Biology subjects

Goudet, J.

Publications and source records attributed to Goudet, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Widespread but cryptic introgression shapes genetic diversity in natural populations

Introgression following hybridization is increasingly recognized as a major driver of evolution. However, its importance depends on its frequency in nature, which remains to be quantified. To address this, we provide a snapshot of ongoing introgression in a whole species assemblage (4126 ant colonies). 23% of all 82 local species show signs of introgression, which is more than twice previous estimates. Introgression is typically subtle, yet contributes measurably to genetic diversity. Species divergence, rather than classical prezygotic reproductive barriers (mating phenology, ecological niche, fine-scale habitat use) constrains introgression, suggesting that the main reproductive barriers are postzygotic at this stage of divergence. Our results indicate that introgression may be a common but often overlooked feature of natural communities.

evolutionary biology↗

bioRxiv2026

LAVA: a method for identifying local and global adaptation in structured populations

Demonstrating that local adaptation drives phenotypic divergence in quantitative traits requires distinguishing selection from neutral differentiation. Existing methods for detecting selection on quantitative traits, particularly QST - FST comparisons, rely on simplified assumptions about population structure. These methods assume equal relatedness among all subpopulations, which is not necessarily true in a real metapopulation. When assumptions are violated, it has been shown that QST - FST leads to elevated false positive rates. Here we present MONET, a model for the neutral evolution of traits that creates a robust baseline against which hypotheses on trait evolution can be tested. We show how the null model provided by MONET can be the basis of two tests: one based on the log-ratio of ancestral variances (logAV) statistics we previously introduced, and another, based on testing the influence of environmental variables from the populations of origin on the phenotypic traits measured in a common garden. MONET is implemented in an R-package as a Bayesian linear mixed-effect framework modeling population structure through relatedness matrices. We show through extensive simulations across different population structures and selective scenarios how our two hypothesis tests based on MONET maintain proper calibration while maintaining or exceeding the power of alternative methods.

evolutionary biology↗

bioRxiv2026

A chromosome-level, haplotype-resolved genome assembly for the barn owl, Tyto alba

Recent advances in long-read sequencing have enabled near telomere-to-telomere (T2T) assemblies across diverse taxa. However, avian genomes remain challenging due to numerous microchromosomes, small, typically < 20Mb, elements that are gene-, GC-, and repeat-rich. As a consequence, microchromosomes are often missing from genome assemblies. Here, we present a chromosome-level, haplotype-resolved genome assembly for the Western barn owl (Tyto alba). Using a trio-binning strategy with Illumina parental reads combined with PacBio HiFi and Oxford Nanopore Technologies data, we generated two phased contig sets. These were scaffolded into 40 linkage groups using a linkage map. Comparative analyses identified unplaced HiFi scaffolds corresponding to microchromosomes, which we integrated into six additional microchromosomes using long reads information. The two assemblies present 46 chromosomes, matching the karyotype of the species. They exhibit strong synteny between parental haplotypes, except for a [~]38 Mb complex region on chromosome 7 containing nested inversions. This high-quality reference provides the first haplotype-resolved and chromosome-level genome for Strigiformes, enabling fine-scale studies of structural variation and avian genome evolution.

genomics↗

bioRxiv2026

The effect of age and sex on the rate of de novo mutations in barn owls

The rate of new mutations is the ultimate source of genetic variation, and thus, a fundamental quantity in evolution. Mutation rates vary across the tree of life, influenced by selection pressures and life-history traits. Within species, mutation rates and types show subtle differences between sexes as well as a positive association with parental age. Most of the direct estimates come from a few mammal species, often primates, and their generality has not been fully realised. Using 33 parent-offspring trios, we investigate the mutation rate in the barn owl (Tyto alba) and show that this species has a mutation rate of 5.6 x 10-9, matching rates of passerine species with a similar generation time of 2-3 years. Using different phasing methods we show that fathers pass on twice as many mutations as mothers and identify subtle differences in the sex-specific spectra of mutations. We also find that the number of mutations increases with paternal age, bringing direct evidence for germline senescence in birds. While across-species mutation rates and types appear conserved, the potential for within species variation due to age is substantial.

