Biology subjects

Roques, L.

Publications and source records attributed to Roques, L..

13 recordsLinked to original sources

bioRxiv2026

Common molecular determinants underlie potyvirus host species jumps and resistance breakdown.

Given their rapid evolutionary dynamics, viruses offer a powerful system to investigate the mechanisms underlying host jumps. Here, we experimentally evolved endive necrotic mosaic virus (ENMV) in five plant hosts within the family Asteraceae: two putative ancestral hosts (Lactuca sativa and Tragopogon pratensis), and three alternative crop or weed species (Cichorium endivia, Zinnia elegans and Calendula arvensis). The resulting evolved viral populations, together with the ancestral strain, were then evaluated in a reciprocal cross-inoculation experiment across all five host species. ENMV exhibited clear adaptive responses in two hosts, Z. elegans and C. arvensis, with increased infection success and higher systemic viral accumulation compared to the ancestral virus. In contrast, no evidence of adaptation was detected in L. sativa, T. pratensis and C. endivia. Strikingly, strong cross-adaptation emerged between Z. elegans and C. arvensis: viral populations evolved in either host consistently outperformed those evolved in other hosts, as well as the ancestral strain, when infecting the reciprocal host. Sequencing of the VPg cistron in adapted populations revealed multiple nonsynonymous mutations, several of which arose independently across evolutionary lineages and in both Z. elegans and C. arvensis selection regimes. Functional assays using an infectious ENMV cDNA clone demonstrated that seven of these substitutions, individually or in combination, significantly increased the infection rate in both Z. elegans and C. arvensis. Notably, several of these substitutions also enhanced infectivity across four additional Asteraceae species among the eleven tested, without a clear relationship to host phylogenetic distance. Remarkably, all identified substitutions map to amino acid positions or adjacent residues in VPg previously implicated in the breakdown of recessive resistance genes against potyviruses in both crop and model plant systems. Together, these results suggest that adaptation to host resistance and host range expansion in potyviruses may rely, at least in part, on shared molecular pathways.

evolutionary biology↗

bioRxiv2026

Inferring the multi-host fitness landscape of endive necrotic mosaic virus from cross-inoculation experiments

Fitness landscapes offer a compact representation of adaptation, yet are rarely inferred from sparse multi-environment data. We present a Bayesian approach to infer an effective multi-host phenotypic fitness landscape from cross-inoculation assays by linking successful infection probabilities to Fishers geometrical model and to an explicit decomposition of establishment routes. The model estimates (i) the distance matrix among host-specific phenotypic optima, (ii) target-host permissiveness through the widths of fitness peaks, (iii) target-specific differences in the efficiency with which phenotypic suitability translates into successful infection, and (iv) the conditional probabilities that successful infections are attributed to direct establishment, rescue from standing variation in the source inoculum, or de novo rescue in the target host. We apply the approach to an experimental evolution dataset for endive necrotic mosaic virus evolved on five Asteraceae hosts and challenged in a full cross-inoculation design. The inferred landscape can be visualized as a phenotypic map of the host community, revealing pronounced heterogeneity in target-host permissiveness and a geometry broadly concordant with host phylogeny. By grounding assay-derived distances in an explicit mechanistic model, the approach provides a parsimonious representation of multi-host constraints that can be used to discuss establishment barriers and potential springboard hosts in heterogeneous communities. More broadly, it offers a general method for inferring effective fitness landscapes from sparse multi-environment data.

evolutionary biology↗

bioRxiv2025

Time-resolved bottleneck analysis in bacterial infection dynamics

Within-host pathogen dynamics are shaped by successive host-imposed barriers that generate bottlenecks and ultimately determine infection outcome, yet these processes remain difficult to study in vivo. Here, we use neutral genetic barcoding to quantify the root-entry bottleneck during infection of tomato by the bacterial soil-borne phytopathogen Ralstonia pseudosolanacearum. We establish an updated theoretical framework showing that the temporal structure of pathogen entry, often overlooked, is a key determinant of root colonisation. We introduce the concept of time-resolved bottleneck, capturing infection scenarios in which entry occurs continuously while the pathogen population simultaneously expands within the host. We develop quantitative tools that exploit barcode dynamics to disentangle the respective roles of motility, growth, and spatial competition, enabling direct inference of in vivo pathogen fluxes and growth rates and linking host susceptibility to mechanistic features of colonisation. Extending beyond plants, reanalysis of two independent animal infection datasets reveals previously unrecognised within-host development patterns. Together, these results show that time-resolved bottleneck is a general principle of bacterial infection dynamics and propose a new standard for barcoding-based studies: a host- and pathogen-agnostic framework that is directly applicable to a majority of existing STAMP(-R)-style datasets, distributed as an open, annotated R/Python notebook to facilitate community reuse.

