Heredity

Meiotic recombination is a ubiquitous feature of sexual reproduction, ensuring proper disjunction of homologous chromosomes, and creating new combinations of alleles upon which selection can act. By identifying the genetic drivers of recombination rate variation, we can begin to understand its evolution. Here, we revisit an analysis investigating the genetic architecture of gamete autosomal crossover counts (ACC) in a wild population of Soay sheep (Ovis aries) using a much larger dataset (increasing from 3,300 to 7,235 gametes and from [~]39,000 to [~]415,000 SNPs for genome-wide association analysis). Animal models fitting genomic relatedness confirmed that ACC was heritable in both females (h2 = 0.18) and males (h2 = 0.12). Genome-wide association studies identified two regions associated with ACC variation. A region on chromosome 6 containing RNF212 explained 46% of heritable variation in female ACC, but was not associated with male ACC, confirming the previous finding. A region on chromosome 7 containing RNF212B explained 20-25% of variation in ACC in both males and females. Both RNF212 and RNF212B have been repeatedly associated with recombination rate in other mammal species. These findings confirm that moderate to large effect loci can underpin ACC variation in wild mammals, and provide a foundation for further studies on the evolution of recombination rates.

The competitive ability of domesticated plants, which may have conferred a fitness advantage in the wild, may result in a reduction of yield in agricultural and forestry contexts, as what matters is the group rather than the individual performance. Traits related to competitive ability can be affected by the presence or absence of related individuals in their neighborhood. Consequently, local relatedness might reveal plant-to-plant interaction that can enhance the predictive abilities of genomic models when accounted for, though it remains difficult to measure. To overcome this difficulty, we analyzed data from the French breeding program of Populus nigra L., where 1,452 genotypes were replicated six to eight times, each time encountering a different neighborhood. We assessed local relatedness and investigated genomic estimated breeding values on tree height and vulnerability to rust with a single-step GBLUP incorporating local relatedness as a covariate. The results indicate that incorporating local relatedness as an additional factor in GBLUP models has a significantly greater influence on resistance to rust than on tree height, though its overall effect on genomic predictions themselves was limited. The influence of local relatedness is small but likely trait-specific, and the genetic architecture of the trait under selection could attenuate or improve the efficacy of breeding for group performance.

Estimation of the effective size (Ne) of large populations with a continuous distribution across wide geographic areas and limited dispersal of individuals has been elusive so far. Estimates of the contemporary Ne from genetic markers for such large, structured populations, typically of plant and marine species, tend to be strongly biased downwards, which has led to question their relevance. Here we show that a recently proposed estimation method of Ne from linkage disequilibrium between markers, which accounts for population structure, yields estimates of metapopulation Ne when the sampling area is sufficiently large. The method is applied to empirical data of maritime pine (Pinus pinaster Aiton). While previous estimates of Ne in pine populations were of the order of a few hundred individuals, we show that estimates of the metapopulation Ne can reach values of the order of tens of thousands of individuals. This result is especially relevant from a conservation point of view, as populations with Ne lower than 500 individuals are considered to be under the risk of extinction.

A decade of association studies in multiple organisms suggests that most complex traits are polygenic; that is, they have a genetic architecture determined by numerous loci distributed across the genome, each with small effect-size. Thus, determining the degree of polygenicity and its variation across traits, environments and years is useful to understand the genetic basis of phenotypic variation. In this study, we applied multilocus approaches to estimate the degree of polygenicity of fitness-related traits in a long-lived plant (Pinus pinaster Ait., maritime pine) and to analyze how polygenicity changes across environments and years. To do so, we evaluated five categories of fitness-related traits (survival, height, phenology-related, functional, and biotic-stress response traits) in a clonal common garden network, planted in contrasted environments (over 12,500 trees). First, most of the analyzed traits showed evidence of local adaptation based on QST-FST comparisons. Second, we observed a remarkably stable degree of polygenicity, averaging 6% (range of 0-27%), across traits, environments and years. As previously suggested for humans, some of these traits showed also evidence of negative selection, which could explain, at least partially, the high degree of polygenicity. The observed genetic architecture of fitness-related traits in maritime pine supports the polygenic adaptation model. Because polygenic adaptation can occur rapidly, our study suggests that current predictions on the capacity of natural forest tree populations to adapt to new environments should be revised, which is of special relevance in the current context of climate change.

