Heredity

Over the past decade there has been increasing interest in the use of microhaplotype markers in autopolyploid taxa. This has been driven by theoretical and observed improvements in signals of allelic dosage, linkage, and heritability. Yet, to date there has been little investigation into the suitability of microhaplotype markers for estimating kinship. Here, we develop the theory of kinship estimation from microhaplotypes, introduce the MCHap microhaplotype caller for autopolyploid populations, and apply these methods to a highly diverse germplasm population of mixed-ploidy Actinidia (kiwifruit and relatives). We find that microhaplotype-based kinship estimates are generally superior to equivalent single nucleotide variant based estimates. This is because microhaplotypes minimize the coalescent signal among alleles which may bias estimates within the context of a recent reference population. Hence, kinship estimates from microhaplotypes more accurately capture the recent demographic history of a population. These findings are supported by both coalescent simulations and the analysis of real data. Our findings are relevant to organisms of any ploidy, but most actionable in highly heterozygous taxa such as Actinidia.

The European flat oyster (Ostrea edulis), like numerous other oyster species, has been exploited for millennia and cultivated and translocated for centuries. Following a severe population decline, and in the context of ongoing conservation and restoration programs, genetic considerations must now be addressed to avoid mistakes. The objective of our study was to complement population genetic studies conducted at various scales along European coasts. Our sampling primarily targeted the French Atlantic, English Channel, and Mediterranean coasts, aiming to provide a fine-scale genetic characterization of populations in these regions. By integrating SNP array and low-coverage sequencing datasets, we obtained a comprehensive overview of the population genetic structure of Ostrea edulis across western Europe. Most previously identified clusters in Western Europe were confirmed. In France, populations assigned to these clusters exhibited notable within-patch homogeneity. However, two key findings emerged: (1) an extensive overlap zone between the Atlantic and western Mediterranean clusters, spanning at least from southern Portugal to southern France, and (2) the detection of a novel, clearly distinct cryptic cluster east of the English Channel, whose geographic range remains to be better delineated. These insights are critical for informing management decisions, particularly as restoration and conservation plans are currently being implemented across the species range.

Ectomycorrhizal (EM) fungi are vital to forest ecosystems, supporting tree growth and survival. However, their inclusion in conservation policy and action remains limited and little is known about the status of their genetic diversity, which is essential for their long-term survival and adaptation. The Global Biodiversity Framework adopted a genetic indicator based on the effective population size, Ne, to monitor genetic diversity in all species. To date, it is still uncertain how Ne, a key parameter, can be reliably assessed in species with complex life history traits. Ectomycorrhizal fungi are a highly diverse group of taxa displaying haplodiplontic life cycles with partially clonal reproduction. Here, we review the literature to understand how these life history traits might affect Ne and its estimation in six species of EM fungi. We estimated Ne in 19 populations using eight genetic and genomic datasets from selected studies. We compared Ne estimates using Linkage Disequilibrium (LD) and Sibship Frequency (SF) methods. We tested how Ne estimates change due to partial clonality and genetic structure gradients and whether the number of genetic markers influence the precision of the estimates. We show a systematic bias in Ne estimations when large clones are present and when populations are not correctly delimited. We found both methods are not robust to these factors, which makes them unreliable for conservation assessment purposes in EM fungi. This study provides new perspectives for further research into the links between life history traits and the effective population size of ectomycorrhizal fungi.

Parental ageing can influence offspring through non-genetic mechanisms. The contribution of epigenetic inheritance parental effects still remains poorly understood. DNA methylation is a widespread regulator of gene expression that changes during development and ageing and can also act as a mediator of intergenerational effects. We tested whether age-related changes in parental DNA methylation are transmitted to offspring in the short-lived turquoise killifish (Nothobranchius furzeri, Cyprinodontiformes). Using reduced-representation sequencing, we quantified genome-wide DNA methylation and examined methylation dynamics at individual loci. The overall proportion of methylated CpG sites increased during early ageing but declined at later ages, revealing a non-linear trajectory with substantial among-individual variation. Despite these age-related changes, we found no evidence that parental methylation patterns were transmitted to offspring, either at the genome-wide level or at individual loci. Our findings indicate that although DNA methylation undergoes pronounced age-dependent remodelling in adult killifish, these changes are not detectably inherited by the next generation. We discuss these results in the context of epigenetic inheritance and ageing in vertebrate model systems.

