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bioRxiv2024

Genetic architecture of heritable leaf microbes

AbstractHost-associated microbiomes are shaped by both their environment and host genetics, and often impact host performance. The scale of host genetic variation important to microbes is largely unknown, yet fundamental to the community assembly of host-associated microbiomes, and with implications for the eco-evolutionary dynamics of microbes and hosts. Using Ipomoea hederacea, Ivy-leaved morning glory, we generated matrilines differing in quantitative genetic variation and leaf shape, which is controlled by a single Mendelian locus. We then investigated the relative roles of Mendelian and quantitative genetic variation in structuring the leaf microbiome, and how these two sources of genetic variation contributed to microbe heritability. We found that despite large effects of the environment, both Mendelian and quantitative genetic host variation contribute to microbe heritability, and that the cumulative small effect genomic differences due to matriline explained as much or more microbial variation than a single large effect locus. Furthermore, our results are the first to suggest that leaf shape itself contributes to variation in the abundances of some phyllosphere microbes. ImportanceWe investigated how host genetic variation affected the assembly of Ipomoea hederaceas natural microbiome. We found that the genetic architecture of leaf-associated microbiomes involves both quantitative genetic variation and Mendelian traits, with similar contributions to microbe heritability. The existence of Mendelian and quantitative genetic variation for host-associated microbes means that plant evolution at the leaf shape locus or other quantitative genetic loci has the potential to shape microbial abundance, and community composition.

ecology↗
bioRxiv2024

Genetic Diversity of Zymoseptoria tritici Populations in Central and South-eastern Ethiopia

Septoria tritici blotch (STB), caused by the hemibiotrophic fungus Zymoseptoria tritici, is a serious threat to global wheat production, and a major bottleneck to wheat production in Ethiopia. Accurate identification and analysis of the pathogens genetic structure helps inform robust STB management. This study analyzed the molecular identity and genetic structure of 200 Z. tritici isolates retrieved from diseased crops in central and south-eastern regions of Ethiopia. Allelic diversity at 12 simple sequence repeat (SSR) loci was examined for all 200 isolates, and 165 isolates were identified by Sanger sequencing of the internal transcribed spacer (ITS) region of nuclear DNA (rDNA) region. The microsatellites were highly polymorphic, with mean number of alleles (Na) = 6.23, effective alleles (Ne) =2.90, Neis gene diversity (H) =0.57, and polymorphic information content (PIC) =0.59, and an analysis of molecular variance confirmed the presence of low population differentiation (Fixation Index (FST) = 0.02, Gene Flow (Nm) = 14.7), with 95% of the total genetic variation residing within populations, and only 5% residing between populations. The highest genetic diversity (Number of allele (Na) = 9.33, Effective number of allele (Ne) = 3.41 and Neis gene diversity (H) = 0.68) was observed in the Oromia special zone surrounding Finfinnee (OSZ) Z. tritici populations, followed by Arsi and North Shewa populations, indicating that these areas are ideal for multi-location germplasm resistance screening, and also pathogen genetic and genomic analyses. Cluster analyses did not clearly divide the populations into genetically separate clusters according to their geographic sampling areas, probably because of high gene flow. All individual samples showed genetic admixture, and shared genomic backgrounds from two subgroups (K=2). Overall, the SSR markers proved to be highly informative and effective genetic tools for unlocking the pathogens genetic structure. The Z. tritici populations of central and southeast Ethiopia exhibit high genetic diversity, indicating the need to deploy durable and diverse disease management strategies. North Shewa, OSZ, Arsi and West Arsi administrative zones represent hotspots for genetic and genomic analyses of Z. tritici. Moreover, these areas would be excellent locations for host-pathogen interaction studies, and wheat germplasm screening for STB resistance.

plant biology↗
bioRxiv2024

Multivariate Trait Evolution: Models for the Evolution of the Quantitative Genetic G-Matrix on Phylogenies.