microbiology↗

bioRxiv2024

Cell expansion-division under resource sharing: a novel framework for modeling fruit growth dynamics

Fruit growth is determined by cell expansion and division, processes that are closely linked to the availability and allocation of resources. By influencing environmental and growing conditions, agricultural practices affect these processes and ultimately many key indicators of fruit quality and yield. Given the multifaceted complexity underlying fruit growth dynamics, a process-based framework that can link genetic and environmental inputs to observables of economic and nutritional interest has become essential for predicting and improving agricultural outcomes. Here we present a mathematical framework that integrates cellular dynamics with resource allocation mechanisms to model the interplay between division, expansion and resource limitation in fruit cells. The model captures the temporal evolution of total fruit mass, cell number and cell mass distribution, reflecting data across genotypes and environmental conditions from tomato growth experiments. This sheds light on the possible relationships between genetic traits, growth conditions and fruit traits, and provides a predictive tool for optimizing fruit yield and quality under agricultural practices. Our minimal but mechanistic approach has broader implications for understanding resource-limited growth in multicellular systems.

ecology↗

bioRxiv2022

On the evolutionary trade-off between growth anddispersal during a range expansion

Individuals who invest more in the development of their dispersal-related traits often reduce their investment in reproduction. Thus, there are two possible eco-evolutionary strategies: grow faster or disperse faster (R -- D arbitrage). Here we explore, through a reaction-diffusion model, how spatial heterogeneity can shape the R -- D trade-off by studying the spreading dynamics of a consumer species exploiting a resource in a spatially fragmented environment. Based on numerical simulations and analytical solutions derived from simpler models, we show that the classical mathematical symmetry between the effects of growth and dispersal on the spatial spreading speed is broken in the presence of competition between phenotypes. At the back of the forefront, the dynamics is almost always driven by the R specialists. On the forefront, R-strategies are favored in spatially homogeneous environments, but the introduction of heterogeneity leads to a shift towards D-strategies. This effect is even stronger when spatial heterogeneity affects the diffusion term and when spatial fragmentation is lower. Introducing mutations between phenotypes produces an advantage towards the R-strategy and homogenizes the distribution of phenotypes, also leading to more polymorphism on the forefront.

evolutionary biology↗

bioRxiv2021

Dynamics of Aedes albopictus invasion. Insights from a spatio-temporal model

France displays a latitudinal range for the expansion of Aedes albopictus invasive populations that is not yet completely colonized providing a critical opportunity to address key invasion processes. We propose a spatio-temporal model (DISTIGRI) to describe and predict current and future expansion at both intra- and inter-annual scales of A. albopictus. This process-based model integrates mechanistic descriptions of the developmental cycle and the dispersal process of A. albopictus within a reaction-diffusion framework, depending on climatic suitability and photoperiod with a high spatio-temporal resolution. Using this model coupled with a climatic database, we propose several maps describing the current intra-annual distribution of A. albopictus, including the date of first emergence and the length of the period with significant adult presence. We also compute its future distribution over the next 10 years under several climatic scenarios, which shows a range expansion with a strong dependence on the climatic scenario. The outputs of the model may constitute a valuable asset for designing control and avoidance strategies, and to anticipate the biting nuisance with a high spatio-temporal resolution. These outputs also emphasize the importance of taking both dispersal and life cycle into account to obtain accurate descriptions of out-of-equilibrium processes such as ongoing invasions.

ecology↗

bioRxiv2021

The emergence of a birth-dependent mutation rate in asexuals: causes and consequences

