Biology subjects

Servin, B.

Publications and source records attributed to Servin, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Historical and Contemporary Management of Genetic Diversity in French Local Horse Breeds: Insights from Genomic Data

The phenotypic and genetic diversity of horses worldwide today likely resulted from two main events: (i) domestication and, afterwards, (ii) breed creation. While many studies discuss the origin and domestication of horses, very few focus on the second important event, which has largely shaped the genetic architecture of horses at present. This study exhaustively examined all 18 local horse breeds from France, all of which are endangered by small census sizes, making them prone to suffer from genetic drift, loss of diversity, and inbreeding depression. While pedigrees are available, they are often incomplete or error-prone. Thus, we used molecular markers to reconstruct the history of French local breeds and to monitor the evolution of genetic diversity and its link to management practices. The study was based on 976 animals (approx. 50 per breed), spanning two time periods corresponding to the change in management from public stud farms to privatization. The samples were genotyped using a 10K SNP array dedicated to genetic resources characterization. French local horses can be classified not only phenotypically but also genetically into two categories: the light 'territory' breeds and heavier 'draft' breeds, with regular gene flow observed between the two groups that are linked to historical records. The evolution of kinship and inbreeding over the two time periods exhibited distinct patterns between the cohorts and across the breeds, reflecting various consequences of different management practices. To conclude, this study was the first to exhaustively depict the evolution of French local horses, while it also demonstrated the usefulness of genomic data in monitoring genetic diversity and evaluating the effectiveness of management programs.

genomics↗

bioRxiv2026

Genetic determinants of intraspecific variation in crossover frequencies in the honeybee, Apis mellifera

Meiotic recombination facilitates natural selection and is necessary for correct chromosomal segregation in most sexually reproducing species. Crossover rates vary greatly both within and among species, but the determinants of this variation are not fully understood. The honeybee Apis mellifera has extremely high recombination rates. Honeybee males (drones) are haploid, which enables the distribution of crossovers to be directly estimated from the progeny of a single reproductive female (queen). Here we map crossover events in the honeybee using whole genome sequencing of 1509 drone progeny of 184 queens. This allows us to assay intra-specific variation in recombination rate and its genetic and non-genetic determinants. We estimate the average crossover rate as 23 cM/Mb, with between 22 and 88 crossovers events detected in individual offspring. We estimate 28% of this variation is additive heritable variation among queens. There is no effect of queen age or genetic background on crossover rate. A genome-wide association study identifies variation in the gene mlh1 as associated with mean crossover rate. We estimate that variation in the gene is associated with a 10% difference in crossover rate between the two homozygous genotypes at the most significant SNP. This gene has a well-established role in recombination and variation in the gene could affect crossover rates by affecting resolution of Holliday junctions as crossovers. This is the first gene discovered to be associated with recombination rate variation in an insect. Adaptive evolution of this gene could potentially underlie the extremely high recombination rates in honeybees.

genomics↗

bioRxiv2025

Genome landscape and genetic architecture of recombination in domestic goats (Capra Hircus)

BackgroundRecombination is a fundamental biological process, both in participating to the creation of viable gametes and as a driver of genetic diversity. Characterising recombination is therefore of strong interest in breeding populations. In this study, we used [~]50K genotyped data and pedigree from two French populations (Alpine and Saanen) of domestic goats (Capra hircus) to build sex-specific recombination maps, and to explore the genetic basis of two recombination phenotypes: genome-wide recombination rate (GRR) and intra-chromosomal shuffling. ResultsSex-specific recombination maps showed higher recombination in males than females for both breeds (Alpine autosomal map size = 35.1M in males and 30.5M in females; Saanen map size = 34.0M in males and 29.0M in females). Heterochiasmy is particularly notable on small chromosomes, and at both ends of the chromosomes. Yet, no difference in shuffling has been found between populations. Genetic parameters on recombination phenotypes could only be estimated in males, due to lack of data in females. Both phenotypes are significantly heritable (h{superscript 2}=0.12 (0.03) for GRR and h{superscript 2}=0.034 (0.015) for shuffling, when pooling breeds). GWAS on male GRR identified several significant loci, including RNF212, RNF212B and SSH1, the last one being a novel locus for this phenotype. Correlation of SNP effects between breeds is low for both recombination phenotypes (0.25 for GRR and 0.04 for shuffling), indicating different genetic determinants in the two breeds. ConclusionsThis study contributes to the understanding of recombination evolution in ruminants, both between breeds and species.

