Submit a preprint

Latest recommendationsrsstwitter

IdTitleAuthorsAbstractPicture▼Thematic fieldsRecommenderReviewersSubmission date
09 Nov 2018
article picture

Field evidence for manipulation of mosquito host selection by the human malaria parasite, Plasmodium falciparum

Malaria host manipulation increases probability of mosquitoes feeding on humans

Recommended by based on reviews by Olivier Restif, Ricardo S. Ramiro and 1 anonymous reviewer

Parasites can manipulate their host’s behaviour to ensure their own transmission. These manipulated behaviours may be outside the range of ordinary host activities [1], or alter the crucial timing and/or location of a host’s regular activity. Vantaux et al show that the latter is true for the human malaria parasite, Plasmodium falciparum [2]. They demonstrate that three species of Anopheles mosquito were 24% more likely to choose human hosts, rather than other vertebrates, for their blood feed when they harboured transmissible stages (sporozoites) compared to when they were uninfected, or infected with non-transmissible malaria parasites [2]. Host choice is crucial for the malaria parasite Plasmodium falciparum to complete its life-cycle, as their host range is much narrower than the mosquito’s for feeding; P. falciparum can only develop in hominids, or closely related apes [3].
The study only shows this stage-dependent parasite manipulation retrospectively (by identifying host type and parasite stage in mosquitoes after their blood feed [2]). There was no difference in the preferences of infectious (with sporozoites) or un-infectious (infected without sporozoites, or uninfected) mosquitoes between human versus cow hosts in a choice test [2]. This suggests that the final decision about whether to feed occurs when the mosquito is in close range of the host.
This, coupled with previous findings, shows that vector manipulation is a fine-tuned business, that can act at multiple stages of the parasite life-cycle and on many behaviours [4]. Indeed, mosquitoes with non-transmissible Plasmodium stages (oocysts) are more reluctant to feed than sporozoite-infected mosquitoes [5] as vectors can be killed by their host whilst feeding, doing so before they are ready to transmit is risky for the malaria parasite. Thus, it seems that Plasmodium is, to some extent, master of its vector; commanding it not to feed when it cannot be transmitted, to feed when it is ready to be transmitted and to feed on the right type of host. What does this mean for our understanding of malaria transmission and epidemics?
Vantaux et al use a mathematical model, parameterised using data from this experiment, to highlight the consequences of this 24% increase in feeding on humans for P. falciparum transmission. They show that this increase raises the number of infectious bites humans receive from 4 (if sporozoite-infected mosquitoes had the same probability as uninfected mosquitoes) to 14 (an increase in 250%), for mosquitoes with a 15-day life-span, at ratios of 1:1 mosquitoes to humans. Longer mosquito life-spans and higher ratios of mosquitoes to humans further increases the number of infectious bites.
These results [2] have important implications for epidemiological forecasting and disease management. Public health strategies could focus on possible ways to trap sporozoite-infected mosquitoes, mimicking cues they use to locate their human hosts, or identify the behaviour of mosquitoes harbouring non-yet infectious Plasmodium, and trap them before they bite. Moreover, the results of the model show that failing to take into account the preference for humans of sporozoite-infected mosquitoes could underestimate the size of pending epidemics.
An important question previously raised is whether Plasmodium-induced alteration in host behaviour really is manipulation, or just a side-effect of being infected [4,5]. The fact that Vantaux et al show that these altered feeding behaviours increases the likelihood of transmission, in that a sporozoite-infected mosquito is more likely to feed on a human, strongly suggests that it is adaptive for the parasite [2]. Ultimately, to show that it is manipulation would require the identification of molecular factors released by Plasmodium that are responsible for physiological changes in the mosquito [6].

