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17 May 2021
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Relative time constraints improve molecular dating

Dating with constraints

Recommended by based on reviews by David Duchêne and 1 anonymous reviewer

Estimating the absolute age of diversification events is challenging, because molecular sequences provide timing information in units of substitutions, not years. Additionally, the rate of molecular evolution (in substitutions per year) can vary widely across lineages. Accurate dating of speciation events traditionally relies on non-molecular data. For very fast-evolving organisms such as SARS-CoV-2, for which samples are obtained over a time span, the collection times provide this external information from which we can learn the rate of molecular evolution and date past events (Boni et al. 2020). In groups for which the fossil record is abundant, state-of-the-art dating methods use fossil information to complement molecular data, either in the form of a prior distribution on node ages (Nguyen & Ho 2020), or as data modelled with a fossilization process (Heath et al. 2014).

Dating is a challenge in groups that lack fossils or other geological evidence, such as very old lineages and microbial lineages. In these groups, horizontal gene transfer (HGT) events have been identified as informative about relative dates: the ancestor of the gene's donor must be older than the descendants of the gene's recipient. Previous work using HGTs to date phylogenies have used methodologies that are ad-hoc (Davín et al 2018) or employ a small number of HGTs only (Magnabosco et al. 2018, Wolfe & Fournier 2018).

Szöllősi et al. (2021) present and validate a Bayesian approach to estimate the age of diversification events based on relative information on these ages, such as implied by HGTs. This approach is flexible because it is modular: constraints on relative node ages can be combined with absolute age information from fossil data, and with any substitution model of molecular evolution, including complex state-of-art models. To ease the computational burden, the authors also introduce a two-step approach, in which the complexity of estimating branch lengths in substitutions per site is decoupled from the complexity of timing the tree with branch lengths in years, accounting for uncertainty in the first step. Currently, one limitation is that the tree topology needs to be known, and another limitation is that constraints need to be certain. Users of this method should be mindful of the latter when hundreds of constraints are used, as done by Szöllősi et al. (2021) to date the trees of Cyanobacteria and Archaea.

Szöllősi et al. (2021)'s method is implemented in RevBayes, a highly modular platform for phylogenetic inference, rapidly growing in popularity (Höhna et al. 2016). The RevBayes tutorial page features a step-by-step tutorial "Dating with Relative Constraints", which makes the method highly approachable.

References:

Boni MF, Lemey P, Jiang X, Lam TT-Y, Perry BW, Castoe TA, Rambaut A, Robertson DL (2020) Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic. Nature Microbiology, 5, 1408–1417. https://doi.org/10.1038/s41564-020-0771-4

Davín AA, Tannier E, Williams TA, Boussau B, Daubin V, Szöllősi GJ (2018) Gene transfers can date the tree of life. Nature Ecology & Evolution, 2, 904–909. https://doi.org/10.1038/s41559-018-0525-3

Heath TA, Huelsenbeck JP, Stadler T (2014) The fossilized birth–death process for coherent calibration of divergence-time estimates. Proceedings of the National Academy of Sciences, 111, E2957–E2966. https://doi.org/10.1073/pnas.1319091111

Höhna S, Landis MJ, Heath TA, Boussau B, Lartillot N, Moore BR, Huelsenbeck JP, Ronquist F (2016) RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language. Systematic Biology, 65, 726–736. https://doi.org/10.1093/sysbio/syw021

Magnabosco C, Moore KR, Wolfe JM, Fournier GP (2018) Dating phototrophic microbial lineages with reticulate gene histories. Geobiology, 16, 179–189. https://doi.org/10.1111/gbi.12273

Nguyen JMT, Ho SYW (2020) Calibrations from the Fossil Record. In: The Molecular Evolutionary Clock: Theory and Practice  (ed Ho SYW), pp. 117–133. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-030-60181-2_8

Szollosi, G.J., Hoehna, S., Williams, T.A., Schrempf, D., Daubin, V., Boussau, B. (2021) Relative time constraints improve molecular dating. bioRxiv, 2020.10.17.343889, ver. 8  recommended and peer-reviewed by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2020.10.17.343889

Wolfe JM, Fournier GP (2018) Horizontal gene transfer constrains the timing of methanogen evolution. Nature Ecology & Evolution, 2, 897–903. https://doi.org/10.1038/s41559-018-0513-7

Relative time constraints improve molecular datingGergely J Szollosi, Sebastian Hoehna, Tom A Williams, Dominik Schrempf, Vincent Daubin, Bastien Boussau<p style="text-align: justify;">Dating the tree of life is central to understanding the evolution of life on Earth. Molecular clocks calibrated with fossils represent the state of the art for inferring the ages of major groups. Yet, other informat...Bioinformatics & Computational Biology, Genome Evolution, Phylogenetics / PhylogenomicsCécile Ané2020-10-21 23:39:17 View
29 Nov 2023
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Individual differences in developmental trajectory leave a male polyphenic signature in bulb mite populations

What determines whether to scramble or fight in male bulb mites

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

A classic textbook example in evolutionary ecology for phenotypic plasticity—the expression of different phenotypes by a genotype under different environmental conditions—is on Daphnia (Dodson 1989). If various species of this small crustacean are exposed to predation risk or cues thereof, their offspring show induced defense phenotypes including helmets, neck teeth, or head- and tail-spines. These induced morphological changes lower the risk of being eaten by a predator. As in Daphnia, induction can span over generations, while other induced phenotypic plastic changes are almost instantaneous, including many responses in physiology and behaviour (Gabriel et al. 2005). 

