Publications by authors named "Aurelien Tellier"

Article Synopsis
  • Understanding pathogen resistance genes, especially NLRs, in Solanum chilense requires looking at factors that influence gene gain and loss, which is detailed in a new reference genome study.
  • The study reveals that variations in NLR loci across 20 populations show higher within-population diversity than between-population diversity, linking NLR diversity to population dynamics rather than environmental factors.
  • Findings indicate that genetic drift and demographic history, along with some weak selection for local adaptation, significantly influence the evolution of NLRs in this plant species.
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Article Synopsis
  • Drought stress significantly hinders plant growth, and this study focuses on how the wild tomato Solanum chilense adaptively responds to it in arid environments in South America.
  • Through transcriptome analysis under varying conditions, researchers identify two main gene networks involved in drought response: one regulating the cell cycle, which is older and more stable, and another related to metabolism, which is newer and more variable.
  • The integration of population genomics shows that older genes under positive selection are more interconnected in these networks, suggesting that adaptations to drought stress first occur in key genes, leading to changes that may contribute to species evolution and colonization of drier areas.
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With the availability of high-quality full genome polymorphism (SNPs) data, it becomes feasible to study the past demographic and selective history of populations in exquisite detail. However, such inferences still suffer from a lack of statistical resolution for recent, for example bottlenecks, events, and/or for populations with small nucleotide diversity. Additional heritable (epi)genetic markers, such as indels, transposable elements, microsatellites, or cytosine methylation, may provide further, yet untapped, information on the recent past population history.

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Host-pathogen coevolution is defined as the reciprocal evolutionary changes in both species due to genotype × genotype (G×G) interactions at the genetic level determining the outcome and severity of infection. While co-analyses of hosts and pathogen genomes (co-genome-wide association studies) allow us to pinpoint the interacting genes, these do not reveal which host genotype(s) is/are resistant to which pathogen genotype(s). The knowledge of this so-called infection matrix is important for agriculture and medicine.

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Pathogen species are experiencing strong joint demographic and selective events, especially when they adapt to a new host, for example through overcoming plant resistance. Stochasticity in the founding event and the associated demographic variations hinder our understanding of the expected evolutionary trajectories and the genetic structure emerging at both neutral and selected loci. What would be the typical genetic signatures of such a rapid adaptation event is not elucidated.

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Seed banking (or dormancy) is a widespread bet-hedging strategy, generating a form of population overlap, which decreases the magnitude of genetic drift. The methodological complexity of integrating this trait implies it is ignored when developing tools to detect selective sweeps. But, as dormancy lengthens the ancestral recombination graph (ARG), increasing times to fixation, it can change the genomic signatures of selection.

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The speed of population adaptation to changing biotic and abiotic environments is determined by the interaction between genetic drift, positive selection and linkage effects. Many marine species (fish, crustaceans), invertebrates and pathogens of humans and crops, exhibit sweepstakes reproduction characterized by the production of a very large amount of offspring (fecundity phase) from which only a small fraction may survive to the next generation (viability phase). Using stochastic simulations, we investigate whether the occurrence of sweepstakes reproduction affects the efficiency of a positively selected unlinked locus, and thus, the speed of adaptation since fecundity and/or viability have distinguishable consequences on mutation rate, probability and fixation time of advantageous alleles.

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The evolution from outcrossing to selfing occurred recently across the eukaryote tree of life in plants, animals, fungi, and algae. Despite short-term advantages, selfing is hypothetically an evolutionary dead-end reproductive strategy. The tippy distribution on phylogenies suggests that most selfing species are of recent origin.

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Adaptation can occur at remarkably short timescales in natural populations, leading to drastic changes in phenotypes and genotype frequencies over a few generations only. The inference of demographic parameters can allow understanding how evolutionary forces interact and shape the genetic trajectories of populations during rapid adaptation. Here we propose a new Approximate Bayesian Computation (ABC) framework that couples a forward and individual-based model with temporal genetic data to disentangle genetic changes and demographic variations in a case of rapid adaptation.

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Nucleotide-binding leucine-rich-repeat receptors (NLR), the largest group of genes associated with plant disease resistance (R), have attracted attention due to their crucial role in protecting plants from pathogens. Genome-wide studies of NLRs have revealed conserved domains in the annotated tomato genome. The 321 genes identified in the tomato genome have been randomly mapped to 12 chromosomes.

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Positive selection is the driving force underpinning local adaptation and leaves footprints of selective sweeps on the underlying major genes. Quantifying the timing of selection and revealing the genetic bases of adaptation in plant species occurring in steep and varying environmental gradients are crucial to predict a species' ability to colonize new niches. We use whole-genome sequence data from six populations across three different habitats of the wild tomato species Solanum chilense to infer the past demographic history and search for genes under strong positive selection.