evolutionary biology↗

bioRxiv2026

Allelic Association Analyses: Estimation Recommendations

We review the rich literature on the estimation of measures of inbreeding, relatedness and population structure, beginning with Sewall Wrights F-statistics and moving onto the descriptive statistics of Masatoshi Nei and Clark Cockerham. The current availability of genome-level single nucleotide variant data is allowing for sophisticated treatments of inferred identity by descent segments and inferred ancestral recombination graphs. Underlying such disparate methods is an emphasis of characterizing the descent status of alleles within and between individuals and populations and we have found allele-sharing statistics a convenient framework for examining the differences and similarities among different estimators. We have been able to resolve some long-standing reported differences among estimators, especially those involving the work of Nei. In the course of our algebraic and empirical treatment of descent measure estimation we have been able to formulate a set of five recommendations. Following the early work of Sewall Wright, we recommend 1. State that descent measures for pairs of alleles are relative to values in a reference set of allele pairs. With this view, we recommend 2. Use estimators that preserve descent measure rankings over different reference sets. Allele-sharing estimators satisfy this recommendation. Reducing genotypic data to allelic data has the benefit of reducing dimensionality, but we recommend 3. If genotypic data are available, avoid having to assume Hardy-Weinberg equilibrium by not reducing them to allelic data. Partly as a consequence of working with genotypic data, we recommend 4. Recognize that allele frequencies do not need to be estimated. Not estimating allele frequencies prevents the confounding of descent estimates for target pairs of alleles by the status of all pairs in a reference set. On the basis of both theoretical and empirical results, finally we recommend 5. Consider both inbreeding and kinship when estimating either one. It is difficult to envisage a natural population with relatedness but no inbreeding, or vice versa.

genomics↗

bioRxiv2025

Benchmarking imputation accuracy in the presence or absence of a reference panel

Whole genome sequencing (WGS) of a large number of samples is costly. Solutions to reduce this cost include targeting a proportion of the genome (e.g. SNP arrays) or lowering the sequencing depth (low-coverage WGS, lcWGS) but both solutions suffer from either genotype missingness or uncertainty. Genomic imputation addresses this problem by inferring missing or uncertain genotypes using a collection of high quality genomic data (a reference panel). However, certain methods can impute a lcWGS dataset without a reference panel. Because the investment into generating a reference panel can be prohibitively expensive in non-model species, a benchmarking of the accuracy of these alternative methods of imputation can help inform study design. Here, we imputed a dataset of 2800 lcWGS in the presence and absence of a reference panel of 502 samples. We used 32 individuals sequenced at both high and low coverage to estimate the accuracy of each method and explored the limitations of lcWGS sample size and reference panel size. Although the best results were achieved with a large reference panel, using only a lcWGS dataset showed accurate imputation, when over 500 samples were used and we account for missing data and low frequency alleles. In addition, imputing with or without a reference panel gave similar results in a GWAS for a polygenic trait but required some quality control in the identification of homozygous-by-descent segments. Thus, while using a reference panel remains the ideal approach, imputation in suitably large lcWGS datasets can provide sufficient accuracy given proper quality control.

genomics↗

bioRxiv2025

Genomic bases of short-term evolution in the wild revealed by long-term monitoring and population-scale sequencing

Understanding how wild populations adapt to rapid environmental change requires linking phenotypic evolution to its genomic basis over contemporary timescales. This remains challenging because genetic and environmental effects are often intertwined. Here, we leverage a 30-year study of Swiss barn owls (Tyto alba) to explore this process. During this period, owls have evolved darker plumage and increased spottiness, two melanin-based traits associated with fitness. Whole-genome sequencing of 3,102 individuals reveals that these traits are largely controlled by few loci of major effect with partially overlapping architectures. Temporal allele frequency analyses show subtle but consistent shifts at these loci. Simulations indicate that genetic drift alone cannot explain these changes, whereas models incorporating selection do. Our findings demonstrate that selection on a small number of loci can drive rapid phenotypic evolution in the wild. This work underscores the adaptive potential of natural populations and the value of long-term genomic monitoring under accelerating climate change.

evolutionary biology↗

bioRxiv2025

Growth effects and the underlying genetic architecture of inbreeding depression in a wild raptor