Larvae male bulb mites also show plasticity in morphologies throughout development. They can develop into a costly adult fighter morphology or a less costly, but vulnerable, scrambler type. The question Deere and Smallegange (Deere & Smallegange 2023) address is whether male bulb mite larvae can anticipate which type will likely be adaptive once they become adult, or alternatively, whether the resource availability or population density they experience during their larvae phase determines frequencies of adult scrambler and fighter types. They explore this question through experimental evolution, by removing different fractions of developing intermediate larva types. They thereby manipulate the stage structure of populations and alter selective forces on these stages. The potential shift of fixed genetics, imposed by the experimental selection regimes, is evaluated by fitness assays in green garden experiments.

The exciting extension to classical experiments on phenotypic plasticity is that the authors aim at exploring eco-evolutionary feedbacks experimentally in a system that is a little more complex than basic host-parasite or predator-prey systems. The latter involve, for instance, rotifer-algae dynamics (Yoshida et al. 2003; Becks et al. 2012) or similar simple lab systems for which eco-evolutionary feedbacks have been demonstrated. The challenge for the exploration of more complex systems is revealed in the study by Deere and Smallegange. Their findings suggest that the frequencies of adult male morphotype is triggered by the environmental condition (nutrient availability) during the larval phase, i.e. a simple environmental induced plastic response. No fixed genetic shift in determining adult morphotype frequencies occurs. The trigger at the larva phase remains also not perfectly determined in their experiments, as population density and resource (food) availability are partly confounded. Additional complexity and selective aspects come into play in this system, as the targeted developmental stages that develop into fighter male morphs are also dispersal morphs. If selection on dispersal to avoid residing in food-limited environments is strong, triggering genetic shifts in fighter morphs by local population structure might be hard to experimentally achieve. Small sample sizes limit conclusions on complex interactions among duration of the experiment, population size, developmental stage types, and adult fighter frequencies. The presented study (Deere & Smallegange 2023) helps to bridge theoretical predictions and empirical evidence for eco-evolutionary feedbacks that goes beyond simple ecological-driven changes in population dynamics (Govaert et al. 2019).  

 

References

 

Becks, L., Ellner, S.P., Jones, L.E. & Hairston, N.G. (2012). The functional genomics of an eco-evolutionary feedback loop: linking gene expression, trait evolution, and community dynamics. Ecol. Lett., 15, 492-501.
https://doi.org/10.1111/j.1461-0248.2012.01763.x
 
Deere, J.A. & Smallegange, I.M. (2023). Individual differences in developmental trajectory leave a male polyphenic signature in bulb mite populations. bioRxiv, 2023.02.06.527265, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology.
https://doi.org/10.1101/2023.02.06.527265
 
Dodson, S. (1989). Predator-induced Reaction Norms. Bioscience, 39, 447-452.
https://doi.org/10.2307/1311136
 
Gabriel, W., Luttbeg, B., Sih, A. & Tollrian, R. (2005). Environmental tolerance, heterogeneity, and the evolution of reversible plastic responses. Am. Nat., 166, 339-53.
https://doi.org/10.1086/432558
 
Govaert, L., Fronhofer, E.A., Lion, S., Eizaguirre, C., Bonte, D., Egas, M., et al. (2019). Eco-evolutionary feedbacks-Theoretical models and perspectives. Funct. Ecol., 33, 13-30.
https://doi.org/10.1111/1365-2435.13241
 
Yoshida, T., Jones, L.E., Ellner, S.P., Fussmann, G.F. & Hairston, N.G. (2003). Rapid evolution drives ecological dynamics in a predator-prey system. Nat. 2003 4246946, 424, 303-306.
https://doi.org/10.1038/nature01767

Individual differences in developmental trajectory leave a male polyphenic signature in bulb mite populationsJacques A. Deere & Isabel M. Smallegange<p style="text-align: justify;">Developmental plasticity alters phenotypes and can in that way change the response to selection. When alternative phenotypes show different life history trajectories, developmental plasticity can also affect, and be...Evolutionary Ecology, Life History, Phenotypic Plasticity, Sexual SelectionUlrich Karl Steiner2023-02-07 12:14:33 View
29 Nov 2022
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Joint inference of adaptive and demographic history from temporal population genomic data

Inference of genome-wide processes using temporal population genomic data

Recommended by based on reviews by Lawrence Uricchio and 2 anonymous reviewers

Evolutionary genomics, and population genetics in particular, aim to decipher the respective influence of neutral and selective forces shaping genetic polymorphism in a species/population. This is a much-needed requirement before scanning genome data for footprints of species adaptation to their biotic and abiotic environment (Johri et al. 2022). In general, we would like to quantify the proportion of the genome evolving neutrally and under selective (positive, balancing and negative) pressures (Kern and Hahn 2018, Johri et al. 2021). We thus need to understand patterns of linked selection along the genome, that is how the distribution of genetic polymorphisms is shaped by selected sites and the recombination landscape. The present contribution by Pavinato et al. (2022) provides an additional method in the population genomics toolbox to quantify the extent of linked positive and negative selection using temporal data.

The availability of genomics data for model and non-model species has led to improvement of the modeling framework for demography and selection (Johri et al. 2022), but also new inference methods making use of the full genome data based on the Sequential Markovian Coalescent (SMC, Li and Durbin 2011), Approximate Bayesian Computation (ABC, Jay et al. 2019), ABC and machine learning (Pudlo et al. 2016, Raynal et al. 2019) or Deep Learning (Sanchez et al. 2021). These methods are based on one sample in time and the use of the coalescent theory to reconstruct the past (demographic) history. However, it is also possible to obtain for many species temporal data sampled over several time points. For species with short generation time (in experimental evolution or monitored populations), one can sample a population every couple of generations as exemplified with Drosophila melanogaster (Bergland et al. 2010). For species with longer generation times that cannot be easily regularly sampled in time, it becomes possible to sequence available specimens from museums (e.g. Cridland et al. 2018) or ancient DNA samples. Methods using temporal data are based on the classical population genomics assumption that demography (migration, population subdivision, population size changes) leaves a genome-wide signal, while selection leaves a localized signal in the close vicinity of the causal mutation. Several methods do assess the demography of a population (change in effective population size, Ne, in time) using temporal data (e.g. Jorde and Ryman 2007) which can be used to calibrate the detection of loci under strong positive selection (Foll et al. 2014). Recently Buffalo and Coop (2020) used genome-wide covariance between allele frequency changes across time samples (and across replicates) to quantify the effects of linked selection over short timescales. 

