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16 Dec 2016
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Spatiotemporal microbial evolution on antibiotic landscapes

A poster child for experimental evolution

Recommended by and

Evolution is usually studied via two distinct approaches: by inferring evolutionary processes from relatedness patterns among living species or by observing evolution in action in the laboratory or field. A recent study by Baym and colleagues in Science [1] has now combined these approaches by taking advantage of the pattern left behind by spatially evolving bacterial populations.

Evolution is often considered too slow to see, and can only be inferred by studying patterns of relatedness using phylogenetic trees. Increasingly, however, researchers are moving nature into the lab and watching as evolution unfolds under their noses. The field of experimental evolution follows evolutionary change in the laboratory over 10s to 1000s of generations, yielding insights into bacterial, viral, plant, or fly evolution (among many other species) that are simply not possible in the field. Yet, as powerful as experimental evolution is, it lacks a posterchild. There is no Galapagos finch radiation, nor a stunning series of cichlids to showcase to our students to pique their interests. Let’s face it, E. coli is no stickleback! And while practitioners of experimental evolution can explain the virtues of examining 60,000 generations of bacterial evolution in action, appreciating this nevertheless requires a level of insight and imagination that often eludes students, who need to see “it” to get it.

Enter MEGA, an idea and a film that could become the new face of experimental evolution. It replaces big numbers of generations or images of scientists, with an actual picture of the scientific result. MEGA, or Microbial Evolution and Growth Arena, is essentially an enormous petri dish and is the brainchild of Michael Baym, Tami Leiberman and their colleagues in Roy Kishony’s lab at Technion Israel Institute of Technology and Harvard Medical School. The idea of MEGA is to allow bacteria to swim over a spatially defined landscape while adapting to the local conditions, in this case antibiotics. When bacteria are inoculated onto one end of the plate they consume resources while swarming forward from the plate edge. In a few days, the bacteria grow into an area with antibiotics to which they are susceptible. This stops growth until a mutation arises that permits the bacteria to jump this hurdle, after which growth proceeds until the next hurdle of a 10-fold higher antibiotic concentration, and so on. By this simple approach, Baym et al. [1] evolved E. coli that were nearly 105-fold more resistant to two different antibiotics in just over 10 days. In addition, they identified the mutations that were required for these changes, showed that mutations conferring smaller benefits were required before bacteria could evolve maximal resistance, observed changes to the mutation rate, and demonstrated the importance of spatial structure in constraining adaptation.

For one thing, the rate of resistance evolution is impressive, and also quite scary given the mounting threat of antibiotic-resistant pathogens. However, MEGA also offers a uniquely visual insight into evolutionary change. By taking successive images of the MEGA plate, the group was able to watch the bacteria move, get trapped because of their susceptibility to the antibiotic, and then get past these traps as new mutations emerged that increased resistance. Each transition showcases evolution in real time. In addition, by leaving a spatial pattern of evolutionary steps behind, the MEGA plate offers unique opportunities to thoroughly investigate these steps when the experiment is finished. For instance, subsequent steps in mutational pathways can be characterized, but also their effects on fitness can be quantified in situ by measuring changes in survival and reproduction. This new method is undoubtedly a boon to the field of experimental evolution and offers endless opportunities for experimental elaboration. Perhaps of equal importance, MEGA is a tool that is portable to the classroom and to the public at large. Don’t believe in evolution? Watch this. You only have time for a short internship or lab practical? No problem. Don’t worry much about antibiotic resistance? Check this out. Like the best experimental tools, MEGA is simple but allows for complicated insights. And even if it is less charismatic than a finch, it still allows for the kinds of “gee-whiz” insights that will get students hooked on evolutionary biology.