Post-harvest physiological deterioration (PPD) represents a significant challenge of cassava production and commercialization. This multifaceted biological process involves a series of mechanisms, including enzymatic stress responses, alterations in gene expression, protein synthesis, accumulation of secondary metabolites, and ultimately, programmed cell death. These changes render the storage roots unpalatable and unmarketable. Therefore, unraveling the genetic architecture of PPD and exploring the interactions of associated genes during its early and late stages is essential for the crop production. We used modern genetic resources to unravel the genetic basis of PPD, based on a genome-wide association study (GWAS), utilizing a combination of different models, including BLINK (Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway), SUPER (Settlement of MLM Under Progressively Exclusive Relationship), and MLMM (Multi-locus mixed models). The phenotyping dataset spanned five years and included evaluations from 42 different trials, evaluating the Embrapa (Brazilian Agricultural Research Corporation) germplasm along with a population derivative from a genomic selection cycle. We utilized a genotype dataset comprising 26,000 high-quality SNPs (single nucleotide polymorphisms). Our findings indicated four significant genetic variants located on chromosomes 2, 5, and 13, which together explain 35.83 % of the phenotypic variation. These variants are associated with genes that are closely linked to the pathways activated during the early and late symptoms of PPD. The identification of these three key genes provides valuable insights into the genetic architecture of PPD and lays a strong foundation for molecular breeding, supporting the efforts to identify cassava genotypes with enhanced PPD tolerance, the identified genomic regions may be incorporated into genomic selection models, thereby enhancing marker-assisted selection (MAS) and improving breeding strategies for long shelf life and high-quality agronomic cassava cultivars for the cassava community.

Genomic health estimates help inform conservation and management decisions, with genetic load and runs-of-homozygosity (ROH) being two key metrics. White-tailed deer (Odocoileus virginianus) and mule deer (O. hemionus) are found throughout North America, with some populations declining or of conversation concern. Using genome-wide data from samples across their range, we provide the first estimate of genetic load in mule deer, and revisit ROH estimates using model-based approaches. These updated estimates of ROH notable showed elevated inbreeding in the Key deer, consistent with current conservation designations. We also detected a relatively high number loss-of function mutations in mule deer that we attributed to historical bottlenecks. Notably, we observed an increased overall genetic load in O. hemionus from the Pacific Northwest.

Anthropogenic copper (Cu) contamination from agriculture, mining, and industrial runoff creates environmental gradients affecting physiology and behavior in wild populations. While Cu toxicity in Drosophila melanogaster is well characterized, it remains unclear whether Cu resistance is one integrated trait or several independently evolving components. Using a subset of recombinant inbred lines (RILs) from the Drosophila Synthetic Population Resource (DSPR), we measured three components of Cu response: feeding avoidance, oviposition avoidance, and physiological tolerance (median lethal time, LT50) under sustained Cu exposure. All three traits showed substantial phenotypic variation among RILs. Feeding and oviposition avoidance were both highly heritable (H 2 ~ 0.88), and RIL identity accounted for 49.5% of the variance in LT50. However, the three traits showed no significant correlation across RILs, indicating distinct genetic architecture. We identified a single male specific quantitative trait locus (QTL) on chromosome 2R that explained 17.7% of the variation in feeding preference; the interval included candidate detoxification genes Jheh1, Jheh2, Jheh3 and sano, the latter of which is associated with olfactory behavior. No significant QTL were detected for oviposition preference, suggesting a highly polygenic structure that may difficult to detect with our limited panel size. Together, these results indicate that Cu resistance in D. melanogaster is genetically modular. Behavioral avoidance during feeding, oviposition, and physiological tolerance are heritable but architecturally distinct components, each with potential to respond to selection independently.

