Understanding how species respond to environmental changes is becoming increasingly important in order to predict the future of biodiversity and species distributions under current global warming conditions (Rezende 2020; Bennett et al 2021). Two key factors to take into account in these predictions are the tolerance of organisms to heat stress and subsequently how they adapt to increasingly warmer temperatures. Coupled with this, one important factor that is often overlooked when addressing the evolution of thermal tolerance, is the correlated responses in traits that are important to fitness, such as life histories, behavior and the underlying metabolic processes.

The rate and intensity of the thermal stress are expected to be major factors in shaping the evolution of heat tolerance and correlated responses in other traits. For instance, lower rates of thermal stress are predicted to select for individuals with a slower metabolism (Santos et al 2012), whereas low metabolism is expected to lead to a lower reproductive rate (Dammhahn et al 2018). To quantify the importance of the rate and intensity of thermal stress on the evolutionary response of heat tolerance and correlated response in behavior, Mesas et al (2021) performed experimental evolution in Drosophila subobscura using selective regimes with slow or fast ramping protocols. Whereas both regimes showed increased heat tolerance with similar evolutionary rates, the correlated responses in thermal performance curves for locomotor behavior differed between selection regimes. These findings suggest that thermal rate and intensity may shape the evolution of correlated responses in other traits, urging the need to understand possible correlated responses at relevant levels such as life history and metabolism. 

In the present contribution, Mesas and Castañeda (2022) investigate whether the disparity in thermal performance curves observed in the previous experiment (Mesas et al 2021) could be explained by differences in metabolic energy production and consumption, and how this correlated with the reproductive output (fecundity and viability). Overall, the authors show some evidence for lowered enzyme activity and increased performance in life-history traits, particularly for the slow-ramping selected flies. Specifically, the authors observe a reduction in glucose metabolism and increased viability when evolving under slow ramping stress. Interestingly, both regimes show a general increase in fecundity, suggesting that adaptation to these higher temperatures is not costly (for reproduction) in the ancestral environment. The evidence for a somewhat lower metabolism in the slow-ramping lines suggests the evolution of a slow “pace of life”. The “pace of life” concept tries to bridge variation across several levels namely metabolism, physiology, behavior and life history, with low “pace of life” organisms presenting lower metabolic rates, later reproduction and higher longevity than fast “pace of life” organisms (Dammhahn et al 2018, Tuzun & Stocks 2022).  As the authors state there is not a clear-cut association with the expectations of the pace of life hypothesis since there was evidence for increased reproductive output under both selection intensity regimes. This suggests that, given sufficient trait genetic variance, positively correlated responses may emerge during some stages of thermal evolution. As fecundity estimates in this study were focussed on early life, the possibility of a decrease in the cumulative reproductive output of the selected flies, even under benign conditions, cannot be excluded. This would help explain the apparent paradox of increased fecundity in selected lines. In this context, it would also be interesting to explore the variation in reproductive output at different temperatures, i.e to obtain thermal performance curves for life histories. 

Mesas and Castañeda (2022) raise important questions to pursue in the future and contribute to the growing evidence that, in order to predict the distribution of ectothermic species under current global warming conditions, we need to expand beyond determining the physiological thermal limits of each organism (Parratt et al 2021). Ultimately, integrating metabolic, life-history and behavioral changes during evolution under different thermal stresses within a coherent framework is key to developing better predictions of temperature effects on natural populations.  

References

Bennett, J.M., Sunday, J., Calosi, P. et al. The evolution of critical thermal limits of life on Earth. Nat Commun 12, 1198 (2021). https://doi.org/10.1038/s41467-021-21263-8

Dammhahn, M., Dingemanse, N.J., Niemelä, P.T. et al. Pace-of-life syndromes: a framework for the adaptive integration of behaviour, physiology and life history. Behav Ecol Sociobiol 72, 62 (2018). https://doi.org/10.1007/s00265-018-2473-y