Reference

[1] Baym M, Lieberman TD, Kelsic ED, Chait R, Gross R, Yelin I, Kishony R. 2016. Spatiotemporal microbial evolution on antibiotic landscapes. Science 353:1147-1151. doi: 10.1126/science.aag0822

Spatiotemporal microbial evolution on antibiotic landscapesBaym M, Lieberman TD, Kelsic ED, Chait R, Gross R, Yelin I, Kishony RA key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device,...Adaptation, Evolutionary Applications, Experimental EvolutionDaniel Rozen2016-12-14 14:26:06 View
28 Feb 2023
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Primate sympatry shapes the evolution of their brain architecture

Macroevolutionary drivers of brain evolution in primates

Recommended by based on reviews by Paula Gonzalez, Orlin Todorov and 3 anonymous reviewers

Studying the evolution of animal cognition is challenging because many environmental and species-related factors can be intertwined, which is further complicated when looking at deep-time evolution. Previous knowledge has emphasized the role of intraspecific interactions in affecting the socio-ecological environment shaping cognition. However, much less is known about such an effect at the interspecific level. Yet, the coexistence of different species in the same geographic area at a given time (sympatry) can impact the evolutionary history of species through character displacement due to biotic interactions. Trait evolution has been observed and tested with morphological external traits but more rarely with brain evolution. Compared to most species’ traits, brain evolution is even more delicate to assess since specific brain regions can be involved in different functions, may they be individual-based and social-based information processing. 

In a very original and thoroughly executed study, Robira & Perez-Lamarque (2023) addressed the question: How does the co-occurrence of congeneric species shape brain evolution and influence species diversification? By considering brain size as a proxy for cognition, they evaluated whether species sympatry impacted the evolution of cognition in frugivorous primates. Fruit resources are hard to find, not continuous through time, heterogeneously distributed across space, but can be predictable. Hence, cognition considerably shapes the foraging strategy and competition for food access can be fierce. Over long timescales, it remains unclear whether brain size and the pace of species diversification are linked in the context of sympatry, and if so how. Recent studies have found that larger brain sizes can be associated with higher diversification rates in birds (Sayol et al. 2019). Similarly, Robira & Perez-Lamarque (2023) thus wondered if the evolution of brain size in primates impacted their dynamic of species diversification, which has been suggested (Melchionna et al. 2020) but not tested.

Prior to anything, Robira & Perez-Lamarque (2023) had to retrace the evolutionary history of sympatry between frugivorous primate lineages through time using the primate tree of life, species’ extant distribution, and process-based models to estimate ancestral range evolution. To infer the effect of species sympatry on the evolution of cognition in frugivorous primates, the authors evaluated the support for phylogenetic models of brain size evolution accounting or not for species sympatry and investigated the directionality of the selection induced by sympatry on brain size evolution. Finally, to better understand the impact of cognition and interactions between primates on their evolutionary success, they tested for correlations between brain size or species’ sympatry and species diversification.

Robira & Perez-Lamarque (2023) found that the evolution of the whole brain or brain regions used in immediate information processing was best fitted with models not considering sympatry. By contrast, models considering species sympatry best predicted the evolution of brain regions related to long-term memory of interactions with the socio-ecological environment, with a decrease in their size along with stronger sympatry. Specifically, they found that sympatry was associated with a decrease in the relative size of the hippocampus and striatum, but had no significant effect on the neocortex, cerebellum, or overall brain size.

The hippocampus is a brain region that plays a crucial role in processing and memorizing spatiotemporal information, which is relevant for frugivorous primates in their foraging behavior. The study suggests that competition between sympatric species for limited food resources may lead to a more complex and unpredictable food distribution, which may in turn render cognitive foraging not advantageous and result in a selection for smaller brain regions involved in foraging. Niche partitioning and dietary specialization in sympatry may also impact cognitive abilities, with more specialized diets requiring lower cognitive abilities and smaller brain region sizes.

On the other hand, the absence of an effect of sympatry on brain regions involved in immediate sensory information processing, such as the cerebellum and neocortex, suggests that foragers do not exploit cues left out by sympatric heterospecific species, or they may discard environmental cues in favor of social cues.

