Biology subjects

Czuppon, P.

Publications and source records attributed to Czuppon, P..

15 recordsLinked to original sources

bioRxiv2025

A population genetics model explaining overdispersion in active transposable elements

Active transposable element (TE) families often show overdispersion (variance greater than the mean), which is in contrast to the predictions of classical Poisson-based models and related theories built on the same approximation. To address this gap, we develop a diploid stochastic model of TE dynamics under free recombination, based on a biparental Moran model with transposition, excision, purifying selection, and derive mean and variance dynamics of TE copy numbers at two stages of the life cycle: before and after transposition and excision. We show that overdispersion arises naturally through transposition generating positive linkage disequilibrium between TE insertion sites with the disequilibrium persisting even under free recombination. The higher the transposition rate, the stronger the resulting overdispersion. Underdispersion and Poisson-like variation are instead stage-dependent: neither is expected after transposition and excision, while both remain possible beforehand, governed by the curvature of the fitness function. We further show that maintaining positive equilibrium copy numbers, and thus sustaining overdispersion, requires the net transposition rate to remain below roughly 0.5 insertions per copy per generation, a constraint satisfied by observed natural populations to maintain genome stability. A qualitative comparison with the DPGP3 Zambian Drosophila melanogaster dataset, focusing on TE insertions in high-recombination euchromatic regions shows that most TE families are overdispersed and that many also exhibit the predicted right-skewness and excess-kurtosis patterns, which are predicted by our model. These results identify overdispersion as a natural outcome of active TE dynamics and provide a mechanistic framework for understanding the full distribution of TE copy numbers in highly recombining regions.

genetics↗

bioRxiv2025

A century of theories of balancing selection

Traits that affect organismal fitness are often very genetically variable. This genetic variation is vital for populations to adapt to their environments, but it is also surprising given that nature (after all) "selects" the best genotypes at the expense of those that fall short. Explaining the extensive genetic variation of fitness-related traits is thus a longstanding puzzle in evolutionary biology, with cascading implications for ecology, conservation, and human health. Balancing selection--an umbrella term for scenarios of natural selection that maintain genetic variation-- is a century-old explanation to resolve this paradox that has gained recent momentum from genome-scale methods for detecting it. Yet evaluating whether balancing selection can, in fact, resolve the paradox is challenging, given the logistical constraints of distinguishing balancing selection from alternative hypotheses and the daunting collection of theoretical models that formally underpin this debate. Here, we track the development of balancing selection theory over the last century and provide an accessible review of this rich collection of models. We first outline the range of biological scenarios that can generate balancing selection. We then examine how fundamental features of genetic systems--including non-random mating between individuals, differences in ploidy, genetic drift, and different genetic architectures of traits-- have been progressively incorporated into the theory. We end by linking these theoretical predictions to ongoing empirical efforts to understand the evolutionary processes that explain genetic variation.

evolutionary biology↗

bioRxiv2024

Maintenance of long-term transposable element activity in genomes through regulation by nonautonomous elements

Transposable elements are DNA sequences that can move and replicate within genomes. Broadly, there are two types: autonomous elements, which encode the necessary enzymes for transposition, and nonautonomous elements which rely on the enzymes produced by autonomous elements for their transposition. Nonautonomous elements have been proposed to regulate the numbers of transposable elements, which is a possible explanation for the persistence of transposition activity over long evolutionary times. However, previous modeling studies indicate that interactions between autonomous and nonautonomous elements usually result in the extinction of one type. Here, we study a stochastic model that allows for the stable coexistence of autonomous and nonautonomous retrotransposons. We determine the conditions for this coexistence and derive an analytical expression for the stationary distribution of their copy numbers, showing that nonautonomous elements regulate stochastic fluctuations and the number of autonomous elements in stationarity. We find that the stationary variances of each element can be expressed as a function of the average copy numbers and their covariance, enabling data comparison and model validation. These results suggest that continued transposition activity of transposable elements, regulated by nonautonomous elements, is a possible evolutionary outcome that could for example explain the long co-evolutionary history of autonomous LINE1 and nonautonomous Alu element transposition in the human ancestry.

evolutionary biology↗

bioRxiv2024

The role of evolving niche choice in herbivore adaptation to host plants

Individuals living in heterogeneous environments often choose microenvironments that provide benefits to their fitness. Theory predicts that such "niche choice" can promote rapid adaptation to novel environments and help maintain genetic diversity. An open question of large applied importance is how niche choice and niche choice evolution affect the evolution of insecticide resistance in phytophagous insects. We, therefore, developed an individual-based model based on phytophagous insects to examine the evolution of insecticide resistance and host plant choice via oviposition preferences. To find biologically realistic parameter ranges, we performed an empirical literature survey on insecticide resistance in major agricultural pests and also conducted a density-dependent survival experiment using potato beetles. We find that, in comparison to a scenario where individuals randomly oviposit eggs on toxic or non-toxic plants, the evolution of niche choice generally leads to slower evolution of resistance and facilitates the coexistence of different phenotypes. Our simulations also reveal that recombination rate and dominance effects can influence the evolution of both niche choice and resistance. Thus, this study provides new insights into the effects of niche choice on resistance evolution and highlights the need for more studies on the genetic basis of resistance and choice.