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Vaccination hesitancy is a major obstacle to achieving and maintaining herd immunity. Therefore, public health authorities need to understand the dynamics of an anti-vaccine opinion in the population. We introduce a spatially structured mathematical model of opinion dynamics with reinforcement.

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Article Synopsis
  • Coevolution involves complex interactions between species, ranging from mutualistic relationships to host-parasite dynamics, driving adaptation within ecosystems.
  • Despite its importance, there is a lack of understanding regarding the genomic processes that facilitate coevolution in natural environments, particularly how species interact with changing ecological conditions.
  • The text highlights recent advancements in coevolutionary theory and genomics, identifies gaps in knowledge, and suggests a framework for studying coevolution through ecological genomics that considers both spatial and temporal factors.
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Due to the relevance for conservation biology, there is an increasing interest to extend evolutionary genomics models to plant, animal or microbial species. However, this requires to understand the effect of life-history traits absent in humans on genomic evolution. In this context, it is fundamentally of interest to generalize the replicator equation, which is at the heart of most population genomics models.

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Contemporary gene flow, when resumed after a period of isolation, can have crucial consequences for endangered species, as it can both increase the supply of adaptive alleles and erode local adaptation. Determining the history of gene flow and thus the importance of contemporary hybridization, however, is notoriously difficult. Here, we focus on two endangered plant species, Arabis nemorensis and A.

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Article Synopsis
  • * The review highlights three new methods—co-GWAS, population genomics extensions, and temporal correlations—that help identify coevolving genetic loci and reconstruct coevolutionary history.
  • * The authors discuss the principles, advantages, and limitations of these approaches across various organisms and note the need for further research to enhance understanding of coevolution through full genome data.
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Several methods based on the sequentially Markovian coalescent (SMC) make use of full genome sequence data from samples to infer population demographic history including past changes in population size, admixture, migration events and population structure. More recently, the original theoretical framework has been extended to allow the simultaneous estimation of population size changes along with other life history traits such as selfing or seed banking. The latter developments enhance the applicability of SMC methods to nonmodel species.

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Several methods based on the Sequential Markovian coalescence (SMC) have been developed that make use of genome sequence data to uncover population demographic history, which is of interest in its own right and is a key requirement to generate a null model for selection tests. While these methods can be applied to all possible kind of species, the underlying assumptions are sexual reproduction in each generation and non-overlapping generations. However, in many plants, invertebrates, fungi and other taxa, those assumptions are often violated due to different ecological and life history traits, such as self-fertilization or long term dormant structures (seed or egg-banking).

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There is a long-standing interest in understanding host-parasite coevolutionary dynamics and associated fitness effects. Increasing amounts of genomic data for both interacting species offer a promising source to identify candidate loci and to infer the main parameters of the past coevolutionary history. However, so far no method exists to perform the latter.

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Background: Coevolution is a selective process of reciprocal adaptation in hosts and parasites or in mutualistic symbionts. Classic population genetics theory predicts the signatures of selection at the interacting loci of both species, but not the neutral genome-wide polymorphism patterns. To bridge this gap, we build an eco-evolutionary model, where neutral genomic changes over time are driven by a single selected locus in hosts and parasites via a simple biallelic gene-for-gene or matching-allele interaction.

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Despite the wealth of empirical and theoretical studies, the origin and maintenance of cooperation is still an evolutionary riddle. In this context, ecological life-history traits which affect the efficiency of selection may play a role despite being often ignored. We consider here species such as bacteria, fungi, invertebrates and plants which exhibit resting stages in the form of a quiescent state or a seed bank.

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Wild tomato species, like , are important germplasm resources for enhanced biotic and abiotic stress resistance in tomato breeding. also serves as a model to study adaptation of plants to drought and the evolution of seed banks. The absence of a well-annotated reference genome in this compulsory outcrossing, very diverse species limits in-depth studies on the genes involved.

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Achieving high intraspecific genetic diversity is a critical goal in ecological restoration as it increases the adaptive potential and long-term resilience of populations. Thus, we investigated genetic diversity within and between pristine sites in a fossil floodplain and compared it to sites restored by hay transfer between 1997 and 2014. RAD-seq genotyping revealed that the stenoecious floodplain species Arabis nemorensis is co-occurring with individuals that, based on ploidy, ITS-sequencing and morphology, probably belong to the close relative Arabis sagittata, which has a documented preference for dry calcareous grasslands but has not been reported in floodplain meadows.

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