In the present contribution, Pavinato et al. (2022) make use of temporal data to draw the joint estimation of demographic and selective parameters using a simulation-based method (ABC-Random Forests). This study by Pavinato et al. (2022) builds a framework allowing to infer the census size of the population in time (N) separately from the effect of genetic drift, which is determined by change in effective population size (Ne) in time, as well estimates of genome-wide parameters of selection. In a nutshell, the authors use a forward simulator and summarize genome data by genomic windows using classic statistics (nucleotide diversity, Tajima’s D, FST, heterozygosity) between time samples and for each sample. They specifically use the distributions (higher moments) of these statistics among all windows. The authors combine as input for the ABC-RF, vectors of summary statistics, model parameters and five latent variables: Ne, the ratio Ne/N, the number of beneficial mutations under strong selection, the average selection coefficient of strongly selected mutations, and the average substitution load. Indeed, the authors are interested in three different types of selection components: 1) the adaptive potential of a population which is estimated as the population mutation rate of beneficial mutations (θb), 2) the number of mutations under strong selection (irrespective of whether they reached fixation or not), and 3) the overall population fitness which is a function of the genetic load. In other words, the novelty of this method is not to focus on the detection of loci under selection, but to infer key parameters/distributions summarizing the genome-wide signal of demography and (positive and negative) selection. As a proof of principle, the authors then apply their method to a dataset of feral populations of honey bees (Apis mellifera) collected in California across many years and recovered from Museum samples (Cridland et al. 2018). The approach yields estimates of Ne which are on the same order of magnitude of previous estimates in hymenopterans, and the authors discuss why the different populations show various values of Ne and N which can be explained by different history of admixture with wild but also domesticated lineages of bees.

This study focuses on quantifying the genome-wide joint footprints of demography, and strong positive and negative selection to determine which proportion of the genome evolves neutrally or not. Further application of this method can be anticipated, for example, to study species with ecological and life-history traits which generate discrepancies between census size and Ne, for example for plants with selfing or seed banking (Sellinger et al. 2020), and for which the genome-wide effect of linked selection is not fully understood.

References

Johri P, Aquadro CF, Beaumont M, Charlesworth B, Excoffier L, Eyre-Walker A, Keightley PD, Lynch M, McVean G, Payseur BA, Pfeifer SP, Stephan W, Jensen JD (2022) Recommendations for improving statistical inference in population genomics. PLOS Biology, 20, e3001669. https://doi.org/10.1371/journal.pbio.3001669

Kern AD, Hahn MW (2018) The Neutral Theory in Light of Natural Selection. Molecular Biology and Evolution, 35, 1366–1371. https://doi.org/10.1093/molbev/msy092

Johri P, Riall K, Becher H, Excoffier L, Charlesworth B, Jensen JD (2021) The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects. Molecular Biology and Evolution, 38, 2986–3003. https://doi.org/10.1093/molbev/msab050

Pavinato VAC, Mita SD, Marin J-M, Navascués M de (2022) Joint inference of adaptive and demographic history from temporal population genomic data. bioRxiv, 2021.03.12.435133, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.03.12.435133

Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. Nature, 475, 493–496. https://doi.org/10.1038/nature10231

Jay F, Boitard S, Austerlitz F (2019) An ABC Method for Whole-Genome Sequence Data: Inferring Paleolithic and Neolithic Human Expansions. Molecular Biology and Evolution, 36, 1565–1579. https://doi.org/10.1093/molbev/msz038

Pudlo P, Marin J-M, Estoup A, Cornuet J-M, Gautier M, Robert CP (2016) Reliable ABC model choice via random forests. Bioinformatics, 32, 859–866. https://doi.org/10.1093/bioinformatics/btv684

Raynal L, Marin J-M, Pudlo P, Ribatet M, Robert CP, Estoup A (2019) ABC random forests for Bayesian parameter inference. Bioinformatics, 35, 1720–1728. https://doi.org/10.1093/bioinformatics/bty867

Sanchez T, Cury J, Charpiat G, Jay F (2021) Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation. Molecular Ecology Resources, 21, 2645–2660. https://doi.org/10.1111/1755-0998.13224

Bergland AO, Behrman EL, O’Brien KR, Schmidt PS, Petrov DA (2014) Genomic Evidence of Rapid and Stable Adaptive Oscillations over Seasonal Time Scales in Drosophila. PLOS Genetics, 10, e1004775. https://doi.org/10.1371/journal.pgen.1004775

Cridland JM, Ramirez SR, Dean CA, Sciligo A, Tsutsui ND (2018) Genome Sequencing of Museum Specimens Reveals Rapid Changes in the Genetic Composition of Honey Bees in California. Genome Biology and Evolution, 10, 458–472. https://doi.org/10.1093/gbe/evy007

Jorde PE, Ryman N (2007) Unbiased Estimator for Genetic Drift and Effective Population Size. Genetics, 177, 927–935. https://doi.org/10.1534/genetics.107.075481

Foll M, Shim H, Jensen JD (2015) WFABC: a Wright–Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data. Molecular Ecology Resources, 15, 87–98. https://doi.org/10.1111/1755-0998.12280