genetics↗

bioRxiv2025

Inferring domestic goat demographic history through ancient genome imputation

Goats were among the earliest managed animals, making them a natural model to explore the genetic consequences of domestication. However, a challenge in ancient genomic analysis is the relatively low genome coverage for most samples, limiting analysis to pseudohaploid genotypes. Genotype imputation offers potential to alleviate this limitation by improving information content and accuracy in low coverage genomes. To test this we used published high coverage (>8x) goat palaeogenomes, imputing downsampled genomes using the VarGoats dataset (1,372 individuals) as a reference panel. Measuring concordance between imputed and high coverage genotypes, we find high concordance after filtering for common (>5%), high confidence variants, with 0.5x genomes reaching >0.97 concordance. There is a trade-off between coverage, genotype probability (GP) thresholds, and genotype recovery, where higher coverage and more lenient GP thresholds result in higher recovery, and a reduction in heterozygous false-positive rates with stricter thresholds. We then imputed 36 goat palaeogenomes with [≥]0.5x coverage to examine runs-of-homozygosity (ROH) and identity-by-descent (IBD) patterns. Using a novel approach combining ROH profiles across tools, we find that among Neolithic goats, ROH increases with distance from the Zagros Mountains, suggesting a large effect of the initial dispersal of managed herds. Inbreeding levels decrease across Southwest Asia in more recent periods. IBD mirrored this pattern, with less relatedness in the early herding site of Ganj Dareh compared to higher relatedness in goats from later in the dispersal process. These findings provide insights into the genetic consequences of early goat management on demography, and confirm the utility of imputation in leveraging low coverage palaeogenomes. SignificancePaleogenomics offers crucial insight into how animals were domesticated, but poor DNA preservation in ancient remains often limits the reach of genetic analyses. We utilise a cutting-edge technique, genotype imputation, to recover missing genetic information from ancient low coverage goat genomes and shine light on their domestication process. Early domestic goats showed low overall runs-of-homozygosity (ROH) and relatedness. We find that during the Neolithic, runs-of-homozygosity (ROH) and relatedness among goats increased, likely a consequence of the movement of herds beyond their natural range by humans. Inbreeding levels decline in more recent periods, potentially due to expanded herd sizes, animal trade networks, or improved husbandry practices. These findings challenge long-standing assumptions about domestication bottlenecks and highlight how ancient DNA can be used to uncover complex evolutionary histories, even from low coverage ancient samples.

genomics↗

bioRxiv2024

SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data

Genomic samples collected from a single population over several generations provide direct access to the genetic diversity changes occurring within a specific time period. This provides information about both demographic and adaptive processes acting on the population during that period. A common approach to analyze such data is to model observed allele counts in finite samples using a Hidden Markov Model (HMM) where hidden states are true allele frequencies over time (i.e. a trajectory). The HMM framework allows one to compute the full likelihood of the data, while accounting both for the stochastic evolution of population allele frequencies along time and for the noise arising from sampling a limited number of individuals at possibly spread out generations. Several such HMM methods have been proposed so far, differing mainly in the way they model the transition probabilities of the Markov chain. Following Paris et al. (2019a), we consider here the Beta with Spikes approximation, which avoids the computational issues associated to the Wright-Fisher model while still including fixation probabilities, in contrast to other standard approximations of this model like the Gaussian or Beta distributions. To facilitate the analysis and exploitation of genomic time series data, we present an improved version of Paris et al. (2019a) s approach, denoted SelNeTime, whose computation time is drastically reduced and which accurately estimates effective population size (assuming no selection) or the selection intensity at each locus (given a previously estimated value of N). We also evaluate the performance of this method in realistic situations where selection is present and both demography and selection need to be inferred. SelNeTime is implemented in a user friendly python package, which can also easily simulate genomic time series data under a user-defined evolutionary model and sampling design.

