We currently live in the Anthropocene, the geological age characterized by a profound impact of human populations in the ecosystems and the environment. While there is little doubt about the action of humans in the shaping of present landscapes, it can be difficult to determine what the state of those landscapes was before humans started to modify them. This is the case of the Madagascar grasslands, whose origins have been debated with arguments proposing them either as anthropogenic, created with the arrival of humans around 2000BP, or as ancient features of the natural landscape with a forest fragmentation process due to environmental changes pre-dating human arrival [e.g. 1,2]. One way to clarify this question is through the genetic study of native species. Population continuity and fragmentation along time shape the structure of the genetic diversity in space. Species living in a uniform continuous habitat are expected to show genetic structuring determined only by geographical distance. Recent changes of the habitat can take many generations to reshape that genetic structure [3]. Thus, we expect genetic structure to reflect ancient features of the landscape.

The work by Jordi Salmona and collaborators [4] studies the factors determining the population genetic structure of the Malagasy spiny olive (Noronhia spinifolia). This narrow endemic species is distributed in the discontinuous forest patches of the Loky-Manambato region (northern Madagascar). Jordi Salmona and collaborators genotyped 72 individuals distributed across the species distribution with restriction associated DNA sequencing and organelle microsatellite markers. Then, they studied the population genetic structure of the species. Using isolation-by-resistance models [5], they tested the influence of several landscape features (forest cover, roads, rivers, slope, etc.) on the connectivity between populations. Maternally inherited loci (chloroplast and mitochondria) and bi-parentally inherited loci (nuclear), were analysed separately in an attempt to identify the role of pollen and seed dispersal in the connectivity of populations.

Despite the small distribution of the species, Jordi Salmona and collaborators [4] found remarkable levels of genetic diversity. The spatial structure of this diversity was found to be mainly explained by the forest cover of the landscape, suggesting that the landscape has been composed by patches of forests and grasslands for a long time. The main role of forest cover for the connectivity among populations also highlights the importance of riparian forest as dispersal corridors. Finally, differences between organelle and nuclear markers were not enough to establish any strong conclusion about the differences between pollen and seed dispersal.

The results presented by Jordi Salmona and collaborators [4] contribute to the understanding of the history and ecology of understudied Madagascar ecosystems. Previous population genetic studies  in some forest-dwelling mammals have been interpreted as supporting an old age for the fragmented landscapes in northern Madagascar [e.g. 1,6]. To my knowledge, this is the first study on a tree species. While this work might not completely settle the debate, it emphasizes the importance of studying a diversity of species to understand the biogeographic dynamics of a region.

References

1. Quéméré, E., X. Amelot, J. Pierson, B. Crouau-Roy, L. Chikhi (2012) Genetic data suggest a natural prehuman origin of open habitats in northern Madagascar and question the deforestation narrative in this region. Proceedings of the National Academy of Sciences of the United States of
America 109: 13028–13033. https://doi.org/10.1073/pnas.1200153109
2. Joseph, G.S., C.L. Seymour (2020) Madagascan highlands: originally woodland and forest containing endemic grasses, not grazing-adapted grassland. Proceedings of the Royal Society B: Biological Sciences 287: 20201956. https://doi.org/10.1098/rspb.2020.1956
3. Landguth, E.L., S.A. Cushman, M.K. Schwartz, K.S. McKelvey, M. Murphy, G. Luikart (2010) Quantifying the lag time to detect barriers in landscape genetics. Molecular Ecology 19: 4179–
4191. https://doi.org/10.1111/j.1365-294X.2010.04808.x
4. Salmona J., Dresen A, Ranaivoson AE, Manzi S, Pors BL, Hong-Wa C, Razanatsoa J, Andriaholinirina NV, Rasoloharijaona S, Vavitsara M-E, Besnard G (2021) How ancient forest fragmentation and riparian connectivity generate high levels of genetic diversity in a micro-endemic Malagasy tree. bioRxiv, 2020.11.25.394544, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2020.11.25.394544
5. McRae, B.H. (2006) Isolation by resistance. Evolution 60: 1551–1561. https://doi.org/10.1111/j.0014-3820.2006.tb00500.x
6. Rakotoarisoa J.-E., M. Raheriarisena, S.M. Goodman (2013) Late Quaternary climatic vegetational shifts in an ecological transition zone of northern Madagascar: insights from genetic analyses of two endemic rodent species. Journal of Evolutionary Biology 26: 1019–1034. https://doi.org/10.1111/jeb.12116