Genetic covariance matrices (G-matrices) are a key focus for research and predictions from quantitative genetic evolutionary models of multiple traits. There is a consensus among quantitative geneticists that the G-matrix can evolve through deep time. Yet, quantitative genetic models for the evolution of the G-matrix are conspicuously lacking. In contrast, the field of macroevolution has several stochastic models for univariate traits evolving on phylogenies. However, despite much research into multivariate phylogenetic comparative methods, analytical models of how multivariate trait matrices might evolve on phylogenies have not been considered. Here we show how three analytical models for the evolution of matrices and multivariate traits on phylogenies, based on Lie group theory, Riemannian geometry and stochastic differential (diffusion) equations, can be combined to unify quantitative genetics and macroevolutionary theory in a coherent mathematical framework. The models provide a basis for understanding how G-matrices might evolve on phylogenies, and we show how to fit models to data via simulation using Approximate Bayesian Computation. Such models can be used to generate and test hypotheses about the evolution of genetic variances and covariances, together with the evolution of the traits themselves, and how these might vary across a phylogeny. This unification of macroevolutionary theory and quantitative genetics is an important advance in the study of phenotypes, allowing for the construction of a synthetic quantitative theory of the evolution of species and multivariate traits over deep time. Lay SummaryWe unite Quantitative Genetics, the major mathematical theory of multivariate quantitative trait microevolution, with the mathematical theory of multivariate macroevolution. To do this, we allow the key component of quantitative genetic theory, the matrix of additive genetic variances and covariances (the G-matrix) to evolve along evolutionary trees. This is an advance because the G-matrix is assumed to be constant in quantitative genetics (for convenience), but it has been recognised that it evolves on macroevolutionary timescales (in deep time). Uniting Quantitative Genetics with macroevolutionary theory allows for a more complete mathematical description of Darwins theory of evolution, and allows for further testing of evolutionary hypotheses.

evolutionary biology↗
bioRxiv2024

Genetic ancestry and population structure in the All of Us Research Program cohort

The NIH All of Us Research Program (All of Us) aims to build one of the worlds most diverse population biomedical datasets in support of equitable precision medicine. For this study, we analyzed participant genomic variant data to assess the extent of population structure and to characterize patterns of genetic ancestry for the All of Us cohort (n=297,549). Unsupervised clustering of genomic principal component analysis (PCA) data revealed a non-uniform distribution of genetic diversity and substantial population structure in the All of Us cohort, with dense clusters of closely related participants interspersed among less dense regions of genomic PC space. Supervised genetic ancestry inference was performed using genetic similarity between All of Us participants and global reference population samples. Participants show diverse genetic ancestry, with major contributions from European (66.4%), African (19.5%), Asian (7.6%), and American (6.3%) continental ancestry components. Participant genetic similarity clusters show group-specific genetic ancestry patterns, with distinct patterns of continental and subcontinental ancestry among groups. We also explored how genetic ancestry changes over space and time in the United States (US). African and American ancestry are enriched in the southeast and southwest regions of the country, respectively, whereas European ancestry is more evenly distributed across the US. The diversity of All of Us participants genetic ancestry is negatively correlated with age; younger participants show higher levels of genetic admixture compared to older participants. Our results underscore the ancestral genetic diversity of the All of Us cohort, a crucial prerequisite for genomic health equity.

bioinformatics↗
bioRxiv2025

Mosaic accumulation of somatic genetic variation and estimates of age in the long-lived reef-building coral Acropora palmata

Somatic genetic variation (SOGV), accumulating during an organisms lifetime, was traditionally viewed as detrimental rather than adaptive due to links with cancer and senescence. However, in modular organisms like corals, deleterious mutations can be purged at the cellular or polyp level, while adaptive mutations may rise in frequency as polyps create genetically distinct modules. Quantifying the somatic genetic landscape in corals is necessary to understand the role these mutations may have in coral and clonal animal development and evolution. Here, we catalog somatic genetic variation in eight Acropora palmata colonies from Curacao. Whole genomes were sequenced (70-100x depth), documenting mutation variant allele frequency shifts as genets aged. Large numbers of SOGVs were observed in six- to ten-year-old colonies, and inferred mutation rates were used to age a genet of uncertain age to almost a century old. Although mutations were not fixed at the polyp or branch levels, i.e. they always displayed frequencies <0.5 as expected at mutating homozygous sites, their allele frequencies followed a power-law distribution, similar to aging human tissues. No signs of positive selection were found; instead SOGVs in the colony of uncertain age were under purifying selection. In one colony, mutations in 28 samples from along a branch were analyzed using a SNP microarray. Contrary to expectations, genetic and physical distances were unrelated. This observation together with the observed lack of fixation may be explained by a large stem cell population, the de-differentiation or dormancy of stem cells, the contribution of strong purifying selection, or a combination of the previously mentioned. Our findings provide a neutral framework against which to test for module-level selection of genetic variation in corals, explore the relationship between physical and genetic distance within a colony, and apply a somatic genetic clock to colonies of Acropora palmata. This work provides necessary fundamental insights into the landscape of somatic mutations in reef-building coral, highlighting the importance of studying these mutations as they may contribute to genetic diversity and adaptability in colonial animals.

