuali...Evolutionary Ecology, Species interactionsFrancois Massol2021-08-20 12:25:40 View
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
18 May 2018
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Modularity of genes involved in local adaptation to climate despite physical linkage

Differential effect of genes in diverse environments, their role in local adaptation and the interference between genes that are physically linked

Recommended by ORCID_LOGO based on reviews by Tanja Pyhäjärvi and 1 anonymous reviewer

The genome of eukaryotic species is a complex structure that experience many different interactions within itself and with the surrounding environment. The genetic architecture of a phenotype (that is, the set of genetic elements affecting a trait of the organism) plays a fundamental role in understanding the adaptation process of a species to, for example, different climate environments, or to its interaction with other species. Thus, it is fundamental to study the different aspects of the genetic architecture of the species and its relationship with its surronding environment. Aspects such as modularity (the number of genetic units and the degree to which each unit is affecting a trait of the organism), pleiotropy (the number of different effects that a genetic unit can have on an organism) or linkage (the degree of association between the different genetic units) are essential to understand the genetic architecture and to interpret the effects of selection on the genome. Indeed, the knowledge of the different aspects of the genetic architecture could clarify whether genes are affected by multiple aspects of the environment or, on the contrary, are affected by only specific aspects [1,2].

The work performed by Lotterhos et al. [3] sought to understand the genetic architecture of the adaptation to different environments in lodgepole pine (Pinus contorta), considering as candidate SNPs those previously detected as a result of its extreme association patterns to different environmental variables or to extreme population differentiation. This consideration is very important because the study is only relevant if the studied markers are under the effect of selection. Otherwise, the genetic architecture of the adaptation to different environments would be masked by other (neutral) kind of associations that would be difficult to interpret [4,5]. In order to understand the relationship between genetic architecture and adaptation, it is relevant to detect the association networks of the candidate SNPs with climate variables (a way to measure modularity) and if these SNPs (and loci) are affected by single or multiple environments (a way to measure pleiotropy).

The authors used co-association networks, an innovative approach in this field, to analyse the interaction between the environmental information and the genetic polymorphism of each individual. This methodology is more appropriate than other multivariate methods - such as analysis based on principal components - because it is possible to cluster SNPs based on associations with similar environmental variables. In this sense, the co-association networks allowed to both study the genetic and physical linkage between different co-associations modules but also to compare two different models of evolution: a Modular environmental response architecture (specific genes are affected by specific aspects of the environment) or a Universal pleiotropic environmental response architecture (all genes are affected by all aspects of the environment). The representation of different correlations between allelic frequency and environmental factors (named galaxy biplots) are especially informative to understand the effect of the different clusters on specific aspects of the environment (for example, the co-association network ‘Aridity’ shows strong associations with hot/wet versus cold/dry environments).

The analysis performed by Lotterhos et al. [3], although it has some unavoidable limitations (e.g., only extreme candidate SNPs are selected, limiting the results to the stronger effects; the genetic and physical map is incomplete in this species), includes relevant results and also implements new methodologies in the field. To highlight some of them: the preponderance of a Modular environmental response architecture (evolution in separated modules), the detection of physical linkage among SNPs that are co-associated with different aspects of the environment (which was unexpected a priori), the implementation of co-association networks and galaxy biplots to see the effect of modularity and pleiotropy on different aspects of environment. Finally, this work contains remarkable introductory Figures and Tables explaining unambiguously the main concepts [6] included in this study. This work can be treated as a starting point for many other future studies in the field.