References

[1] Thomas, F., Schmidt-Rhaesa, A., Martin, G., Manu, C., Durand, P., & Renaud, F. (2002). Do hairworms (Nematomorpha) manipulate the water seeking behaviour of their terrestrial hosts? Journal of Evolutionary Biology, 15(3), 356–361. doi: 10.1046/j.1420-9101.2002.00410.x
[2] Vantaux, A., Yao, F., Hien, D. F., Guissou, E., Yameogo, B. K., Gouagna, L.-C., … Lefevre, T. (2018). Field evidence for manipulation of mosquito host selection by the human malaria parasite, Plasmodium falciparum. BioRxiv, 207183 ver 6. doi: 10.1101/207183
[3] Prugnolle, F., Durand, P., Ollomo, B., Duval, L., Ariey, F., Arnathau, C., … Renaud, F. (2011). A Fresh Look at the Origin of Plasmodium falciparum, the Most Malignant Malaria Agent. PLOS Pathogens, 7(2), e1001283. doi: 10.1371/journal.ppat.1001283
[4] Cator, L. J., Lynch, P. A., Read, A. F., & Thomas, M. B. (2012). Do malaria parasites manipulate mosquitoes? Trends in Parasitology, 28(11), 466–470. doi: 10.1016/j.pt.2012.08.004
[5] Cator, L. J., George, J., Blanford, S., Murdock, C. C., Baker, T. C., Read, A. F., & Thomas, M. B. (2013). “Manipulation” without the parasite: altered feeding behaviour of mosquitoes is not dependent on infection with malaria parasites. Proceedings. Biological Sciences, 280(1763), 20130711. doi: 10.1098/rspb.2013.0711
[6] Herbison, R., Lagrue, C., & Poulin, R. (2018). The missing link in parasite manipulation of host behaviour. Parasites & Vectors, 11. doi: 10.1186/s13071-018-2805-9

Field evidence for manipulation of mosquito host selection by the human malaria parasite, Plasmodium falciparumAmelie Vantaux, Franck Yao, Domonbabele FdS Hien, Edwige Guissou, Bienvenue K Yameogo, Louis-Clement Gouagna, Didier Fontenille, Francois Renaud, Frederic Simard, Carlo Constantini, Frederic Thomas, Karine Mouline, Benjamin Roche, Anna Cohuet, Kou...<p>Whether the malaria parasite *Plasmodium falciparum* can manipulate mosquito host choice in ways that enhance parasite transmission toward human is unknown. We assessed the influence of *P. falciparum* on the blood-feeding behaviour of three of...Evolutionary EcologyAlison Duncan2018-02-28 09:12:14 View
19 Dec 2016
article picture
POSTPRINT

Geographic body size variation in the periodical cicadas Magicicada: implications for life cycle divergence and local adaptation

Megacicadas show a temperature-mediated converse Bergmann cline in body size (larger in the warmer south) but no body size difference between 13- and 17-year species pairs

Recommended by and

Periodical cicadas are a very prominent insect group in North America that are known for their large size, good looks, and loud sounds. However, they are probably known best to evolutionary ecologists because of their long juvenile periods of 13 or 17 years (prime numbers!), which they spend in the ground. Multiple related species living in the same area are often coordinated in emerging as adults during the same year, thereby presumably swamping any predators specialized on eating them.
Life history differences between the 13yr and 17yr cicadas are a particular focus of interest. For example, as it takes time to grow large, one would expect 17yr cicadas to be larger than 13yr cicadas on average. Koyama et al. [1] investigate geographic body size clines for 7 species of periodical cicadas in eastern North America, whose phylogenetic relationships are resolved, in a life history context, using an impressively large number of populations (Fig. 1 of [1]). The authors report generally female-biased sexual body size dimorphism (SSD), and (however not for all species) a positive relationship of body size with habitat annual mean temperature taken from weather data and a negative correlation with latitude (Fig. 3 of [1]). The latter is consistent with a converse Bergmann cline. Crucially, body size of two at least partly sympatric 13y & 17y sister species pairs did not differ (by much), contrary to expectation because the 17y species have more time to grow larger. 13y cicadas must therefore generally grow faster (or 17y cicadas slower) to in the end acquire the same (optimal?) body size. The phylogenetically oldest 13y cicada species, however, is larger, suggesting that selection for large (optimal?) body size has relaxed over evolutionary time, for unknown reasons (about which the authors speculate). A mechanistic explanation for this phenomenon is suggested based on the hypothesis that 17y cicadas simply arrest or slow down growth early during their juvenile stage to delay emergence for 4 further years (Fig. 2 of [1]).
We think this is an impressive data set, and the life history question addressed in this prominent insect taxon should appeal to readers generally interested in whole-organism evolution despite being largely descriptive.