Subterranean rodents represent an interesting model system for molecular ecologists. Their lifestyle is associated with fragmented environments, limited dispersal ability, and low fecundity. These characteristics all are expected to increase inter- and intrapopulation differentiation and reduce intra- population genetic diversity, yet the published empirical data revealed the lack of generality of this pattern. This emphasizes the importance of accumulating more data on individual species to understand what factors shape the genetic dynamics of populations. This study represents the first characterization of the population genetic diversity and fine-scale genetic structure of a highly specialized subterranean vole, Ellobius talpinus. We used nine microsatellite loci and a fragment of the mitochondrial D-loop to investigate genetic patterns of two distant populations: the Novosibirsk population at the extreme northeastern edge of the species range, and the sub-peripheral Saratov population. As a result, the two populations exhibit distinct patterns of genetic structure. The Novosibirsk population showed a low nuclear diversity with an observed heterozygosity (Ho) of 0.34 and an unbiased expected heterozygosity (uHe) of 0.55. Mitochondrial D-loop was nearly monomorphic with over 90% of the observed haplotypes being identical, resulting in a haplotype diversity (Hd) of 0.14 and nucleotide diversity ({pi}) of 0.0004. In contrast, the Saratov population displayed moderate nuclear (Ho = 0.64; uHe = 0.76) and high mitochondrial variation (Hd = 0.83;{pi} = 0.034), compared to the surface-dwelling voles. Nine haplotypes representing four well-differentiated mitochondrial clades were found in the Saratov population. In a heterogeneous landscape, significant genetic differentiation was revealed at both intermediate (dozens of kilometers) and fine (several kilometers) scales. However, within the continuous suitable habitat, no fine-scale spatial structure was observed apart from that caused by kin clustering. The spatial genetic patterns revealed in E. talpinus appear to reflect a combination of effects of strong social structure, local natural and anthropogenic barriers limiting dispersal opportunities, and occasional long-distance dispersal.

Lifespan is a heritable trait with a polygenic architecture. Experimental evolution in combination with re-sequencing has often been used to identify candidate loci for lifespan in Drosophila melanogaster. Previous experiments showed that Drosophila populations experimentally evolved to increase late-life reproduction showed a correlated responses in development time, body size, but also lifespan. Subsequent whole genome sequencing allowed for the identification of candidate loci that correlated to lifespan differentiation. However, it remains difficult to assess whether candidate loci affect lifespan and to what extent such loci pleiotropically underpin multiple traits. Furthermore, recent studies indicate that lifespan effects of loci are often context dependent, but genotype-by-genotype interactions remain understudied. Therefore, here, we report on a study where we genotyped 3210 individuals for 32 candidate loci that emerged from our evolve and re-sequence experiment and tested, (1) whether these loci significantly affected lifespan, (2) the effect size of each locus, and, (3) how these loci mutually interact, i.e. determine the level of epistasis in moulding lifespan. Of the 32 loci, six showed significant main effect associations, of which three loci showed effects of 6.6 days difference in lifespan or larger, while the overall average lifespan was 41.7 days. Eight additional significant pairwise interactions between loci were found, of which four (single) main effects and one three-way interaction was significant. Lastly, we found that alleles that increased lifespan did not necessarily have higher frequencies in populations that showed increased lifespan, indicating that lifespan itself had not been the major target of selection. Our study indicates that individual genotyping following an evolve and re-sequencing study is essential to understand the mechanistic basis of polygenetic adaptation.

Estimating the extent of genetic differentiation between populations is an important measure in population genetics, ecology and evolutionary biology. Fixation index or FST is an important measure, which is routinely used to quantify this. Previous studies have shown that FST estimated for selectively constrained regions was significantly lower than that estimated for neutral regions. By deriving the theoretical relationship between FST at neutral and constrained sites we show that an excess in the fraction of deleterious variations segregating within populations compared to that segregates between populations is the cause for the reduction in FST estimated at constrained sites. Using whole genome data, our results revealed that the magnitude of reduction in FST estimates obtained for selectively constrained regions was much higher for distantly related populations compared to those estimated for closely related pairs. For example, the reduction was 49% for comparison between European-African populations, 31% for European-Asian comparison, 16% for the Northern-Southern European pair and only 4% for the comparison involving two Southern European (Italian and Spanish) populations. Since deleterious variants are purged over time due to purifying selection, their contribution to the among population diversity at constrained sites decreases with the increase in the divergence between populations. However, within population diversity remain the same for all pairs compared above and therefore FST estimated at constrained sites for distantly related populations are much smaller than those estimated for closely related populations. Our results suggest that the level of population divergence should be considered when comparing constrained site FST estimates obtained for different pairs of populations.