Buffalo V, Coop G (2020) Estimating the genome-wide contribution of selection to temporal allele frequency change. Proceedings of the National Academy of Sciences, 117, 20672–20680. https://doi.org/10.1073/pnas.1919039117

Sellinger TPP, Awad DA, Moest M, Tellier A (2020) Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLOS Genetics, 16, e1008698. https://doi.org/10.1371/journal.pgen.1008698

Joint inference of adaptive and demographic history from temporal population genomic dataVitor A. C. Pavinato, Stéphane De Mita, Jean-Michel Marin, Miguel de Navascués<p style="text-align: justify;">Disentangling the effects of selection and drift is a long-standing problem in population genetics. Simulations show that pervasive selection may bias the inference of demography. Ideally, models for the inference o...Adaptation, Population Genetics / GenomicsAurelien Tellier2021-10-20 09:41:26 View
06 Mar 2023
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Extrinsic mortality and senescence: a guide for the perplexed

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

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

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

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

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

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

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

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

REFERENCES

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

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

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

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

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

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

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

Extrinsic mortality and senescence: a guide for the perplexedCharlotte de Vries, Matthias Galipaud, Hanna Kokko<p style="text-align: justify;">Do environments or species traits that lower the mortality of individuals create selection for delaying senescence? Reading the literature creates an impression that mathematically oriented biologists cannot agree o...Evolutionary Dynamics, Evolutionary Ecology, Evolutionary Theory, Life HistorySinead English2022-08-26 14:30:16 View
18 Nov 2022
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Fitness costs and benefits in response to artificial artesunate selection in Plasmodium

The importance of understanding fitness costs associated with drug resistance throughout the life cycle of malaria parasites

Recommended by based on reviews by Sarah Reece and Marianna Szucs

Antimalarial resistance is a major hurdle to malaria eradication efforts. The spread of drug resistance follows basic evolutionary principles, with competitive interactions between resistant and susceptible malaria strains being central to the fitness of resistant parasites. These competitive interactions can be used to design resistance management strategies, whereby a fitness cost of resistant parasites can be exploited through maintaining competitive suppression of the more fit drug-susceptible parasites. This can potentially be achieved using lower drug dosages or lower frequency of drug treatments. This approach has been demonstrated to work empirically in a rodent malaria model [1,2] and has been demonstrated to have clinical success in cancer treatments [3]. However, these resistance management approaches assume a fitness cost of the resistant pathogen, and, in the case of malaria parasites in general, and for artemisinin resistant parasites in particular, there is limited information on the presence of such fitness cost. The best suggestive evidence for the presence of fitness costs comes from the discontinuation of the use of the drug, which, in the case of chloroquine, was followed by a gradual drop in resistance frequency over the following decade [see e.g. 4,5]. However, with artemisinin derivative drugs still in use, alternative ways to study the presence of fitness costs need to be undertaken. 
There are several good in vitro studies demonstrating artemisinin resistant parasites being competitively suppressed by wildtype parasites [see e.g. 6–9], however, these have the limitation that they will only be able to detect the fitness cost during the blood stage of the infection and in an artificial environment. So far, there have not been animal models that have thoroughly studied the presence of resistance fitness costs for artemisinin resistant parasites. Moreover, in these types of studies, the focus is mostly on the fitness cost as detected in the vertebrate host. However, malaria parasites spent a significant portion of their life cycle in the mosquito host, where fitness costs could also be expressed. Overall, it is the fitness over the entire life cycle of the parasite that would determine if and to what extent a reduction in resistance frequency would be observed when the use of a drug is stopped. 
Here, Villa and colleagues present a study to quantify such fitness cost of artesunate-resistant parasites, not only in a vertebrate host, but also in the mosquito vector [10]. They used the underutilized model system of avian malaria species Plasmodium relictum in canaries. Villa and colleagues selected for several different resistance strains, which had a similar delayed clearance phenotype as observed in the field. Interestingly, they did not find evidence of a fitness cost in the vertebrate host. In fact, the resistant strains reached greater parasitaemia than the susceptible strains. From this set of experiments it is unclear whether this is an anomaly or a relevant result. Future work should establish this, though fitness benefits associated with drug resistance have been seen before in Leishmania parasites [11]. An important caveat to the present study is that the parasites were grown in the absence of competition and it is feasible that a cost is not detected when growing by themselves, but would become apparent when in competition. However, these types of experiments are technologically more challenging to perform as it would require an accurate quantification methodology able to distinguish based on one SNP. This problem has been circumvented by either using relative peak height in sanger sequencing [12], or via the likely more accurate route of pyrosequencing [7–9], though these methodologies only give relative frequencies rather than absolute densities. 
 
The most interesting observation in the study by Villa et al is that the authors detected a fitness cost being played out in the mosquito vector, where the resistant strains had a decreased infectivity compared to the susceptible strain. This finding is important because 1) it demonstrates that the whole life cycle needs to be taken into account when understanding fitness costs, 2) resistance management strategies that are based on treatment within the vertebrate host may not have the intended effect if the cost does not play out in this host, and 3) it opens new research avenues to explore the possibility of exploiting fitness costs in mosquito vector. Future research should focus on incorporating these assays on fitness costs in mosquitoes, particularly for P. falciparum parasites. Additionally, it would be interesting to expand this work in a competitive environment, both in the vertebrate host as in the mosquito host. Finally, it would be important to establish the generalizability of such fitness cost in mosquitoes. If it is a significant factor, mathematical models could incorporate this effect in predictions on the spread of resistance.