Reference

[1] Koyama T, Ito H, Kakishima S, Yoshimura J, Cooley JR, Simon C, Sota T. 2015. Geographic body size variation in the periodical cicadas Magicicada: implications for life cycle divergence and local adaptation. Journal of Evolutionary Biology 28:1270-1277. doi: 10.1111/jeb.12653

Geographic body size variation in the periodical cicadas Magicicada: implications for life cycle divergence and local adaptationKoyama T, Ito H, Kakishima S, Yoshimura J, Cooley JR, Simon C, Sota TSeven species in three species groups (Decim, Cassini and Decula) of periodical cicadas (*Magicicada*) occupy a wide latitudinal range in the eastern United States. To clarify how adult body size, a key trait affecting fitness, varies geographical...Adaptation, Evolutionary Ecology, Life History, Macroevolution, Phylogeography & Biogeography, SpeciationWolf Blanckenhorn2016-12-19 10:39:22 View
13 Dec 2016
article picture
POSTPRINT

A supergene determines highly divergent male reproductive morphs in the ruff

Supergene Control of a Reproductive Polymorphism

Recommended by and

Two back-to-back papers published earlier this year in Nature Genetics provide compelling evidence for the control of a male reproductive polymorphism in a wading bird by a "supergene", a cluster of tightly linked genes [1-2]. The bird in question, the ruff (Philomachus pugnax), has a rather unusual reproductive system that consists of three distinct types of males ("reproductive morphs"): aggressive "independents" who represent the majority of males; a smaller fraction of non-territorial "satellites" who are submissive towards "independents"; and "faeders" who mimic females and are rare. Previous work has shown that the male morphs differ in major aspects of mating and aggression behavior, plumage coloration and body size, and that – intriguingly – this complex multi-trait polymorphism is apparently controlled by a single autosomal Mendelian locus with three alleles [3]. To uncover the genetic control of this polymorphism two independent teams, led by Terry Burke [1] and Leif Andersson [2], have set out to analyze the genomes of male ruffs. Using a combination of genomics and genetics, both groups managed to pin down the supergene locus and map it to a non-recombining, 4.5 Mb large inversion which arose 3.8 million years ago. While "independents" are homozygous for the ancestral uninverted sequence, "satellites" and "faeders" carry evolutionarily divergent, dominant alternative haplotypes of the inversion. Thus, as in several other notable cases, for example the supergene control of disassortative mating, aggressiveness and plumage color in white-throated sparrows [4], of mimicry in Heliconius and Papilio butterflies [5-6], or of social structure in ants [7], an inversion – behaving as a single "locus" – underpins the mechanistic basis of the supergene. More generally, and beyond inversions, a growing number of studies now shows that selection can favor the evolution of suppressed recombination, thereby leading to the emergence of clusters of tightly linked loci which can then control – presumably due to polygenic gene action – a suite of complex phenotypes [8-10]. A largely unresolved question in this field concerns the identity of the causative alleles and loci within a given supergene. Recent progress on this question has been made for example in Papilio polytes butterflies where a mimicry supergene has been found to involve – surprisingly – only a single but large gene: multiple mimicry alleles in the doublesex gene are maintained in strong linkage disequilibrium via an inversion. It will clearly be of great interest to see future examples of such a fine-scale genetic dissection of supergenes. In conclusion, we were impressed by the data and analyses of Küpper et al. [1] and Lamichhaney et al. [2]: both papers beautifully illustrate how genomics and evolutionary ecology can be combined to make new, exciting discoveries. Both papers will appeal to readers with an interest in supergenes, inversions, the interplay of selection and recombination, or the genetic control of complex phenotypes.