Sirtuin proteins are class III histone deacetylases that are involved in a variety of fundamental biological functions mostly related to aging. These proteins are located in different subcellular compartments and are associated with different biological functions such as metabolic regulation, stress response, and cell cycle control [1]. In mammals, the sirtuin gene family is composed of seven paralogs (SIRT1-7) grouped into four classes [2]. Due to their involvement in maintaining cell cycle integrity, sirtuins have been studied as a way to understand fundamental mechanisms governing longevity [1]. Indeed, the downregulation of sirtuin genes with aging seems to explain much of the pathophysiology that accumulates with aging [3]. Biomedical studies have thus explored the potential therapeutic implications of sirtuins [4] but whether they can effectively be used as molecular targets for the treatment of human diseases remains to be demonstrated [1]. Despite this biomedical interest and some phylogenetic analyses of sirtuin paralogs mostly conducted in mammals, a comprehensive evolutionary analysis of the sirtuin gene family at the scale of vertebrates was still lacking.

In this preprint, Opazo and collaborators [5] took advantage of the increasing availability of whole-genome sequences for species representing all main groups of vertebrates to unravel the evolution of the sirtuin gene family. To do so, they undertook a phylogenomic approach in its original sense aimed at improving functional predictions by evolutionary analysis [6] in order to inventory the full vertebrate sirtuin gene repertoire and reconstruct its precise duplication history. Harvesting genomic databases, they extracted all predicted sirtuin proteins and performed phylogenetic analyses based on probabilistic inference methods. Maximum likelihood and Bayesian analyses resulted in well-resolved and congruent phylogenetic trees dividing vertebrate sirtuin genes into three major clades. These analyses also revealed an additional eighth paralog that was previously overlooked because of its restricted phyletic distribution. This newly identified sirtuin family member (named SIRT8) was recovered with unambiguous statistical support as a sister-group to the SIRT3 clade. Comparative genomic analyses based on conserved gene synteny confirmed that SIRT8 was present in all sampled non-amniote vertebrate genomes (cartilaginous fish, bony fish, coelacanth, lungfish, and amphibians) except cyclostomes. SIRT8 has thus most likely been lost in the last common ancestor of amniotes (mammals, reptiles, and birds). Discovery of such previously unknown genes in vertebrates is not completely surprising given the plethora of high-quality genomes now available. However, this study highlights the importance of considering a broad taxonomic sampling to infer evolutionary patterns of gene families that have been mostly studied in mammals because of their potential importance for human biology.

Based on its phylogenetic position as closely related to SIRT3 within class I, it could be predicted that the newly identified SIRT8 paralog likely has a deacetylase activity and is probably located in mitochondria. To test these evolutionary predictions, Opazo and collaborators [5] conducted further bioinformatics analyses and functional experiments using the elephant shark (Callorhinchus milii) as a model species. RNAseq expression data were analyzed to determine tissue-specific transcription of sirtuin genes in vertebrates, including SIRT8 found to be mainly expressed in the ovary, which suggests a potential role in biological processes associated with reproduction. The elephant shark SIRT8 protein sequence was used with other vertebrates for comparative analyses of protein structure modeling and subcellular localization prediction both pointing to a probable mitochondrial localization. The protein localization and its function were further characterized by immunolocalization in transfected cells, and enzymatic and functional assays, which all confirmed the prediction that SIRT8 proteins are targeted to the mitochondria and have deacetylase activity. The extensive experimental efforts made in this study to shed light on the function of this newly discovered gene are both rare and highly commendable.