References

[1] Huijben S, Bell AS, Sim DG, Tomasello D, Mideo N, Day T, et al. 2013. Aggressive chemotherapy and the selection of drug resistant pathogens. PLoS Pathog. 9(9): e1003578. https://doi.org/10.1371/journal.ppat.1003578
 
[2] Huijben S, Nelson WA, Wargo AR, Sim DG, Drew DR, Read AF. 2010. Chemotherapy, within-host ecology and the fitness of drug-resistant malaria parasites. Evolution (N Y). 64(10): 2952-68. https://doi.org/10.1111/j.1558-5646.2010.01068.x
 
[3] Zhang J, Cunningham JJ, Brown JS, Gatenby RA. 2017. Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer. Nat Commun. 8(1). https://doi.org/10.1038/s41467-017-01968-5
 
[4] Laufer MK, Takala-Harrison S, Dzinjalamala FK, Stine OC, Taylor TE, Plowe C v. 2010. Return of chloroquine-susceptible falciparum malaria in Malawi was a reexpansion of diverse susceptible parasites. J Infect Dis. 202(5): 801-808. https://doi.org/10.1086/655659 

[5] Mharakurwa S, Matsena-Zingoni Z, Mudare N, Matimba C, Gara TX, Makuwaza A, et al. 2021. Steep rebound of chloroquine-sensitive Plasmodium falciparum in Zimbabwe. J Infect Dis. 223(2): 306-9. https://doi.org/10.1093/infdis/jiaa368
 
[6] Tirrell AR, Vendrely KM, Checkley LA, Davis SZ, McDew-White M, Cheeseman IH, et al. 2019. Pairwise growth competitions identify relative fitness relationships among artemisinin resistant Plasmodium falciparum field isolates. Malar J. 18: 295. https://doi.org/10.1186/s12936-019-2934-4
 
[7] Hott A, Tucker MS, Casandra D, Sparks K, Kyle DE. 2015. Fitness of artemisinin-resistant Plasmodium falciparum in vitro. J Antimicrob Chemother. 70(10): 2787-2796. https://doi.org/10.1093/jac/dkv199
 
[8] Straimer J, Gnädig NF, Stokes BH, Ehrenberger M, Crane AA, Fidock DA. 2017. Plasmodium falciparum K13 mutations differentially impact ozonide susceptibility and parasite fitness in vitro. mBio. 8(2): e00172-17. https://doi.org/10.1128/mBio.00172-17
 
[9] Nair S, Li X, Arya GA, McDew-White M, Ferrari M, Nosten F, et al. 2018. Fitness costs and the rapid spread of kelch13-C580Y substitutions conferring artemisinin resistance. Antimicrob Agents Chemother. 62(9). https://doi.org/10.1128/AAC.00605-18
 
[10] Villa M, Berthomieu A, Rivero A. Fitness costs and benefits in response to artificial artesunate selection in Plasmodium. 2022. bioRxiv, 20220128478164, ver 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.01.28.478164
 
[11] Vanaerschot M, Decuypere S, Berg M, Roy S, Dujardin JC. 2013. Drug-resistant microorganisms with a higher fitness--can medicines boost pathogens? Crit Rev Microbiol. 39(4): 384-394. https://doi.org/10.3109/1040841X.2012.716818
 
[12] Hassett MR, Roepe PD. In vitro growth competition experiments that suggest consequences of the substandard artemisinin epidemic that may be accelerating drug resistance in P. falciparum malaria. 2021. PLoS One. 16(3): e0248057. https://doi.org/10.1371/journal.pone.0248057

Fitness costs and benefits in response to artificial artesunate selection in PlasmodiumVilla M, Berthomieu A, Rivero A<p style="text-align: justify;">Drug resistance is a major issue in the control of malaria. Mutations linked to drug resistance often target key metabolic pathways and are therefore expected to be associated with biological costs. The spread of dr...Evolutionary Applications, Life HistorySilvie Huijben2022-01-31 13:01:16 View
30 Jun 2023
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How do monomorphic bacteria evolve? The Mycobacterium tuberculosis complex and the awkward population genetics of extreme clonality

How the tubercle bacillus got its genome: modernising, modelling, and making sense of the stories we tell

Recommended by based on reviews by 2 anonymous reviewers

In this instructive review, Stritt and Gagneux offer a balanced perspective on the evolutionary forces shaping Mycobacterium tuberculosis and make the case that our instinct for storytelling be balanced with quantitative models. M. tuberculosis is perhaps the best-known clonal bacterial pathogen – evolving largely in the absence of horizontal gene transfer. Its genome is full of puzzling patterns, including much higher GC content than most intracellular pathogens (which suggests efficient selection to resist AT-skewed mutational bias) but a very high ratio of nonsynonymous to synonymous substitution rates (dN/dS ~ 0.5, typically interpreted as weak selection against deleterious amino acid changes). 

The authors offer alternative explanations for these patterns, framing the question: is M. tuberculosis evolution shaped mainly by drift or by efficient selection? They propose that this question can only be answered by accounting for the pathogen’s extreme clonality. A clonal lifestyle can have its advantages, for example when adaptations must arise in a particular order (Kondrashov and Kondrashov 2001). An important disadvantage highlighted by the authors are linkage effects: without recombination to shuffle them up, beneficial mutations are linked to deleterious mutations in the same genome (hitchhiking) and purging deleterious mutations also purges neutral diversity across the genome (background selection). The authors propose the latter – efficient purifying selection and strong linkage – as an explanation for the low genetic diversity observed in M. tuberculosis. This is of course not exclusive of other related explanations, such as clonal interference (Gerrish and Lenski 1998). They also champion the use of forward evolutionary simulations (Haller and Messer 2019) to model the interplay between selection, recombination, and demography as a powerful alternative to traditional backward coalescent models.

