Biology subjects

Dutheil, J. Y.

Publications and source records attributed to Dutheil, J. Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Model-based inference of gene expression noise from single-cell RNA-sequencing data

The heterogeneity of expression levels among genetically identical cells, termed gene expression noise, is a property of the gene expression process whose importance in the biology of organisms and their evolution is increasingly recognized. Measuring gene expression noise requires single-cell expression data, as obtained from single-cell RNA sequencing (scRNASeq). Its estimation, however, is challenging owing to (i) the presence of technical noise in addition to biological noise, and (ii) the heterogeneity of cell types in the sampled population. We propose a maximum-likelihood framework to infer biological noise from scRNASeq data, while accounting for technical noise, dropout probabilities, and distinct cell sequencing depths. We demonstrate the parameter identifiability using simulations and that the resulting noise estimates are uncorrelated from the mean gene expression, and therefore do not need extra correction in downstream analyses, easing intra- and inter-genome comparisons. Using two technical replicates of scR-NASeq data from the wild yeast Saccharomyces paradoxus, we show that expression noise can be inferred in a reproducible manner.

bioinformatics↗

bioRxiv2026

The Shifting Tempo of Evolution: Mapping Site-Specific Rate Shifts Across the Tree of Life

Evolutionary rates vary widely among sites in protein sequences, reflecting differences in functional constraints across residues. Individual sites can also experience lineage-specific shifts in substitution rates--a process known as heterotachy--when selective pressures change during evolution. Although such temporal variation has long been recognized, the mechanisms underlying lineage-specific rate shifts and the factors shaping their distribution across protein families remain poorly understood. Here we map site-specific rate shifts across thousands of orthologous protein families spanning the tree of life. Among more than 1.8 million aligned amino-acid sites, over one quarter show evidence of lineage-specific rate changes. Rate shifts are more frequent in families with deep evolutionary origins, including those tracing back to LUCA, whereas younger clade-specific families generally show lower proportions of rate-shifting sites. We next examined whether local structural features predict where rate shifts occur. Residue burial shows only a weak association with rate-shift probability, and its direction differs across domains, with buried residues enriched for rate shifts in Archaea but surface-exposed residues showing slightly higher probabilities in Eukaryota. Moreover, rate-shifting sites rarely form spatial clusters within protein structures, indicating that structural constraints do not globally determine their locations. Despite their widespread occurrence, rate-shifting sites have limited impact on phylogenetic reconstruction beyond random site variation. Together, these results show that lineage-specific rate shifts are a pervasive feature of protein evolution shaped primarily by evolutionary ancestry and phylogenetic depth.

evolutionary biology↗

bioRxiv2025

A Zur-dependent regulatory RNA involved in maintaining zinc homeostasis in Staphylococcus aureus

Small regulatory RNAs (sRNAs) are key drivers of bacterial adaptation to environmental fluctuations, including iron and manganese restriction imposed by the host. This study explored the repertoire of sRNAs produced by the human pathogen Staphylococus aureus in response to metal limitation. Two sRNAs, S1077 and ZinS (RsaX20), regulated by zinc (Zn) availability, were identified. Further investigations revealed that, similar to the cnt operon from which it derives, S1077 synthesis is controlled by the transcription factors Zur and Fur. In contrast, zinS transcription is solely repressed by Zur. Amongst the ZinS targets are several Zn-dependent enzymes, such as the alcohol dehydrogenase Adh, whose synthesis is negatively regulated by ZinS. Loss of ZinS does not alter staphylococcal metal accumulation, suggesting a role in a Zn-sparing response. Remarkably, zinS also encodes a small peptide, ZinP. Genomic analysis suggests that the regulatory portion of ZinS emerged from the 3 untranslated region of zinP in S. aureus and closely related species after horizontal gene transfer from phylogenetically distant organisms. All our findings demonstrate that sRNAs also facilitate bacterial adaptation to Zn limitation, and that genetic exchange and subsequent neofunctionalization have enabled S. aureus to adapt to metal-restricted environments.

