Biology subjects

Tellier, A.

Publications and source records attributed to Tellier, A..

32 records · Page 2Linked to original sources

bioRxiv2021

Approximate Bayesian computation untangles signatures of contemporary and historical hybridization between two endangered species

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. sagittata, which hybridize naturally in a sympatric population located on the banks of the Rhine. Using reduced genome sequencing, we determined the phylogeography of the two taxa but report only a unique sympatric population. Molecular variation in chloroplast DNA indicated that A. sagittata is the principal receiver of gene flow. Applying classical D-statistics and its derivatives to whole-genome data of 35 accessions, we detect gene flow not only in the sympatric population but also among allopatric populations. Using an Approximate Bayesian computation approach, we identify the model that best describes the history of gene flow between these taxa. This model shows that low levels of gene flow have persisted long after speciation. Around 10 000 years ago, gene flow stopped and a period of complete isolation began. Eventually, a hotspot of contemporary hybridization was formed in the unique sympatric population. Occasional sympatry may have helped protect these lineages from extinction in spite of their extremely low diversity.

evolutionary biology↗

bioRxiv2020

Limits and Convergence properties of theSequentially Markovian Coalescent

Many methods based on the Sequentially Markovian Coalescent (SMC) have been and are being developed. These methods make use of genome sequence data to uncover population demographic history. More recently, new methods have extended the original theoretical framework, allowing the simultaneous estimation of the demographic history and other biological variables. These methods can be applied to many different species, under different model assumptions, in hopes of unlocking the population/species evolutionary history. Although convergence proofs in particular cases have been given using simulated data, a clear outline of the performance limits of these methods is lacking. We here explore the limits of this methodology, as well as present a tool that can be used to help users quantify what information can be confidently retrieved from given datasets. In addition, we study the consequences for inference accuracy violating the hypotheses and the assumptions of SMC approaches, such as the presence of transposable elements, variable recombination and mutation rates along the sequence and SNP call errors. We also provide a new interpretation of the SMC through the use of the estimated transition matrix and offer recommendations for the most efficient use of these methods under budget constraints, notably through the building of data sets that would be better adapted for the biological question at hand.

genomics↗

bioRxiv2019

Cross-Species association statistics for genome-wide studies of host and parasite polymorphism data

Uncovering the genes governing host-parasite coevolutionary interactions is of importance for disease management. The increasing availability of host and parasite full genome-data allows for cross-species genome-wide association studies based on the genomic data of in-fected hosts and their associated parasite strains sampled from natural populations (i.e. natural co-GWAs). Such studies focus on searching for cross-species allelic associations between pairs of host and parasite SNPs. We aim to quantify the power of natural co-GWAs to pinpoint loci under coevolution with respect to the intrinsic complexities of coevolutionary systems, such as the genetic specificity of the interaction and the temporal allele frequency changes resulting from the interaction. Therefore, we develop the cross-species association (CSA) and the cross-species prevalence (CSP) indices, the latter additionally incorporating genomic data from uninfected hosts. To provide an assessment of the statistical power of these indices, we analytically derive their genome-wide False Discovery Rates (FDR) based on the neutral site-frequency spectrum of the host and the parasite population. Using two coevolutionary models, we investigate under which parameter regimes these indices pin-point the coevolving loci. Under trench warfare dynamics, CSA and CSP are very accurate in pinpointing the loci under coevolution, while under arms race dynamics the power is limited especially for gene-for-gene interactions. Furthermore, we reveal that the combination of both indices across time samples is an indicator for the specificity of the interaction. Our results provide novel insights into the power and biological interpretation of natural cross-species association studies.