AO_SCPLOWBSTRACTC_SCPLOWIn unicellular organisms such as bacteria and in most viruses, mutations mainly occur during reproduction. Thus, genotypes with a high birth rate should have a higher mutation rate. However, standard models of asexual adaptation such as the replicator-mutator equation often neglect this generation-time effect. In this study, we investigate the emergence of a positive dependence between the birth rate and the mutation rate in models of asexual adaptation and the consequences of this dependence. We show that it emerges naturally at the population scale, based on a large population limit of a stochastic time-continuous individual-based model with elementary assumptions. We derive a reaction-diffusion framework that describes the evolutionary trajectories and steady states in the presence of this dependence. When this model is coupled with a phenotype to fitness landscape with two optima, one for birth, the other one for survival, a new trade-off arises in the population. Compared to the standard approach with a constant mutation rate, the symmetry between birth and survival is broken. Our analytical results and numerical simulations show that the trajectories of mean phenotype, mean fitness and the stationary phenotype distribution are in sharp contrast with those displayed for the standard model. The reason for this is that the usual weak selection limit does not hold in a complex landscape with several optima associated with different values of the birth rate. Here, we obtain trajectories of adaptation where the mean phenotype of the population is initially attracted by the birth optimum, but eventually converges to the survival optimum, following a hook-shaped curve which illustrates the antagonistic effects of mutation on adaptation.

evolutionary biology↗

bioRxiv2020

Emerging strains of watermelon mosaic virus in Southeastern France: model-based estimation of the dates and places of introduction

Where and when alien organisms are successfully introduced are central questions to elucidate biotic and abiotic conditions favorable to the introduction, establishment and spread of invasive species. We propose a modelling framework to analyze multiple introductions by several invasive genotypes or genetic variants, in competition with a resident population, when observations provide knowledge on the relative proportions of each variant at some dates and places. This framework is based on a mechanistic-statistical model coupling a reaction-diffusion model with a probabilistic observation model. We apply it to a spatio-temporal dataset reporting the relative proportions of five genetic variants of watermelon mosaic virus (WMV, genus Potyvirus, family Potyviridae) in infections of commercial cucurbit fields. Despite the parsimonious nature of the model, it succeeds in fitting the data well and provides an estimation of the dates and places of successful introduction of each emerging variant as well as a reconstruction of the dynamics of each variant since its introduction.

ecology↗

bioRxiv2019

Dynamics of adaptation in an anisotropic phenotype-fitness landscape

We study the dynamics of adaptation of a large asexual population in a n-dimensional phenotypic space, under anisotropic mutation and selection effects. When n = 1 or under isotropy assumptions, the replicator-mutator equation is a standard model to describe these dynamics. However, the n-dimensional anisotropic case remained largely unexplored. We prove here that the equation admits a unique solution, which is interpreted as the phenotype distribution, and we propose a new and general framework to the study of the quantitative behavior of this solution. Our method builds upon a degenerate nonlocal parabolic equation satisfied by the distribution of the fitness components, and a nonlocal transport equation satisfied by the cumulant generating function of the joint distribution of these components. This last equation can be solved analytically and we then get a general formula for the trajectory of the mean fitness and all higher cumulants of the fitness distribution, over time. Such mean fitness trajectory is the typical outcome of empirical studies of adaptation by experimental evolution, and can thus be compared to empirical data. In sharp contrast with the known results based on isotropic models, our results show that the trajectory of mean fitness may exhibit (n - 1) plateaus before it converges. It may thus appear non-saturating for a transient but possibly long time, even though a phenotypic optimum exists. To illustrate the empirical relevance of these results, we show that the anisotropic model leads to a very good fit of Escherichia coli long-term evolution experiment, one of the most famous experimental dataset in experimental evolution. The two evolutionary epochs that have been observed in this experiment have long puzzled the community: we propose that the pattern may simply stem form a climbing hill process, but in an anisotropic fitness landscape.

evolutionary biology↗

bioRxiv2019

Population persistence under high mutation rate: from evolutionary rescue to lethal mutagenesis

Populations may genetically adapt to severe stress that would otherwise cause their extirpation. Recent theoretical work, combining stochastic demography with Fishers geometric model of adaptation, has shown how evolutionary rescue becomes unlikely beyond some critical intensity of stress. Increasing mutation rates may however allow adaptation to more intense stress, raising concerns about the effectiveness of treatments against pathogens. This previous work assumes that populations are rescued by the rise of a single resistance mutation. However, even in asexual organisms, rescue can also stem from the accumulation of multiple mutations in a single genome. Here, we extend previous work to study the rescue process in an asexual population where the mutation rate is sufficiently high so that such events may be common. We predict both the ultimate extinction probability of the population and the distribution of extinction times. We compare the accuracy of different approximations covering a large range of mutation rates. Moderate increase in mutation rates favors evolutionary rescue. However, larger increase leads to extinction by the accumulation of a large mutation load, a process called lethal mutagenesis. We discuss how these results could help design \"evolution-proof\" anti-pathogen treatments that even highly mutable strains could not overcome.