microbiology↗

bioRxiv2025

Polarizing SNPs without outgroup

Asserting which allele is ancestral or derived, known as polarization, is a prerequisite of many population and quantitative genetic methods. In particular, it allows inference of the unfolded site-frequency spectrum (uSFS). The most widely used approaches are based on outgroup data. However, for studies on species for which closely related outgroups are difficult to obtain, information on many sites of interest may be missed due to alignment problems. Here, we present PolarBEAR (Polarization By Estimation of the Ancestral recombination graph), a method that uses the local genealogies from the ancestral recombination graph (ARG) to infer ancestral states. We show that PolarBEAR can reach high accuracy in polarization and uSFS estimation using simulations under several scenarios. This accuracy, however, heavily depends on the ARG used as input. It is maximal when the true ARGs is used, but can be very low depending on the ARG reconstruction method employed. We also applied our method to human population data and compared it with the outgroup-based method est-sfs. Although our method could not infer the ancestral state with high confidence at certain positions, it obtained results for positions that est-sfs could not polarize due to missing outgroup data. The polarization results of the two methods were highly consistent at positions inferred by both methods. The two methods inferred similar uSFS, with PolarBEAR estimating slightly fewer high-frequency derived alleles. Furthermore, we demonstrate that PolarBEAR is robust to the mutation model used, while est-sfs exhibits a bias in the presence of heterogeneous base composition. PolarBEAR can complement outgroup-based methods, or replace them when no appropriate outgroup sequence is available.

evolutionary biology↗

bioRxiv2024

Experimental evaluation of a direct fitness effect of the de novo evolved mouse gene Pldi

De novo evolved genes emerge from random non-coding sequences and have, therefore, no homologs from which a function could be inferred. While expression analysis and knockout experiments can provide insights into the function, they do not directly test whether the gene is beneficial for its carrier. Here, we have used a seminatural environment experiment to test the fitness of the previously identified de novo evolved mouse gene Pldi, which is thought to be involved in sperm differentiation. We used a knockout mouse strain for this gene and competed it against its parental wildtype strain for several generations of free reproduction. We found that the knockout (ko) allele frequency decreased consistently across three replicates of the experiment. Using an approximate Bayesian computation framework that simulated the data under a demographic scenario mimicking the experiments demography, we could estimate a fitness coefficient ranging between 0.15 to 0.67 for the wildtype allele compared to the ko allele in males. We conclude that a gene that has evolved de novo from a random intergenic sequence can have a measurable fitness benefit.

evolutionary biology↗

bioRxiv2023

When is gene expression noise advantageous?

The variability of gene expression levels, also known as gene expression noise, is an evolvable trait subject to selection. While gene expression noise is detrimental in constant environments where the expression level is under stabilizing selection, it may be beneficial in changing environments when the phenotype is far from the optimum. However, expression noise propagates along the gene network, making the evolution of connected genes interdependent. Here, we explore how their position in the gene network constrains the evolution of genes under selection using an in silico evolution experiment. We simulate the evolution of populations of model gene regulatory networks under directional and fluctuating selection on the gene expression level while allowing the basal expression level and expression noise level to mutate. We find that expression noise is only transiently favoured under directional selection, but high levels of noise can be maintained in a fluctuating selection regime. Furthermore, target genes, regulated by other genes, were more likely to increase their gene-specific expression noise than regulator genes. These findings suggest that both the mean and variance of gene expression levels respond to selection due to changing environments - and do so in a network-dependent manner. They further point at gene expression noise as a putative mechanism for populations to escape extinction when facing environmental changes.

evolutionary biology↗

bioRxiv2023

On the estimation of genome-average recombination rates

The rate at which recombination events occur in a population is an indicator of its effective population size and the organisms reproduction mode. It determines the extent of linkage disequilibrium along the genome and, thereby, the efficacy of both purifying and positive selection. The population recombination rate can be inferred using models of genome evolution in populations. Classical methods based on the patterns of linkage-disequilibrium provide the most accurate estimates, providing large sample sizes are used and the demography of the population is properly accounted for. Here, the capacity of approaches based on the sequentially Markov coalescent (SMC) to infer the genome-average recombination rate from as little as a single diploid genome is examined. SMC approaches provide highly accurate estimates even in the presence of changing population sizes, providing that (1) within genome heterogeneity is accounted for and (2) classical maximum-likelihood optimization algorithms are employed to fit the model. SMC-based estimates proved sensitive to the presence of gene conversion, which leads to an overestimation of the recombination rate if conversion events are frequent. Conversely, methods based on the correlation of heterozygosity succeed in disentangling the rate of crossing over from that of gene conversion events, but only when the population size is constant and the recombination landscape homogeneous. These results call for a convergence of these two methods to obtain accurate and comparable estimates of recombination rates between populations.