1Despite its potentially devastating effects, the prevalence and underlying mechanisms of inbreeding depression in wild populations are still relatively under-explored. Here, we use whole-genome sequence data from >3,000 wild barn owls from Switzerland to investigate the presence, severity, and genetic architecture of inbreeding depression in three morphological traits. Using a combination of linear models (accounting for age) and non-linear models (to measure growth effects) we clearly show inbreeding depression is present in this population. Moreover, by breaking-down the timing of the effects we also have a better ability to detect inbreeding depression, as in some traits we find that it manifests during juvenile growth, and in others during adulthood. To our knowledge this is the first study to show direct evidence for inbreeding depression during the crucial early life weight gain period in a wild animal. We further show that certain trait-specific patterns may reflect differences in environmental influences across life stages, as we find that heritability is often lower before adulthood. We also use two classes of genomic inbreeding coefficients: FROH and FUniW, and while the directionality of effects is equivalent, the strength of evidence regarding the presence of inbreeding depression differs depending on the coefficient used. This discrepancy might give some insight into the frequency distribution of responsible variants, as each coefficient weights variants differently based on their population frequencies. Finally, an assessment of local genomic inbreeding effects highlights a handful of regions with significantly deleterious effects, alongside many regions with a smaller contribution to the observed inbreeding depression. Overall, we provide a comprehensive overview of the effects of inbreeding in this wild population, highlighting the dynamic interplay between environmental influences and the selection pressure against inbred individuals.

evolutionary biology↗

bioRxiv2025

A method for identifying spatially divergent selection in structured populations.

Species occupy diverse, heterogeneous environments, which expose populations to spatially varied selective pressures. Populations in different environments can diverge due to local adaptation. However, neutral evolution can also drive population divergence. Thus, testing for local adaptation requires a neutral baseline for population differentiation. The classical QST -FST comparison was developed for this purpose. Yet, QST -FST frequently fails to account for the complexities of population structure because the theory underlying this comparison assumes that all subpopulations are equally related, resulting in inflated false positive rates in metapopulations that deviate from the island model. To address this limitation we use estimates of between- and within-population relatedness to model population structure. Using those relatedness matrices, we infer the between- and within-population ancestral additive genetic variances under a mixed-effects model. Under neutrality, these inferred variances are expected to be equal. We propose here a test to detect selection based on the comparison of these two estimates of the ancestral variance and we compare its performance with earlier solutions. We find our method is well calibrated across various population structures and has high power to detect adaptive divergence. Author summaryPopulations of the same species often face different environmental pressures, driving them to adapt locally. However, even in the absence of adaptation, subpopulations can diverge due to random genetic drift and limited migration. Distinguishing between adaptive evolution and random divergence is a central challenge in evolutionary biology. Traditional methods, such as QST -FST comparison, assume equal relatedness among subpopulations--a simplification that rarely holds in complex real-world scenarios, leading to flawed conclusions. To overcome this limitation, we developed a novel method that incorporates genetic relatedness among subpopulations, leveraging quantitative genetic theory to estimate ancestral additive genetic variances. Our approach provides a powerful tool for testing local adaptation, reliably distinguishing adaptive divergence from drift across a variety of population structures.

evolutionary biology↗

bioRxiv2024

The recombination landscape of the barn owl, from families to populations

Homologous recombination is a meiotic process that generates diversity along the genome and interacts with all evolutionary forces. Despite its importance, studies of recombination landscapes are lacking due to methodological limitations and a dearth of appropriate data. Linkage mapping based on familial data gives unbiased sex-specific broad-scale estimates of recombination while linkage disequilibrium (LD) based inference based on population data provides finer resolution data albeit depending on the effective population size and acting selective forces. In this study, we use a combination of these two methods, using a dataset of whole genome sequences and elucidate the recombination landscape for the Afro-European barn owl (Tyto alba). Linkage mapping allows us to refine the genome assembly to a chromosome-level quality. We find subtle differences in crossover placement between sexes that leads to differential effective shuffling of alleles. LD based estimates of recombination are concordant with family-based estimates and identify large variation in recombination rates within and among linkage groups. Larger chromosomes show variation in recombination rates while smaller chromosomes have a universally high rate which shapes the diversity landscape. We also identify local recombination hotspots in accordance with other studies in birds lacking the PRDM9 gene. However these hotspots show very little evolutionary stability when compared among populations with shallow genetic differentiation. Overall, this comprehensive analysis enhances our understanding of recombination dynamics, genomic architecture, and sex-specific variation in the barn owl, contributing valuable insights to the broader field of avian genomics. Article summaryTo study recombination events we look either in family data or in population data, with each method having advantages over the other. In this study we use both approaches to quantify the barn owl recombination landscape. We find that differences exist between sexes, populations and chromosomes.

genomics↗

bioRxiv2024

Estimation of Jacquard's genetic identity coefficients with bi-allelic variants by constrained least-squares