At times, Stritt and Gagneux are pessimistic about our existing methods – arguing that dN/dS and homoplasies “tell us little about the frequency and strength of selection.” Even though I favour a more optimistic view, I fully agree that our traditional population genetic metrics are sensitive to a slew of different deviations from a standard neutral evolution model and must be interpreted with caution. As I and others have argued, the extent of recombination (measured as the amount of linkage in a genome) is a key factor in determining how best to test for natural selection (Shapiro et al. 2009) and to conduct genotype-phenotype association studies (Chen and Shapiro 2021) in microbes. While this article is focused on the well-studied M. tuberculosis complex, there are many parallels with other clonal bacteria, including pathogens and symbionts. Whatever your favourite bug, we must all be careful to make sure the stories we tell about them are not “just so tales” but are supported, to the extent possible, by data and quantitative models.

References

Chen, Peter E., and B. Jesse Shapiro. 2021. "Classic Genome-Wide Association Methods Are Unlikely to Identify Causal Variants in Strongly Clonal Microbial Populations." bioRxiv. 
https://doi.org/10.1101/2021.06.30.450606
 
Gerrish, P. J., and R. E. Lenski. 1998. "The Fate of Competing Beneficial Mutations in an Asexual Population." Genetica 102-103 (1-6): 127-44.
https://doi.org/10.1023/A:1017067816551
 
Haller, Benjamin C., and Philipp W. Messer. 2019. "SLiM 3: Forward Genetic Simulations Beyond the Wright-Fisher Model." Molecular Biology and Evolution 36 (3): 632-37.
https://doi.org/10.1093/molbev/msy228
 
Kondrashov, F. A., and A. S. Kondrashov. 2001. "Multidimensional Epistasis and the Disadvantage of Sex." Proceedings of the National Academy of Sciences of the United States of America 98 (21): 12089-92.
https://doi.org/10.1073/pnas.211214298
 
Shapiro, B. Jesse, Lawrence A. David, Jonathan Friedman, and Eric J. Alm. 2009. "Looking for Darwin's Footprints in the Microbial World." Trends in Microbiology 17 (5): 196-204.
https://doi.org/10.1016/j.tim.2009.02.002 

Stritt, C., Gagneux, S. (2023). How do monomorphic bacteria evolve? The Mycobacterium tuberculosis complex and the awkward population genetics of extreme clonality. EcoEvoRxiv, ver.3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.32942/X2GW2P

How do monomorphic bacteria evolve? The *Mycobacterium tuberculosis* complex and the awkward population genetics of extreme clonalityChristoph Stritt, Sebastien Gagneux<p style="text-align: justify;">Exchange of genetic material through sexual reproduction or horizontal gene transfer is ubiquitous in nature. Among the few outliers that rarely recombine and mainly evolve by <em>de novo</em> mutation are a group o...Evolutionary Dynamics, Genome Evolution, Molecular Evolution, Population Genetics / Genomics, Reproduction and SexB. Jesse Shapiro Gonçalo Themudo2022-12-16 13:41:53 View
02 Sep 2022
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Introgression between highly divergent sea squirt genomes: an adaptive breakthrough?

A match made in the Anthropocene: human-mediated adaptive introgression across a speciation continuum

Recommended by based on reviews by Michael Westbury, Andrew Foote and Erin Calfee

The long-distance transport and introduction of new species by humans is increasingly leading divergent lineages to interact, and sometimes interbreed, even after thousands or millions of years of separation. It is thus of prime importance to understand the consequences of these contemporary admixture events on the evolutionary fitness of interacting organisms, and their ecological implications.

Ciona robusta and Ciona intestinalis are two species of sea squirts that diverged between 1.5 and 2 million years ago and recently came into contact again. This occurred through human-mediated introduction of C. robusta (native to the Northwest Pacific) into the range of C. intestinalis (the English channeled Northeast Atlantic). In this study, Fraïsse et al. (2022) follow up on earlier work by Le Moan et al. (2021), who had identified a long genomic hotspot of introgression of C. robusta ancestry segments in chromosome 5 of C. intestinalis. The hotspot bears suggestive evidence of positive selection and the authors aimed to investigate this further using fully phased whole-genome sequences.

The authors narrow down on the exact boundaries of the introgressed region, and make a compelling case that it has been the likely target of positive selection after introgression, using various complementary approaches based on patterns of population differentiation, haplotype structure and local levels of diversity in the region. Using extensive demographic modeling, they also show that the introgression event was likely recent (approximately 75 years ago), and distinct from other tracts in the C. intestinalis genome that are likely a product of more ancient episodes of interbreeding in the past 30,000 years. Narrowing down on the potential drivers of selection, the authors show that candidate SNPs in the region overlap with the cytochrome family 2 subfamily U gene - involved in the detoxification of exogenous compounds - potentially reflecting adaptation to chemicals encountered in the sea squirt's environment. There also appears to be copy number variation at the candidate SNPs, which provides clues into the adaptation mechanism in the region.

All reviewers agreed that the work carried out by the authors is elegant and the results are robustly supported and well presented. In a round of reviews, various clarifications of the manuscript were suggested by the reviewers, including on the quality of the newly generated sequencing data, and some suggestions for qualifications on the conclusions reached by the authors as well as changes in the figures to increase their clarity. The authors addressed the different concerns of the reviewers, and the new version is much improved. 

This study into human-mediated introgression and its consequences for adaptation is, in my view, both well thought-out and executed. I therefore provide an enthusiastic recommendation of this manuscript.