Overall, this work by Opazo and collaborators [5] provides a comprehensive phylogenomic study of the sirtuin gene family in vertebrates based on detailed evolutionary analyses using state-of-the-art phylogenetic reconstruction methods. It also illustrates the power of adopting an integrative comparative approach supplementing the reconstruction of the duplication history of the gene family with complementary functional experiments in order to elucidate the function of the newly discovered SIRT8 family member. These results provide a reference phylogenetic framework for the evolution of sirtuin genes and the further functional characterization of the eight vertebrate paralogs with potential relevance for understanding the cellular biology of aging and its associated diseases in human.

References

[1] Vassilopoulos A, Fritz KS, Petersen DR, Gius D (2011) The human sirtuin family: Evolutionary divergences and functions. Human Genomics, 5, 485. https://doi.org/10.1186/1479-7364-5-5-485

[2] Yamamoto H, Schoonjans K, Auwerx J (2007) Sirtuin Functions in Health and Disease. Molecular Endocrinology, 21, 1745–1755. https://doi.org/10.1210/me.2007-0079

[3] Morris BJ (2013) Seven sirtuins for seven deadly diseases ofaging. Free Radical Biology and Medicine, 56, 133–171. https://doi.org/10.1016/j.freeradbiomed.2012.10.525

[4] Bordo D Structure and Evolution of Human Sirtuins. Current Drug Targets, 14, 662–665. http://dx.doi.org/10.2174/1389450111314060007

[5] Opazo JC, Vandewege MW, Hoffmann FG, Zavala K, Meléndez C, Luchsinger C, Cavieres VA, Vargas-Chacoff L, Morera FJ, Burgos PV, Tapia-Rojas C, Mardones GA (2022) How many sirtuin genes are out there? evolution of sirtuin genes in vertebrates with a description of a new family member. bioRxiv, 2020.07.17.209510, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.  https://doi.org/10.1101/2020.07.17.209510

[6] Eisen JA (1998) Phylogenomics: Improving Functional Predictions for Uncharacterized Genes by Evolutionary Analysis. Genome Research, 8, 163–167. https://doi.org/10.1101/gr.8.3.163

The emergence and spread of insecticide resistance compromises the efficiency of insecticides as prevention tool against the transmission of insect-transmitted diseases (Moyes et al. 2017). In this context, the understanding of the genetic mechanisms of resistance and the way resistant alleles spread in insect populations is necessary and important to envision resistance management policies. A common and important mechanism of insecticide resistance is gene amplification and in particular amplification of insecticide detoxification genes, which leads to the overexpression of these genes (Bass & Field, 2011). Cattel and coauthors (2020) adopt a combination of experimental approaches to study the role of gene amplification in resistance to organophosphate insecticides in the mosquito Aedes aegypti and its occurrence in populations of South East Asia and to develop a molecular test to track resistance alleles.
Their first approach consists in performing an artificial selection on laboratory Ae. Aegypti populations started with individuals collected in Laos. In the selected population, an initial 90% mortality by adult exposure to the organophosphate insecticide malathion is imposed. This population shows a steep increase in resistance to malathion and other organophosphate insecticides, which is absent in the paired control population. The transcriptomic patterns of the control and the evolved populations as well as of a reference sensitive population reveals, among other differences, the over-expression of five carboxy/choline esterase (CCE) genes in the insecticide selected population. These five genes happen to be clustered in the Ae. aegypti genome and whole genome sequencing of a highly resistant population combined to qPCR test on genomic DNA showed that the overexpression of these genes is due to gene amplification. Although it would have been more elegant to have replicate selected and control populations and to perform the transcriptomic and the genomic analyses directly on the experimental populations, the authors gather a set of experimental evidence which combined to previous knowledge on the function of the amplified and over-expressed genes and on their implication in organophosphate insecticide resistance in other species allow to discard the possibility that this gene amplification spread by drift in the selected population.
In a second part of the paper, copy number variation for CCE genes is checked in field sample populations. This test reveals the presence of resistance alleles in half of the fourteen South East Asia populations sampled. Very interestingly, it also reveals a high level of complexity and diversity among the resistance alleles: it shows first the existence, both in the experimental and the field populations, of at least two amplified alleles (differing by the number of genes amplified) and second a high variation in the copy number of amplified genes. This indicates that gene amplification as a molecular resistance mechanism has actually lead to a high diversity of resistance alleles. These alleles are likely to differ both by the level of resistance conferred and the fitness cost imposed in the absence of the insecticide and these two values are affecting the evolution of their frequency in the field and ultimately the spread of resistance.
The last part of the paper is devoted to the development of a high-throughput Taqman assay which allows to determine rapidly the copy number of one of the esterase genes amplified in the resistance alleles described earlier. This assay is nicely validated and will definitely be a useful tool to determine the occurrence of these resistance alleles in field population. The fact that it gives access to the copy number will also allow to follow its copy number across time and get insight into the complexity of resistance evolution by gene amplification.
To sum up, this paper studies the implication of carboxy/choline esterase genes amplification in organophosphate resistance evolution in Ae. aegypti, reveals the diversity among individuals and populations of this resistance mechanism, because of variation both in the identity of the genes amplified and in their copy number and sets up a fast and efficient tool to detect and follow the spread of these resistant alleles in the field. Additionally, the different experimental approaches adopted have generated genomic and transcriptomic data, of which only the part related to CCE gene amplification has been exploited. These data are very likely to reveal other genomic and expression determinants of resistance that will give access to an extra degree of complexity in organophosphate insecticide resistance determinism and evolution.