evolutionary biology↗

bioRxiv2024

SMARTER-database: a tool to explore genomic diversity in small ruminants

Underutilized sheep and goat breeds have the ability to adapt to challenging environments due to their genetic composition. Integrating publicly available genomic datasets with new data will facilitate genetic diversity analyses; however, this process is complicated by important data discrepancies, such as outdated assembly versions or different data formats. Here we present the SMARTER-database, a collection of tools and scripts to standardize genomic data and metadata mainly from SNP chips arrays on global small ruminant populations with a focus on reproducibility. SMARTER-database harmonizes genotypes for about 12,000 sheep and 6,000 goats to a uniform coding and assembly version. Users can access the genotype data via FTP and interact with the metadata through a web interface or programmatically using their custom scripts, enabling efficient filtering and selection of samples. These tools will empower researchers to focus on the crucial aspects of adaptation and contribute to livestock sustainability, leveraging the rich dataset provided by the SMARTER-database. Availability & ImplementationThe code is available as open source software under the MIT license at https://github.com/cnr-ibba/SMARTER-database.

bioinformatics↗

bioRxiv2024

Sequence-based genome-wide association studies reveal the polygenic architecture of Varroa destructor resistance in Western honey bees Apis mellifera

Honey bees, Apis mellifera, have experienced the full impacts of globalisation, including the recent invasion by the parasitic mite Varroa destructor which has become one of the main causes of colony losses worldwide. Despite its lethal effects, some colonies have developed defence strategies conferring colony resistance and, assuming non-null heritability, selective breeding of naturally resistant bees could be a sustainable way to fight infestations. Here we report on the largest genome-wide association study performed on honey bees to understand the genetic basis of multiple phenotypes linked to varroa resistance. This study was performed on whole genome sequencing of more than 1,500 colonies belonging to different ancestries and combined in a meta-analysis. Results show that varroa resistance is polygenic. A total of 60 genetic markers were identified as having a significant impact in at least one of the tested populations pinpointing several regions of the honey bee genome. Our results also support strategies for genomic selection in honey bee breeding.

genetics↗

bioRxiv2023

The black honey bee genome: insights on specific structural elements and a first step towards pan-genomes

BackgroundThe actual honey bee reference genome, HAv3.1, was produced from a commercial line sample, thought to have a largely dominant Apis mellifera ligustica genetic background. Apis mellifera mellifera, often referred to as the black bee, has a separate evolutionary history and is the original type in western and northern Europe. Growing interest in this subspecies for conservation and non-professional apicultural practices, together with the necessity of deciphering genome backgrounds in hybrids, triggered the necessity for a specific genome assembly. Moreover, having several high-quality genomes is becoming key for taking structural variations into account in pan-genome analyses. ResultsPacific Bioscience technology long reads were produced from a single haploid black bee drone. Scaffolding contigs into chromosomes was done using a high-density genetic map. This allowed for a re-estimation of the honey recombination rate, over-estimated in some previous studies, due to mis-assemblies resulting in spurious inversions in the older reference genomes. The sequence continuity obtained is very high and the only limit towards continuous chromosome-wide sequences seem to be due to tandem repeat arrays usually longer than 10 kb and belonging to two main families, the 371 and 91 bp repeats, causing problems in the assembly process due to high internal sequence similarity. Our assembly was used together with the reference genome, for genotyping two structural variants by a pan-genome graph approach with Graphtyper2. Genotypes obtained were either correct or missing, when compared to an approach based on sequencing depth analysis, and genotyping rates were 89 and 76 % for the two variants respectively. ConclusionsOur new assembly for the Apis mellifera mellifera honey bee subspecies demonstrates the utility of multiple high-quality genomes for the genotyping of structural variants, with a test case on two insertions and deletions. It will therefore be an invaluable resource for future studies, for instance including structural variants in GWAS. Having used a single haploid drone for sequencing allowed a refined analysis of very large tandem repeat arrays, raising the question of their function in the genome. High quality genome assemblies for multiple subspecies such as presented here, are crucial for emerging projects using pan-genomes.

genomics↗

bioRxiv2023

Comparison of genomic-enabled cross selection criteria for the improvement of inbred line breeding populations