References

[1] Hancock AM, Brachi B, Faure N, Horton MW, Jarymowycz LB, Sperone FG, Toomajian C, Roux F & Bergelson J. 2011. Adaptation to climate across the Arabidopsis thaliana genome. Science 334: 83–86. doi: 10.1126/science.1209244
[2] Wagner GP & Zhang J. The pleiotropic structure of the genotype­phenotype map: the evolvability of complex organisms. Nature Review Genetics 12: 204–213. doi: 10.1038/nrg2949
[3] Lotterhos KE, Yeaman S, Degner J, Aitken S, Hodgins K. 2018. Modularity of genes involved in local adaptation to climate despite physical linkage. bioRxiv 202481, ver. 4 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/202481
[4] Lotterhos KE & Whitlock MC. 2014. Evaluation of demographic history and neutral parameterization on the performance of FST outlier tests. Molecular Ecology 23: 2178–2192. doi: 10.1111/mec.12725
[5] Lotterhos KE & Whitlock MC. 2015. The relative power of genome scans to detect local adaptation depends on sampling design and statistical method. Molecular Ecology 24: 1031–1046. doi: 10.1111/mec.13100
[6] Paaby AB & Rockman MV. 2013. The many faces of pleiotropy. Trends in Genetics 29: 66-73. doi: 10.1016/j.tig.2012.10.010

Modularity of genes involved in local adaptation to climate despite physical linkageKatie E. Lotterhos, Sam Yeaman, Jon Degner, Sally Aitken, Kathryn Hodgins<p>Background: Physical linkage among genes shaped by different sources of selection is a fundamental aspect of genetic architecture. Theory predicts that evolution in complex environments selects for modular genetic architectures and high recombi...Adaptation, Bioinformatics & Computational Biology, Genome EvolutionSebastian Ernesto Ramos-Onsins2017-10-15 19:21:57 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
07 Nov 2017
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MaxTiC: Fast ranking of a phylogenetic tree by Maximum Time Consistency with lateral gene transfers

Dating nodes in a phylogeny using inferred horizontal gene transfers

Recommended by and based on reviews by Alexandros Stamatakis, Mukul Bansal and 2 anonymous reviewers

Dating nodes in a phylogeny is an important problem in evolution and is typically performed by using molecular clocks and fossil age estimates [1]. The manuscript by Chauve et al. [2] reports a novel method, which uses lateral gene transfers to help ordering nodes in a species tree. The idea is that a lateral gene transfer can only occur between two species living at the same time, which indirectly informs on node relative ages in a phylogeny: the donor species cannot be more recent than the recipient species. Horizontal gene transfers are increasingly recognized as frequent, even in eukaryotes, and especially in micro-organisms that have little fossil records [3-7]. Yet, such an important source of information has been very rarely used so far for inferring relative node ages in phylogenies. In this context, the method by Chauve et al. [2] represents an innovative and original approach to a difficult problem. An obvious limitation of the approach is that it relies on inferences of horizontal transfers, which detection is in itself a difficult problem. Incomplete taxon sampling, or the extinction of the true donor lineage may render patterns difficult to interpret in a temporary fashion. Yet, for clades with no fossils this may be the only piece of information we have at hand, and the growing amount of sequence data is likely to minimize issues derived from incomplete sampling.

The developed method, MaxTiC (for Maximal Time Consistency) [2], represents a very nice application of theoretical developments on the well-known « Feedback Arc Set » computer science problem to the evolutionary question of ordering nodes in a phylogeny. MaxTiC uses as input a species tree and a set of time constraints based on lateral gene transfers inferred using other softwares, and minimizes conflicts between node ordering and these time constraints. The application of MaxTiC on simulated datasets indicated that node ordering was fairly accurate [2]. MaxTiC is implemented in a freely available software, which represents original and relevant contribution to the field of evolutionary biology.

References

[1] Donoghue P and Smith M, editors. 2003. Telling the evolutionary time. CRC press.