evolutionary biology↗

bioRxiv2023

Large-scale analyses reveal the contribution of adaptive evolution in pathogenic and non-pathogenic fungal species

Genome studies of fungal pathogens have presented evidence for exceptionally high rates of evolution. It has been proposed that rapid adaptation is a hallmark of pathogen evolution that facilitates the invasion of new host niches and the overcoming of intervention strategies such as fungicide applications and drug treatments. To which extent high levels of genetic variation within and between species correlate with adaptive protein evolution in fungi more generally has so far not been explored. In this study, we addressed the contribution of adaptive evolution relative to genetic drift in 20 fungal species, hereby exploring genetic variation in 2,478 fungal genomes. We reannotated positions of protein-coding genes to obtain a high-quality dataset of 234,427 full-length core gene and 25,612 accessory gene alignments. We applied an extension of the McDonald-Kreitman test that models the distributions of fitness effects to infer the rate of adaptive ({omega}A) and non-adaptive ({omega}NA) non-synonymous substitutions in protein-coding genes. To explore the relevance of recombination on local adaptation rates, we inferred the population genomic recombination rate for all 20 species. Our analyses reveal extensive variation in rates of adaptation and show that high rates of adaptation are not a hallmark of a pathogenic lifestyle. Up to 83% of non-synonymous substitutions are adaptive in the species Parastagonospora nodorum. However, non-synonymous substitutions in other species, including the prominent rice-infecting pathogen Magnaporthe oryzae, are predominantly non-adaptive (neutral or slightly deleterious). Correlating adaptation measures with effective population size and recombination rate, we show that effective population size is a primary determinant of adaptive evolution in fungi. At the genome scale, recombination rate variation explains variation in both {omega}A and {omega}NA. Finally, we demonstrate the robustness of our estimates using simulations. We underline the value of population genetic principles in studies of fungal evolution, and we highlight the importance of demographic processes in adaptive evolution of pathogenic and non-pathogenic species.

evolutionary biology↗

bioRxiv2023

Evidence for adaptive evolution towards high magnetic sensitivity of potential magnetoreceptor in songbirds

Migratory birds possess remarkable accuracy in orientation and navigation, which involves various compass systems including the magnetic compass. Identifying the primary magnetosensor remains a fundamental open question. Cryptochromes (Cry) have been shown to be magnetically sensitive, specifically Cry4 shows enhanced magnetic sensitivity in migratory songbirds compared to resident species. Here, we investigate cryptochromes and their potential involvement in magnetoreception in a phylogenetic framework, integrating molecular evolutionary analyses with protein dynamics modeling. We base our analysis on 363 bird genomes and associate different selection regimes with migratory behaviour. We show that Cry4 is characterized by strong positive selection and high variability, typical characteristics of sensor proteins. We identify key sites that likely facilitated the evolution of a highly optimized sensory protein for night time compass orientation in songbirds and a potential functional shift or specialisation. Additionally, we show that Cry4 was lost in hummingbirds, parrots and Tyranni (Suboscines) and thus identified a natural comparative gene knockout, which can be used to test the function of Cry4 in birds. In contrast, the other two cryptochromes Cry1 and Cry2, were highly conserved in all species, indicating basal, non-sensory functions. Our results strengthen the hypothesised role of Cry4 as sensor protein in (night)-migratory songbirds.

evolutionary biology↗

bioRxiv2022

The rate of adaptive molecular evolution in wild and domesticated Saccharomyces cerevisiae populations