This is a remarkable study that highlights the importance of considering the impact of ecological factors, such as sympatry, on the evolution of specific brain regions involved in cognitive processes, and the potential trade-offs in brain region size due to niche partitioning and dietary specialization in sympatry. Further research is needed to explore the mechanisms behind these effects and to test for the possible role of social cues in the evolution of brain regions. This study provides insights into the selective pressures that shape brain evolution in primates.

References

Melchionna M, Mondanaro A, Serio C, Castiglione S, Di Febbraro M, Rook L, Diniz-Filho JAF, Manzi G, Profico A, Sansalone G, Raia P (2020) Macroevolutionary trends of brain mass in Primates. Biological Journal of the Linnean Society, 129, 14–25. https://doi.org/10.1093/biolinnean/blz161

Robira B, Perez-Lamarque B (2023) Primate sympatry shapes the evolution of their brain architecture. bioRxiv, 2022.05.09.490912, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.05.09.490912

Sayol F, Lapiedra O, Ducatez S, Sol D (2019) Larger brains spur species diversification in birds. Evolution, 73, 2085–2093. https://doi.org/10.1111/evo.13811

Primate sympatry shapes the evolution of their brain architectureBenjamin Robira, Benoit Perez-Lamarque<p style="text-align: justify;">The main hypotheses on the evolution of animal cognition emphasise the role of conspecifics in affecting the socio-ecological environment shaping cognition. Yet, space is often simultaneously occupied by multiple sp...Behavior & Social Evolution, Bioinformatics & Computational Biology, Evolutionary Ecology, Macroevolution, Phylogenetics / Phylogenomics, Phylogeography & BiogeographyFabien Condamine2022-05-10 13:43:02 View
05 Oct 2022
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Do closely related species interact with similar partners? Testing for phylogenetic signal in bipartite interaction networks

Testing for phylogenetic signal in species interaction networks

Recommended by based on reviews by Joaquin Calatayud and Thomas Guillerme

Species are immersed within communities in which they interact mutualistically, as in pollination or seed dispersal, or nonreciprocally, such as in predation or parasitism, with other species and these interactions play a paramount role in shaping biodiversity (Bascompte and Jordano 2013). Researchers have become increasingly interested in the processes that shape these interactions and how these influence community structure and responses to disturbances. Species interactions are often described using bipartite interaction networks and one important question is how the evolutionary history of the species involved influences the network, including whether there is phylogenetic signal in interactions, in other words whether closely related species interact with other closely related species (Bascompte and Jordano 2013, Perez-Lamarque et al. 2022). To address this question different approaches, correlative and model-based, have been developed to test for phylogenetic signal in interactions, although comparative analyses of the performance of these different metrics are lacking. In their article Perez-Lamarque et al. (2022) set out to test the statistical performance of two widely-used methods, Mantel tests and Phylogenetic Bipartite Linear Models (PBLM; Ives and Godfray 2006) using simulations. Phylogenetic signal is measured as the degree to which distance to the nearest common ancestor predicts the observed similarity in trait values among species. In species interaction networks, the data are actually the between-species dissimilarity among interacting species (Perez-Lamarque et al. 2022), and typical approaches to test for phylogenetic signal cannot be used. However, the Mantel test provides a useful means of analyzing the correlation between two distance matrices, the between-species phylogenetic distance and the between-species dissimilarity in interactions. The PBLM approach, on the other hand, assumes that interactions between species are influenced by unobserved traits that evolve along the phylogenies following a given phenotypic evolution model and the parameters of this model are interpreted in terms of phylogenetic signal (Ives and Godfray 2006). Perez-Lamarque et al (2022) found that the model-based PBLM approach has a high type-I error rate, in other words it often detected phylogenetic signal when there was none. The simple Mantel test was found to present a low type-I error rate and moderate statistical power. However, it tended to overestimate the degree to which species interact with dissimilar partners. In addition to the aforementioned analyses, the authors also tested whether the simple Mantel test was able to detect phylogenetic signal in interactions among species within a given clade in the phylogeny, as phylogenetic signal in species interactions may be localized within specific clades. The article concludes with general guidelines for users wishing to test phylogenetic signal in their interaction networks and illustrates them with an example of an orchid-mycorrhizal fungus network from the oceanic island of La Réunion (Martos et al 2012). This broadly accessible article provides a valuable analysis of the performance of tests of phylogenetic signal in interaction networks enabling users to make informed choices of the analytical methods they wish to employ, and provide useful and detailed guidelines. Therefore, the work should be of broad interest to researchers studying species interactions.  