[2] Chauve C, Rafiey A, Davin AA, Scornavacca C, Veber P, Boussau B, Szöllősi GJ, Daubin V and Tannier E. 2017. MaxTiC: Fast ranking of a phylogenetic tree by Maximum Time Consistency with lateral gene transfers. bioRxiv 127548, ver. 6 of 6th November 2017. doi: 10.1101/127548

[3] Ropars J, Rodríguez de la Vega RC, Lopez-Villavicencio M, Gouzy J, Sallet E, Debuchy R, Dupont J, Branca A and Giraud T. 2015. Adaptive horizontal gene transfers between multiple cheese-associated fungi. Current Biology 19, 2562–2569. doi: 10.1016/j.cub.2015.08.025

[4] Novo M, Bigey F, Beyne E, Galeote V, Gavory F, Mallet S, Cambon B, Legras JL, Wincker P, Casaregola S and Dequin S. 2009. Eukaryote-to-eukaryote gene transfer events revealed by the genome sequence of the wine yeast Saccharomyces cerevisiae EC1118. Proceeding of the National Academy of Science USA, 106, 16333–16338. doi: 10.1073/pnas.0904673106

[5] Naranjo-Ortíz MA, Brock M, Brunke S, Hube B, Marcet-Houben M, Gabaldón T. 2016. Widespread inter- and intra-domain horizontal gene transfer of d-amino acid metabolism enzymes in Eukaryotes. Frontiers in Microbiology 7, 2001. doi: 10.3389/fmicb.2016.02001

[6] Alexander WG, Wisecaver JH, Rokas A, Hittinger CT. 2016. Horizontally acquired genes in early-diverging pathogenic fungi enable the use of host nucleosides and nucleotides. Proceeding of the National Academy of Science USA. 113, 4116–4121. doi: 10.1073/pnas.1517242113

[7] Marcet-Houben M, Gabaldón T. 2010. Acquisition of prokaryotic genes by fungal genomes. Trends in Genetics. 26, 5–8. doi: 10.1016/j.tig.2009.11.007

MaxTiC: Fast ranking of a phylogenetic tree by Maximum Time Consistency with lateral gene transfersCédric Chauve, Akbar Rafiey, Adrian A. Davin, Celine Scornavacca, Philippe Veber, Bastien Boussau, Gergely J Szöllosi, Vincent Daubin, and Eric TannierLateral gene transfers (LGTs) between ancient species contain information about the relative timing of species diversification. Specifically, the ancestors of a donor species must have existed before the descendants of the recipient species. Hence...Bioinformatics & Computational Biology, Evolutionary Dynamics, Genome Evolution, Life History, Molecular Evolution, Phylogenetics / PhylogenomicsTatiana Giraud2017-06-28 13:40:52 View
06 Sep 2022
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Masculinization of the X-chromosome in aphid soma and gonads

Sex-biased gene expression is not tissue-specific in Pea Aphids

Recommended by and based on reviews by Ann Kathrin Huylmans and 1 anonymous reviewer

Sexual antagonism (SA), wherein the fitness interests of the sexes do not align, is inherent to organisms with two (or more) sexes.  SA leads to intra-locus sexual conflict, where an allele that confers higher fitness in one sex reduces fitness in the other [1, 2].  This situation leads to what has been referred to as "gender load", resulting from the segregation of SA alleles in the population.  Gender load can be reduced by the evolution of sex-specific (or sex-biased) gene expression.  A specific prediction is that gene-duplication can lead to sub- or neo-functionalization, in which case the two duplicates partition the function in the different sexes.  The conditions for invasion by a SA allele differ between sex-chromosomes and autosomes, leading to the prediction that (in XY or XO systems) the X should accumulate recessive male-favored alleles and dominant female-favored alleles; similar considerations apply in ZW systems ([3, but see 4].

Aphids present an interesting special case, for several reasons: they have XO sex-determination, and three distinct reproductive morphs (sexual females, parthenogenetic females, and males).  Previous theoretical work by the lead author predict that the X should be optimized for male function, which was borne out by whole-animal transcriptome analysis [5].  