evolutionary biology↗

bioRxiv2019

Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data

Several methods based on the Sequential Markovian Coalescent (SMC) have been developed to use full genome sequence data to uncover population demographic history, which is of interest in its own right and a key requirement to generate a null model for selection tests. While these methods can be applied to all possible species, the underlying assumptions are sexual reproduction at each generation and no overlap of generations. However, in many plant, invertebrate, fungi and other species, 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). We develop a novel SMC-based method to infer 1) the rates of seed/egg-bank and of self-fertilization, and 2) the populations past demographic history. Using simulated data sets, we demonstrate the accuracy of our method for a wide range of demographic scenarios and for sequence lengths from one to 30 Mb using four sampled genomes. Finally, we apply our method to a Swedish and a German population of Arabidopsis thaliana demonstrating a selfing rate of ca. 0.8 and the absence of any detectable seed-bank. In contrast, we show that the water flea Daphnia pulex exhibits a long lived egg-bank of three to 18 generations. In conclusion, we here present a novel method to infer accurate demographies and life-history traits for species with selfing and/or seed/egg-banks. Finally, we provide recommendations on the use of SMC-based methods for non-model organisms, highlighting the importance of the per site and the effective ratios of recombination over mutation.

evolutionary biology↗

bioRxiv2019

Inference of coevolutionary dynamics and parameters from host and parasite polymorphism data of repeated experiments

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 do so. By coupling a gene-for-gene model with coalescent simulations, we first show that three types of biological cost, resistance, infectivity and infection, define the allele frequencies at the internal equilibrium point of the coevolution model, which in return determine the strength of the selective signatures signatures at host and parasite loci. We apply an Approximate Bayesian Computation (ABC) approach on simulated datasets to infer these costs by jointly integrating host and parasite polymorphism data at the coevolving loci. To control for the effect of genetic drift on coevolutionary dynamics, we assume that 10 or 30 repetitions are available from controlled experiments or several natural populations. We study two scenarios: 1) the cost of infection and population sizes (host and parasite) are unknown while costs of infectivity and resistance are known, and 2) all three costs are unknown while populations sizes are known. Using the ABC model choice procedure, we show that for both scenarios, we can distinguish with high accuracy pairs of loci from host and parasite under coevolution from neutrally evolving loci, though the statistical power decreases with higher cost of infection. The accuracy of parameter inference is also very high under both scenarios especially when using both host and parasite data because parasite polymorphism data do inform on host costs and vice-versa. As the false positive rate to detect genes under coevolution is small, we suggest to use our method to identify host and parasite candidate loci for further functional studies.\n\nAuthor summaryIt is of importance for agriculture and medicine to understand host-parasite antagonistic coevolutionary dynamics and the deleterious associated fitness effects, as well as to reveal the genes underpinning these interactions. The increasing amount of genomic data for hosts and parasites offer a promising source to identify such candidate loci, but also to use statistical inference methods to reconstruct the past coevolutionary history. In our study we attempt to draw inference of the past coevolutionary history at key host and parasites loci using sequence data from several individuals and across several experimental replicates. We demonstrate that using a Bayesian statistical method, it is possible to estimate the parameters driving the interaction of hosts and parasites at these loci for thousands of generations. The main parameter that can be estimated is the fitness loss by hosts upon infection. Our method and results can be applied to experimental coevolution data with sequences at the key candidate loci providing enough repetitions and large enough population sizes. As a proof of principle, our results open the door to reconstruct past coevolutionary dynamics using sequence data of interacting species.

evolutionary biology↗

bioRxiv2019

The de novo reference genome and transcriptome assemblies of the wild tomato species Solanum chilense