References

Bass C, Field LM (2011) Gene amplification and insecticide resistance. Pest Management Science, 67, 886–890. https://doi.org/10.1002/ps.2189
Cattel J, Haberkorn C, Laporte F, Gaude T, Cumer T, Renaud J, Sutherland IW, Hertz JC, Bonneville J-M, Arnaud V, Nous C, Fustec B, Boyer S, Marcombe S, David J-P (2020) A genomic amplification affecting a carboxylesterase gene cluster confers organophosphate resistance in the mosquito Aedes aegypti: from genomic characterization to high-throughput field detection. bioRxiv, 2020.06.08.139741, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. https://doi.org/10.1101/2020.06.08.139741
Moyes CL, Vontas J, Martins AJ, Ng LC, Koou SY, Dusfour I, Raghavendra K, Pinto J, Corbel V, David J-P, Weetman D (2017) Contemporary status of insecticide resistance in the major Aedes vectors of arboviruses infecting humans. PLOS Neglected Tropical Diseases, 11, e0005625. https://doi.org/10.1371/journal.pntd.0005625

Understanding the factors that shape the virome of a host is key to understanding virus ecology and evolution (Obbard, 2018; French & Holmes, 2020). There is still much to learn about the diversity and distribution of viruses in a host community (Wille et al., 2019; Chen et al., 2023). The viruses of parasitoid wasps are well studied, and their viruses, or integrated viral genes, are known to suppress their insect host’s immune response to enhance parasitoid survival (Herniou et al., 2013; Coffman et al., 2022). Likewise, the insect virome is being increasingly well studied (Shi et al., 2016), with the virome of Drosophila species being particularly well characterised over the best part of the last century (L'Heritier & Teissier, 1937; L'Heritier, 1970; Brun & Plus, 1980; Longdon et al., 2010; Longdon et al., 2011; Longdon et al., 2012; Webster et al., 2015; Webster et al., 2016; Medd et al., 2018; Wallace et al., 2021). However, the viromes of parasitoids and their insect host communities have been less well studied (Leigh et al., 2018; Caldas-Garcia et al., 2023), and the inherent connectivity between parasitoids and their hosts provides an interesting system to study virus host range and cross-species transmission.

Here, Varaldi et al (Varaldi et al., 2024) have examined the viruses associated with a community of nine Drosophilidae hosts and six parasitoids. Using both RNA and DNA sequencing of insects reared for two generations, they selected viruses that are maintained in the lab either via vertical transmission or contamination of rearing medium. From 55 pools of insects they found 53 virus-like sequences, 37 of which were novel. Parasitoids were host to nearly twice as many viruses as their Drosophila hosts, although they note this could be due to differences in the rearing temperatures of the hosts.  