Through its fermentative capacities, Saccharomyces cerevisiae was central in the development of civilization during the Neolithic period, and the yeast remains of importance in industry and biotechnology giving rise to bona fide domesticated populations. Here, we conduct a population genomic study of domesticated and wild populations of S. cerevisiae. Using coalescent analyses, we report that the effective population size of yeast populations decreased since the divergence with S. paradoxus. We fitted models of distribution of fitness effects to infer the rate of adaptive ({omega}a) and non-adaptive ({omega}na) non-synonymous substitutions in protein-coding genes. We report an overall limited contribution of positive selection to S. cerevisiae protein evolution, albeit with higher rates of adaptive evolution in wild compared to domesticated populations. Our analyses revealed the signature of background selection and possibly Hill-Robertson interference, as recombination was found to be negatively correlated with{omega} na and positively correlated with{omega} a. However, the effect of recombination on{omega} a was found to be labile, as it is only apparent after removing the impact of codon usage bias on the synonymous site frequency spectrum and disappears if we control for the correlation with{omega} na, suggesting it could be an artefact of the decreasing population size. Furthermore, the rate of adaptive non-synonymous substitutions is significantly correlated with the residue solvent exposure, a relation that cannot be explained by the populations demography. Together, our results provide a detailed characterization of adaptive mutations in protein-coding genes across S. cerevisiae populations.

evolutionary biology↗

bioRxiv2022

Being noisy in a crowd: differential selective pressure on gene expression noise in model gene regulatory networks

Expression noise, the variability of the amount of gene product among isogenic cells grown in identical conditions, originates from the inherent stochasticity of diffusion and binding of the molecular players involved in transcription and translation. It has been shown that expression noise is an evolvable trait and that central genes exhibit less noise than peripheral genes in gene networks. A possible explanation for this pattern is increased selective pressure on central genes since they propagate their noise to downstream targets, leading to noise amplification. To test this hypothesis, we developed a new gene regulatory network model with inheritable stochastic gene expression and simulated the evolution of gene-specific expression noise under constraint at the network level. Stabilizing selection was imposed on the expression level of all genes in the network and rounds of mutation, selection, replication and recombination were performed. We observed that local network features affect both the probability to respond to selection, and the strength of the selective pressure acting on individual genes. In particular, the reduction of gene-specific expression noise as a response to stabilizing selection on the mean expression is higher in genes with higher centrality metrics. Furthermore, global topological structures such as network diameter, centralization and average degree affect the average expression variance and average selective pressure acting on constituent genes. Our results demonstrate that selection at the network level leads to differential selective pressure at the gene level, and local and global network characteristics are an essential component of gene-specific expression noise evolution.

evolutionary biology↗

bioRxiv2021

The structural determinants of intra-protein compensatory substitutions

Compensating substitutions happen when one mutation is advantageously selected because it restores the loss of fitness induced by a previous deleterious mutation. How frequent such mutations occur in evolution and what is the structural and functional context permitting their emergence remain open questions. We built an atlas of intra-protein compensatory substitutions using a phylogenetic approach and a dataset of 1,630 bacterial protein families for which high-quality sequence alignments and experimentally derived protein structures were available. We identified more than 51,000 positions coevolving by the mean of predicted compensatory mutations. Using the evolutionary and structural properties of the analyzed positions, we demonstrate that compensatory mutations are scarce (typically only a few in the protein history) but widespread (the majority of proteins experienced at least one). Typical coevolving residues are evolving slowly, are located in the protein core outside secondary structure motifs, and are more often in contact than expected by chance, even after accounting for their evolutionary rate and solvent exposure. An exception to this general scheme are residues coevolving for charge compensation, which are evolving faster than non-coevolving sites, in contradiction with predictions from simple coevolutionary models, but similar to stem pairs in RNA. While sites with a significant pattern of coevolution by compensatory mutations are rare, the comparative analysis of hundreds of structures ultimately permits a better understanding of the link between the three-dimensional structure of a protein and its fitness landscape.

evolutionary biology↗

bioRxiv2021

Mutation rate variation shapes genome-wide diversity in Drosophila melanogaster

What shapes the distribution of nucleotide diversity along the genome? Attempts to answer this question have sparked debate about the roles of neutral stochastic processes and natural selection in molecular evolution. However, the mechanisms of evolution do not act in isolation, and integrative models that simultaneously consider the influence of multiple factors on diversity are lacking; without them, confounding factors lurk in the estimates. Here we present a new statistical method that jointly infers the genomic landscapes of genealogies, recombination rates and mutation rates. In doing so, our model captures the effects of genetic drift, linked selection and local mutation rates on patterns of genomic variation. We then formalize a causal model of how these microevolutionary mechanisms interact, and cast it as a linear regression to estimate their individual contributions to levels of diversity along the genome. Our analyses reclaim the well-established signature of linked selection in Drosophila melanogaster, but we estimate that the mutation landscape is the major driver of the genome-wide distribution of diversity in this species. Furthermore, our simulation results suggest that in many evolutionary scenarios the mutation landscape will be a crucial factor shaping diversity, depending notably on the genomic window size. We argue that incorporating mutation rate variation into the null model of molecular evolution will lead to more realistic inferences in population genomics.

