Biology subjects

Vitalis, R.

Publications and source records attributed to Vitalis, R..

6 recordsLinked to original sources

bioRxiv2026

The dynamics of barrier locus accumulation during speciation with gene flow

Understanding how reproductive isolation (RI) evolves in the context of gene flow is central to explaining how new species arise. Theory predicts that the accumulation of barrier loci depends on the interplay between divergent selection, recombination, and genomic architecture. However, empirical tests that track these processes across multiple stages of divergence within species remain scarce. The pea aphid complex, which comprises sympatric host-specialised biotypes spanning a continuum of divergence, provides a powerful opportunity to examine how ecological adaptation drives reproductive isolation despite ongoing gene flow. Using whole-genome sequencing data from 13 sympatric European biotypes, we constructed a dense, reference-anchored view of genomic divergence that controls for shared genetic background and recombination landscape. Joint analyses of genetic differentiation, absolute divergence, genetic diversity, recombination, and introgression rates reveal a consistent signature of divergence with gene flow and enable robust identification of barrier loci. Across the divergence continuum, RI is highly polygenic, but barrier loci are clustered and enriched in low-recombination regions and large chromosomal rearrangements, which are expected to strengthen linkage disequilibrium and promote the coupling of barrier effects. While genome-wide differentiation and the number of barrier loci increase gradually with divergence, differentiation within barrier loci displays patterns consistent with non-continuous dynamics, which could reflect threshold effects predicted by theory. Barrier loci contain excesses of salivary effector, detoxification and chemosensory genes, highlighting their central role in host plant specialisation and RI. The representation of these gene categories varies across divergence levels, and some loci are shared among independent biotype comparisons, suggesting common functional routes to specialisation via parallel evolution or introgression. Together, our results provide a comprehensive view of the genomic architecture and evolutionary dynamics underlying speciation with gene flow, illustrating how tightly linked, polygenic architectures can facilitate adaptation and diversification in natural populations.

evolutionary biology↗

bioRxiv2024

Estimating hierarchical F-statistics from Pool-Seq data

Introduced over seventy years ago, F -statistics have been and remain central to population and evolutionary genetics. Among them, FST is one of the most commonly used descriptive statistics in empirical studies, notably to characterize the structure of genetic polymorphisms within and between populations, to shed light on the evolutionary history of populations, or to identify marker loci under differential selection for adaptive traits. However, the use of FST in simplified population models can overlook important hierarchical structures, such as geographic or temporal subdivisions, potentially leading to misleading interpretations and increasing false positives in genome scans for adaptive differentiation. Hierarchical F -statistics have been introduced to account for multiple predefined levels of population structure. Several estimators have also been proposed, including robust ones implemented in the popular R package hierfstat. Nevertheless, these were primarily designed for individual genotyping data and can be computationally intensive for large genomic datasets. In this study, we extend previous work by developing unbiased method-of-moments estimators for hierarchical F -statistics tailored for Pool-Seq data, a cost-effective alternative to individual genome sequencing. These Pool-Seq estimators have been developed in an anova framework, using definitions based on identity-in-state probabilities. The new estimators have been implemented in an updated version of the R package poolfstat, together with estimators for sample allele count data derived from individual genotyping data. We validate and compare the performance of these estimators through extensive simulations under a hierarchical island model. Finally, we apply these estimators to real Pool-Seq data from Drosophila melanogaster populations, demonstrating their usefulness in revealing population structure and identifying loci with high differentiation within or between groups of subpopulations and associated with spatial or temporal genetic variation.

genetics↗

bioRxiv2020

Evolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift

Resurrection studies are a useful tool to measure how phenotypic traits have changed in populations through time. If these traits modifications correlate with the environmental changes that occurred during the time period, it suggests that the phenotypic changes could be a response to selection. Selfing, through its reduction of effective size, could challenge the ability of a population to adapt to environmental changes. Here, we used a resurrection study to test for adaptation in a selfing population of Medicago truncatula, by comparing the genetic composition and flowering times across 22 generations. We found evidence for evolution towards earlier flowering times by about two days and a peculiar genetic structure, typical of highly selfing populations, where some multilocus genotypes (MLGs) are persistent through time. We used the change in frequency of the MLGs through time as a multilocus fitness measure and built a selection gradient that suggests evolution towards earlier flowering times. Yet, a simulation model revealed that the observed change in flowering time could be explained by drift alone, provided the effective size of the population is small enough (<150). These analyses suffer from the difficulty to estimate the effective size in a highly selfing population, where effective recombination is severely reduced.