Long-term studies of isolated animal populations have greatly improved the understanding of various evolutionary processes. However, potentially elevated inbreeding in those compared to wild populations is a common concern. Conventionally, inbreeding has been investigated using reconstructed pedigrees, but nowadays it can be done directly at the genomic level. Here, we utilize genomic data from an intensively studied isolated rhesus macaque (Macaca mulatta) population on the small island Cayo Santiago (Puerto Rico), which was founded in 1938 with wild animals from India. We quantified inbreeding levels by inferring runs of homozygosity (ROH), i.e., long identical haplotypes inherited from both parents. We identified ROH in 97 ~5x-coverage genomes from Cayo Santiago and, for comparison, in 79 rhesus macaque genomes from five wild populations from China. Notably, this conventionally considered low-coverage data proved sufficient to infer ROHs >4 centimorgans long after imputing the genomes using a reference panel. Our results revealed that the ROH-derived effective population size on Cayo Santiago, 420 individuals, falls within the ranges we inferred in wild populations. Moreover, a general scarcity of individuals with long ROH in both the Cayo and wild populations indicates very few cases of close-kin breeding, suggesting that mechanisms to avoid close-kin breeding operate in rhesus macaques, both in wild and isolated populations. Taken together, our results suggest that Cayo Santiago remains a representative study population.

Drought during reproductive development and grain filling is a major constraint to bread wheat productivity in rainfed environments. In the present study, we employed genome-wide association analysis in an untapped diversity panel of wheat genotypes relevant to natural dryland conditions. A total of 186 genotypes were evaluated for drought-related physiological, biomass, and architectural traits under terminal rainfed stress in Azerbaijan. Relative water content, plant height, fresh weight, dry weight, flag leaf length, and flag leaf width were assessed at the milk ripening stage. These data were subjected to genome-wide association analysis using 19,737 SNP markers to identify loci and epistatic interactions involved in the determination of these traits. The panel showed broad phenotypic variation and significant genotypic effects for all traits, with broad-sense heritability ranging from 0.991 for plant height to 0.385 for flag leaf width. GWAS identified a major locus for relative water content on chromosome 2D at SNP marker AX-86184518, which explained 11.94% of the genotypic variation. Candidate-gene analysis highlighted the proximal WEB-family-like gene TraesCS2D03G1001000 as the main candidate gene. Plant height showed strong additive loci, mainly on chromosomes 2A and 4A, whereas biomass and flag leaf traits showed suggestive additive loci and epistatic interactions. These findings provide candidate loci and interaction patterns in the genetic make-up of essential traits, which may facilitate indirect selection in breeding new varieties.

Parental qualities can influence the development and fitness of their offspring via genetic and non-genetic effects. Although these effects are often linked to parental phenotypes, the effect of parental genetic variation linked with relevant phenotypes is less well understood. We performed full factorial crosses based on parental genotypes for an age-at-maturity-related gene, vgll3, to investigate how the parental genotypes influence Atlantic salmon (Salmo salar) offspring survival, growth, and development in their early life. Beyond the connection with age at maturity, the additional association between vgll3 and body condition in Atlantic salmon offers a potential pathway by which the maternal vgll3 genotype could influence offspring early life fitness. Combined with measurements of maternal phenotype and egg characteristics, the crossing design therefore allowed us to disentangle the maternal and paternal genetic and non-genetic contributions to variation in offspring survival and phenotypic traits. The phenotypic traits measured were hatching length and yolk sac area, growth, and yolk sac consumption and conversion efficiency. Parental vgll3 genotype did not influence the majority of our measured egg traits or alevin traits except for a genetic effect of paternal vgll3 genotype on offspring survival, whereby the paternal late maturation allele was associated with higher survival. Maternal effects were strongest for survival and for traits associated with hatching and weaker for alevin growth and yolk sac usage. Paternal effects on the measured alevin traits were negligible. The results from our study demonstrate that both maternal and paternal effects have the potential to influence offspring early life fitness traits.