They next quantified if species, year, season, or location played a role in structuring the virome, finding only a significant effect of host species, which explained just over 50% of the variation in virus distribution. No evidence was found of related species sharing more similar virus communities. Although looking at a limited number of species, this suggests that these viruses are not co-speciating or preferentially host switching between closely related species.

Finally, they carried out crosses between lines of the parasitoid Leptopilina heterotoma that were infected and uninfected for a novel Iflavirus found in their sequencing data.  They found evidence of high levels of maternal transmission and lower level horizontal transmission between wasp larvae parasitising the same host. No evidence of changes in parasitoid-induced mortality, developmental success or the sex ratio was found in iflavirus-infected parasitoids. Interestingly individuals infected with this RNA virus also contained viral DNA, but this did not appear to be integrated into the wasp genome.

Overall, this work has taken the first steps in examining the community structure of the virome of parasitoids together with their Drosophilidae hosts. This work will not doubt stimulate follow-up studies to explore the evolution and ecology of these novel virus communities.

References

Brun G, Plus N (1980) The viruses of Drosophila. In: The genetics and biology of Drosophila eds Ashburner M & Wright TRF), pp. 625-702. Academic Press, New York.
 
Caldas-Garcia GB, Santos VC, Fonseca PLC, de Almeida JPP, Costa MA, Aguiar ERGR (2023) The Viromes of Six Ecosystem Service Provider Parasitoid Wasps. Viruses, 15. https://doi.org/10.3390/v15122448
 
Chen YM, Hu SJ, Lin XD, Tian JH, Lv JX, Wang MR, Luo XQ, Pei YY, Hu RX, Song ZG, Holmes EC, Zhang YZ (2023) Host traits shape virome composition and virus transmission in wild small mammals. Cell, 186, 4662-4675 e4612. https://doi.org/10.1016/j.cell.2023.08.029
 
Coffman KA, Hankinson QM, Burke GR (2022) A viral mutualist employs posthatch transmission for vertical and horizontal spread among parasitoid wasps. Proceedings of the National Academy of Sciences of the United States of America, 119. https://doi.org/10.1073/pnas.2120048119
 
French RK, Holmes EC (2020) An Ecosystems Perspective on Virus Evolution and Emergence. Trends in Microbiology, 28, 165-175. https://doi.org/10.1016/j.tim.2019.10.010
 
Herniou EA, Huguet E, Thézé J, Bézier A, Periquet G, Drezen JM (2013) When parasitic wasps hijacked viruses: genomic and functional evolution of polydnaviruses. Philosophical Transactions of the Royal Society B-Biological Sciences, 368. https://doi.org/10.1098/rstb.2013.0051
 
L'Heritier PH (1970) Drosophila viruses and their role as evolutionary factors. Evolutionary Biology, 4, 185-209
 
L'Heritier PH, Teissier G (1937) Une anomalie physiologique héréditaire chez la Drosophile. C.R. Acad. Sci. Paris, 231, 192-194
 
Leigh BA, Bordenstein SR, Brooks AW, Mikaelyan A, Bordenstein SR (2018) Finer-Scale Phylosymbiosis: Insights from Insect Viromes. Msystems, 3. https://doi.org/10.1128/mSystems.00131-18
 
Longdon B, Obbard DJ, Jiggins FM (2010) Sigma viruses from three species of Drosophila form a major new clade in the rhabdovirus phylogeny. Proceedings of the Royal Society B, 277, 35-44. 
https://doi.org/10.1098/rspb.2009.1472
 
Longdon B, Wilfert L, Jiggins FM (2012) The Sigma Viruses of Drosophila. Caister Academic Press, Norfolk, UK.
 