evolutionary biology↗

bioRxiv2020

Power and limits of selection genome scans on temporal data from a selfing population

AO_SCPLOWBSTRACTC_SCPLOWTracking genetic changes of populations through time allows a more direct study of the evolutionary processes acting on the population than a single contemporary sample. Several statistical methods have been developed to characterize the demography and selection from temporal population genetic data. However, these methods are usually developed under the assumption of outcrossing reproduction and might not be applicable when there is substantial selfing in the population. Here, we focus on a method to detect loci under selection based on a genome scan of temporal differentiation, adapting it to the particularities of selfing populations. Selfing reduces the effective recombination rate and can extend hitch-hiking effects to the whole genome, erasing any local signal of selection on a genome scan. Therefore, selfing is expected to reduce the power of the test. By means of simulations, we evaluate the performance of the method under scenarios of adaptation from new mutations or standing variation at different rates of selfing. We find that the detection of loci under selection in predominantly selfing populations remains challenging even with the adapted method. Still, selective sweeps from standing variation on predominantly selfing populations can leave some signal of selection around the selected site thanks to historical recombination before the sweep. Under this scenario, ancestral advantageous alleles at low frequency leave the strongest local signal, while new advantageous mutations leave no local footprint of the sweep.

evolutionary biology↗

bioRxiv2018

Measuring genetic differentiation from Pool-seq data

The recent advent of high throughput sequencing and genotyping technologies enables the comparison of patterns of polymorphisms at a very large number of markers. While the characterization of genetic structure from individual sequencing data remains expensive for many non-model species, it has been shown that sequencing pools of individual DNAs (Pool-seq) represents an attractive and cost-effective alternative. However, analyzing sequence read counts from a DNA pool instead of individual genotypes raises statistical challenges in deriving correct estimates of genetic differentiation. In this article, we provide a method-of-moments estimator of FST for Pool-seq data, based on an analysis-of-variance framework. We show, by means of simulations, that this new estimator is unbiased, and outperforms previously proposed estimators. We evaluate the robustness of our estimator to model misspecification, such as sequencing errors and uneven contributions of individual DNAs to the pools. Last, by reanalyzing published Pool-seq data of different ecotypes of the prickly sculpin Cottus asper, we show how the use of an unbiased FST estimator may question the interpretation of population structure inferred from previous analyses.

evolutionary biology↗

bioRxiv2017

Population genomics of bank vole populations reveals associations between immune related genes and the epidemiology of Puumala hantavirus in Sweden

Infectious pathogens are major selective forces acting on individuals. The recent advent of high-throughput sequencing technologies now enables to investigate the genetic bases of resistance/susceptibility to infections in non-model organisms. From an evolutionary perspective, the analysis of the genetic diversity observed at these genes in natural populations provides insight into the mechanisms maintaining polymorphism and their epidemiological consequences. We explored these questions in the context of the interactions between Puumala hantavirus (PUUV) and its reservoir host, the bank vole Myodes glareolus. Despite the continuous spatial distribution of M. glareolus in Europe, PUUV distribution is strongly heterogeneous. Different defence strategies might have evolved in bank voles as a result of co-adaptation with PUUV, which may in turn reinforce spatial heterogeneity in PUUV distribution. We performed a genome scan study of six bank vole populations sampled along a North/South transect in Sweden, including PUUV endemic and non-endemic areas. We combined candidate gene analyses (Tlr4, Tlr7, Mx2 genes) and high throughput sequencing of RAD (Restriction-site Associated DNA) markers. We found evidence for outlier loci showing high levels of genetic differentiation. Ten outliers among the 52 that matched to mouse protein-coding genes corresponded to immune related genes and were detected using ecological associations with variations in PUUV prevalence. One third of the enriched pathways concerned immune processes, including platelet activation and TLR pathway. In the future, functional experimentations should enable to confirm the role of these these immune related genes with regard to the interactions between M. glareolus and PUUV.

evolutionary biology↗