BackgroundWild tomato species, like Solanum chilense, are important germplasm resources for enhanced biotic and abiotic stress resistance in tomato breeding. In addition, S. chilense serves as a model system to study adaptation of plants to drought and to investigate the evolution of seed banks. However to date, the absence of a well annotated reference genome in this compulsory outcrossing, very diverse species limits in-depth studies on the genes involved.\n\nFindingsWe generated [~]134 Gb of DNA and 157 Gb of RNA sequence data of S chilense, which yielded a draft genome with an estimated length of 914 Mb in total encoding 25,885 high-confidence (hc) predicted gene models, which show homology to known protein-coding genes of other tomato species. Approximately 71% (18,290) of the hc gene models are additionally supported by RNA-seq data derived from leaf tissue samples. A benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis of predicted gene models retrieved 93.3% BUSCO genes, which is in the current range of high-quality genomes for non-inbred plants. To further verify the genome annotation completeness and accuracy, we manually inspected the NLR resistance gene family and assessed its assembly quality. We revealed the existence of unique gene families of NLRs to S. chilense. Comparative genomics analyses of S. chilense, cultivated tomato S. lycopersicum and its wild relative S. pennellii revealed similar levels of highly syntenic gene clusters between the three species.\n\nConclusionsWe generated the first genome and transcriptome sequence assembly for the wild tomato species Solanum chilense and demonstrated its value in comparative genomics analyses. We make these genomes available for the scientific community as an important resource for studies on adaptation to biotic and abiotic stress in Solanaceae, on evolution of self-incompatibility, and for tomato breeding.

plant biology↗

bioRxiv2019

Neutral genomic signatures of host-parasite coevolution.

Coevolution is a selective process of reciprocal adaptation between antagonistic or mutualistic symbionts and their host. Classic population genetics theory predicts the signatures of selection at the interacting loci but not the neutral genome-wide polymorphism patterns. We here build a coevolutionary model with cyclic changes in the host and parasite population sizes. Using an analytical framework, we investigate if and when these population size changes can be observed in the neutral site frequency spectrum of the host and parasite full genome data. We show that polymorphism data sampled over time can capture the changes in the population size of the parasite but not of the host because genetic drift and mutations occur on different time scales in the coevolving species. This is due to the small parasite population size at the onset of the coevolutionary history subsequently undergoing a series of strong bottlenecks. We also show that tracking coevolutionary cycles is more likely for a small amount of parasite per host and for multiple parasite generations per host generation. Our results demonstrate that time sampling of host and parasite full genome data are crucial to infer the co-demographic history of interacting species.

evolutionary biology↗

bioRxiv2018

Strengths and potential pitfalls of hay-transfer for ecological restoration revealed by RAD-seq analysis in two floodplain Arabis species

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 flood-plain and compared it to sites restored by hay-transfer between 1997 and 2014. RAD-seq genotyping revealed that the stenoecious flood-plain species Arabis nemorensis is co-occurring in pristine and restored sites with its relative Arabis sagittata, which has a documented preference for dry calcareous grasslands but has not been reported in floodplain meadows. We show that hay-transfer maintains genetic diversity for both species. In addition, in A. sagittata, transfer from multiple genetically isolated pristine sites resulted in restored sites with increased diversity and admixed local genotypes. In A. nemorensis, transfer also maintained diversity, but did not create novel admixture dynamics because genetic diversity between pristine sites was less differentiated. Thus, the effects of hay-transfer on genetic diversity also depend on the genetic makeup of each species in the donor communities, especially when material is mixed. Our results demonstrate the efficiency of hay-transfer for habitat restoration and emphasize the importance of pre-restoration characterization of micro-geographic patterns of intraspecific diversity of the community to guarantee that restoration practices reach their goal, i.e. maximize the adaptive potential of the entire restored plant community. Overseeing these patterns may differentially alter the adaptive potential of species present, thereby altering the balance between species in the community. Additionally, our comparison of summary statistics obtained from de novo and reference-based RAD-seq pipelines show that the genomic impact of restoration can be reliably monitored on species lacking prior genomic knowledge.

ecology↗

bioRxiv2018

Host-parasite coevolution can promote the evolution of seed banking as a bet-hedging strategy