The Jacquard genetic identity coefficients are of fundamental importance in relatedness research. We address the estimation of these coefficients as well as other relatedness parameters that derive from them such as kinship and inbreeding coefficients using a concise matrix framework. Estimation of the Jacquard coefficients via likelihood methods and the expectation-maximization algorithm is computationally very demanding for large numbers of polymorphisms. We propose a constrained least squares approach to estimate the Jacquard coefficients. A simulation study shows constrained least squares achieves root-mean-squared errors that are comparable with those of the maximum likelihood approach, in particular when founder allele frequencies are unknown, while obtaining enormous computational savings.

genetics↗

bioRxiv2023

Detecting inbreeding depression in structured populations

Measuring inbreeding as well as its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However, there is no consensus on the most appropriate method, neither for quantification of inbreeding itself nor for the model to estimate its effect on specific traits. In this project, we simulated traits based on simulated genomes from a large pedigree and empirical whole-genome sequences of human data from populations with various sizes and structure (from the 1,000 Genomes project). We compare the ability of various inbreeding coefficients (F) to quantify the strength of inbreeding depression: allele sharing, two versions of the correlation of uniting gametes which differ in the weight they attribute to each locus and two identical-by-descent segments-based estimators. We also compare two models: the standard linear model and a linear mixed model including a genetic relatedness matrix (GRM) as random effect to account for the non-independence of observations. We find linear mixed models give better results in scenarios with population or family structure. Within the mixed models, we compare three different GRM matrices and show that in homogeneous populations, there is little difference among the different F and GRM for inbreeding depression quantification. However, as soon as strong population or family structure is present, the strength of inbreeding depression can be most efficiently estimated only if (i) the phenotypes are regressed on inbreeding coefficient based on a weighted version of the correlation of uniting gametes, which gives more weight to common alleles and (ii) with the GRM obtained from an allele sharing relatedness estimator.

genomics↗

bioRxiv2023

An allele-sharing, moment-based estimator of global, population specific and population pairs FST under a general model of population structure

Being able to properly quantify genetic differentiation is key to understanding the evolutionary potential of a species. One central parameter in this context is FST, the mean coancestry within populations relative to the mean coancestry between populations. Researchers have been estimating FST globally or between pairs of populations for a long time. More recently, it has been proposed to estimate population specific FST values, and between population-pair mean relative coancestry. Here, we review the several definitions and estimation methods of FST, and stress that they provide values relative to a reference population. We show the good statistical properties of an allele sharing, method of moments based estimator of FST (global, population specific and population pairs) under a very general model of population structure. We point to the limitation of existing likelihood and Bayesian estimators when the populations are not independent. Last, we show that recent attempts to estimate absolute, rather than relative, mean coancestry fail to do so. Author summary

evolutionary biology↗

bioRxiv2023

The genomic architecture of a continuous color polymorphism in the European barn owl (Tyto alba)

The maintenance of color polymorphism in populations has fascinated evolutionary biologists for decades. Studies of color variation in wild populations often focus on discrete color traits exhibiting simple inheritance patterns, while studies on continuously varying traits remain rare. Here, we studied the continuous white to rufous color polymorphism in the European barn owl (Tyto alba). Using a Genome Wide Association approach on whole-genome data of 75 barn owls sampled across Europe, we identified, in addition to a previously known MC1R mutation, two regions involved in this color polymorphism. We show that the combination of the three explains 80.37% (95% credible interval 58.45 to 100%) of the color variation. Among the two newly identified regions, the one on the sexual chromosome (Z) shows a large signal of differentiation in the Swiss population when contrasting individuals with different morph but the same MC1R genotype. We suggest it may play a role in the sexual dimorphism observed locally in the species. These results, uncovering two new genomic regions, provide keys to better understand the molecular bases of the color polymorphism as well as the mechanisms responsible for its maintenance in the European barn owl at both continental and local scales.

genomics↗

bioRxiv2023

Where and when local adaptation happens: lessons from the European barn owl (Tyto alba)

Although local adaptation influences species distributions, its role in driving evolutionary resilience under climate change remains unclear. Current predictive models focus on genetic adaptation to present climates, providing limited insight into future adaptive capacity. We hypothesise that historical responses to climatic shifts can reveal future adaptive potential. Combining ecological niche modelling and genomic analyses, we investigated spatiotemporal patterns and mechanisms of local adaptation of the Western Palearctic barn owl (Tyto alba). Ecological modelling revealed that barn owls now occupy a broader climatic niche than during the Last Glacial Maximum. Genomic analyses indicated ongoing adaptation, with regions under selection linked to environmental factors across all populations. Our findings demonstrate that local adaptation drives evolutionary changes across populations, enabling colonisation of new habitats and shaping responses to climate change in resident populations. We demonstrate that standing genetic diversity plays a crucial role in adaptation to past, present, and future environmental shifts.