Mesas, A,  Jaramillo, A,  Castañeda, LE.  Experimental evolution on heat tolerance and thermal performance curves under contrasting thermal selection in Drosophila subobscura. J Evol Biol  34, 767– 778 (2021). https://doi.org/10.1111/jeb.13777

Mesas, A, Castañeda, LE Evolutionary responses of energy metabolism, development, and reproduction to artificial selection for increasing heat tolerance in Drosophila subobscura. bioRxiv, 2022.02.03.479001, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.02.03.479001

Parratt, S.R., Walsh, B.S., Metelmann, S. et al. Temperatures that sterilize males better match global species distributions than lethal temperatures. Nat. Clim. Chang. 11, 481–484 (2021). https://doi.org/10.1038/s41558-021-01047-0

Santos, M, Castañeda, LE, Rezende, EL Keeping pace with climate change: what is wrong with the evolutionary potential of upper thermal limits? Ecology and evolution, 2(11), 2866-2880 (2012). https://doi.org/10.1002/ece3.385

Tüzün, N, Stoks, R. A fast pace-of-life is traded off against a high thermal performance. Proceedings of the Royal Society B, 289(1972), 20212414 (2022). https://doi.org/10.1098/rspb.2021.2414

Rezende, EL, Bozinovic, F, Szilágyi, A, Santos, M. Predicting temperature mortality and selection in natural Drosophila populations. Science, 369(6508), 1242-1245  (2020). https://doi.org/10.1126/science.aba9287

Human economic activity is responsible for the vast majority of ongoing extinction, but that does not mean lineages are being affected willy-nilly. For amphibians [1] and South African flowering plants [2], young species have a somewhat higher than expected chance of being threatened with extinction. In contrast, older Australian marsupial lineages seem to be more at risk [3]. Both of the former studies suggested that situations leading to peripheral isolation might simultaneously increase ongoing speciation and current threat via small geographic range, while the authors of the latter study suggested that older species might have evolved increasingly narrow niches. Here, Andrew Tanentzap and colleagues [4] dig deeper into the putative links between species age, niche breadth and threat status. Across 500-some plant genera worldwide, they find that, indeed, ""younger"" species (i.e. from younger and faster-diversifying genera) were more likely to be listed as imperiled by the IUCN, consistent with patterns for amphibians and African plants. Given this, results from their finer-level analyses of conifers are initially bemusing: here, ""older"" (i.e., on longer terminal branches) species were at higher risk. This would make conifers more like Australian marsupials, with the rest of the plants being more like amphibians. However, here where the data were more finely grained, the authors detected a second interesting pattern: using an intriguing matched-pair design, they detect a signal of conifer species niches seemingly shrinking as a function of age. The authors interpret this as consistent with increasing specialization, or loss of ancestral warm wet habitat, over paleontological time. It is true that conifers in general are older than plants more generally, with some species on branches that extend back many 10s of millions of years, and so a general loss of suitable habitat makes some sense. If so, both the pattern for all plants (small initial ranges heightening extinction) and the pattern for conifers (eventual increasing specialization or habitat contraction heightening extinction) could occur, each on a different time scale. As a coda, the authors detected no effect of age on threat status in palms; however, this may be both because palms have already lost species to climate-change induced extinction, and because they are thought to speciate more via long-distance dispersal and adaptive divergence then via peripheral isolation.
Given how quickly ranges can change, how hard it is to measure niche breadth, and the qualitatively different time scales governing past diversification and present-day extinction drivers, this is surely not the last word on the subject, even for plants. However, even the hint of a link between drivers of extinction in the Anthropocene and drivers of diversification through the ages is intellectually exciting and, perhaps, even, somehow, of practical importance.