Accurately estimating relatedness between samples is crucial in genetics and epidemiological analysis. Using genome-wide single nucleotide polymorphisms (SNPs), it is now feasible to measure realized relatedness even in the absence of pedigree. However, the sampling variation in SNP-based measures and factors affecting method-of-moments relatedness estimators have not been fully explored, whilst static cut-off thresholds have traditionally been employed to classify relatedness levels for decades. Here, we introduce the deepKin framework as a moment-based relatedness estimation and inference method that incorporates data-specific cut-off threshold determination. It addresses the limitations of previous moment estimators by leveraging the sampling variance of the estimator to provide statistical inference and classification. Key principles in relatedness estimation and inference are provided, including inferring the critical value required to reject the hypothesis of unrelatedness, which we refer to as the deepest significant relatedness, determining the minimum effective number of markers, and understanding the impact on statistical power. Through simulations, we demonstrate that deepKin accurately infers both unrelated pairs and relatives with the support of sampling variance. We then apply deepKin to two subsets of the UK Biobank dataset. In the 3K Oxford subset, tested with four sets of SNPs, the SNP set with the largest effective number of markers and correspondingly the smallest expected sampling variance exhibits the most powerful inference for distant relatives. In the 430K British White subset, deepKin identifies 212,120 pairs of significant relatives and classifies them into six degrees. Additionally, cross-cohort significant relative ratios among 19 assessment centers located in different cities are geographically correlated, while within-cohort analyses indicate both an increase in close relatedness and a potential increase in diversity from north to south throughout the UK. Overall, deepKin presents a novel framework for accurate relatedness estimation and inference in biobank-scale datasets. For biobank-scale application we have implemented deepKin as an R package, available in the GitHub repository (https://github.com/qixininin/deepKin).

Deciphering the genetic architecture of complex quantitative phenotypes remains challenging in quantitative genetics. These traits not only depend of multiple genetic factors but are also established over time and environments. Although quantitative genetics has investigated the genetic determinism of phenotypic plasticity in contrasted environmental conditions, the time related phenotypic plasticity has received less attention. Here we proposed a multivariate Bayesian framework, the Bayesian Varying Coefficient Model, designed for analysing the genetic architecture of the time related phenotypic plasticity by a multilocus approach. We applied the BVCM to time series phenotypes measured at various time scales (daily, monthly, yearly) across a diverse set of biological species. We included in this study: yeast (Saccharomyces cerevisiae), fungi (Fusarium graminearum), eucalyptus (Eucalyptus urophylla x E. grandis), and sweet cherry tree (Prunus avium). The BVCM results were compared with those obtained with a known genome-wide association method carried out time by time. For all species and traits, the BVCM was able to detect the major QTL identified by marker-trait association methods and revealed additional genetic regions of weak effect. It also increased the phenotypic variance explained for most of the phenotypes considered. It revealed dynamic QTLs with transitory, increasing or decreasing effects over time. By considering both the temporal and genetic multivariate structures in a single statistical model, we increased our understanding of the genetic architecture of complex traits notably by reducing the issue of missing heritability. More broadly, this work raises the foundation for extended applications in functional genomics, evolutionary ecology, and crop breeding programs, in which time-related phenotypic plasticity remains crucial for predicting and selecting key quantitative complex traits. Key messageBy capturing the genetic factors influencing the time related phenotypic plasticity, our approach contributes to a deeper understanding of the dynamic nature of genotype-phenotype relationships.