References

Bascompte J, Jordano P (2013) Mutualistic Networks. Princeton University Press. https://doi.org/10.1515/9781400848720

Ives AR, Godfray HCJ (2006) Phylogenetic Analysis of Trophic Associations. The American Naturalist, 168, E1–E14. https://doi.org/10.1086/505157

Martos F, Munoz F, Pailler T, Kottke I, Gonneau C, Selosse M-A (2012) The role of epiphytism in architecture and evolutionary constraint within mycorrhizal networks of tropical orchids. Molecular Ecology, 21, 5098–5109. https://doi.org/10.1111/j.1365-294X.2012.05692.x

Perez-Lamarque B, Maliet O, Pichon B, Selosse M-A, Martos F, Morlon H (2022) Do closely related species interact with similar partners? Testing for phylogenetic signal in bipartite interaction networks. bioRxiv, 2021.08.30.458192, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.08.30.458192

Do closely related species interact with similar partners? Testing for phylogenetic signal in bipartite interaction networks Benoît Perez-Lamarque, Odile Maliet, Benoît Pichon, Marc-André Selosse, Florent Martos, Hélène Morlon<p style="text-align: justify;">Whether interactions between species are conserved on evolutionary time-scales has spurred the development of both correlative and process-based approaches for testing phylogenetic signal in interspecific interactio...Evolutionary Ecology, Species interactionsAlejandro Gonzalez Voyer2022-03-10 13:48:15 View
20 Dec 2022
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How does the mode of evolutionary divergence affect reproductive isolation?

A general model of fitness effects following hybridisation

Recommended by based on reviews by Luis-Miguel Chevin and Juan Li

Studying the effects of speciation, hybridisation, and evolutionary outcomes following reproduction from divergent populations is a major research area in evolutionary genetics [1]. There are two phenomena that have been the focus of contemporary research. First, a classic concept is the formation of ‘Bateson-Dobzhansky-Muller’ incompatibilities (BDMi) [2–4] that negatively affect hybrid fitness. Here, two diverging populations accumulate mutations over time that are unique to that subpopulation. If they subsequently meet, then these mutations might negatively interact, leading to a loss in fitness or even a complete lack of reproduction. BDMi formation can be complex, involving multiple genes and the fitness changes can depend on the direction of introgression [5]. Second, such secondary contact can instead lead to heterosis, where offspring are fitter than their parental progenitors [6].

Understanding which outcomes are likely to arise require one to know the potential fitness effects of mutations underlying reproductive isolation, to determine whether they are likely to reduce or enhance fitness when hybrids are formed. This is far from an easy task, as it requires one to track mutations at several loci, along with their effects, across a fitness landscape.

The work of De Sanctis et al. [7] neatly fills in this knowledge gap, by creating a general mathematical framework for describing the consequences of a cross from two divergent populations. The derivations are based on Fisher’s Geometric Model, which is widely used to quantify selection acting on a general fitness landscape that is affected by several biological traits [8,9], and has previously been used in theoretical studies of hybridisation [10–12]. By doing so, they are able to decompose how divergence at multiple loci affects offspring fitness through both additive and dominance effects.