Here [6], the authors extend that work to investigate “tissue”-specific (heads, legs and gonads), sex-specific gene expression.  They argue that, if intra-locus SA is the primary driver of sex-biased gene expression, it should be generally true in all tissues.  They set up as an alternative the possibility that sex-biased gene expression could also be driven by dosage compensation.  They cite references supporting their argument that "dosage compensation (could be) stronger in the brain", although the underlying motivation for that argument appears to be based on empirical evidence rather than theoretical predictions.      

At any rate, the results are clear: all tissues investigated show masculinization of the X.  Further, X-linked copies of gene duplicates were more frequently male-biased than duplicated autosomal genes or X-linked single-copy genes.

To sum up, this is a nice empirical study with clearly interpretable (and interpreted) results, the most obvious of which is the greater sex-biased expression in sexually-dimorphic tissues.  Unfortunately, as the authors emphasize, there is no general theory by which SA, variable dosage-compensation, and meiotic sex chromosome inactivation can be integrated in a predictive framework.  It is to be hoped that empirical studies such as this one will motivate deeper and more general theoretical investigations.

References

[1] Rice WR, Chippindale AK (2001) Intersexual ontogenetic conflict. Journal of Evolutionary Biology 14: 685-693. https://doi.org/10.1046/j.1420-9101.2001.00319.x

[2] Bonduriansky R, Chenoweth SF (2009) Intralocus sexual conflict. Trends Ecol Evol 24: 280-288. https://doi.org/10.1016/j.tree.2008.12.005

[3] Rice WR. (1984) Sex chromosomes and the evolution of sexual dimorphism. Evolution 38: 735-742. https://doi.org/10.1086/595754

[4] Fry JD (2010) The genomic location of sexually antagonistic variation: some cautionary comments. Evolution 64: 1510-1516. https://doi.org/10.1111%2Fj.1558-5646.2009.00898.x

[5] Jaquiéry J, Rispe C, Roze D, Legeai F, Le Trionnaire G, Stoeckel S, et al. (2013) Masculinization of the X Chromosome in the Pea Aphid. PLoS Genetics 9. https://doi.org/10.1371/journal.pgen.1003690

[6] Jaquiéry J, Simon J-C, Robin S, Richard G, Peccoud J, Boulain H, Legeai F, Tanguy S, Prunier-Leterme N, Le Trionnaire G (2022) Masculinization of the X-chromosome in aphid soma and gonads. bioRxiv, 2021.08.13.453080, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.08.13.453080 

Masculinization of the X-chromosome in aphid soma and gonadsJulie Jaquiery, Jean-Christophe Simon, Stephanie Robin, Gautier Richard, Jean Peccoud, Helene Boulain, Fabrice Legeai, Sylvie Tanguy, Nathalie Prunier-Leterme, Gael Letrionnaire<p>Males and females share essentially the same genome but differ in their optimal values for many phenotypic traits, which can result in intra-locus conflict between the sexes. Aphids display XX/X0 sex chromosomes and combine unusual X chromosome...Genetic conflicts, Genome Evolution, Reproduction and SexCharles Baer2021-08-16 08:56:08 View
12 Nov 2020
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Limits and Convergence properties of the Sequentially Markovian Coalescent

Review and Assessment of Performance of Genomic Inference Methods based on the Sequentially Markovian Coalescent