Individual phenotypes often depend on the genotypes of other individuals within a group. These phenomena are termed indirect genetic effects (IGEs) and have been distinguished from direct genetic effects (DGEs) using quantitative genetic models. Recent studies have utilized high-resolution polymorphism data to enable genomic prediction (GP) and genome-wide association study (GWAS) of IGEs, but unified methods remain limited. Here we integrate polygenic and oligogenic IGEs using a multi-kernel mixed model incorporating two random effects with a single covariance parameter. Underlying this implementation, the Ising model of ferromagnetics enabled us to simplify locus-wise and background IGEs for GWAS and GP, respectively. Our simulations demonstrated that, while the previous and present models exhibited similar performance, the present model can infer a trade-off between DGEs and IGEs. By applying this method to three species of woody plants, we found evidence for intergenotypic competition in aspen and apple trees, but limited evidence in climbing grapevines. Based on GWAS, we also detected significant variants associated with the competitive IGEs on the apple trunk growth. Our study offers a flexible implementation for GWAS/GP of IGEs, thereby providing an effective tool to dissect the genetic architecture of group performance.

The Faroe Islands are a small archipelago located in the North Atlantic likely colonized by a small group of founders sometime between 50 and 300 CE. Post colonization, the Faroese people have been largely isolated from admixture with mainland and other island populations in the region. As such, the initial founder effect and subsequent genetic drift are likely major contributors to the modern genetic diversity found among the Faroese. In this study, we assess the utility of Y-chromosomal microsatellites to detect founder effect in the Faroe Islands through the construction of haplotype networks and a novel empirical method, mutational distance from modal haplotype histograms (MDM), for the visualization and evaluation of population bottlenecks. We compared samples from the Faroe Islands and Iceland to possible regional source populations and documented a loss of diversity associated with founder events. Additionally, within-haplogroup diversity statistics reveals lower haplotype diversity and richness within both the Faroe Islands and Iceland, consistent with a small founder population colonizing both regions. However, in the within-haplogroup networks, the Faroe Islands are found within the larger set of potential source populations while Iceland is consistently found on isolated branches. Moreover, comparisons of within-haplogroup MDM histograms document a clear founder signal in the Faroes and Iceland, but the strength of this signal is haplogroup-dependent which may be indicative of more recent admixture or other demographic processes. The results of the current study and lack of conformity between Icelandic and Faroese haplotypes implies that the two populations were founded by different paternal gene pools and there is no detectable post-founder admixture between the two groups.

Animal domestication and artificial selection give rise to gradual changes at the genomic level in populations. Subsequent footprints of selection known as selection signatures or selective sweeps have been traced in the genomes of many animal livestock species by exploiting variations in linkage disequilibrium patterns and/or reduction of genetic diversity. Domestication of most aquatic species is recent in comparison with land animals, and salmonids are one of the most important fish species in aquaculture. Coho salmon (Oncorhynchus kisutch), cultivated primarily in Chile, has been subject to breeding programs to improve growth, disease resistance traits, and flesh color. This study aimed to identify selection signatures that may be involved in adaptation to culture conditions and traits of productive interest. To do so, individuals of two domestic populations cultured in Chile were genotyped with 200 thousand SNPs, and analyses were conducted using iHS, XP-EHH and CLR. Several signatures of selection on different chromosomal regions were detected across both populations. Some of the identified regions under selection contained genes such anapc2, alad, chp2 and myn that have been previously associated with body weight in Atlantic salmon or sec24d and robo1 that have been associated with disease resistance to Piscirickettsia salmonis in coho salmon. Findings in our study can contribute to an integrated genome-wide map of selection signatures, to help identify the genetic mechanisms of phenotypic diversity in coho salmon.

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.