References

[1] Küpper C, Stocks M, Risse JE, dos Remedios N, Farrell LL, McRae SB, Morgan TC, Karlionova N, Pinchuk P, Verkuil YI, et al. 2016. A supergene determines highly divergent male reproductive morphs in the ruff. Nature Genetics 48:79-83. doi: 10.1038/ng.3443

[2] Lamichhaney S, Fan G, Widemo F, Gunnarsson U, Thalmann DS, Hoeppner MP, Kerje S, Gustafson U, Shi C, Zhang H, et al. 2016. Structural genomic changes underlie alternative reproductive strategies in the ruff (Philomachus pugnax). Nature Genetics 48:84-88. doi: 10.1038/ng.3430

[3] Lank DB, Smith CM, Hanotte O, Burke T, Cooke F. 1995. Genetic polymorphism for alternative mating behaviour in lekking male ruff Philomachus pugnax. Nature 378:59-62. doi: 10.1038/378059a0

[4] Tuttle Elaina M, Bergland Alan O, Korody Marisa L, Brewer Michael S, Newhouse Daniel J, Minx P, Stager M, Betuel A, Cheviron Zachary A, Warren Wesley C, et al. 2016. Divergence and Functional Degradation of a Sex Chromosome-like Supergene. Current Biology 26:344-350. doi: 10.1016/j.cub.2015.11.069

[5] Joron M, Frezal L, Jones RT, Chamberlain NL, Lee SF, Haag CR, Whibley A, Becuwe M, Baxter SW, Ferguson L, et al. 2011. Chromosomal rearrangements maintain a polymorphic supergene controlling butterfly mimicry. Nature 477:203-206. doi: 10.1038/nature10341

[6] Kunte K, Zhang W, Tenger-Trolander A, Palmer DH, Martin A, Reed RD, Mullen SP, Kronforst MR. 2014. doublesex is a mimicry supergene. Nature 507:229-232. doi: 10.1038/nature13112

[7] Wang J, Wurm Y, Nipitwattanaphon M, Riba-Grognuz O, Huang Y-C, Shoemaker D, Keller L. 2013. A Y-like social chromosome causes alternative colony organization in fire ants. Nature 493:664-668. doi: 10.1038/nature11832

[8] Thompson MJ, Jiggins CD. 2014. Supergenes and their role in evolution. Heredity 113:1-8. doi: 10.1038/hdy.2014.20

[9] Schwander T, Libbrecht R, Keller L. 2014. Supergenes and Complex Phenotypes. Current Biology 24:R288-R294. doi: 10.1016/j.cub.2014.01.056

[10] Charlesworth D. 2015. The status of supergenes in the 21st century: recombination suppression in Batesian mimicry and sex chromosomes and other complex adaptations. Evolutionary Applications 9:74-90. doi: 10.1111/eva.12291

A supergene determines highly divergent male reproductive morphs in the ruffKüpper C, Stocks M, Risse JE, dos Remedios N, Farrell LL, McRae SB, Morgan TC, Karlionova N, Pinchuk P, Verkuil YI, et al.Three strikingly different alternative male mating morphs (aggressive 'independents', semicooperative 'satellites' and female-mimic 'faeders') coexist as a balanced polymorphism in the ruff, *Philomachus pugnax*, a lek-breeding wading bird1, 2, 3....Adaptation, Genotype-Phenotype, Life History, Population Genetics / Genomics, Reproduction and SexThomas Flatt2016-12-13 17:28:13 View
18 Aug 2020
article picture

Early phylodynamics analysis of the COVID-19 epidemics in France

SARS-Cov-2 genome sequence analysis suggests rapid spread followed by epidemic slowdown in France