References

[1] Greenberg, D. A., & Mooers, A. Ø. (2017). Linking speciation to extinction: Diversification raises contemporary extinction risk in amphibians. Evolution Letters, 1, 40–48. doi: 10.1002/evl3.4
[2] Davies, T. J., Smith, G. F., Bellstedt, D. U., Boatwright, J. S., Bytebier, B., Cowling, R. M., Forest, F., et al. (2011). Extinction risk and diversification are linked in a plant biodiversity hotspot. PLoS Biology, 9:e1000620. doi: 10.1371/journal.pbio.1000620
[3] Johnson, C. N., Delean S., & Balmford, A. (2002). Phylogeny and the selectivity of extinction in Australian marsupials. Animal Conservation, 5, 135–142. doi: 10.1017/S1367943002002196
[4] Tanentzap, A. J., Igea, J., Johnston, M. G., & Larcombe, M. G. (2018). Range size dynamics can explain why evolutionarily age and diversification rate correlate with contemporary extinction risk in plants. bioRxiv, 152215, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/152215

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

Organisms often show robustness to genetic or environmental perturbations. Whether these two components of robustness can evolve separately is the focus of the paper by Le Rouzic [1]. Using theoretical analysis and individual-based computer simulations of a gene regulatory network model, he shows that multiple aspects of robustness can be investigated as a set of pleiotropically linked quantitative traits. While genetically correlated, various robustness components (e.g., mutational, developmental, homeostasis) of gene expression in the regulatory network evolved more or less independently from each other under directional selection. The quantitative approach of Le Rouzic could explain both how unselected robustness components can respond to selection on other components and why various robustness-related features seem to have their own evolutionary history. Moreover, he shows that all components were evolvable, but not all to the same extent. Robustness to environmental disturbances and gene expression stability showed the largest responses while increased robustness to genetic disturbances was slower. Interestingly, all components were positively correlated and remained so after selection for increased or decreased robustness.

This study is an important contribution to the discussion of the evolution of robustness in biological systems. While it has long been recognized that organisms possess the ability to buffer genetic and environmental perturbations to maintain homeostasis (e.g., canalization [2]), the genetic basis and evolutionary routes to robustness and canalization are still not well understood. Models of regulatory gene networks have often been used to address aspects of robustness evolution (e.g., [3]). Le Rouzic [1] used a gene regulatory network model derived from Wagner’s model [4]. The model has as end product the expression level of a set of genes influenced by a set of regulatory elements (e.g., transcription factors). The level and stability of expression are a property of the regulatory interactions in the network.

Le Rouzic made an important contribution to the study of such gene regulation models by using a quantitative genetics approach to the evolution of robustness. He crafted a way to assess the mutational variability and selection response of the components of robustness he was interested in. Le Rouzic’s approach opens avenues to investigate further aspects of gene network evolutionary properties, for instance to understand the evolution of phenotypic plasticity.

Le Rouzic also discusses ways to measure his different robustness components in empirical studies. As the model is about gene expression levels at a set of protein-coding genes influenced by a set of regulatory elements, it naturally points to the possibility of using RNA sequencing to measure the variation of gene expression in know gene networks and assess their robustness. Robustness could then be studied as a multidimensional quantitative trait in an experimental setting.

References

[1] Le Rouzic, A (2022) Gene network robustness as a multivariate character. arXiv: 2101.01564, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://arxiv.org/abs/2101.01564

[2] Waddington CH (1942) Canalization of Development and the Inheritance of Acquired Characters. Nature, 150, 563–565. https://doi.org/10.1038/150563a0

[3] Draghi J, Whitlock M (2015) Robustness to noise in gene expression evolves despite epistatic constraints in a model of gene networks. Evolution, 69, 2345–2358. https://doi.org/10.1111/evo.12732

[4] Wagner A (1994) Evolution of gene networks by gene duplications: a mathematical model and its implications on genome organization. Proceedings of the National Academy of Sciences, 91, 4387–4391. https://doi.org/10.1073/pnas.91.10.4387

Domestication is a complex process that imprints the demography and the genomes of domesticated populations, enforcing strong selective pressures on traits favourable to humans, e.g. for food production [1]. Domestication has been quite intensely studied in plants and animals, but less so in micro-organisms such as fungi, despite their assets (e.g. their small genomes and tractability in the lab). This elegant study by Bennetot and collaborators [2] on the cheese-making fungus Geotrichum candidum adds to the mounting body of studies in the genomics of fungi, proving they are excellent models in evolutionary biology for studying adaptation and drift in eukaryotes [3].