River network connectivity and postglacial history jointly shape patterns of pollen-and seed-mediated gene flow in riparian plants, yet their relative contributions across spatial and temporal scales remain incompletely understood. Myricaria germanica Desv., a pioneer riparian shrub formerly widespread along European rivers but now restricted to fragmented headwaters, provides an ideal model to investigate how river systems structure genetic connectivity. We analysed genetic diversity, population structure, and migration across 2,212 individuals from 67 populations spanning 12 Central European river catchments using 20 nuclear and six chloroplast microsatellite loci. By integrating biparentally inherited nuclear markers with maternally inherited chloroplast markers, we disentangled pollen- and seed-mediated gene flow across historical and contemporary timescales. Both marker systems revealed low genetic diversity, high inbreeding, and strong population differentiation. Nuclear microsatellites showed significant isolation by distance and extensive historical connectivity, with coalescent analyses indicating high pollen-mediated gene flow among catchments and identifying the Rhine and Danube as major long-term sources of migrants. In contrast, chloroplast microsatellites exhibited stronger spatial structure, limited admixture, and highly directional historical seed dispersal, consistent with constrained hydrochorous dispersal routes. Contemporary migration analyses further showed that present-day seed-mediated gene flow is largely confined within catchments, despite widespread historical pollen connectivity. Together, these results support a two-phase postglacial history in M. germanica, involving rare, directional seed dispersal during recolonization followed by prolonged pollen-mediated gene flow. Our findings highlight catchments as biologically meaningful management units and underscore the importance of conserving river network connectivity to preserve both the evolutionary legacy and long-term adaptive potential of riparian populations.

Recent research in humans and both model and non-model animals has shown that DNA methylation (DNAm), an epigenetic modification, is one of the mechanisms underlying the aging process. DNAm-based indices predict mortality and provide valuable insights into biological aging mechanisms. Although sex-dependent differences in lifespan are ubiquitous and sex chromosomes are thought to play an important role in sex-specific aging, they have been largely ignored in epigenetic aging studies. We characterized the genome-wide distribution of age-related CpG sites from longitudinal samples in two avian species (zebra finch and jackdaw), including for the first time the avian sex chromosomes (Z and the female-specific, haploid W). In both species, we find a small fraction of the CpG sites to show age-related changes in DNAm with the majority of them being located on the haploid, female-specific W chromosome where DNAm levels predominantly decrease with age. Age-related CpG sites were overrepresented on the zebra finch but underrepresented on the jackdaw Z chromosome. Our results highlight distinct age-related changes in sex chromosome DNAm compared to the rest of the genome in two avian species, suggesting this previously understudied feature of sex chromosomes may be instrumental in sex-dependent aging. Moreover, studying the DNAm of sex chromosomes might be particularly useful in aging research, facilitating the identification of shared (sex-dependent) age-related pathways and processes between phylogenetically diverse organisms.

BackgroundBiological control is a sustainable strategy to combat agricultural pests. Yet, due to legislation, importing non-native biocontrol agents is increasingly restricted. Thus, selective breeding of biocontrol traits of native species is suggested to enhance performance of existing biocontrol agents. Genomic prediction is a new alternative to exploit genetic variation for improving biocontrol efficacy. This study aims to establish proof-of-principle for genomic prediction in insect biocontrol agents, using wing morphology traits in the parasitoid Nasonia vitripennis Walker (Pteromalidae) as a model. MethodsWe performed genomic prediction using a Genomic Best Linear Unbiased Prediction (GBLUP) model, using a total of 1,230 individuals with 8,639 SNPs generated by genotyping-by-sequencing (GBS). We used individuals from two generations from the outbred HVRx population, 717 individuals from generation G169 and 513 from generation G172. To assess genomic prediction accuracy, we used across- generation validation: forward validation for G172 from G169, backward in time validation for G169 from G172, and also 5-fold cross-validation, randomly using one fifth of the population as validiation and the others as training groups. ResultsFor size-related traits, including tibia length, wing length, width, and second moment wing area, the accuracy of genomic prediction was close to zero in both across-generation validations, but much higher in 5-fold cross-validation (ranging 0.54-0.68). For the shape-related trait wing aspect ratio, a high accuracy was found for all three validation strategies, with 0.47 for across-generation forward validation, 0.65 for across-generation backward validation, and 0.54 for 5-fold cross-validation. ConclusionPromising accuracies were observed for all traits in 5-fold cross-validation, but not in the across-generation validations. Overall, applying genomic selection in insect biocontrol agents with a relative small effective population size seems promising. However, factors such as the biology of insects, the techniques of phenotyping, and costs of large-scale genotyping still challenge the application of genomic selection to biocontrol agents.