A key result arising from their analyses is demonstrating how offspring fitness can be captured by two main functions. The first one is the ‘net effect of evolutionary change’ that, broadly defined, measures how phenotypically divergent two populations are. The second is the ‘total amount of evolutionary change’, which reflects how many mutations contribute to divergence and the effect sizes captured by each of them. The authors illustrate these measurements using simulations covering different scenarios, demonstrating how different parental states can lead to similar fitness outcomes. They also propose experimental methods to measure the underlying mutational effects.

This study neatly demonstrates how complex genetic phenomena underlying hybridisation can be captured using fairly simple mathematical formulae. This powerful approach will thus open the door for future research to investigate hybridisation in more detail, whether it is by expanding on these theoretical models or using the elegant outcomes to quantify fitness effects in experiments.

 

References

1. Coyne JA, Orr HA. Speciation. Sunderland, Mass: Sinauer Associates; 2004.
2. Bateson W, Seward A. Darwin and modern science. Heredity and variation in modern lights. 1909;85: 101. https://doi.org/10.1017/CBO9780511693953.007
3. Dobzhansky T. Genetics and the Origin of Species. Columbia university press; 1937.
4. Muller HJ. Isolating mechanisms, evolution and temperature. Biol Symp. 1942;6: 71-125.
5. Fraïsse C, Elderfield JAD, Welch JJ. The genetics of speciation: are complex incompatibilities easier to evolve? J Evol Biol. 2014;27: 688-699. https://doi.org/10.1111/jeb.12339
6. Birchler JA, Yao H, Chudalayandi S, Vaiman D, Veitia RA. Heterosis. The Plant Cell. 2010;22: 2105-2112. https://doi.org/10.1105/tpc.110.076133
7. De Sanctis B, Schneemann H, Welch JJ. How does the mode of evolutionary divergence affect reproductive isolation? bioRxiv. 2022. 2022.03.08.483443 version 4. https://doi.org/10.1101/2022.03.08.483443 
8. Fisher RA. The genetical theory of natural selection. Oxford: The Clarendon Press; 1930. https://doi.org/10.5962/bhl.title.27468 
9. Tenaillon O. The Utility of Fisher's Geometric Model in Evolutionary Genetics. Annu Rev Ecol Evol Syst. 2014;45: 179-201. https://doi.org/10.1146/annurev-ecolsys-120213-091846
10. Barton NH. The role of hybridization in evolution. Molecular Ecology. 2001;10: 551-568. https://doi.org/10.1046/j.1365-294x.2001.01216.x 
11. Chevin L-M, Decorzent G, Lenormand T. Niche Dimensionality and The Genetics of Ecological Speciation. Evolution. 2014;68: 1244-1256. https://doi.org/10.1111/evo.12346 
12. Fraïsse C, Gunnarsson PA, Roze D, Bierne N, Welch JJ. The genetics of speciation: Insights from Fisher's geometric model. Evolution. 2016;70: 1450-1464. https://doi.org/10.1111/evo.12968

How does the mode of evolutionary divergence affect reproductive isolation?Bianca De Sanctis, Hilde Schneemann, John J. Welch<p>When divergent populations interbreed, the outcome will be affected by the genomic and phenotypic differences that they have accumulated. In this way, the mode of evolutionary divergence between populations may have predictable consequences for...Adaptation, Evolutionary Theory, Hybridization / Introgression, Population Genetics / Genomics, SpeciationMatthew Hartfield2022-03-30 14:55:46 View
16 Nov 2022
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Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice

Tinder in mice: A match made with the sense of smell

Recommended by ORCID_LOGO based on reviews by Angeles de Cara, Ludovic Claude Maisonneuve and 1 anonymous reviewer

Differentiation-based genome scans lie at the core of speciation and adaptation genomics research. Dating back to Lewontin & Krakauer (1973), they have become very popular with the advent of genomics to identify genome regions of enhanced differentiation relative to neutral expectations. These regions may represent genetic barriers between divergent lineages and are key for studying reproductive isolation. However, genome scan methods can generate a high rate of false positives, primarily if the neutral population structure is not accounted for (Bierne et al. 2013). Moreover, interpreting genome scans can be challenging in the context of secondary contacts between diverging lineages (Bierne et al. 2011), because the coupling between different components of reproductive isolation (local adaptation, intrinsic incompatibilities, mating preferences, etc.) can occur readily, thus preventing the causes of differentiation from being determined.