Longdon B, Wilfert L, Osei-Poku J, Cagney H, Obbard DJ, Jiggins FM (2011) Host switching by a vertically-transmitted rhabdovirus in Drosophila. Biology Letters, 7, 747-750. 
https://doi.org/10.1098/rsbl.2011.0160
 
Medd NC, Fellous S, Waldron FM, Xuereb A, Nakai M, Cross JV, Obbard DJ (2018) The virome of Drosophila suzukii, an invasive pest of soft fruit. Virus Evol, 4, vey009. 
https://doi.org/10.1093/ve/vey009
 
Obbard DJ (2018) Expansion of the metazoan virosphere: progress, pitfalls, and prospects. Curr Opin Virol, 31, 17-23. https://doi.org/10.1016/j.coviro.2018.08.008
 
Shi M, Lin XD, Tian JH, Chen LJ, Chen X, Li CX, Qin XC, Li J, Cao JP, Eden JS, Buchmann J, Wang W, Xu J, Holmes EC, Zhang YZ (2016) Redefining the invertebrate RNA virosphere. Nature. https://doi.org/10.1038/nature20167
 
Varaldi J, Lepetit D, Burlet N, Faber C, Baretje B, Allemand R (2024) Community structure of heritable viruses in a Drosophila-parasitoids complex. bioRxiv, 2023.2007.2029.551099, ver.3, peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2023.07.29.551099
 
Wallace MA, Coffman KA, Gilbert C, Ravindran S, Albery GF, Abbott J, Argyridou E, Bellosta P, Betancourt AJ, Colinet H, Eric K, Glaser-Schmitt A, Grath S, Jelic M, Kankare M, Kozeretska I, Loeschcke V, Montchamp-Moreau C, Ometto L, Onder BS, Orengo DJ, Parsch J, Pascual M, Patenkovic A, Puerma E, Ritchie MG, Rota-Stabelli O, Schou MF, Serga SV, Stamenkovic-Radak M, Tanaskovic M, Veselinovic MS, Vieira J, Vieira CP, Kapun M, Flatt T, Gonzalez J, Staubach F, Obbard DJ (2021) The discovery, distribution, and diversity of DNA viruses associated with Drosophila melanogaster in Europe. Virus Evol, 7, veab031. https://doi.org/10.1093/ve/veab031
 
Webster CL, Longdon B, Lewis SH, Obbard DJ (2016) Twenty-Five New Viruses Associated with the Drosophilidae (Diptera). Evol Bioinform Online, 12, 13-25. https://doi.org/10.4137/EBO.S39454
 
Webster CL, Waldron FM, Robertson S, Crowson D, Ferrai G, Quintana JF, Brouqui JM, Bayne EH, Longdon B, Buck AH, Lazzaro BP, Akorli J, Haddrill PR, Obbard DJ (2015) The discovery, distribution and evolution of viruses associated with Drosophila melanogaster. Plos Biology, 13(7): e1002210. https://doi.org/10.1371/journal.pbio.1002210
 
Wille M, Shi M, Klaassen M, Hurt AC, Holmes EC (2019) Virome heterogeneity and connectivity in waterfowl and shorebird communities. ISME J, 13, 2603-2616. https://doi.org/10.1038/s41396-019-0458-0

It is easy to define phenotypic plasticity as a mechanism by which traits change in response to a modification of the environment. Many complex mechanisms are nevertheless involved with plastic responses, their strength, and stability (e.g., reliability of cues, type of exposure, genetic expression, epigenetics). It is rather intuitive to think that environmental cues perceived at different stages of development will logically drive different phenotypic responses (Fawcett and Frankenhuis 2015). However, it has proven challenging to try and explain, or model how and why different effects are caused by similar cues experienced at different developmental or life stages (Walasek et al. 2022). The impact of these ‘sensitive windows’ on the stability of plastic responses within or across generations remains unclear. In their paper entitled “Sensitive windows for within- and trans-generational plasticity of anti-predator defences”, Tariel-Adam (2023) address this question.

In this paper, Tariel et al. acknowledge the current state of the art, i.e., that some traits influenced by the environment at early life stages become fixed later in life (Snell-Rood et al. 2015) and that sensitive windows are therefore more likely to be observed during early stages of development. Constructive exchanges with the reviewers illustrated that Tariel et al. presented a clear picture of the knowledge on sensitive windows from a conceptual and a mechanistic perspective, thereby providing their study with a strong and elegant rationale. Tariel et al. outlined that little is known about the significance of this scenario when it comes to transgenerational plasticity. Theory predicts that exposure late in the life of parents should be more likely to drive transgenerational plasticity because the cue perceived by parents is more likely to be reliable if time between parental exposure and offspring expression is short (McNamara et al. 2016). I would argue that although sensible, this scenario is likely oversimplifying the complexity of evolutionary, ecological, and inheritance mechanisms at play (Danchin et al. 2018). Tariel-Adam et al. (2023) point out in their paper how the absence of experimental results limits our understanding of the evolutionary and adaptive significance of transgenerational plasticity and decided to address this broad question.