evolutionary biology↗

bioRxiv2018

Dynamics of fitness distributions in the presence of a phenotypic optimum: an integro-differential approach

We propose an integro-differential description of the dynamics of the fitness distribution in an asexual population under mutation and selection, in the presence of a phenotype optimum. Due to the presence of this optimum, the distribution of mutation effects on fitness depends on the parents fitness, leading to a non-standard equation with \"context-dependent\" mutation kernels.\n\nUnder general assumptions on the mutation kernels, which encompass the standard n dimensional Gaussian Fishers geometrical model (FGM), we prove that the equation admits a unique time-global solution. Furthermore, we derive a nonlocal nonlinear transport equation satisfied by the cumulant generating function of the fitness distribution. As this equation is the same as the equation derived by Martin and Roques (2016) while studying stochastic Wright-Fisher-type models, this shows that the solution of the main integro-differential equation can be interpreted as the expected distribution of fitness corresponding to this type of microscopic models, in a deterministic limit. Additionally, we give simple sufficient conditions for the existence/non-existence of a concentration phenomenon at the optimal fitness value, i.e, of a Dirac mass at the optimum in the stationary fitness distribution. We show how it determines a phase transition, as mutation rates increase, in the value of the equilibrium mean fitness at mutation-selection balance. In the particular case of the FGM, consistently with previous studies based on other formalisms (Waxman and Peck, 1998, 2006), the condition for the existence of the concentration phenomenon simply requires that the dimension n of the phenotype space be larger than or equal to 3 and the mutation rate U be smaller than some explicit threshold.\n\nThe accuracy of these deterministic approximations are further checked by stochastic individual-based simulations.

evolutionary biology↗

bioRxiv2018

When sinks become sources: adaptive colonization in asexuals

The successful establishment of a population into a new empty habitat outside of its initial niche is a phenomenon akin to evolutionary rescue in the presence of immigration. It underlies a wide range of processes, such as biological invasions by alien organisms, host shifts in pathogens or the emergence of resistance to pesticides or antibiotics from untreated areas.\n\nIn this study, we derive an analytically tractable framework to describe the coupled evolutionary and demographic dynamics of asexual populations in a source-sink system. In particular, we analyze the influence of several factors -- immigration rate, mutational parameters, and harshness of the stress induced by the change of environment -- on the establishment success in the sink (i.e. the formation of a self-sufficient population in the sink), and on the time until establishment. To this aim, we use a classic phenotype-fitness landscape (Fishers geometrical model in n dimensions) where source and sink habitats determine distinct phenotypic optima. The harshness of stress, in the sink, is determined by the distance between the fitness optimum in the sink and that of the source. The dynamics of the full distribution of fitness and of population size in the sink are analytically predicted under a strong mutation strong immigration limit where the population is always polymorphic.\n\nThe resulting eco-evolutionary dynamics depend on mutation and immigration rates in a non straightforward way. Below some mutation rate threshold, establishment always occurs in the sink, following a typical four-phases trajectory of the mean fitness. The waiting time to this establishment is independent of the immigration rate and decreases with the mutation rate. Beyond the mutation rate threshold, lethal mutagenesis impedes establishment and the sink population remains so, albeit with an equilibrium state that depends on the details of the fitness landscape. We use these results to get some insight into possible effects of several management strategies.

evolutionary biology↗

bioRxiv2018

When higher carrying capacities lead to faster propagation

This preprint has been reviewed and recommended by Peer Community In Ecology (https://dx.doi.org/10.24072/pci.ecology.100004). Finding general patterns in the expansion of natural populations is a major challenge in ecology and invasion biology. Classical spatio-temporal models predict that the carrying capacity (K) of the environment should have no influence on the speed (v) of an expanding population. We tested the generality of this statement with reaction-diffusion equations, stochastic individual-based models, and microcosms experiments with Trichogramma chilonis wasps. We investigated the dependence between K and v under different assumptions: null model (Fisher-KPP-like assumptions), strong Allee effects, and positive density-dependent dispersal. These approaches led to similar and complementary results. Strong Allee effects, positive density-dependent dispersal and demographic stochasticity in small populations lead to a positive dependence between K and v. A positive correlation between carrying capacity and propagation speed might be more frequent than previously expected, and be the rule when individuals at the edge of a population range are not able to fully drive the expansion.

ecology↗