Bennetot et al. newly showed with whole genome sequences that all G. candidum strains isolated from cheese form a monophyletic clade subdivided into three genetically differentiated populations with several admixed strains, while the wild strains sampled from diverse geographic locations form a sister clade. This suggests the wild progenitor was not sampled in the present study and calls for future exciting work on the domestication history of the G. candidum fungus. The authors scanned the genomes for footprints of adaptation to the cheese environment and identified promising candidates, such as a gene involved in iron uptake (this element is limiting in cheese). Their functional genome analysis also provides evidence for higher contents of transposable elements in cheese-making strains, likely due to relaxed selection during the domestication process.

This paper is particularly impressive in that the authors complemented the population genomic approach with the phenotypic characterization of the strains and tested their ability to outcompete common fungal food spoilers. The authors convincingly showed that cheese-making strains display phenotypic differences relative to wild relatives for multiple traits such as slower growth, lower proteolysis activity and a greater amount of volatiles attractive to consumers, these phenotypes being beneficial for cheese making.

Finally, this work is particularly inspiring because it thoroughly discusses convergent evolution during domestication in different cheese-associated fungi. Indeed, studying populations experiencing similar environmental pressures is fundamental to understanding whether evolution is repeatable [4]. For instance, all three cheese populations of G. candidum exhibit a lower genetic diversity than wild populations. However, only one population displays a stronger domestication syndrome, resembling the Penicillium camemberti situation [5]. Furthermore, different cheese-making practices may have led to varying situations with clonal lineages in non-Roquefort P. roqueforti and P. camemberti [5, 6], while the cheese-making G. candidum populations still harbour some diversity. In a nutshell, Bennetot's study makes an important contribution to evolutionary biology and highlights the value of diversifying our model organisms toward under-represented clades.

REFERENCES

[1] Diamond J (2002) Evolution, consequences and future of plant and animal domestication. Nature 418: 700–707. https://doi.org/10.1038/nature01019

[2] Bennetot B, Vernadet J-P, Perkins V, Hautefeuille S, Rodríguez de la Vega RC, O’Donnell S, Snirc A, Grondin C, Lessard M-H, Peron A-C, Labrie S, Landaud S, Giraud T, Ropars J (2023) Domestication of different varieties in the cheese-making fungus Geotrichum candidum. bioRxiv, 2022.05.17.492043, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.05.17.492043 

[3] Gladieux P, Ropars J, Badouin H, Branca A, Aguileta G, de Vienne DM, Rodríguez de la Vega RC, Branco S, Giraud T (2014) Fungal evolutionary genomics provides insight into the mechanisms of adaptive divergence in eukaryotes. Mol. Ecol. 23: 753–773. https://doi.org/10.1111/mec.12631

[4] Bolnick DI, Barrett RD, Oke KB, Rennison DJ, Stuart YE (2018) (Non)Parallel evolution. Ann. Rev. Ecol. Evol. Syst. 49: 303–330. https://doi.org/10.1146/annurev-ecolsys-110617-062240 

[5] Ropars J, Didiot E, Rodríguez de la Vega RC, Bennetot B, Coton M, Poirier E, Coton E, Snirc A, Le Prieur S, Giraud T (2020) Domestication of the Emblematic White Cheese-Making Fungus Penicillium camemberti and Its Diversification into Two Varieties. Current Biol. 30: 4441–4453.e4. https://doi.org/10.1016/j.cub.2020.08.082

[6] Dumas, E, Feurtey, A, Rodríguez de la Vega, RC, Le Prieur S, Snirc A, Coton M, Thierry A, Coton E, Le Piver M, Roueyre D, Ropars J, Branca A, Giraud T (2020) Independent domestication events in the blue-cheese fungus Penicillium roqueforti. Mol Ecol. 29: 2639–2660. https://doi.org/10.1111/mec.15359