A crucial step in inbred plant breeding is the choice of mating design to derive high-performing inbred varieties while also maintaining a competitive breeding population to secure sufficient genetic gain in future generations. In practice, the mating design usually relies on crosses involving the best parental inbred lines to ensure high mean progeny performance. This excludes crosses involving lower performing but more complementary parents in terms of favorable alleles. We predicted crosses with putative outstanding progenies (high mean and high variance progeny distribution) using genomic prediction models to assess the value of top progeny. This study compared the benefits and drawbacks of seven genomic cross selection criteria (CSC) in terms of genetic gain for one trait and genetic diversity in the next generation. Six CSC were already published and we have proposed an improved CSC that can estimate the proportion of progeny above a threshold defined for the whole mating plan. We simulated mating designs optimized using different CSC and 835 elite parents from a real breeding program that were evaluated between 2000 and 2016. We applied constraints on parental contributions and genetic similarities between parents according to usual breeder practices. Our results showed that CSC based on progeny variance estimation increased the genetic value of superior progenies by up to 5% in the next generation compared to CSC based on the progeny mean estimation (i.e. parental genetic values) alone. It also increased the genetic gain (up to 4%) and/or maintained more genetic diversity at QTLs (up to 4% more genic variance when the marker effects were perfectly estimated).

genetics↗

bioRxiv2023

Sex-differences in the genetic architecture of individual recombination rates in wild house sparrows (Passer domesticus).

Meiotic recombination through chromosomal crossing-over is a fundamental feature of sex and an important driver of genomic diversity. It ensures proper disjunction, allows increased selection responses, and prevents mutation accumulation; however, it is also mutagenic and can break up favourable haplotypes. This cost/benefit dynamic is likely to vary depending on mechanistic and evolutionary contexts, and indeed, recombination rates show huge variation in nature. Identifying the genetic architecture of this variation is key to understanding its causes and consequences. Here, we investigate individual recombination rate variation in wild house sparrows (Passer domesticus). We integrate genomic and pedigree data to identify autosomal crossover counts (ACC) and intra-chromosomal allelic shuffling ([r]intra) in 13,056 gametes. Females had 1.37 times higher ACC, and 1.55 times higher[r] intra than males. ACC and[r] intra were heritable in females and males (ACC h2 = 0.23 and 0.11;[r] intra h2 = 0.12 and 0.14), but cross-sex additive genetic correlations were low (rA = 0.29 and 0.32 for ACC and[r] intra). Conditional bivariate analyses showed that all measures remained heritable after accounting for genetic values in the opposite sex, indicating that sex-specific ACC and[r] intra can evolve somewhat independently. Genome-wide models showed that ACC and[r] intra are polygenic and driven by many small-effect loci, many of which are likely to act in trans as global recombination modifiers. Our findings show that recombination rates of females and males can have different evolutionary potential in wild birds, providing a compelling mechanism for the evolution of sexual dimorphism in recombination.

genetics↗

bioRxiv2022

Discovering genomic regions associated with the phenotypic differentiation of European local pig breeds

BackgroundIntensive selection of modern pig breeds resulted in genetic improvement of productive traits while local pig breeds remained less performant. As they have been bred in extensive systems, they have adapted to specifical environmental conditions resulting in a rich genotypic and phenotypic diversity. This study is based on European local pig breeds genetically characterized using DNA-pool sequencing data and phenotypically characterized using breed level phenotypes related to stature, fatness, growth and reproductive performance traits. These data were analyzed using a dedicated approach to detect selection signatures linked to phenotypic traits in order to uncover potential candidate genes that may be under adaptation to specific environments. ResultsGenetic data analysis of European pig breeds revealed four main axes of genetic variation represented by Iberian and modern breeds (i.e. Large White, Landrace, and Duroc). In addition, breeds clustered according to their geographical origin, for example French Gascon and Basque breeds, Italian Apulo Calabrese and Casertana breeds, Spanish Iberian and Portuguese Alentejano breeds. Principal component analysis of phenotypic data distinguished between larger and leaner breeds with better growth potential and reproductive performance on one hand and breeds that were smaller, fatter, and had low growth and reproductive efficiency on the other hand. Linking selection signatures with phenotype identified 16 significant genomic regions associated with stature, 24 with fatness, 2 with growth and 192 with reproduction. Among them, several regions contained candidate genes with possible biological effect on stature, fatness, growth and reproduction performance traits. For example, strong associations were found for stature in two regions containing the ANXA4 and ANTXR1 genes, for fatness containing the DNMT3A and POMC genes and for reproductive performance containing the HSD17B7 gene. ConclusionsThe present study on European local pig breeds used a dedicated approach for searching selection signatures supported by phenotypic data at the breed level to identify potential candidate genes that may have adapted to different living environments and production systems. Results can be useful to define conservation programs of local pig breeds.