Seed (egg) banking is a common bet-hedging strategy maximizing the fitness of organisms facing environmental unpredictability by the delayed emergence of offspring. Yet, this condition often requires fast and drastic stochastic shifts between good and bad years. We hypothesize that the host seed banking strategy can evolve in response to coevolution with parasites because the coevolutionary cycles promote a gradually changing environment over longer times than seed persistence. We study the evolution of host germination fraction as a quantitative trait using both pairwise competition and multiple mutant competition methods, while the germination locus can be genetically linked or unlinked with the host locus under coevolution. In a gene-for-gene model of coevolution, hosts evolve a seed bank strategy under unstable coevolutionary cycles promoted by moderate to high costs of resistance or strong disease severity. Moreover, when assuming genetic linkage between coevolving and germination loci, the resistant genotype always evolves seed banking in contrast to susceptible hosts. Under a matching-allele interaction, both hosts genotypes exhibit the same seed banking strategy irrespective of the genetic linkage between loci. We suggest host-parasite coevolution as an additional hypothesis for the evolution of seed banking as a temporal bet-hedging strategy.

evolutionary biology↗

bioRxiv2017

The evolutionary history of the current global Ramularia collo-cygni epidemic

Ramularia Leaf Spot (RLS) has emerged as a threat for barley production in many regions of the world. Late appearance of unspecific symptoms caused that Ramularia collo-cygni could only by molecular diagnostics be detected as the causal agent of RLS. Although recent research has shed more light on the biology and genomics of the pathogen, the cause of the recent global spread remains unclear.\n\nTo address urgent questions, especially on the emergence to a major disease, life-cycle, transmission, and quick adaptation to control measures, we de-novo sequenced the genome of R. collo-cygni (urug2 isolate). Additionally, we sequenced fungal RNA from 6 different conditions, which allowed for an improved genome annotation. This resulted in a high quality draft assembly of about 32 Mb, with only 78 scaffolds with an N50 of 2.1 Mb. The overall annotation enabled the prediction of 12.346 high confidence genes. Genomic comparison revealed that R. collo-cygni has significantly diverged from related Dothidiomycetes, including gain and loss of putative effectors, however without obtaining species-specific genome features.\n\nTo evaluate the species-wide genetic diversity, we sequenced the genomes of 19 R. collo-cygni isolates from multiple geographic locations and diverse hosts and mapped sequences to our reference genome. Admixture analyses show that R. collo-cygni is world-wide genetically uniform and that samples do not show a strong clustering on either geographical location or host species. To date, the teleomorph of R. collo-cygni has not been observed. Analysis of linkage disequilibrium shows that in the world-wide sample set there are clear signals of recombination and thus sexual reproduction, however these signals largely disappear when excluding three outliers samples, suggesting that the main global expansion of R. collo-cygni comes from mixed or clonally propagating populations. We further analysed the historic population size (Ne) of R. collo-cygni using Bayesian simulations.\n\nWe discuss how our genomic data and population genetics analysis can help understand the current R. collo-cygni epidemic and provide different hypothesis that are supported by our data. We specifically highlight how recombination, clonal spreading and lack of host-specificity could further support global epidemics of this increasingly recognized plant disease and suggest specific approaches to combat this pathogen.

plant biology↗

bioRxiv2017

A small subset of NLR genes drives local adaptation to pathogens in wild tomato

O_LINucleotide binding site, Leucine-rich repeat Receptors (NLRs), are canonical resistance (R) genes in plants, fungi and animals, functioning as central (helper) and peripheral (sensor) genes in a signalling network. We investigate NLR evolution during the colonisation of novel habitats in a model tomato species, Solanum chilense.\nC_LIO_LIWe used R-gene enrichment sequencing (RENSeq) to obtain polymorphism data at NLRs of 140 plants sampled across 14 populations covering the whole species range. We inferred the past demographic history of habitat colonisation by resequencing whole genomes from three S. chilense plants from three key populations, and performing Approximate Bayesian Computation using data from the 14 populations.\nC_LIO_LIUsing these parameters we simulated the genetic differentiation statistics distribution expected under neutral NLR evolution, and identified small subsets of outlier NLRs exhibiting signatures of selection across populations.\nC_LIO_LINLRs under selection between habitats are more often helper genes, while those showing signatures of adaptation in single populations are more often sensor-NLRs. Thus, centrality in the NLR network does not constrain NLR evolvability, and new mutations in central genes in the network are key for R gene adaptation during colonisation of different habitats.\nC_LI

evolutionary biology↗

bioRxiv2017

Effects of population- and seed bank noise on neutral evolution and efficacy of natural selection