Breeding programs are essential in aquaculture, improving economically and environmentally important traits. In aquaculture systems, animals are raised in large groups, where social interactions are frequent and can influence individual performance. In these circumstances, indirect genetic effects can play an important role in the response to selection, and consequently, their effects on selection outcomes must be analyzed. This study aimed to evaluate the implications of heterogeneous social interaction effects on fish breeding programs using stochastic simulations. We simulated a fish breeding program with 2000 selection candidates from 1000 families formed by a partial mating design of 100 males and 100 females. Social interactions were simulated, affected by the target phenotype and two latent-personality traits. We investigated how genetic gains and phenotypic variances are affected by the magnitude and direction of social interaction effects on the target phenotype, different selection strategies, and the genetic correlations between the target phenotype and personality traits. Our results showed that increased social interaction effects lead to greater phenotypic variability in the target trait. Under mass selection, the genetic means of personality traits change, and these changes depend on the strength and direction of genetic correlations between the focal and personality traits. Conversely, group selection did not increase phenotypic variability but reduced genetic gain for the focal trait compared to mass selection. Moreover, group selection did not alter the genetic means of personality traits. However, this approach increased the rate of inbreeding per generation, which could be mitigated by optimizing the number of families per group.

O_LIInbreeding depression plays a fundamental role in evolution. To help detect and characterize viability loci that underlie inbreeding depression, we forced self-pollinated plants from self-incompatible populations of Leavenworthia alabamica to produce families of progeny that were genotyped at hundreds of mapped single nucleotide polymorphism (SNP) loci. C_LIO_LIBayesian analysis of segregation data for each SNP was used to explore support for different dominance and selection coefficients at linked viability loci in different genomic regions. C_LIO_LIThere was some support for overdominance (or pseudo-overdominance) at a few viability loci, as well as for recessiveness and underdominance. One recessive viability locus mapped to the genomic region of the novel self-incompatibility locus in Leavenworthia alabamica, but in general there was no support for strongly recessive viability loci of major effect. C_LIO_LIThe results are consistent with earlier findings showing that inbreeding depression is recalcitrant to purging in Leavenworthia alabamica. The results also help account for the maintenance of self-incompatibility in this species and are consistent with expectations from evolutionary genetic theory that recessive, deleterious alleles linked to loci under balancing selection are sheltered from selection. C_LI

The reproductive system of an organism impacts the emergence and evolution of adaptive variants in response to selective constraints. The understanding of the sexual mode of reproduction in pathogens helps to understand their life history. In filamentous Ascomycete fungi, mating type system and the production of gametes are required to reproduce sexually. In the phytopathogenic Ascomycete Pyricularia oryzae, studies of the genetic determinants of sexual reproduction are still limited to the mating type system. This study focuses on identifying the genes involved in male fertility through the production of male gametes known as microconidia. We performed a GWAS analysis coupled with a local score approach on a wild recombinant population of Pyricularia oryzae phenotyped for microconidia production. We identified one genomic region significantly associated with the quantity of microconidia produced. This region contained nine candidate genes, some of them annotated with functions associated to sexual reproduction in model fungi such as Neurospora crassa, Podospora anserina and Sordaria macrospora. The most promising candidate gene contains a Jumonji domain. Proteins belonging to the Jumonji family are conserved among Eukaryotes and are known to be involved in chromatin regulation.

Sexual selection arises from individual differences in reproductive success, which can drive the maintenance of genetic polymorphisms in genes subject to balancing selection by the pleiotropic effects that trade-off between survival and reproduction. However, the extent to which sexual selection maintains genetic polymorphisms in wild populations remains unclear. Here, we explored on genomic signatures of balancing selection and selective sweep in the northern medaka, Oryzias sakaizumii in Japan by performing whole-genome resequencing of wild individuals. In addition, we re-evaluated the population genetic structure and admixture of Oryzias latipes and O. sakaizumii across the Japanese archipelago and detected genomic regions affected by introgression. Regions with signatures of selection from multiple statistics were located on eleven chromosomes. In particular, a region spanning 4.25 to 6.80 Mb on chromosome 18 showed high genetic diversity that could not be explained by sex differentiation or introgression from O. latipes in Eastern Japan. This pattern suggests that balancing selection maintains genetic polymorphisms in O. sakaizumii. Specifically, because a previously reported quantitative trait locus associated with female mating behavior overlaps with this region, we infer that sexual selection contributes to the maintenance of genetic polymorphism at this locus.