References

Fraïsse C, Le Moan A, Roux C, Dubois G, Daguin-Thiébaut C, Gagnaire P-A, Viard F and Bierne N (2022) Introgression between highly divergent sea squirt genomes: an adaptive breakthrough? bioRxiv, 2022.03.22.485319, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.03.22.485319

Le Moan A, Roby C, Fraïsse C, Daguin-Thiébaut C, Bierne N, Viard F (2021) An introgression breakthrough left by an anthropogenic contact between two ascidians. Molecular Ecology, 30, 6718–6732. https://doi.org/10.1111/mec.16189

Introgression between highly divergent sea squirt genomes: an adaptive breakthrough?Christelle Fraïsse, Alan Le Moan, Camille Roux, Guillaume Dubois, Claire Daguin-Thiébaut, Pierre-Alexandre Gagnaire, Frédérique Viard, Nicolas Bierne<p style="text-align: justify;">Human-mediated introductions are reshuffling species distribution on a global scale. Consequently, an increasing number of allopatric taxa are now brought into contact, promoting introgressive hybridization between ...Adaptation, Hybridization / Introgression, Population Genetics / GenomicsFernando Racimo2022-04-14 15:30:42 View
17 Jun 2022
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Spontaneous parthenogenesis in the parasitoid wasp Cotesia typhae: low frequency anomaly or evolving process?

The potential evolutionary importance of low-frequency flexibility in reproductive modes

Recommended by based on reviews by Michael Lattorff and Jens Bast

Occasional events of asexual reproduction in otherwise sexual taxa have been documented since a long time. Accounts range from observations of offspring development from unfertilized eggs in Drosophila to rare offspring production by isolated females in lizards and birds (e.g., Stalker 1954, Watts et al 2006, Ryder et al. 2021). Many more such cases likely await documentation, as rare events are inherently difficult to observe. These rare events of asexual reproduction are often associated with low offspring fitness (“tychoparthenogenesis”), and have mostly been discarded in the evolutionary literature as reproductive accidents without evolutionary significance. Recently, however, there has been an increased interest in the details of evolutionary transitions from sexual to asexual reproduction (e.g., Archetti 2010, Neiman et al.2014, Lenormand et al. 2016), because these details may be key to understanding why successful transitions are rare, why they occur more frequently in some groups than in others, and why certain genetic mechanisms of ploidy maintenance or ploidy restoration are more often observed than others. In this context, the hypothesis has been formulated that regular or even obligate asexual reproduction may evolve from these rare events of asexual reproduction (e.g., Schwander et al. 2010).

A new study by Capdevielle Dulac et al. (2022) now investigates this question in a parasitoid wasp, highlighting also the fact that what is considered rare or occasional may differ from one system to the next. The results show “rare” parthenogenetic production of diploid daughters occurring at variable frequencies (from zero to 2 %) in different laboratory strains, as well as in a natural population. They also demonstrate parthenogenetic production of female offspring in both virgin females and mated ones, as well as no reduced fecundity of parthenogenetically produced offspring. These findings suggest that parthenogenetic production of daughters, while still being rare, may be a more regular and less deleterious reproductive feature in this species than in other cases of occasional asexuality. Indeed, haplodiploid organisms, such as this parasitoid wasp have been hypothesized to facilitate evolutionary transitions to asexuality (Neimann et al. 2014, Van Der Kooi et al. 2017). First, in haploidiploid organisms, females are diploid and develop from normal, fertilized eggs, but males are haploid as they develop parthenogenetically from unfertilized eggs. This means that, in these species, fertilization is not necessarily needed to trigger development, thus removing one of the constraints for transitions to obligate asexuality (Engelstädter 2008, Vorburger 2014). Second, spermatogenesis in males occurs by a modified meiosis that skips the first meiotic division (e.g., Ferree et al. 2019). Haploidiploid organisms may thus have a potential route for an evolutionary transition to obligate parthenogenesis that is not available to organisms: The pathways for the modified meiosis may be re-used for oogenesis, which might result in unreduced, diploid eggs. Third, the particular species studied here regularly undergoes inbreeding by brother-sister mating within their hosts. Homozygosity, including at the sex determination locus (Engelstädter 2008), is therefore expected to have less negative effects in this species compared to many other, non-inbreeding haplodipoids (see also Little et al. 2017). This particular species may therefore be less affected by loss of heterozygosity, which occurs in a fashion similar to self-fertilization under many forms of non-clonal parthenogenesis. 

Indeed, the study also addresses the mechanisms underlying parthenogenesis in the species. Surprisingly, the authors find that parthenogenetically produced females are likely produced by two distinct genetic mechanisms. The first results in clonality (maintenance of the maternal genotype), whereas the second one results in a loss of heterozygosity towards the telomeres, likely due to crossovers occurring between the centromeres and the telomeres. Moreover, bacterial infections appear to affect the propensity of parthenogenesis but are unlikely the primary cause. Together, the finding suggests that parthenogenesis is a variable trait in the species, both in terms of frequency and mechanisms. It is not entirely clear to what degree this variation is heritable, but if it is, then these results constitute evidence for low-frequency existence of variable and heritable parthenogenesis phenotypes, that is, the raw material from which evolutionary transitions to more regular forms of parthenogenesis may occur.

 

References

Archetti M (2010) Complementation, Genetic Conflict, and the Evolution of Sex and Recombination. Journal of Heredity, 101, S21–S33. https://doi.org/10.1093/jhered/esq009

Capdevielle Dulac C, Benoist R, Paquet S, Calatayud P-A, Obonyo J, Kaiser L, Mougel F (2022) Spontaneous parthenogenesis in the parasitoid wasp Cotesia typhae: low frequency anomaly or evolving process? bioRxiv, 2021.12.13.472356, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.12.13.472356

Engelstädter J (2008) Constraints on the evolution of asexual reproduction. BioEssays, 30, 1138–1150. https://doi.org/10.1002/bies.20833

Ferree PM, Aldrich JC, Jing XA, Norwood CT, Van Schaick MR, Cheema MS, Ausió J, Gowen BE (2019) Spermatogenesis in haploid males of the jewel wasp Nasonia vitripennis. Scientific Reports, 9, 12194. https://doi.org/10.1038/s41598-019-48332-9

van der Kooi CJ, Matthey-Doret C, Schwander T (2017) Evolution and comparative ecology of parthenogenesis in haplodiploid arthropods. Evolution Letters, 1, 304–316. https://doi.org/10.1002/evl3.30