Recommended by based on reviews by Luca Ferretti and 2 anonymous reviewers

Sequencing and analyzing SARS-Cov-2 genomes in nearly real time has the potential to quickly confirm (and inform) our knowledge of, and response to, the current pandemic [1,2]. In this manuscript [3], Danesh and colleagues use the earliest set of available SARS-Cov-2 genome sequences available from France to make inferences about the timing of the major epidemic wave, the duration of infections, and the efficacy of lockdown measures. Their phylodynamic estimates -- based on fitting genomic data to molecular clock and transmission models -- are reassuringly close to estimates based on 'traditional' epidemiological methods: the French epidemic likely began in mid-January or early February 2020, and spread relatively rapidly (doubling every 3-5 days), with people remaining infectious for a median of 5 days [4,5]. These transmission parameters are broadly in line with estimates from China [6,7], but are currently unknown in France (in the absence of contact tracing data). By estimating the temporal reproductive number (Rt), the authors detected a slowing down of the epidemic in the most recent period of the study, after mid-March, supporting the efficacy of lockdown measures.
Along with the three other reviewers of this manuscript, I was impressed with the careful and exhaustive phylodynamic analyses reported by Danesh et al. [3]. Notably, they take care to show that the major results are robust to the choice of priors and to sampling. The authors are also careful to note that the results are based on a limited sample size of SARS-Cov-2 genomes, which may not be representative of all regions in France. Their analysis also focused on the dominant SARS-Cov-2 lineage circulating in France, which is also circulating in other countries. The variations they inferred in epidemic growth in France could therefore be reflective on broader control policies in Europe, not only those in France. Clearly more work is needed to fully unravel which control policies (and where) were most effective in slowing the spread of SARS-Cov-2, but Danesh et al. [3] set a solid foundation to build upon with more data. Overall this is an exemplary study, enabled by rapid and open sharing of sequencing data, which provides a template to be replicated and expanded in other countries and regions as they deal with their own localized instances of this pandemic.

References

[1] Grubaugh, N. D., Ladner, J. T., Lemey, P., Pybus, O. G., Rambaut, A., Holmes, E. C., & Andersen, K. G. (2019). Tracking virus outbreaks in the twenty-first century. Nature microbiology, 4(1), 10-19. doi: 10.1038/s41564-018-0296-2
[2] Fauver et al. (2020) Coast-to-Coast Spread of SARS-CoV-2 during the Early Epidemic in the United States. Cell, 181(5), 990-996.e5. doi: 10.1016/j.cell.2020.04.021
[3] Danesh, G., Elie, B., Michalakis, Y., Sofonea, M. T., Bal, A., Behillil, S., Destras, G., Boutolleau, D., Burrel, S., Marcelin, A.-G., Plantier, J.-C., Thibault, V., Simon-Loriere, E., van der Werf, S., Lina, B., Josset, L., Enouf, V. and Alizon, S. and the COVID SMIT PSL group (2020) Early phylodynamics analysis of the COVID-19 epidemic in France. medRxiv, 2020.06.03.20119925, ver. 3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/2020.06.03.20119925
[4] Salje et al. (2020) Estimating the burden of SARS-CoV-2 in France. hal-pasteur.archives-ouvertes.fr/pasteur-02548181
[5] Sofonea, M. T., Reyné, B., Elie, B., Djidjou-Demasse, R., Selinger, C., Michalakis, Y. and Samuel Alizon, S. (2020) Epidemiological monitoring and control perspectives: application of a parsimonious modelling framework to the COVID-19 dynamics in France. medRxiv, 2020.05.22.20110593. doi: 10.1101/2020.05.22.20110593
[6] Rambaut, A. (2020) Phylogenetic analysis of nCoV-2019 genomes. virological.org/t/phylodynamic-analysis-176-genomes-6-mar-2020/356
[7] Li et al. (2020) Early transmission dynamics in Wuhan, China, of novel coronavirus–infected pneumonia. N Engl J Med, 382: 1199-1207. doi: 10.1056/NEJMoa2001316

Early phylodynamics analysis of the COVID-19 epidemics in FranceGonché Danesh, Baptiste Elie,Yannis Michalakis, Mircea T. Sofonea, Antonin Bal, Sylvie Behillil, Grégory Destras, David Boutolleau, Sonia Burrel, Anne-Geneviève Marcelin, Jean-Christophe Plantier, Vincent Thibault, Etienne Simon-Loriere, Sylvie va...<p>France was one of the first countries to be reached by the COVID-19 pandemic. Here, we analyse 196 SARS-Cov-2 genomes collected between Jan 24 and Mar 24 2020, and perform a phylodynamics analysis. In particular, we analyse the doubling time, r...Evolutionary Epidemiology, Molecular Evolution, Phylogenetics / PhylogenomicsB. Jesse Shapiro2020-06-04 13:13:57 View
22 May 2023
article picture