evolutionary biology↗

bioRxiv2023

On the structure of an evolutionary transition: dependence and cohesion in incipient endosymbioses

Eukaryogenesis is the prototypical example of an egalitarian evolutionary transition in individuality, and endosymbiosis, more generally, is central to the origins of many complex biological systems. Why do only some symbioses undergo such a transition, and how does the host-symbiont relationship change during this process? Here, we characterise endosymbiosis by two emergent collective-level properties: host and symbiont survival as a collective ("mutual dependence") and the level of synchronised reproduction ("reproductive cohesion"). Using adaptive dynamics, we study the evolution of the traits underlying these properties. First, by adding a carrying capacity for the collective population - a realism omitted in previous models - we find novel reasons why complete dependence or cohesion might not evolve, thus providing further theoretical support for the rarity of transitions in individuality. Second, our model suggests that asymmetries in evolutionary outcomes of hosts and symbionts can be explained by a difference in their population growth parameters, coupled with their shared fate when in a collective. Lastly, we show that during the early stages of an endosymbiosis, even if investments in dependence and cohesion are uncorrelated, mutual dependence arises faster than reproductive cohesion. Our results hence shed light on three aspects of endosymbiosis: coevolution between the host and symbiont, coevolution between dependence and cohesion, and ultimately on the opportunity of undergoing an evolutionary transition. Connecting to ecological factors, this work uncovers fundamental properties of endosymbioses, providing a clear way forward for theoretical and empirical investigations.

evolutionary biology↗

bioRxiv2023

Stochastic within-host dynamics of antibiotic resistance: Resistant survival probability, size at the end of treatment and carriage time after treatment

The use of an antibiotic may lead to the emergence and spread of bacterial strains resistant to this antibiotic. Experimental and theoretical studies have investigated the drug dose that minimizes the risk of resistance evolution over the course of treatment of an individual, showing that the optimal dose will either be the highest or the lowest drug concentration possible to administer; however, no analytical results exist that help decide between these two extremes. To address this gap, we develop a stochastic mathematical model of bacterial dynamics under antibiotic treatment. We explore various scenarios of density regulation (bacterial density affects cell birth or death rates), and antibiotic modes of action (biostatic or biocidal). We derive analytical results for the survival probability of the resistant subpopulation until the end of treatment, the size of the resistant subpopulation at the end of treatment, the carriage time of the resistant subpopulation until it is replaced by a sensitive one after treatment, and we verify these results with stochastic simulations. We find that the scenario of density regulation and the drug mode of action are important determinants of the survival of a resistant subpopulation. Resistant cells survive best when bacterial competition reduces cell birth and under biocidal antibiotics. Compared to an analogous deterministic model, the population size reached by the resistant type is larger and carriage time is slightly reduced by stochastic loss of resistant cells. Moreover, we obtain an analytical prediction of the antibiotic concentration that maximizes the survival of resistant cells, which may help to decide which drug dosage (not) to administer. Our results are amenable to experimental tests and help link the within and between host scales in epidemiological models.

evolutionary biology↗

bioRxiv2023

High turnover of de novo transcripts in Drosophila melanogaster

Most of the transcribed eukaryotic genomes are composed of non-coding transcripts. Among these transcripts, some are newly transcribed when compared to outgroups and are referred to as de novo transcripts. De novo transcripts have been shown to play a major role in de novo gene emergence. However, little is known about the rates at which de novo transcripts are gained and lost in individuals of the same species. Here, we address this gap and estimate for the first time the de novo transcript turnover rate. We use DNA long reads and RNA short reads from seven samples of inbred individuals of Drosophila melanogaster to detect de novo transcripts that are (transiently) gained on a short evolutionary time scale. Overall, each sampled individual contains between 2,320 and 2,809 unspliced de novo transcripts with most of them being sample specific. We estimate that around 0.15 transcripts are gained per year, and that each gained transcript is lost at a rate around 5x10-5 per year. This high turnover of transcripts suggests frequent exploration of new genomic sequences within species. These rates provide first empirical estimates to better predict and comprehend the process of de novo gene birth.

genomics↗

bioRxiv2022

Blochmannia endosymbionts reduce brood rearing success in a carpenter ant (Camponotus sp.)