evolutionary biology↗

bioRxiv2022

Effect of reduced genomic representation on using runs of homozygosity for inbreeding characterization

Runs of homozygosity (ROHs) are proxy for genomic Identical-by-Descent segments and are increasingly used to measure individual inbreeding. ROHs analyses are mostly carried out on SNPs-arrays and whole-genome-sequencing data. Softwares recurrently used for their detection usually assume that genomic positions which have not been genotyped are non-variant. This might be true for whole-genome-sequencing data, but not for reduced genomic representations and can lead to spurious ROHs detection. We simulated the outputs of whole-genome-sequencing, two SNP-arrays and RAD-sequencing for three populations with different sizes. We compare the results of ROHs calling with two softwares: PLINK and RZooRoH. We demonstrate that to obtain meaningful estimates of inbreeding coefficients, RZooRoH requires fraction of genome seven times smaller compared to PLINK. When the SNP density is above 20 SNPs/Mb for PLINK and 3 SNPs/Mb for RZooRoH, ranks of ROHs-based inbreeding coefficients are conserved among individuals. With reduced genomic representations, ROHs distributions are consistently biased towards an underestimation of the total numbers of small and an overestimation of the total numbers of large ROHs, except for RZooRoH and high-density SNPs-arrays. We conclude that both ROHs-based inbreeding coefficients and ROHs distributions exact quantification are highly dependent on the fraction of genome sequenced and should thus be treated with caution. However, relative inbreeding estimates, such as comparison between individuals or populations, are reliable with reduced genomic representations providing that the fraction of genome sequenced is large enough. Consequently, we advise researchers working with reduced genomic data to use SNPs-independent measures or model-based ROHs calling methods for inbreeding estimations.

genomics↗

bioRxiv2021

Genomic bases of insularity and ecological divergence in barn owls (Tyto alba) of the Canary Islands

Islands, and the particular organisms that populate them, have long fascinated biologists. Due to their isolation, islands offer unique opportunities to study the effect of neutral and adaptive mechanisms in determining genomic and phenotypical divergence. In the Canary Islands, an archipelago rich in endemics, the barn owl (Tyto alba) is thought to have diverged into a subspecies (T. a. gracilirostris) on the eastern islands, Fuerteventura and Lanzarote. Taking advantage of 40 whole-genomes and modern population genomics tools, we provide the first look at the origin and genetic makeup of barn owls of this archipelago. We show that the Canaries hold diverse, long-standing and monophyletic populations with a neat distinction of gene pools from the different islands. Using new method, less sensitive to structure than classical FST, to detect regions involved in local adaptation to the insular environment, we identified a haplotype-like region likely under positive selection in all Canaries individuals. Genes in this region suggest morphological adaptations to insularity. In the eastern islands, where the subspecies T. a. gracilirostris is present, genomic traces of selection pinpoint signs of locally adapted body proportions and blood pressure, consistent with the smaller size of this population living in a hot arid climate. In turn, genomic regions under selection in the western barn owls from Tenerife showed an enrichment in genes linked to hypoxia, a potential response to inhabiting a small island with a marked altitudinal gradient. Our results illustrate the interplay of neutral and adaptive forces in shaping divergence and early onset speciation.

evolutionary biology↗

bioRxiv2021

Population structure in the MHC region

In his 1972 "The apportionment of human diversity", Lewontin showed that, when averaged over loci, genetic diversity is predominantly attributable to differences among individuals within populations. However, selection on specific genes and genomic regions can alter the apportionment of diversity. We examine genetic diversity at the HLA loci, located within the MHC region. HLA genes code for proteins that are critical to adaptive immunity and are well-documented targets of balancing selection. The SNPs within HLA genes show strong signatures of balancing selection on large timescales and are broadly shared among populations, with low FST values. However, when we analyze haplotypes defined by these SNPs (i.e., which define "HLA alleles"), we find marked differences in frequencies between geographic regions. These differences are not reflected in the FST values because of the extreme polymorphism at HLA loci, illustrating challenges in interpreting FST. Differences in the frequency of HLA alleles among geographic regions are relevant to bone-marrow transplantation, which requires genetic identity at HLA loci between patient and donor. We explore the case of Brazils bone-marrow registry, where a deficit of enrolled volunteers with African ancestry reduces the chance of finding donors for individuals with an MHC region of African ancestry.

genetics↗