Caenorhabditis nematodes are a powerful model clade for evolutionary genetics. Isogenic lines and panels of recombinant inbred lines (RILs) are among the most essential tools for genetic studies in these species. While most Caenorhabditis species are gonochoristic, large RIL panels have only been developed for self-fertilizing species. This gap biases our understanding and limits our ability to address questions related to the genetic architecture of traits in outbred populations, which have radically higher genetic diversity, heterozygosity, and effective recombination than selfers. Having previously identified Caenorhabditis becei as a tractable gonochoristic species due to its moderate inbreeding depression, we generated two panels of advanced-intercross RILs derived from three individual outbred C. becei worms collected from a single locality on Barro Colorado Island, Panama. One panel derives from a pair of worms sampled from a single rotting fig; the other derives from a cross between worms from two different figs. The panels share one founder in common, yielding two half-sib RIL panels. We sequenced and haplotyped the lines, identifying millions of variants and thousands of recombination breakpoints. Using simulations, we demonstrate the suitability of these lines for quantitative genetics studies and QTL mapping. In our single-fig panel, we observe abundant heritable variation in population growth rate, individual body size, and sexual dimorphism for body size. We detected four QTLs associated with population growth rate and show that estimated allelic effects are good predictors of selection that occurred during panel derivation.

Studying the genomic control of dyadic social interactions is gaining traction in animal genetics. However, genetic modeling of social interactions poses several challenges, one of which is whether social interactions should be treated as dyadic traits or as aggregated traits at the individual level. In this study, we systematically compared two approaches: dyadic models using dyadic traits and marginal models using marginally aggregated traits and we derived the algebraic relationships between their variance components. In the application, we used a published dataset on post-mixing aggression in pigs, including both directed and undirected aggression records collected during the 9-hour period after mixing among 797 finishing pigs in 59 social groups, as an example to show how model choice can affect variance estimation. Results showed that dyadic models can estimate genetic effects and permanent environmental effects by exploiting repeated dyadic interaction records, thereby enabling a more complete understanding of the sources of variation underlying social interactions. In contrast, marginal models can bias the estimation and interpretation of genetic components, as the aggregated genetic variance may be confounded with other variance components due to the aggregation of dyadic traits. Marginal models may also lead to overestimation of social group and residual variance. These results can provide useful guidance for choosing appropriate modeling strategies for social interaction traits.

Infection can substantially reduce host fitness and influence population dynamics, yet it is often difficult to detect and quantify in wild animal populations. Molecular tools offer a valuable means of identifying cryptic infection in natural systems. Using whole-genome bisulfite sequencing, we examined whether infection with the parasitic leech Ozobranchus margoi is associated with DNA methylation variation in loggerhead sea turtles (Caretta caretta), while also assessing the potential value of this variation as a biomarker of parasite infection. In nesting females, we identified infection-associated differentially methylated CpG sites associated with genes implicated in immune signalling and cellular regulation. Offspring of infected females also showed infection-associated methylation patterns, despite not being directly exposed to the parasite themselves. Differential methylation analyses identified genes involved in immunity, neurodevelopment and metabolic activity, with limited overlap in associated genes and no overlap in differentially methylated sites between generations. Maternal and offspring genome-wide methylation levels showed a non-linear association that differed subtly with maternal infection status, indicating that infection modifies intergenerational methylation associations. Finally, methylation profiles showed strong discriminatory power for maternal infection status in both maternal and hatchling samples using machine learning models, supporting their potential as candidate biomarkers of cryptic infection. Together, these results show that parasite infection is associated with distinct, generation-specific DNA methylation signatures, and highlight the potential value of epigenetic data for monitoring cryptic infection states in conservation-relevant systems.

Plant regeneration is a dynamic developmental process that spans from cell dedifferentiation to organ reconstruction in response to inductive cues, such as wounding stress and hormonal signals. Although this capacity varies widely both between and within species, a comprehensive understanding of the genetic and epigenetic bases of this variation remains incomplete. To address this issue, we revisited published datasets on natural variation in in vitro regeneration capacity in Arabidopsis thaliana. Using quantitative genetic approaches, including meta-analyses of genome-wide association studies (GWAS) and multi-locus models, we dissected the genetic architecture underlying regeneration traits. Our results showed that shoot regeneration capacity is primarily explained by allelic variation in the cis-regulatory region of WUSCHEL (WUS), a key regulator of shoot meristem formation. Notably, these polymorphisms are also associated with epigenetic variants of the DNA transposon ATDNA2T9C, which is located within the regulatory region. Furthermore, allelic variation in ARABIDOPSIS RESPONSE REGULATOR 2 (ARR2), a positive regulator of cytokinin signaling, is associated with callus formation and greening traits and may promote shoot formation through genetic interactions with WUS alleles. Although in vitro regeneration is controlled by complex, multilayered gene regulatory networks, our results suggest that, in A. thaliana, natural variation in regeneration capacity is largely shaped by a small number of major-effect modifiers together with epigenetic variation and genetic interactions, despite the substantial heterogeneity observed among natural populations.