Smadja and collaborators (2022) applied a sophisticated genome scan for trait association (BAYPASS, Gautier 2015) to underlie the genetic basis of a polygenetic behaviour: assortative mating in hybridizing mice. My interest in this neat study mainly relies on two reasons. First, the authors used an ingenious geographical setting (replicate pairs of “Choosy” versus “Non-Choosy” populations) with multi-way comparisons to narrow down the list of candidate regions resulting from BAYPASS. The latter corrects for population structure, handles cost-effective pool-seq data and allows for gene-based analyses that aggregate SNP signals within a gene. These features reinforce the set of outlier genes detected; however, not all are expected to be associated with mating preference. 

The second reason why this study is valuable to me is that Smadja et al. (2022) complemented the population genomic approach with functional predictions to validate the genetic signal. In line with previous behavioural and chemical assays on the proximal mechanisms of mating preferences, they identified multiple olfactory and vomeronasal receptor genes as highly significant candidates. Therefore, combining genomic signals with functional analyses is a clever way to provide insights into the causes of reproductive isolation, especially when multiple barriers are involved. This is typically true for reinforcement (Butlin & Smadja 2018), suspected to occur in these mice because, in that case, assortative mating (a prezygotic barrier) evolves in response to the cost of hybridization (for example, due to hybrid inviability). 

As advocated by the authors, their study paves the way for future work addressing the genetic basis of reinforcement, a trait of major evolutionary importance for which we lack empirical data. They also make a compelling case using complementary approaches that olfactory and vomeronasal receptors have a central role in mammal speciation.


References:

Bierne N, Welch J, Loire E, Bonhomme F, David P (2011) The coupling hypothesis: why genome scans may fail to map local adaptation genes. Mol Ecol 20: 2044–2072. https://doi.org/10.1111/j.1365-294X.2011.05080.x

Bierne N, Roze D, Welch JJ (2013) Pervasive selection or is it…? why are FST outliers sometimes so frequent? Mol Ecol 22: 2061–2064. https://doi.org/10.1111/mec.12241 

Butlin RK, Smadja CM (2018) Coupling, Reinforcement, and Speciation. Am Nat 191:155–172. https://doi.org/10.1086/695136 

Gautier M (2015) Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates. Genetics 201:1555–1579. https://doi.org/10.1534/genetics.115.181453 

Lewontin RC, Krakauer J (1973) Distribution of gene frequency as a test of the theory of selective neutrality of polymorphisms. Genetics 74: 175–195. https://doi.org/10.1093/genetics/74.1.175 

Smadja CM, Loire E, Caminade P, Severac D, Gautier M, Ganem G (2022) Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice. bioRxiv, 2022.07.21.500634, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.07.21.500634

Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in miceCarole M. Smadja, Etienne Loire, Pierre Caminade, Dany Severac, Mathieu Gautier, Guila Ganem<p>Deciphering the genetic bases of behavioural traits is essential to understanding how they evolve and contribute to adaptation and biological diversification, but it remains a substantial challenge, especially for behavioural traits with polyge...Adaptation, Behavior & Social Evolution, Genotype-Phenotype, SpeciationChristelle Fraïsse2022-07-25 11:54:52 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
14 Dec 2023
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Genetic sex determination in three closely related hydrothermal vent gastropods, including one species with intersex individuals

A shared XY sex chromosome system with variable recombination rates

Recommended by based on reviews by Hugo Darras, Daniel Jeffries and 1 anonymous reviewer

Many species with separate sexes have evolved sex chromosomes, with the sex-limited chromosomes (i.e. the Y or W chromosomes) exhibiting a wide range of genetic divergences from their homologous X or Z chromosomes (Bachtrog et al., 2014). Variable divergences can result from the cessation of recombination between sex chromosomes that occurred at different time points, with the mechanisms of initiation and expansion of recombination suppression along sex chromosomes remaining poorly understood (Charlesworth, 2017). 