Recommended by ORCID_LOGO based on reviews by 3 anonymous reviewers

The human genome not only encodes for biological functions and for what makes us human, it also encodes the population history of our ancestors. Changes in past population sizes, for example, affect the distribution of times to the most recent common ancestor (tMRCA) of genomic segments, which in turn can be inferred by sophisticated modelling along the genome.
A key framework for such modelling of local tMRCA tracts along genomes is the Sequentially Markovian Coalescent (SMC) (McVean and Cardin 2005, Marjoram and Wall 2006) . The problem that the SMC solves is that the mosaic of local tMRCAs along the genome is unknown, both in their actual ages and in their positions along the genome. The SMC allows to effectively sum across all possibilities and handle the uncertainty probabilistically. Several important tools for inferring the demographic history of a population have been developed built on top of the SMC, including PSMC (Li and Durbin 2011), diCal (Sheehan et al 2013), MSMC (Schiffels and Durbin 2014), SMC++ (Terhorst et al 2017), eSMC (Sellinger et al. 2020) and others.
In this paper, Sellinger, Abu Awad and Tellier (2020) review these SMC-based methods and provide a coherent simulation design to comparatively assess their strengths and weaknesses in a variety of demographic scenarios (Sellinger, Abu Awad and Tellier 2020). In addition, they used these simulations to test how breaking various key assumptions in SMC methods affects estimates, such as constant recombination rates, or absence of false positive SNP calls.
As a result of this assessment, the authors not only provide practical guidance for researchers who want to use these methods, but also insights into how these methods work. For example, the paper carefully separates sources of error in these methods by observing what they call “Best-case convergence” of each method if the data behaves perfectly and separating that from how the method applies with actual data. This approach provides a deeper insight into the methods than what we could learn from application to genomic data alone.
In the age of genomics, computational tools and their development are key for researchers in this field. All the more important is it to provide the community with overviews, reviews and independent assessments of such tools. This is particularly important as sometimes the development of new methods lacks primary visibility due to relevant testing material being pushed to Supplementary Sections in papers due to space constraints. As SMC-based methods have become so widely used tools in genomics, I think the detailed assessment by Sellinger et al. (2020) is timely and relevant.
In conclusion, I recommend this paper because it bridges from a mere review of the different methods to an in-depth assessment of performance, thereby addressing both beginners in the field who just seek an initial overview, as well as experienced researchers who are interested in theoretical boundaries and assumptions of the different methods.

References

[1] Li, H., and Durbin, R. (2011). Inference of human population history from individual whole-genome sequences. Nature, 475(7357), 493-496. doi: https://doi.org/10.1038/nature10231
[2] Marjoram, P., and Wall, J. D. (2006). Fast"" coalescent"" simulation. BMC genetics, 7(1), 16. doi: https://doi.org/10.1186/1471-2156-7-16
[3] McVean, G. A., and Cardin, N. J. (2005). Approximating the coalescent with recombination. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1459), 1387-1393. doi: https://doi.org/10.1098/rstb.2005.1673
[4] Schiffels, S., and Durbin, R. (2014). Inferring human population size and separation history from multiple genome sequences. Nature genetics, 46(8), 919-925. doi: https://doi.org/10.1038/ng.3015
[5] Sellinger, T. P. P., Awad, D. A., Moest, M., and Tellier, A. (2020). Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLoS Genetics, 16(4), e1008698. doi: https://doi.org/10.1371/journal.pgen.1008698
[6] Sellinger, T. P. P., Awad, D. A. and Tellier, A. (2020) Limits and Convergence properties of the Sequentially Markovian Coalescent. bioRxiv, 2020.07.23.217091, ver. 3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: https://doi.org/10.1101/2020.07.23.217091
[7] Sheehan, S., Harris, K., and Song, Y. S. (2013). Estimating variable effective population sizes from multiple genomes: a sequentially Markov conditional sampling distribution approach. Genetics, 194(3), 647-662. doi: https://doi.org/10.1534/genetics.112.149096
[8] Terhorst, J., Kamm, J. A., and Song, Y. S. (2017). Robust and scalable inference of population history from hundreds of unphased whole genomes. Nature genetics, 49(2), 303-309. doi: https://doi.org/10.1038/ng.3748

Limits and Convergence properties of the Sequentially Markovian CoalescentThibaut Sellinger, Diala Abu Awad, Aurélien Tellier<p>Many methods based on the Sequentially Markovian Coalescent (SMC) have been and are being developed. These methods make use of genome sequence data to uncover population demographic history. More recently, new methods have extended the original...Population Genetics / GenomicsStephan SchiffelsAnonymous2020-07-25 10:54:48 View
15 Dec 2016
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Limiting opportunities for cheating stabilizes virulence in insect parasitic nematodes