Understanding the genomic basis of early adaptation is a central question in evolutionary biology. Although there is ongoing debate about whether early adaptation is more likely to be driven by polygenic responses or by loci of large effect, few studies of natural populations have been able to address this problem. Furthermore, early adaptation to a novel environment often coincides with founding events, making it difficult to disentangle neutral effects from adaptive genomic changes. Here we take advantage of the unique in situ guppy experimental system, in which we established replicate populations by translocating guppies from a high predation locality to four low predation localities. We present whole genome sequencing from the source population and the four experimental populations, sampled after [~]8-10 generations (first period), and again at [~]18-22 generations (second period). We find signatures of inbreeding only in the first period, despite documented population crashes in the second period. We show genome-wide dynamics of selection as well as selective change at single loci and uncover new targets of selection. Overall, we found signatures of selection at all levels; genome-wide, chromosome, and individual windows are more repeatable among replicates in the first period than in the second period.

Bird migration evolved as an adaptation to seasonally changing habitats. Migratory behaviour can vary within the same species in case of partial migratory behaviour, i.e. one population (or individual) is migratory and another one is resident. Species that exhibit a wide variety of migratory phenotypes provide valuable systems to understand the evolutionary drivers behind different phenotypes and how populations adapt to habitats with distinct seasonality. The European robin (Erithacus rubecula) expresses migratory behaviour in central and northern areas of the species distribution range, whereas populations in the South and on the Macaronesian islands are predominantly resident, providing a suitable system to investigate these questions. We use high coverage whole genome re-sequencing data of 125 European robins to investigate how migration behaviour affects population structure and demography, and how it affects the selection landscape in the genome. Genetic structure in European robins coincides with migratory phenotype and geography and populations are characterised by distinct demographic histories. Our results suggest that both the continental resident population as well as the Macaronesian island populations have derived independently from an ancestral migratory population. Unexpectedly, tests for differential selection revealed extensive positive selection pressure acting across all chromosomes in the resident populations, while selective sweeps are largely absent from migrants. We speculate that this might be an analytical artifact due to mismatching timescales between what population genomics methods can detect and the scale on which migration behaviour likely evolved in the robin. We suggest that future studies on the genomics of migration should more focally account for different time scales on which these processes happen, such as including the wider phylogenomic background of the target species, to capture the full evolutionary history of migratory traits.

Inbreeding depression (the reduction in fitness associated with inbreeding) has been demonstrated in a wide range of animals, but despite its ubiquity, is not an inevitable consequence of inbreeding. As a result, there is uncertainty about the extent to which inbreeding depression poses an ongoing risk to endangered species currently experiencing significant demographic recovery. Quantifying inbreeding depression will be critical if we want to understand these risks. A comprehensive quantification of the fitness costs of inbreeding requires detailed individual-based longitudinal data so lifetime impacts can be assessed. Here, we use an extraordinarily detailed long-term dataset on Mauritius kestrels (Falco punctatus) to explore inbreeding depression in a population currently experiencing significant demographic recovery. To do so, we constructed a social pedigree of 1,758 individuals and combined this with 1,240 nest records and 1,411 individual resighting histories to explore lifetime fitness effects over a 30-year period. Inbreeding increased significantly over time as the population recovered before stabilising. Inbred eggs were less likely to survive to fledging. Inbred adult male and female birds had significantly lower annual reproductive success than outbred individuals because of a lower annual egg-to-fledgling survival probability. This resulted in significantly lower lifetime reproductive success in inbred females but not males, which showed a negative trend. Population growth was negative and extinction risk increased slightly at current levels of inbreeding. These impacts will become more severe should inbreeding levels increase in the future, which is highly likely given ongoing genomic erosion. Taken together, our results demonstrate significant fitness costs associated with inbreeding in Mauritius kestrels, which pose an ongoing risk to population viability. This suggests that monitoring and managing inbreeding risks in endangered species will likely be required even in populations that are showing significant demographic recovery in response to conservation interventions.

