Biology subjects

Capblancq, T.

Publications and source records attributed to Capblancq, T..

8 recordsLinked to original sources

bioRxiv2026

Contrasting signatures of interspecific gene flow in the Atlantic Forest endemic butterfly Heliconius besckei

Gene flow between diverging species can reshuffle genomic variation and greatly influence the speciation process, sometimes reinforcing, sometimes eroding species boundaries. However, the effect of ecological and historical processes on the patterns of introgression remains poorly understood. Here, we focus on the evolutionary history of Heliconius besckei, a geographically restricted butterfly endemic to the Brazilian Atlantic Forest, together with the mimetic H. melpomene nanna, the sympatric non-mimetic H. ethilla narcaea, and its closely related H. numata robigus. Using whole-genome sequencing, genome-wide tests of introgression, demographic modelling and palaeoclimatic species distribution models, we tested the extent and timing of interspecific gene flow in relation to mimicry, ecological context, and changes in geographic overlap. Despite strong genomic differentiation among the four focal Heliconius species, we detected widespread signatures of interspecific gene flow, greatly influenced by geographical overlap. Demographic models including post-divergence gene flow were better supported than strict-isolation models. In addition, genome-wide introgression analyses showed more numerous and larger candidate introgressed regions between H. besckei and H. ethilla narcaea, consistent with recurrent opportunities for exchange between these currently sympatric species. Species distribution models further recovered repeated expansions of suitable habitat for H. besckei during cold periods, providing a potential geographic context for secondary contact within the Atlantic Forest. Together, our results reveal recurrent gene flow occurring under different temporal, geographic, and potentially selective contexts, and show that the evolutionary history of a geographically restricted lineage can be shaped by repeated genetic exchange while substantial species differentiation is maintained.

evolutionary biology↗

bioRxiv2026

Demographic history shapes forest tree vulnerability to climate change

Demographic history is expected to play a central role in shaping population vulnerability to climate change through its lasting effects on effective population sizes and genetic connectivity. However, existing studies report contrasting outcomes, and the consequences of alternative demographic histories have seldom been assessed concurrently across multiple taxa. Here, we analysed population genomic data from six of the major European forest tree species to address this gap. Across species, genetic isolation reduced adaptive potential, as reflected in lower standing genetic diversity. Greater genetic differentiation was also associated with increased maladaptation to climate, whereas the purge or accumulation of deleterious mutations depended on the severity of past demographic events. Finally, the beneficial effects of gene flow were evidenced across the six species by more optimal climate adaptation in highly connected populations. Altogether, our results provide valuable insights into how genetic differentiation, reflecting the combined effects of genetic drift and limited historical gene flow, influences current vulnerability of forest tree populations to climate change.

evolutionary biology↗

bioRxiv2024

Untangling the contribution of adaptive versus non-adaptive processes in the evolution of reproductive isolation between Coenonympha butterflies.

Speciation is a key evolutionary process which has been studied in numerous organisms and at multiple scales, from lineage radiation to gene expression. However, the factors explaining the rise of new species are not yet fully understood, and the relative contribution of neutral versus selective evolutionary processes in triggering and maintaining reproductive isolation between lineages is still debated. To explore this question, we study the divergence of two butterfly species, Coenonympha arcania and C. gardetta (Nymphalidae), which diverged relatively recently but show strong ecological differences. Whole genome sequence data reveal high overall differentiation between the two lineages, best explained by a long period of isolation at the early stage of their divergence. Demographically explicit approaches identify that 6.6% of the genome (32.7 Mbp) is impermeable to gene flow between the two species. Lots of these barrier loci are located on the Z chromosome, potentially spanning 75% of its length which would indicate that a large Z effect is at play in this speciation. Moreover, only a small proportion of barriers showed signatures of selection, suggesting that non-adaptive processes largely contributed to the build-up of reproductive isolation. Therefore, although genes involved in stress response and response to hypoxia are interesting candidates under selection, the adaptation of C. gardetta to alpine conditions may not to be the main driver of speciation. Our study brings an original example of intertwined adaptive and non-adaptive processes leading to reproductive isolation in a speciation with secondary contact and improves our understanding of the genomic underpinnings of species divergence.

evolutionary biology↗

bioRxiv2023

Novel genomic offset metrics account for local adaptation in climate suitability forecasts and inform assisted migration

Local adaptation is increasingly being integrated into macroecological models, offering an evolutionary perspective that has been largely missing from climate change biogeography. Genomic offsets, which quantify the disruption of existing genotype-environment associations under environmental change, are an informative landscape genomic tool that allows for the incorporation of intra-specific adaptive differentiation into forecasts of climate suitability and thus management planning. Gradient forest (GF), a method originally developed to model community turnover along environmental gradients, is now the most commonly used approach in genomic offset estimation. However, major hurdles in the application of GF-derived offsets are (1) an inability to interpret the absolute magnitude of genomic offsets in a biologically meaningful way and (2) uncertainty in how genomic offsets compare to established species-level approaches like Ecological Niche Models (ENMs). We used both ENMs and novel, genomic offset metrics derived from GF modeling of genomic variation along climatic gradients to assess the climate change vulnerability of red spruce (Picea rubens), a cool-temperate tree species endemic to eastern North America. We show how genomic offsets can be standardized relative to contemporary genomic variation across the landscape to better represent their biological significance and facilitate comparisons among studies. In three common gardens, we found a significant negative relationship between standardized genomic offsets and red spruce growth and higher explanatory power for standardized offsets than (raw) climate transfer distances. We also derived new threshold-based metrics that we term Donor and Recipient Importance and which quantify transferability of propagules between donor and recipient localities while minimizing disruption of genotype-environment associations. This approach leverages landscape genomic information to account for local adaptation when predicting climate suitability. ENMs and our novel genomic offset metrics largely agreed in forecasting drastic northward range shifts. Combining several offset-based metrics, we show that the projected northward shift of suitable climate mainly applies to populations located in the center and northern parts of the current range, whereas southern populations might be able to persist in situ owing to specific local climate adaptations. The novel metrics thus yield refined, region-specific prognoses for local persistence and show how management could be improved by considering assisted migration.