The study by Castel et al (2023) describes the serendipitous discovery of a shared XY sex chromosome system in three closely related hydrothermal vent gastropods. The X and Y chromosomes appear to still recombine but at variable rates across the three species. This variation makes the gastropod system a very promising focus for future research on sex chromosome evolution. 

An additional intriguing finding is that some females in one of three gastropod species contain male reproductive tissue in their gonads, providing a fascinating case of a mixed or transitory sexual system. Overall, the study by Castel et al (2023) offers the first insights into the reproduction and sex chromosome system of animals living in deep marine vents, which have remained poorly studied and open outstanding research perspectives on these creatures.

References

Bachtrog, D., J.E.Mank, C.L.Peichel, M.Kirkpatrick, S.P.Otto, T.L. Ashman, M.W.Hahn, J.Kitano, I.Mayrose, R.Ming, et al. 2014.Sex determination: why so many ways of doing it? PLoSBiol. 12:e1001899. https://doi.org/10.1371/journal.pbio.1001899

Charlesworth, D. Young sex chromosomes in plants and animals. 2019. New Phytologist 224: 1095–1107. https://doi.org/10.1111/nph.16002

Castel J, Pradillon F, Cueff V, Leger G, Daguin-Thiébaut C, Ruault S, Mary J, Hourdez S, Jollivet D, and Broquet T 2023. Genetic sex determination in three closely related hydrothermal vent gastropods, including one species with intersex individuals. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2023.04.11.536409

Genetic sex determination in three closely related hydrothermal vent gastropods, including one species with intersex individualsCastel J, Pradillon F, Cueff V, Leger G, Daguin-Thiébaut C, Ruault S, Mary J, Hourdez S, Jollivet D, and Broquet T<p style="text-align: justify;">Molluscs have a wide variety of sexual systems and have undergone many transitions from separate sexes to hermaphroditism or vice versa, which is of interest for studying the evolution of sex determination and diffe...Population Genetics / Genomics, Reproduction and SexTanja Schwander2023-04-14 11:48:25 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 Mar 2023
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Extrinsic mortality and senescence: a guide for the perplexed

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

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

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

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

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

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

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

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

REFERENCES

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

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

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

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

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

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

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

Extrinsic mortality and senescence: a guide for the perplexedCharlotte de Vries, Matthias Galipaud, Hanna Kokko<p style="text-align: justify;">Do environments or species traits that lower the mortality of individuals create selection for delaying senescence? Reading the literature creates an impression that mathematically oriented biologists cannot agree o...Evolutionary Dynamics, Evolutionary Ecology, Evolutionary Theory, Life HistorySinead English2022-08-26 14:30:16 View
11 Apr 2023
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Facultative parthenogenesis: a transient state in transitions between sex and obligate asexuality in stick insects?

Facultative parthenogenesis and transitions from sexual to asexual reproduction

Recommended by ORCID_LOGO based on reviews by 3 anonymous reviewers

Despite a vast array of ways in which organisms can reproduce (Bell, 1982), most animals engage in sexual reproduction (Otto & Lenormand, 2002). A fascinating alternative to sex is parthenogenesis, where offspring are produced asexually from a gamete, typically the egg, without receiving genetic material from another gamete (Simon, Delmotte, Rispe, & Crease, 2003). One of the long-standing questions in the field is why parthenogenesis is not more widespread, given the costs associated with sex (Otto & Lenormand, 2002).  Natural populations of most species appear to be reproducing either sexually or parthenogenetically, even if a species can employ both reproductive modes (Larose et al 2023). Larose et al (2023) highlight the conundrum in this pattern, as organisms that are capable of employing parthenogenesis facultatively would be able to gain the benefits of both modes of reproduction. Why then, is facultative parthenogenesis not more common?