Tariel-Adam et al. (2023) used the context of predator-prey interactions, which is a powerful framework to evaluate the temporality of predator cues and prey responses within and across generations (Sentis et al. 2018). They conducted a very elegant experiment whereby two generations of freshwater snails Physa acuta were exposed to crayfish predator cues at different developmental windows. They triggered the within-generation phenotypic plastic response of inducible defences (e.g., shell thickness) and identified sensitive windows as to evaluate their role in within-generation phenotypic plasticity versus transgenerational plasticity. They used different linear models, which lead to constructive exchanges with reviewers, and between reviewers, well trained on these approaches, in particular on effect sizes, that improved the paper by pushing the discussion all the way towards a consensus. 

Tariel-Adam et al. (2023) results showed that the phenotypic plastic response of different traits was associated with different sensitive windows. Although early-life development was confirmed to be a sensitive window, it was far from being the only developmental stage driving within-generation plastic responses of defence traits. This finding contributes to change our views on plasticity because where theoretical models predict early- and late-life sensitive windows, empirical results gathered here present a more continuous opportunity for sensitive windows over the lifetime of freshwater snails. This is likely because multifactorial mechanisms drive the reliability and adaptive significance of predator cues. To me, this paper most original contribution lies probably in the empirical investigation of sensitive windows underlying transgenerational plasticity. Their finding implies mechanistic ties between sensitive windows driving within-generation and transgenerational plasticity for some traits, but they also shed light on the possible independence of these processes. Although one may be disheartened by these findings illustrating the ability of nature to combine complex mechanisms in order to produce somewhat unpredictable scenarios, one can only find that this unlimited range of phenotypic plasticity scenarios is a wonder to investigate because much remains to be understood. As mentioned in the conclusion of the paper, the opportunity for sensitive windows to drive such a range of plastic responses may also be an opportunity for organisms to adapt to a wide range of environmental demands. 

References

Danchin E, A Pocheville, O Rey, B Pujol, and S Blanchet (2019). Epigenetically facilitated mutational assimilation: epigenetics as a hub within the inclusive evolutionary synthesis. Biological Reviews, 94: 259-282. https://doi.org/10.1111/brv.12453

Fawcett TW, and WE Frankenhuis (2015). Adaptive Explanations for Sensitive Windows in Development. Frontiers in Zoology 12, S3. https://doi.org/10.1186/1742-9994-12-S1-S3 

McNamara JM, SRX Dall, P Hammerstein, and O Leimar (2016). Detection vs. Selection: Integration of Genetic, Epigenetic and Environmental Cues in Fluctuating Environments. Ecology Letters 19, 1267–1276. https://doi.org/10.1111/ele.12663

Sentis A, R Bertram, N Dardenne, et al. (2018). Evolution without standing genetic variation: change in transgenerational plastic response under persistent predation pressure. Heredity 121, 266–281. https://doi.org/10.1038/s41437-018-0108-8 

Snell-Rood EC, EM Swanson, and RL Young (2015). Life History as a Constraint on Plasticity: Developmental Timing Is Correlated with Phenotypic Variation in Birds. Heredity 115, 379–388. https://doi.org/10.1038/hdy.2015.47

Tariel-Adam J, E Luquet, and S Plénet (2023). Sensitive windows for within- and trans-generational plasticity of anti-predator defences. OSF preprints, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.31219/osf.io/mr8hu

Walasek N, WE Frankenhuis, and K Panchanathan (2022). An Evolutionary Model of Sensitive Periods When the Reliability of Cues Varies across Ontogeny. Behavioral Ecology 33, 101–114. https://doi.org/10.1093/beheco/arab113