genetics↗

bioRxiv2021

Multiple adaptive solutions to face climatic constraints: novel insights in the debate over the role of convergence in local adaptation

The extent to which genomic convergence shapes locally adapted phenotypes in different species remains a fundamental question in evolutionary biology. To bring new insights to this debate we set up a framework which aimed to compare the adaptive trajectories of two domesticated mammal species co-distributed in diversified landscapes. We sequenced the genomes of 160 sheep and 161 goats extensively managed along environmental gradients, including temperature, rainfall, seasonality and altitude, to identify genes and biological processes shaping local adaptation. Allele frequencies at adaptive loci were rarely found to vary gradually along environmental gradients, but rather displayed a discontinuous shift at the extremities of environmental clines. Of the more than 430 adaptive genes identified, only 6 were orthologous between sheep and goats and those responded differently to environmental pressures, suggesting different adaptive mechanisms in these two closely related species. Such diversity of adaptive pathways may result from a high number of biological functions involved in adaptation to multiple eco-climatic gradients, and provides more arguments for the role of contingency and stochasticity in adaptation rather than repeatability.

evolutionary biology↗

bioRxiv2021

From group to individual - Genotyping by pool sequencing eusocial colonies

BackgroundEusocial insects play a central role in many ecosystems, and particularly the important pollinator honeybee (Apis mellifera). One approach to facilitate their study in molecular genetics, is to consider whole colonies as single individuals by combining DNA of multiple individuals in a single pool sequencing experiment. Such a technique comes with the drawback of producing data requiring dedicated analytical methods to be fully exploited. Despite this limitation, pool sequencing data has been shown to be informative and cost-effective when working on random mating populations. Here, we present new statistical methods for exploiting pool sequencing data of eusocial colonies in order to reconstruct the genotype of the colony founder, the queen. This leverages the possibility to monitor genetic diversity, perform genomic-based studies or implement selective breeding. ResultsUsing simulations and honeybee real data, we show that the methods allow for a fast and accurate estimation of the genetic ancestry, with correlations of 0.9 with that obtained from individual genotyping, and for an accurate reconstruction of the queen genotype, with 2% genotyping error. We further validate the inference using experimental data on colonies with both pool sequencing and individual genotyping of drones. ConclusionIn this study we present statistical models to accurately estimate the genetic ancestry and reconstruct the genotype of the queen from pool sequencing data from workers of an eusocial colony. Such information allows to exploit pool sequencing for traditional population genetics, association studies and selective breeding. While validated in Apis mellifera, these methods are applicable to other eusocial hymenoptera species.

genomics↗

bioRxiv2021

Complex population structure and haplotype patterns in Western Europe honey bee from sequencing a large panel of haploid drones

Honey bee subspecies originate from specific geographic areas in Africa, Europe and the Middle East. The interest of beekeepers in specific phenotypes has led them to import subspecies to regions outside of their original range. The resulting admixture complicates population genetics analyses and population stratification can be a major problem for association studies. As a typical example, the case of the French population is studied here. We sequenced 870 haploid drones for SNP detection and identified nine genetic backgrounds in 629 samples. Five correspond to subspecies, two to isolated populations and two to human-mediated population management. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long on chromosome 11, representing 1.6 % of the genome and has two major haplotypes, corresponding to the two dominant genetic backgrounds identified.

genetics↗

bioRxiv2021

Local adaptations of Mediterranean sheep and goats through an integrative approach