Larose et al (2023) propose that constraints on being efficient in both sexual and asexual reproduction could cause a trade-off between reproductive modes that favours an obligate strategy of either sex or no sex. This would provide an explanation for why facultative parthenogenesis is rare. Timema stick insects provide an excellent system to investigate reproductive strategies, as some species have parthenogenetic females, while other species are sexual, and they show repeated transitions from sexual reproduction to obligate parthenogenesis (Schwander & Crespi, 2009). The authors performed comprehensive and complementary studies in a recently discovered species T. douglasi, in which populations show both modes of reproduction, with some populations consisting only of females and others showing equal proportions of males and females. The sex ratio varied significantly, with the proportion of females ranging between 43-100% across 29 populations. These populations form a monophyletic clade with clustering into three genetic lineages and only a few cases of admixture. Females from all populations were capable of producing unfertilized eggs, but the hatching success varied hugely among populations and lineages (3-100%). Parthenogenetically produced offspring were homozygous, showing that parthenogenesis causes a complete loss of heterozygosity in a single generation. After producing eggs as virgins, females were mated to assess the capacity to also reproduce sexually, and fertilization increased the hatching success of eggs in two lineages. In one lineage, in which the hatching success of unfertilized eggs is similar to that of other sexually reproducing Timema species, fertilization reduced egg-hatching success, indicating a trade-off between reproductive modes with parthenogenetic reproduction performing best. Approximately 58% of the offspring produced after mating were fertilized, demonstrating the capacity of females to reproduce parthenogenetically also after mating has occurred, however with huge variation among individuals.

This wonderful and meticulously performed study produces strong and complementary evidence for facultative parthenogenesis in T. douglasi populations. The study shows large variation in how reproductive mode is employed, supporting the existence of a trade-off between sexual and parthenogenetic reproduction. This might be an example of an ongoing transition from sexual to asexual reproduction, which indicates that obligate parthenogenesis may derive via transient facultative parthenogenesis. 

REFERENCES

Bell, G. (1982) The Masterpiece of Nature: The Evolution and Genetics of Sexuality. University of California Press. 635 p.

Otto, S. P., & Lenormand, T. (2002). Resolving the paradox of sex and recombination. Nature Reviews Genetics, 3(4), 252-261. https://doi.org/10.1038/nrg761

Schwander, T., & Crespi, B. J. (2009). Multiple direct transitions from sexual reproduction to apomictic parthenogenesis in Timema stick insects. Evolution, 63(1), 84-103. 
https://doi.org/10.1111/j.1558-5646.2008.00524.x

Simon, J.-C., Delmotte, F., Rispe, C., & Crease, T. (2003). Phylogenetic relationships between parthenogens and their sexual relatives: the possible routes to parthenogenesis in animals. Biological Journal of the Linnean Society, 79(1), 151-163. https://doi.org/10.1046/j.1095-8312.2003.00175.x

Larose, C., Lavanchy,  G., Freitas, S., Parker, D.J., Schwander, T. (2023) Facultative parthenogenesis: a transient state in transitions between sex and obligate asexuality in stick insects? bioRxiv, 2022.03.25.485836, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.03.25.485836

Facultative parthenogenesis: a transient state in transitions between sex and obligate asexuality in stick insects?Chloé Larose, Guillaume Lavanchy, Susana Freitas, Darren J. Parker, Tanja Schwander<p>Transitions from obligate sex to obligate parthenogenesis have occurred repeatedly across the tree of life. Whether these transitions occur abruptly or via a transient phase of facultative parthenogenesis is rarely known. We discovered and char...Reproduction and SexTrine Bilde2022-05-20 10:41:13 View