All ants of the species rich genus Camponotus ( carpenter ants) possess the obligate intracellular bacterial mutualist Blochmannia. We tested the relevance of the endosymbiont Blochmannia for offspring rearing using cross-fostering experiments between Camponotus sp. colonies and subcolonies (worker groups), which were either treated with antibiotics to remove Blochmannia or untreated. Our antibiotic treatment reduced the level of Blochmannia endosymbionts in eggs, larvae and workers significantly. Corroborating previous results, we found that eggs from treated colonies had a significantly reduced probability to develop into larvae and almost zero probability to become adults. Surprisingly, subcolonies treated with antibiotics had a significantly higher success in raising their own and foreign eggs from treated and untreated colonies than untreated subcolonies. This might indicate that the Blochmannia symbiosis entails significant costs for the host in terms of brood rearing, i.e., symbiont-free workers are more successful in brood rearing than untreated workers. If confirmed, this would be a rare case where the costs of a symbiosis can be empirically measured and quantified. Alternatively, the antibiotic treatment increased as a side effect the brood rearing effort of workers leading to the differences in brood rearing success of treated workers. But even if that would be the case, it still indicates that workers that have either lost or have a significantly reduced number of endosymbionts can still raise brood from antibiotic-treated and untreated colonies better than untreated workers. Thus Blochmannia, although crucial for brood development, may reduce the amount of brood a colony can raise.

evolutionary biology↗

bioRxiv2021

Revisiting the number of self-incompatibility alleles in finite populations: from old models to new results

Under gametophytic self-incompatibility (GSI), plants are heterozygous at the self-incompatibility locus (S-locus) and can only be fertilized by pollen with a different allele at that locus. The last century has seen a heated debate about the correct way of modeling the allele diversity in a GSI population that was never formally resolved. Starting from an individual-based model, we derive the deterministic dynamics as proposed by Fisher (1958), and compute the stationary S-allele frequency distribution. We find that the stationary distribution proposed by Wright (1964) is close to our theoretical prediction, in line with earlier numerical confirmation. Additionally, we approximate the invasion probability of a new S-allele, which scales inversely with the number of resident S-alleles. Lastly, we use the stationary allele frequency distribution to estimate the population size of a plant population from an empirically obtained allele frequency spectrum, which complements the existing estimator of the number of S-alleles. Our expression of the stationary distribution resolves the long-standing debate about the correct approximation of the number of S-alleles and paves the way to new statistical developments for the estimation of the plant population size based on S-allele frequencies.

evolutionary biology↗

bioRxiv2020

The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics

Sexually antagonistic (SA) genetic variation--in which genotypes favoured in one sex are disfavoured in the other--is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterisation of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research--including FST and FIS statistics, genome-wide association studies (GWAS), pedigree analyses, reciprocal transplant studies, and evolve-and-resequence (E&R) experiments--to evaluate methods for identifying SA genes and genome-wide signals of SA genetic variation. We begin by developing theoretical models for between-sex FST and FIS, including explicit null distributions for each statistic, and using them to critically evaluate putative signals of sex-specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of FST and FIS, along with applications of more direct approaches for characterising SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work. Impact SummaryGenome sequences carry a record of the evolutionary and demographic histories of natural populations. Research over the last two decades has dramatically improved our ability to detect genomic signals of adaptation by natural selection, including several widely-used methods for identifying genes underlying local adaptation and quantitative trait variation. Yet the application of these methods to identify sexually antagonistic (SA) genes--wherein variants that are adaptive for one sex are maladaptive for the other--remains under-explored, despite the potential importance of SA selection as a mechanism for maintaining genetic variation. Indeed, several lines of evidence suggest that SA genetic variation is common within animal and plant populations, underscoring the need for analytical methods that can reliably identify SA genes and genomic signals of SA genetic variation. Here, we integrate statistics and experimental designs that were originally developed within the fields of local adaptation and statistical genomics and apply them to the context of sex-specific adaptation and SA genetic variation. First, we evaluate and extend statistical methods for identifying signals of SA variation from genome sequence data alone. We then apply these methods to re-analyse previously published datasets on allele frequency differences between sexes--a putative signal of SA selection. Second, we highlight more direct approaches for identifying SA genetic variation, which utilise experimental evolution and statistical associations between individual genetic variants and fitness. Third, we provide guidelines for the biological validation, evolutionary analysis, and interpretation of candidate SA polymorphisms. By building upon the strong methodological foundations of local adaptation and statistical genomics research, we provide a roadmap for rigorous analyses of genetic data in the context of sex-specific adaptation, thereby facilitating insights into the role and pervasiveness of SA variation in adaptive evolution.

evolutionary biology↗

bioRxiv2019

How does habitat choice affect evolutionary rescue in subdivided populations?