Weak seed banks influence the signature and detectability of selective sweeps

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

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

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

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

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

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

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

REFERENCES

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

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

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

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

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

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

Weak seed banks influence the signature and detectability of selective sweepsKevin Korfmann, Diala Abu Awad, Aurélien Tellier<p style="text-align: justify;">Seed banking (or dormancy) is a widespread bet-hedging strategy, generating a form of population overlap, which decreases the magnitude of genetic drift. The methodological complexity of integrating this trait impli...Adaptation, Bioinformatics & Computational Biology, Evolutionary Applications, Evolutionary Ecology, Genome Evolution, Life History, Population Genetics / GenomicsRenaud Vitalis2022-05-23 13:01:57 View
06 Mar 2023
article picture

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
05 May 2020
article picture

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
12 Jun 2018
article picture

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

Maternal effects in sex-ratio adjustment

Recommended by based on reviews by 2 anonymous reviewers

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

References

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

Transgenerational cues about local mate competition affect offspring sex ratios in the spider mite Tetranychus urticaeAlison B. Duncan, Cassandra Marinosci, Céline Devaux, Sophie Lefèvre, Sara Magalhães, Joanne Griffin, Adeline Valente, Ophélie Ronce, Isabelle Olivieri<p style="text-align: justify;">In structured populations, competition between closely related males for mates, termed Local Mate Competition (LMC), is expected to select for female-biased offspring sex ratios. However, the cues underlying sex all...Evolutionary Ecology, Life HistoryDries Bonte2017-12-29 16:10:32 View
05 Jun 2018
article picture

The dynamics of preferential host switching: host phylogeny as a key predictor of parasite prevalence and distribution

Shift or stick? Untangling the signatures of biased host switching, and host-parasite co-speciation

Recommended by based on reviews by Damien de Vienne and Nathan Medd

Many emerging diseases arise by parasites switching to new host species, while other parasites seem to remain with same host lineage for very long periods of time, even over timescales where an ancestral host species splits into two or more new species. The ability to understand these dynamics would form an important part of our understanding of infectious disease.

Experiments are clearly important for understanding these processes, but so are comparative studies, investigating the variation that we find in nature. Such comparative data do show strong signs of non-randomness, and this suggests that the epidemiological and ecological processes might be predictable, at least in part. For example, when we map patterns of parasite presence/absence onto host phylogenies, we often find that certain host clades harbour many more parasites than expected, or that closely-related hosts harbour closely-related parasites. Nevertheless, it remains difficult to interpret these patterns to make inferences about ecological and epidemiological processes. This is partly because non-random associations can arise in multiple ways. For example, parasites might be inherited from the common ancestor of related hosts, or might switch to new hosts, but preferentially establish on novel hosts that are closely related to their existing host. Infection might also influence the shape of host phylogeny, either by increasing the rate of host extinction or, conversely, increasing the rate of speciation (as with manipulative symbionts that might induce reproductive isolation).

These various processes have, by and large, been studied in isolation, but the model introduced by Engelstädter and Fortuna [1], makes an important first step towards studying them together. Without such combined analyses, we will not be able to tell if the processes have their own unique signatures, or whether the same sort of non-randomness can arise in multiple ways.

A major finding of the work is that the size of a host clade can be an important determinant of its overall infection level. This had been shown in previous work, assuming that the host phylogeny was fixed, but the current paper shows that it extends also to situations where host extinction and speciation takes place at a comparable rate to host shifting. This finding, then, calls into question the natural assumption that a clade of host species that is highly parasite ridden, must have some genetic or ecological characteristic that makes them particularly prone to infection, arguing that the clade size, rather than any characteristic of the clade members, might be the important factor. It will be interesting to see whether this prediction about clade size is borne out with comparative studies.

Another feature of the study is that the framework is naturally extendable, to include further processes, such as the influence of parasite presence on extinction or speciation rates. No doubt extensions of this kind will form the basis of important future work.