Population genetics models typically consider a fixed population size and a unique selection coefficient. However, population dynamics inherently generate noise in numbers of individuals and selection acts on various components of the individuals fitness. In plant species with seed banks, the size of both the above- and below-ground compartments present noise depending on seed production and the state of the seed bank. We investigate if this noise has consequences on 1) the rate of genetic drift, and 2) the efficacy of selection. We consider four variants of two-allele Moran-type models defined by combinations of presence and absence of noise in above-ground and seed bank compartments. Time scale analysis and dimension reduction methods allow us to reduce the corresponding Fokker-Planck equation to a one-dimensional diffusive Moran model. We first show that if the above-ground noise classically affects the rate of genetic drift, below-ground noise reduces the diversity storage effect of the seed bank. Second, we consider that selection can act on four different components of the plant fitness: plant or seed death rate, seed production or seed germination. Our striking result is that the efficacy of selection for seed death rate or germination rate is reduced by seed bank noise, whereas selection occurring on plant death rate or seed production is not affected. We derive the expected site-frequency spectrum reflecting this heterogeneity in selection efficacy between genes underpinning different plant fitness components. Our results highlight the importance to consider the effect of ecological noise to predict the impact of seed banks on neutral and selective evolution.

evolutionary biology↗

bioRxiv2017

Mutation rates in seeds and seed-banking influence substitution rates across the angiosperm phylogeny

1) BackgroundSeed-banking (the ability to persist in the soil over many generations) is usually considered as a dormant stage where genotypes are \"stored\" as a bet-hedging strategy in response to unpredictable environments. However, seed dormancy may instead have consequences for the integrity of the DNA and generate novel mutations.\n\n2) MethodsWe address this paradox by building phylogenies based on the plastomes and nuclear ITS of species belonging to ten angiosperm clades. In each clade, the substitution rate (branch-length) of a seed-banking species is compared with that of a closely-related non-seed-banking species.\n\n3) ResultsSeed-banking species show as high or higher substitution rates than non-seedbanking species, and therefore mutations occur in dormant seeds at a rate at least as high as in above-ground plants. Moreover, seed born mutations have the same probability to reach fixation as those from above ground. Our results are robust to differences in selection, generation time, and polymorphism.\n\n4) ConclusionsMutations occurring in seeds, and thus seed-banking, affect the population diversity of plant species, and are observable at the macro-evolutionary scale. Our study has consequences for seed storage projects, since the stored seeds are likely to accumulate mutations at a higher rate than previously thought.

evolutionary biology↗

bioRxiv2016

Joint inference of demography and mutation rates from polymorphism data and pedigrees

Inference of demography and mutation rates is of major interest but difficult because genetic data is only informative about the population mutation rate, the product of the effective population size times the mutation rate, and not about these quantities individually. Here we show that this limitation can be overcome by combining genetic data with pedigree information. To successfully use pedigree data, however, important aspects of real populations such as the presence of two sexes, unbalanced sex ratios and overlapping generations have to be taken into account. We present here an extension of the classic Wright-Fisher model accounting for these effects and show that the coalescent process under this model reduces to the classic Kingman coalescent with specific scaling parameters. We further derive the probability of a pedigree under that model and show how pedigree data can thus be used to infer demographic parameters. Finally, we present a computationally efficient inference approach combining pedigree information and genetic data summarized by the site frequency spectrum (SFS) that allows for the joint inference of the mutation rate, sex-specific population sizes and the fraction of overlapping generations. Using simulations we then show that these parameters can be accurately inferred from pedigrees spanning just a few generations, as are available for many species. We finally discuss future possible extensions of the model and inference framework necessary for applications to wild and domesticated species, namely the account for more complex demographies and the uncertainty in assigning pedigree individuals to specific generations.

genetics↗