evolutionary biology↗

bioRxiv2021

Testing the adaptive walk model of gene evolution

Understanding the dynamics of species adaptation to their environments has long been a central focus of the study of evolution. Theories of adaptation propose that populations evolve by "walking" in a fitness landscape. This "adaptive walk" is characterised by a pattern of diminishing returns, where populations further away from their fitness optimum take larger steps than those closer to their optimal conditions. Hence, we expect young genes to evolve faster and experience mutations with stronger fitness effects than older genes because they are further away from their fitness optimum. Testing this hypothesis, however, constitutes an arduous task. Young genes are small, encode proteins with a higher degree of intrinsic disorder, are expressed at lower levels, and are involved in species-specific adaptations. Since all these factors lead to increased protein evolutionary rates, they could be masking the effect of gene age. While controlling for these factors, we used population genomic datasets of Arabidopsis and Drosophila and estimated the rate of adaptive substitutions across genes from different phylostrata. We found that a genes evolutionary age significantly impacts the molecular rate of adaptation. Moreover, we observed that substitutions in young genes tend to have larger physicochemical effects. Our study, therefore, provides strong evidence that molecular evolution follows an adaptive walk model across a large evolutionary timescale.

evolutionary biology↗

bioRxiv2020

Population genomics of the maize pathogen Ustilago maydis: demographic history and role of virulence clusters in adaptation

The tight interaction between pathogens and their hosts results in reciprocal selective forces that impact the genetic diversity of the interacting species. The footprints of this selection differ between pathosystems because of distinct life-history traits, demographic histories, or genome architectures. Here, we studied the genome-wide patterns of genetic diversity of 22 isolates of the causative agent of the corn smut disease, Ustilago maydis, originating from five locations in Mexico, the presumed center of origin of this species. In this species, many genes encoding secreted effector proteins reside in so-called virulence clusters in the genome, an arrangement that is so far not found in other filamentous plant pathogens. Using a combination of population genomic statistical analyses, we assessed the geographical, historical and genome-wide variation of genetic diversity in this fungal pathogen. We report evidence of two partially admixed subpopulations that are only loosely associated with geographic origin. Using the multiple sequentially Markov coalescent model, we inferred the demographic history of the two pathogen subpopulations over the last 0.5 million years. We show that both populations experienced a recent strong bottleneck starting around 10,000 years ago, coinciding with the assumed time of maize domestication. While the genome average genetic diversity is low compared to other fungal pathogens, we estimated that the rate of non-synonymous adaptive substitutions is three times higher in genes located within virulence clusters compared to non-clustered genes, including non-clustered effector genes. These results highlight the role that these singular genomic regions play in the evolution of this pathogen. Significance statementThe maize pathogen Ustilago maydis is a model species to study fungal cell biology and biotrophic host-pathogen interactions. Population genetic studies of this species, however, were so far restricted to using a few molecular markers, and genome-wide comparisons involved species that diverged more than 20 million years ago. Here, we sequenced the genomes of 22 Mexican U. maydis isolates to study the recent evolutionary history of this species. We identified two co-existing populations that went through a recent bottleneck and whose divergence date overlaps with the time of maize domestication. Contrasting the patterns of genetic diversity in different categories of genes, we further showed that effector genes in virulence clusters display a high rate of adaptive mutations, highlighting the importance of these effector arrangements for the adaptation of U. maydis to its host.

genomics↗

bioRxiv2019

The transfer of a mitochondrial selfish element to the nuclear genome and its consequences