References

[1] Engelstädter J and Fortuna NZ. 2018. The dynamics of preferential host switching: host phylogeny as a key predictor of parasite prevalence and distribution. bioRxiv 209254 ver. 5 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/209254

The dynamics of preferential host switching: host phylogeny as a key predictor of parasite prevalence and distributionJan Engelstaedter & Nicole Fortuna<p>New parasites commonly arise through host-shifts, where parasites from one host species jump to and become established in a new host species. There is much evidence that the probability of host-shifts decreases with increasing phylogenetic dist...Bioinformatics & Computational Biology, Evolutionary Epidemiology, Evolutionary Theory, Macroevolution, Phylogenetics / Phylogenomics, Species interactionsLucy Weinert2017-10-30 02:06:06 View
14 Feb 2024
article picture

Distinct patterns of genetic variation at low-recombining genomic regions represent haplotype structure

Discerning the causes of local deviations in genetic variation: the effect of low-recombination regions

Recommended by ORCID_LOGO based on reviews by Claire Merot and 1 anonymous reviewer

In this study, Ishigohoka and colleagues tackle an important, yet often overlooked, question on the causes of genetic variation. While genome-wide patterns represent population structure, local variation is often associated with selection. Authors propose that an alternative cause for variation in individual loci is reduced recombination rate.

To test this hypothesis, authors perform local Principal Component Analysis (PCA) (Li & Ralph, 2019) to identify local deviations in population structure in the Eurasian blackcap (Sylvia atricapilla) (Ishigohoka et al. 2022). This approach is typically used to detect chromosomal rearrangements or any long region of linked loci (e.g., due to reduced recombination or selection) (Mérot et al. 2021). While other studies investigated the effect of low recombination on genetic variation (Booker et al. 2020), here authors provide a comprehensive analysis of the effect of recombination to local PCA patterns both in empirical and simulated data sets. Findings demonstrate that low recombination (and not selection) can be the sole explanatory variable for outlier windows. The study also describes patterns of genetic variation along the genome of Eurasian blackcaps, localising at least two polymorphic inversions (Ishigohoka et al. 2022).

Further investigations on the effect of model parameters (e.g., window sizes and thresholds for defining low-recombining regions), as well as the use of powerful neutrality tests are in need to clearly assess whether outlier regions experience selection and reduced recombination, and to what extent.

References

Booker, T. R., Yeaman, S., & Whitlock, M. C. (2020). Variation in recombination rate affects detection of outliers in genome scans under neutrality. Molecular Ecology, 29 (22), 4274–4279. https://doi.org/10.1111/mec.15501

Ishigohoka, J., Bascón-Cardozo, K., Bours, A., Fuß, J., Rhie, A., Mountcastle, J., Haase, B., Chow, W., Collins, J., Howe, K., Uliano-Silva, M., Fedrigo, O., Jarvis, E. D., Pérez-Tris, J., Illera, J. C., Liedvogel, M. (2022) Distinct patterns of genetic variation at low-recombining genomic regions represent haplotype structure. bioRxiv 2021.12.22.473882, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.12.22.473882

Li, H., & Ralph, P. (2019). Local PCA Shows How the Effect of Population Structure Differs Along the Genome. Genetics, 211 (1), 289–304. https://doi.org/10.1534/genetics.118.301747

Mérot, C., Berdan, E. L., Cayuela, H., Djambazian, H., Ferchaud, A.-L., Laporte, M., Normandeau, E., Ragoussis, J., Wellenreuther, M., & Bernatchez, L. (2021). Locally Adaptive Inversions Modulate Genetic Variation at Different Geographic Scales in a Seaweed Fly. Molecular Biology and Evolution, 38 (9), 3953–3971. https://doi.org/10.1093/molbev/msab143

Distinct patterns of genetic variation at low-recombining genomic regions represent haplotype structureJun Ishigohoka, Karen Bascón-Cardozo, Andrea Bours, Janina Fuß, Arang Rhie, Jacquelyn Mountcastle, Bettina Haase, William Chow, Joanna Collins, Kerstin Howe, Marcela Uliano-Silva, Olivier Fedrigo, Erich D. Jarvis, Javier Pérez-Tris, Juan Carlos Il...<p>Genetic variation of the entire genome represents population structure, yet individual loci can show distinct patterns. Such deviations identified through genome scans have often been attributed to effects of selection instead of randomness. Th...Genome Evolution, Molecular Evolution, Population Genetics / GenomicsMatteo Fumagalli2023-10-13 11:58:47 View