Free-living nematodes are among the most abundant animals on Earth and play critical ecological roles in soil ecosystems. However, the global population structure and evolutionary history of most species remain poorly understood. Here, we analyzed genome-wide variation in Oscheius tipulae using whole-genome sequence data from 31 isolates, including 28 publicly available genomes and three newly collected strains from Korea. Population structure analyses, phylogenomic inference, and ancestry estimation consistently identified three deeply divergent lineages. These analyses did not detect admixture among lineages and collectively supported a predominantly tree-like evolutionary history. Notably, the lineages were structured by latitude rather than geographic proximity. Isolates from similar latitudinal zones clustered together regardless of continental origin, forming three major groups: northern mid-latitude (NML), low-latitude (LL), and southern mid-latitude (SML). This pattern indicates that the lineages have maintained largely independent evolutionary trajectories over extended timescales despite the potential for long-distance dispersal. Furthermore, environmentally associated variants showed significant differentiation among lineages, indicating that environmental selection may contribute to the maintenance of this latitudinally structured diversity. Our results reveal unexpectedly deep global divergence within O. tipulae, and highlight the importance of ecological divergence and long-term lineage retention in shaping the global diversity of this group.

Understanding spatial and temporal connectivity among individuals with different migration strategies is essential for migratory ecology and effective conservation, yet it often requires integrating multiple data sources. In Northeast Atlantic European sea bass (Dicentrarchus labrax), electronic tagging has revealed partial migration, with both resident and long-distance migrants showing fidelity to summer feeding and winter spawning areas. However, the role of regional spawning-site philopatry in shaping migration patterns and stock connectivity remains unclear. Here, we combine reconstructed migration trajectories with genome-wide analyses of gene flow and recent relatedness in 708 individuals sampled from 10 French Atlantic locations. We identify a seasonally shifting genetic discontinuity between the Bay of Biscay (BOB) and Northern (NS) stocks, located off western Brittany during winter spawning and displaced northeastward into the central English Channel during summer feeding. Despite seasonal mixing in the English Channel, an association between individual genetic composition and spawning-site selection supports regional spawning-site philopatry. Analyses of long genomic segments shared identical-by-descent reveal substantially greater connectivity within stocks than between stocks, indicating that philopatry constrains effective gene flow despite seasonal mixing. Reanalysis of independent genomic data further shows that sea bass from the northern Atlantic range predominantly belong to the Northern stock. Together, these results show how seasonal movements reshape spatial genetic structure while maintaining demographic subdivision, with direct implications for fisheries management.

Genotype-environment association (GEA) analyses are widely used to identify loci underlying local adaptation by examining correlations between allele frequencies and environmental variables across a species' range. A major challenge for this approach is distinguishing true adaptive signals from spurious associations arising from population structure. Several methods have been developed to account for population structure, but these methods can suffer from reduced statistical power or increased false positives under some conditions. To address this, we introduce a new GEA method, termed SimGEA. In essence, SimGEA infers a neutral evolutionary model that reproduces the population structure observed in empirical data and uses this model to simulate neutral alleles. By applying the same GEA statistic to both the empirical and simulated data, SimGEA evaluates the significance of observed associations against neutral expectations that account for population structure. We compared the performance of SimGEA with that of existing GEA methods, including LFMM2 and BayPass, using simulations of local adaptation in two-dimensional space. We found that SimGEA consistently controlled the false discovery rate without substantially sacrificing statistical power across the scenarios examined. These results suggest that calibrating statistics using neutral simulations provides a robust and flexible approach for accounting for population structure in GEA analyses.