Application of kin theory to long-standing problem in nematode production for biocontrol

Recommended by and

Much research effort has been extended toward developing systems for managing soil inhabiting insect pests of crops with entomopathogenic nematodes as biocontrol agents. Although small plot or laboratory experiments may suggest a particular insect pest is vulnerable to management in this way, it is often difficult to scale-up nematode production for application at the field- and farm scale to make such a tactic viable. Part of the problem is that entomopathogenic nematode strains must be propagated by serial passage in vivo, because storage by freezing decreases fitness. At the same time, serial propagation results in loss of virulence (ability to infect) over generations in the laboratory, a phenomenon called attenuation.

To probe the underlying reasons for development of attenuation, as a prerequisite to designing strategies to mitigate it, Shapiro-Ilan and Raymond [1] turned to evolutionary theory of social conflict as a possible explanatory framework. Virulence of entomopathogenic nematodes depends on a combination of virulence factors, like various proteases, secreted by both the nematode and symbiotic bacteria to overcome host defenses. Attenuation is characterized in part by a reduced production of these factors. Invasion of a host involves simultaneous attack by a group of nematodes ("cooperators"), which together neutralize host defenses enough to allow individuals to successfully invade. "Cheaters" in the invading population can avoid the metabolic costs of producing virulence factors while reaping the benefits of infecting the host made vulnerable by the cooperators in the population. The authors hypothesize that an increase in frequency of cheaters may contribute to attenuation of virulence during serial propagation in the laboratory. The evolutionary dynamics of cheater frequency in a population have been explored in many contexts as part of kin selection theory. Cheaters can increase in a population by outcompeting cooperators in a host if overall relatedness within the invading population is low. Conversely, frequency of altruism, or costly cooperation, increases in a population if relatedness is high, which is enhanced by low effective dispersal. However, a population that is too isolated can suffer from inbreeding effects, and competition will occur mainly among relatives, which decreases the fitness benefits of altruism.

Shapiro-Ilan and Raymond [1] tested changes in virulence and reproductive output in a serially propagated entomopathogenic nematode, Heterorhabditis floridensis. They compared lines of high or low relatedness, manipulated via multiplicity of infection (MOI) rates (where a low dose of nematodes gives high relatedness and a high dose gives low relatedness); and under global or local competition, manipulated by pooling populations emerging from all or only two host cadavers per generation, respectively. As predicted, treatments of high relatedness (low MOI) and global competition had the greatest level of reproduction, while all lines of low relatedness (high MOI) evolved decreased reproduction and decreased virulence, which led to extinction. The key finding was that lines in the high relatedness (low MOI) and low (local) competition treatment exhibited the most stable virulence through the 12 generations tested. Thus, to minimize attenuation of virulence while maintaining fitness of recently isolated entomopathogenic nematodes, the authors recommend insect hosts be inoculated with low doses of nematodes from inocula pools from as few cadavers as possible.

The application of evolutionary theory, with a clever experimental design, to an important problem in pest management makes this paper particularly noteworthy.

Reference

[1] Shapiro-Ilan D, Raymond B. 2016. Limiting opportunities for cheating stabilizes virulence in insect parasitic nematodes. Evolutionary Applications 9:462-470. doi: 10.1111/eva.12348

Limiting opportunities for cheating stabilizes virulence in insect parasitic nematodesShapiro-Ilan D. and B. RaymondCooperative secretion of virulence factors by pathogens can lead to social conflict when cheating mutants exploit collective secretion, but do not contribute to it. If cheats outcompete cooperators within hosts, this can cause loss of virulence....Adaptation, Behavior & Social Evolution, Evolutionary Applications, Evolutionary Dynamics, Evolutionary Ecology, Evolutionary Epidemiology, Evolutionary Theory, Experimental Evolution, Population Genetics / Genomics, Reproduction and SexThomas Sappington2016-12-15 18:33:39 View