Evolutionary rescue is the process by which a population, in response to an environmental change, successfully avoids extinction through adaptation. In spatially structured environments, dispersal can affect the probability of rescue. Here, we model an environment consisting of patches that degrade one after another, and we investigate the probability of rescue by a mutant adapted to the degraded habitat. We focus on the effects of dispersal and of immigration biases. We find that the probability of evolutionary rescue can undergo up to three phases: (i) starting from low dispersal rates, it increases with dispersal; (ii) at intermediate dispersal rates, it decreases; (iii) finally, at large dispersal rates, the probability of rescue increases again with dispersal, except if mutants are too counter-selected in not-yet-degraded patches. The probability of rescue is generally highest when mutant and wild-type individuals preferentially immigrate into patches that have already undergone environmental change. Additionally, we find that mutants that will eventually rescue the population most likely first appear in non-degraded patches, and that the relative contribution of standing genetic variation vs. de-novo mutations declines with increasing emigration rates. Overall, our results show that habitat choice, when compared to the often studied unbiased immigration scheme, can substantially alter the dynamics of population survival and adaptation to new environments.

evolutionary biology↗

bioRxiv2019

Invasion and extinction dynamics of mating types under facultative sexual reproduction

In sexually reproducing isogamous species, syngamy between gametes is generally not indiscriminate, but rather restricted to occurring between complementary self-incompatible mating types. A longstanding question regards the evolutionary pressures that control the number of mating types observed in natural populations, which ranges from two to many thousands. Here, we describe a population genetic null model of this reproductive system and derive expressions for the stationary probability distribution of the number of mating types, the establishment probability of a newly arising mating type and the mean time to extinction of a resident type. Our results yield that the average rate of sexual reproduction in a population correlates positively with the expected number of mating types observed. We further show that the low number of mating types predicted in the rare-sex regime is primarily driven by low invasion probabilities of new mating type alleles, with established resident alleles being very stable over long evolutionary periods. Moreover, our model naturally exhibits varying selection strength dependent on the number of present mating types. This results in higher extinction and lower invasion rates for an increasing number of residents.

evolutionary biology↗

bioRxiv2018

Evolution of mating types in finite populations: the precarious advantage of being rare

Sexually reproducing populations with self-incompatibility bear the cost of limiting potential mates to individuals of a different type. Rare mating types escape this cost since they are unlikely to encounter incompatible partners, leading to the deterministic prediction of continuous invasion by new mutants and an ever increasing number of types. However, rare types are also at an increased risk of being lost by random drift. Calculating the number of mating types that a population can maintain requires consideration of both the deterministic advantages and the stochastic risks. By comparing the relative importance of selection and drift, we show that a population of size N can maintain a maximum of approximately N1/3 mating types for intermediate population sizes while for large N we derive a formal estimate. Although the number of mating types in a population is quite stable, the rare type advantage promotes turnover of types. We derive explicit formulas for both the invasion and turnover probabilities in finite populations.

evolutionary biology↗

bioRxiv2018

Disentangling eco-evolutionary effects on trait fixation

In population genetics, fixation of traits in a demographically changing population under frequency-independent selection has been extensively analysed. In evolutionary game theory, models of fixation have typically focused on fixed population sizes and frequency-dependent selection. A combination of demographic fluctuations with frequency-dependent interactions such as Lotka-Volterra dynamics has received comparatively little attention. We consider a stochastic, competitive Lotka-Volterra model with higher order interactions between two traits. The emerging individual based model allows for stochastic fluctuations in the frequencies of the two traits and the total population size. We calculate the fixation probability of a trait under differing competition coefficients. This fixation probability resembles qualitatively the deterministic evolutionary dynamics. Furthermore, we partially disentangle the selection effects into their ecological and evolutionary components. We find that changing the evolutionary selection strength also changes the population dynamics and vice versa. Thus, a clean separation of the ecological and evolutionary effects is not possible. The entangled eco-evolutionary processes thus cannot be ignored when determining fixation properties in a co-evolutionary system.

evolutionary biology↗

bioRxiv2017

Limits of noise for autoregulated gene expression

Gene expression is influenced by extrinsic noise (involving a fluctuating environment of cellular processes) and intrinsic noise (referring to fluctuations within a cell under constant environment). We study the standard model of gene expression including an (in-)active gene, mRNA and protein. Gene expression is regulated in the sense that the protein feeds back and either represses (negative feedback) or enhances (positive feedback) its production at the stage of transcription. While it is well-known that negative (positive) feedback reduces (increases) intrinsic noise, we give a precise result on the resulting fluctuations in protein numbers. The technique we use is an extension of the Langevin approximation and is an application of a central limit theorem under stochastic averaging for Markov jump processes (Kang, Kurtz and Popovic, 2014). We find that (under our scaling and in equilibrium), negative feedback leads to a reduction in the Fano factor of at most 2, while the noise under positive feedback is potentially unbounded. The fit with simulations is very good and improves on known approximations.

systems biology↗