ecology↗

bioRxiv2020

Discovery of cryptic plant diversity in one of the harshest environments: the rooftops of the Alps

High altitude temperate mountains have long been considered devoid of life owing to high extinction or low speciation rates during the Pleistocene. We performed a phylogenetic and population genomic investigation of an emblematic high-altitude plant clade (Androsace sect. Aretia, 31 currently recognized species), based on plant surveys conducted during alpinism expeditions. Surprisingly, we inferred that this clade originated in the Miocene and continued diversifying through Pleistocene glaciations, and discovered three novel species of Androsace dwelling on different bedrock types on the rooftops of the Alps. This suggests that temperate high mountains have been cradles of plant diversity even during the Pleistocene, with in-situ speciation driven by the combined action of geography and geology. Our findings have an unexpected historical relevance: H.-B. de Saussure likely observed one of these species during his 1788 expedition to the Mont Blanc and we describe it here, over two hundred years after its first sighting.

evolutionary biology↗

bioRxiv2019

Climate associated genetic variation in Fagus sylvatica and potential responses to climate change in the French Alps.

Local adaptation patterns have been found in many plants and animals, highlighting the genetic heterogeneity of species along their range of distribution. In the next decades, global warming must induce a change in the selective pressures that drive this adaptive variation, forcing a reshuffling of the underlying adaptive allele distributions. For species with low dispersion capacity and long generation time such as trees, the rapidity of the change could imped the migration of beneficial alleles and lower their capacity to track the changing environment. Identifying the main selective pressures driving the adaptive genetic variation is thus necessary when investigating species capacity to respond to global warming. In this study, we investigate the adaptive landscape of Fagus sylvatica along a gradient of populations in the French Alps. Using a ddRAD-seq approach, we identified 7,000 SNPs from 570 individuals across 36 different sites. An RDA-derived method allowed us to identify several SNPs that were strongly associated with climatic gradients; moreover, we defined the primary selective gradients along the natural populations of F. sylvatica in the Alps. Strong effects of elevation and humidity, which contrast north-western and south-eastern site, were found and were believed to be important drivers of genetic adaptation. Finally, simulations of future genetic landscapes that used these findings predicted a severe range contraction and a shift towards higher altitudes for F. sylvatica in the Alps and allowed to identify populations at risk, which could be helpful for future management plans.

evolutionary biology↗

bioRxiv2018

Double-digest RAD-sequencing: do wet and dry protocol parameters impact biological results?

O_LINext-generation sequencing technologies have opened a new era of research in genomics. Among these, restriction enzyme-based techniques such as restriction-site associated DNA sequencing (RADseq) or double-digest RAD-sequencing (ddRADseq) are now widely used in many population genomics fields. From DNA sampling to SNP calling, both wet and dry protocols have been discussed in the literature to identify key parameters for an optimal loci reconstruction.\nC_LIO_LIThe impact of these parameters on downstream analyses and biological results drawn from RADseq or ddRADseq data has however not been fully explored yet. In this study, we tackled this issue by investigating the effects of ddRADseq laboratory (i.e. wet protocol) and bioinformatics (i.e. dry protocol) settings on loci reconstruction and inferred biological signal at two evolutionary scale using two systems: a complex of butterfly species (Coenonympha sp.) and populations of Common beech (Fagus sylvatica).\nC_LIO_LIResults suggest an impact of wet protocol parameters (DNA quantity, number of PCR cycles during library preparation) on the number of recovered reads and SNPs, the number of unique alleles and individual heterozygosity. We also found that bioinformatic settings (i.e. clustering and minimum coverage thresholds) impact loci reconstruction (e.g. number of loci, mean coverage) and SNP calling (e.g. number of SNPs, heterozygosity). We however do not detect an impact of parameter settings on three types of analysis performed with ddRADseq data: measure of genetic differentiation, estimation of individual admixture, and demographic inferences. In addition, our work demonstrates the high reproducibility and low rate of genotyping inconsistencies of the ddRADseq protocol.\nC_LIO_LIThus, our study highlights the impact of wet parameters on ddRADseq protocol with strong consequences on experimental success and biological conclusions. Dry parameters affects loci reconstruction and descriptive statistics but not biological conclusion for the two studied systems. Overall, this study illustrates, with others, the relevance of ddRADseq for population and evolutionary genomics at the inter- or intraspecific scales.\nC_LI

molecular biology↗

bioRxiv2018

How to make use of ordination methods to identify local adaptation: a comparison of genome scans based on PCA and RDA

Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast.

genomics↗