Homing endonucleases (HE) are enzymes capable of cutting DNA at highly specific target sequences, the repair of the generated double-strand break resulting in the insertion of the HE-encoding gene ("homing" mechanism). HEs are present in all three domains of life and viruses; in eukaryotes, they are mostly found in the genomes of mitochondria and chloroplasts, as well as nuclear ribosomal RNAs. We here report the case of a HE that accidentally integrated into a telomeric region of the nuclear genome of the fungal maize pathogen Ustilago maydis. We show that the gene has a mitochondrial origin, but its original copy is absent from the U. maydis mitochondrial genome, suggesting a subsequent loss or a horizontal transfer from a different species. The telomeric HE underwent mutations in its active site and lost its original start codon. A potential other start codon was retained downstream, but we did not detect any significant transcription of the newly created open reading frame, suggesting that the inserted gene is not functional. Besides, the insertion site is located in a putative RecQ helicase gene, truncating the C-terminal domain of the protein. The truncated helicase is expressed during infection of the host, together with other homologous telomeric helicases. This unusual mutational event altered two genes: the integrated HE gene subsequently lost its homing activity, while its insertion created a truncated version of an existing gene, possibly altering its function. As the insertion is absent in other field isolates, suggesting that it is recent, the U. maydis 521 reference strain offers a snapshot of this singular mutational event.

evolutionary biology↗

bioRxiv2017

The genomic rate of adaptation in the fungal wheat pathogen Zymoseptoria tritici

Antagonistic host-pathogen co-evolution is a determining factor in the outcome of infection and shapes genetic diversity at the population level of both partners. While the molecular function of an increasing number of genes involved in pathogenicity is being uncovered, little is known about the molecular bases and genomic impact of hst-pathogen coevolution and rapid adaptation. Here, we apply a population genomic approach to infer genome-wide patterns of selection among thirteen isolates of the fungal pathogen Zymoseptoria tritici. Using whole genome alignments, we characterize intragenic polymorphism, and we apply different test statistics based on the distribution of non-synonymous and synonymous polymorphisms (pN/pS) and substitutions (dN/dS) to (1) characterise the selection regime acting on each gene, (2) estimate rates of adaptation and (3) identify targets of selection. We correlate our estimates with different genome variables to identify the main determinants of past and ongoing adaptive evolution, as well as purifying and balancing selection. We report a negative relationship between pN/pS and fine-scale recombination rate and a strong positive correlation between the rate of adaptive non-synonymous substitutions ({omega}a) and recombination rate. This result suggests a pervasive role of Hill-Robertson interference even in a species with an exceptionally high recombination rate (60 cM/Mb). Moreover, we report that the genome-wide fraction of adaptive non-synonymous substitutions () is ~ 44%, however in genes encoding determinants of pathogenicity we find a mean value of alpha ~ 68% demonstrating a considerably faster rate of adaptive evolution in this class of genes. We identify 787 candidate genes under balancing selection with an enrichment of genes involved in secondary metabolism and host infection, but not predicted effectors. This suggests that different classes of pathogenicity-related genes evolve according to distinct selection regimes. Overall our study shows that sexual recombination is a main driver of genome evolution in this pathogen.

evolutionary biology↗

bioRxiv2017

Comparison of fine-scale recombination maps in fungal plant pathogens reveals dynamic recombination landscapes and intragenic hotspots

Meiotic recombination is an important driver of evolution. Variability in the intensity of recombination across chromosomes can affect sequence composition, nucleotide variation and rates of adaptation. In many organisms recombination events are concentrated within short segments termed recombination hotspots. The variation in recombination rate and positions of recombination hotspot can be studied using population genomics data and statistical methods. In this study, we conducted population genomics analyses to address the evolution of recombination in two closely related fungal plant pathogens: the prominent wheat pathogen Zymoseptoria tritici and a sister species infecting wild grasses Zymoseptoria ardabiliae. We specifically addressed whether recombination landscapes, including hotspot positions, are conserved in the two recently diverged species and if recombination contributes to rapid evolution of pathogenicity traits. We conducted a detailed simulation analysis to assess the performance of methods of recombination rate estimation based on patterns of linkage disequilibrium, in particular in the context of high nucleotide diversity. Our analyses reveal overall high recombination rates, a lack of suppressed recombination in centromeres and significantly lower recombination rates on chromosomes that are known to be accessory. The comparison of the recombination landscapes of the two species reveals a strong correlation of recombination rate at the megabase scale, but little correlation at smaller scales. The recombination landscapes in both pathogen species are dominated by frequent recombination hotspots across the genome including coding regions, suggesting a strong impact of recombination on gene evolution. A significant but small fraction of these hotspots co-localize between the two species, suggesting that hotspots dynamics contribute to the overall pattern of fast evolving recombination in these species.

evolutionary biology↗