In a context of climate change, identifying the genes underlying adaptations to extreme environments is essential. Small ruminants are adapted to a wide variety of habitats and thus, are promising study models. Here, we considered 17 goat and 25 sheep local Mediterranean breeds, in Italy, France and Spain. We proposed, and empirically tested a new methodology to highlight selection signatures in relation to the environments. Based on historical archives, we selected the breeds potentially most linked to a territory and defined their original geographical cradle, including transhumant pastoral areas. For both species, the cradles were arranged along latitudinal gradient of aridity and altitude. Then we used the programs PCAdapt and LFMM. Considering cradles, instead of current GPS coordinates, markedly improved the sensitivity of the LFMM analyses. All the results combined with a systematic literature review, revealed a set of genes with potentially key adaptive roles. Some of these genes, have been found implicated in lipid metabolism (SUCLG2, BMP2), hypoxia/heat stress (UBE2R2/UBAP2), lung function (BMPR2), seasonal patterns (SOX2, DPH6) or neuronal function (TRPC4, TRPC6). For the intergenic region between PCDH9 and KLH1, as well as NBEA, identified in both species, the adaptive role could be strong. We found for RXFP2, associated with sheep horn development, and MSRB3 and SLC26A4, both associated with hearing of sheep, a strong association with the environment gradient. We conclude that our new methodology, which considers breeds in their historical, environmental and anthropological context, provides novel and essential information on local breeds and their unique adaptations.

evolutionary biology↗

bioRxiv2021

Evolution of recombination landscapes in diverging populations of bread wheat.

Reciprocal exchanges of DNA (crossovers) that occur during meiosis are mandatory to ensure the production of fertile gametes in sexually reproducing species. They also contribute to shuffle parental alleles into new combinations thereby fuelling genetic variation and evolution. However, due to biological constraints, the recombination landscape is highly heterogenous along the genome which limits the range of allelic combinations and the adaptability of populations. An approach to better understand the constraints on the recombination process is to study how it evolved in the past. In this work we tackled this question by constructing recombination profiles in four diverging bread wheat (Triticum aestivum L.) populations established from 371 landraces genotyped at 200,062 SNPs. We used linkage disequilibrium (LD) patterns to estimate in each population the past distribution of recombination along the genome and characterize its fine-scale heterogeneity. At the megabase scale, recombination rates derived from LD patterns were consistent with family-based estimates obtained from a population of 406 recombinant inbred lines. Among the four populations, recombination landscapes were significantly positively correlated between each other and shared a statistically significant proportion of highly recombinant intervals. However, this comparison also highlighted that the similarity in recombination landscapes between populations was significantly decreasing with their genetic differentiation in most regions of the genome. This observation was found to be robust to SNP ascertainment and demography and suggests a relatively rapid evolution of factors determining the fine-scale localization of recombination in bread wheat.

genetics↗

bioRxiv2019

Inference of selection from genetic time series using various parametric approximations to the Wright-Fisher model

Detecting genomic regions under selection is an important objective of population genetics. Typical analyses for this goal are based on exploiting genetic diversity patterns in present time data but rapid advances in DNA sequencing have increased the availability of time series genomic data. A common approach to analyze such data is to model the temporal evolution of an allele frequency as a Markov chain. Based on this principle, several methods have been proposed to infer selection intensity. One of their differences lies in how they model the transition probabilities of the Markoiv chain. Using the Wright-Fisher model is a natural choice but its computational cost is prohibitive for large population sizes so approximations to this model based on parametric distributions have been proposed. Here, we compared the performance of some of these approximations with respect to their power to detect selection and estimation of the selection coefficient. We developped a new generic Hidden Markov Model likelihood calculator and applied it on genetic time series simulated under various evolutionary scenarios. The Beta-with-Spikes approximation, which combines discrete fixation probabilities with a continuous Beta distribution, was found to perform consistently better than the others. This distribution provides an almost perfect fit to the Wright-Fisher model in terms of selection inference, for a computational cost that does not increase with population size. We further evaluate this model for population sizes not accessible to the Wright-Fisher model and illustrate its performance on a dataset of two divergently selected chicken populations.

genetics↗

bioRxiv2017

Insights into the genetic determinism andevolution of recombination rates fromcombining multiple genome-wide datasets inSheep

Recombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and datasets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified about 50,000 crossover hotspots on the genome and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting inter-individual variation in recombination rate in Lacaune, including the RNF212 and HEI10 genes and possibly 2 other loci of smaller effects including the KCNJ15 and FSHR genes. Finally, we compared our results to those obtained previously in a distantly related population of domestic sheep, the Soay. This comparison revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome and that the two datasets can be combined to create more precise male meiotic recombination maps in sheep. Despite their similar recombination maps, we show that Soay and Lacaune males exhibit different heritabilities and QTL effects for inter-individual variation in genome-wide recombination rates.

genetics↗