Lenormand T, Engelstädter J, Johnston SE, Wijnker E, Haag CR (2016) Evolutionary mysteries in meiosis. Philosophical Transactions of the Royal Society B: Biological Sciences, 371, 20160001. https://doi.org/10.1098/rstb.2016.0001

Little CJ, Chapuis M-P, Blondin L, Chapuis E, Jourdan-Pineau H (2017) Exploring the relationship between tychoparthenogenesis and inbreeding depression in the Desert Locust, Schistocerca gregaria. Ecology and Evolution, 7, 6003–6011. https://doi.org/10.1002/ece3.3103

Neiman M, Sharbel TF, Schwander T (2014) Genetic causes of transitions from sexual reproduction to asexuality in plants and animals. Journal of Evolutionary Biology, 27, 1346–1359. https://doi.org/10.1111/jeb.12357

Ryder OA, Thomas S, Judson JM, Romanov MN, Dandekar S, Papp JC, Sidak-Loftis LC, Walker K, Stalis IH, Mace M, Steiner CC, Chemnick LG (2021) Facultative Parthenogenesis in California Condors. Journal of Heredity, 112, 569–574. https://doi.org/10.1093/jhered/esab052

Schwander T, Vuilleumier S, Dubman J, Crespi BJ (2010) Positive feedback in the transition from sexual reproduction to parthenogenesis. Proceedings of the Royal Society B: Biological Sciences, 277, 1435–1442. https://doi.org/10.1098/rspb.2009.2113

Stalker HD (1954) Parthenogenesis in Drosophila. Genetics, 39, 4–34. https://doi.org/10.1093/genetics/39.1.4

Vorburger C (2014) Thelytoky and Sex Determination in the Hymenoptera: Mutual Constraints. Sexual Development, 8, 50–58. https://doi.org/10.1159/000356508

Watts PC, Buley KR, Sanderson S, Boardman W, Ciofi C, Gibson R (2006) Parthenogenesis in Komodo dragons. Nature, 444, 1021–1022. https://doi.org/10.1038/4441021a

Spontaneous parthenogenesis in the parasitoid wasp Cotesia typhae: low frequency anomaly or evolving process?Claire Capdevielle Dulac, Romain Benoist, Sarah Paquet, Paul-André Calatayud, Julius Obonyo, Laure Kaiser, Florence Mougel<p style="text-align: justify;">Hymenopterans are haplodiploids and unlike most other Arthropods they do not possess sexual chromosomes. Sex determination typically happens via the ploidy of individuals: haploids become males and diploids become f...Evolutionary Ecology, Life History, Reproduction and SexChristoph Haag2021-12-16 15:25:16 View
25 Jan 2024
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Sperm production and allocation in response to risk of sperm competition in the black soldier fly Hermetia illucens

Elevated sperm production and faster transfer: plastic responses to the risk of sperm competition in males of the black sodier fly Hermetia illuce

Recommended by ORCID_LOGO based on reviews by Rebecca Boulton, Isabel Smallegange and 1 anonymous reviewer

In this paper (Manas et al., 2023), the authors investigate male responses to risk of sperm competition in the black soldier fly Hermetia illuce, a widespread insect that has gained recent attention for its potential to be farmed for sustainable food production (Tomberlin & van Huis, 2020).

Using an experimental approach that simulated low-risk (males were kept individually) and high-risk (males were kept in groups of 10) of sperm competition, they found that males reared in groups showed a significant increase in sperm production compared with males reared individually. This shows a response to the rearing environment in sperm production that is consistent with an increase in the perceived risk of sperm competition.

These males were then used in mating experiments to determine whether sperm allocation to females during mating was influenced by the perceived risk of sperm competition. Mating experiments were initiated in groups, since mating only occurs when more than one male and one female are present, indicating strong sexual selection in the wild. Once a copulation began, the pair was moved to a new environment with no competition, with male competitors, or with other females, to test how social environment and potentially the sex of surrounding individuals influenced sperm allocation during mating. Copulation duration and the number of sperm transferred were subsequently counted.

In these mating experiments, the number of sperm stored in the female spermathecae increased under immediate risk of sperm competition. Interestingly, this was not because males copulated for longer depending on the risk of sperm competition, indicating that males respond plastically to the risk of competition by elevating their investment in sperm production and speed of sperm transfer. There was no difference between competitive environments consisting of males or females respectively, suggesting that it is the presence of other flies per se that influence sperm allocation.

The study provides an interesting new example of how males alter reproductive investment in response to social context and sexual competition in their environment. In addition, it provides new insights into the reproductive biology of the black soldier fly Hermetia illucens, which may be relevant for optimizing farming conditions.

References

Manas F, Labrousse C, Bressac C (2023) Sperm production and allocation in response to risks of sperm competition in the black soldier fly Hermetia illucens. bioRxiv, 2023.06.20.544772, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.  https://doi.org/10.1101/2023.06.20.544772

Tomberlin JK, Van Huis A (2020) Black soldier fly from pest to ‘crown jewel’ of the insects as feed industry: an historical perspective. Journal of Insects as Food and Feed, 6, 1–4. https://doi.org/10.3920/JIFF2020.0003

Sperm production and allocation in response to risk of sperm competition in the black soldier fly Hermetia illucensFrédéric Manas, Carole Labrousse, Christophe Bressac<p style="text-align: justify;">In polyandrous species, competition between males for offspring paternity goes on after copulation through the competition of their ejaculates for the fertilisation of female's oocytes. Given that males allocating m...Reproduction and Sex, Sexual SelectionTrine Bilde2023-06-26 09:41:07 View
12 Jun 2018
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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