genomics↗
bioRxiv2025

Barriers Broken: Genetic Swamping in Restored Brook Trout Populations

Scientists use reintroductions to restore native species to their historical ranges but sometimes can overlook the effects of dispersal on the genetic structure of restored populations. In the Great Smoky Mountains National Park (GRSM), an ambitious reintroduction strategy aims to restore native Brook Trout (Salvelinus fontinalis) populations, which have lost over 75% of their historical habitat within the park. Each restoration requires removing non-native trout and selecting restoration streams with natural barriers to prevent recolonization. Multiple Brook Trout populations are mixed in restoration sites to maximize genetic diversity and to avoid depletion of any single source population. However, a miscommunication during a reintroduction in Anthony Creek, which used three source populations for restoration, inadvertently created an in-situ population genetics study. One segment of the restoration site received fish from all three source populations. However, technicians also unintentionally placed fish from just one source upstream of a natural barrier. Unbeknownst to management, fish from this separate translocation dispersed downstream, potentially altering the desired genetic diversity of the restored population. This study characterizes the genetic changes caused by this unidirectional dispersal. Population genetics theory predicts that such movement leads to genetic swamping. Here, we use genetic and population density data to confirm the directionality of dispersal, estimate the rate of genetic swamping, and assess alternative mitigation strategies. Our results indicate that it is already too late for assisted migration within the restored stream to achieve the intended genetic diversity. Instead introducing additional fish above the second natural barrier would be necessary to equalize the contribution of all three source populations. Understanding the interplay between dispersal behavior and genetic structure is crucial for planning reintroductions and refining conservation strategies for this iconic species.

evolutionary biology↗
bioRxiv2025

Soil composition structures genetic variation across small spatial scales in a rare serpentine endemic plant

Studies of population genetic structure are typically conducted at the scale of species distributions and encompass large distances and substantial environmental variation. However, population genetic structure could also be present in species with highly restricted global distributions, such as habitat specialists with threatened or vulnerable conservation status. For these organisms, low dispersal distances coupled with fine-scale environmental heterogeneity could influence population genetic composition, potentially creating spatial genetic structure and genotype by environment associations. Here we use the serpentine endemic plant Calochortus tiburonensis, with a global distribution of 160 ha, to evaluate whether fine-scale structure in soil composition and low seed dispersal distances result in the development of population genetic structure. We paired soil elemental analysis with a RAD-seq SNP dataset for 24 C. tiburonensis individuals. Although no population structure was detected between C. tiburonensis sampling locations, multiple analyses identified associations between soil composition and genetic distance between individuals. This included associations with nickel and magnesium, two elements that were expected a priori to impact plant fitness in serpentine landscapes. However, redundancy analyses and a generalized dissimilarity model both suggest that total soil variation better explains differences in genetic composition between individuals, implying that selection from the holistic soil environment has a role in matching plant genotypes to the microenvironment. Our results indicate that fine-scale environmental heterogeneity could influence genetic differences between individuals in plant populations, even in the absence of population genetic structure. Additionally, these associations between genetic composition and fine-scale environmental heterogeneity implicate extremely fine-scale environmental heterogeneity as an essential mechanism for preserving genetic variation, particularly within range-limited species.

ecology↗
bioRxiv2025

marApp: An R package and web portal to calculate mutations- and genetic diversity-area relationship for conservation

International conservation policies including the Kunming-Montreal Global Biodiversity Framework now consider genetic diversity of wild species in their targets. However, scalable, theory-driven tools to assess and predict genetic diversity loss are still emerging, limiting their use in conservation planning. Analogous to the species-area relationship, recent work has shown that genetic diversity scales with area, described by the mutations-area relationship (MAR) or genetic-diversity-area relationship (GDAR), can approximate the genetic diversity loss in a species from habitat reduction. To enable application of these insights for conservation practitioners and policy makers, we present the mar R package and marApp web portal, a fast and user-friendly tool for MAR/GDAR analysis. The mar package connects genetic diversity patterns in space to ecological theory, and automates steps from reading genetic and geographic data to simulating various habitat extinction scenarios using MAR/GDAR. The mar package estimates only short-term genetic diversity, providing a lower-limit for the far greater long-term genetic losses, underscoring the need to maximize present-day habitat conservation before it becomes irreversible. As a case example, we showcase predictions of coral (Acropora sp.) genetic diversity loss from reef coverage impacts. We demonstrate the usage of marApp without requirements for prior genetics or coding experiences, and provide downloadable reports for conservation.

ecology↗
bioRxiv2018

Genetic architecture and selective sweeps after polygenic adaptation to distant trait optima

Understanding the genetic basis of phenotypic adaptation to changing environments is an essential goal of population and quantitative genetics. While technological advances now allow interrogation of genome-wide genotyping data in large panels, our understanding of the process of polygenic adaptation is still limited. To address this limitation, we use extensive forward-time simulation to explore the impacts of variation in demography, trait genetics, and selection on the rate and mode of adaptation and the resulting genetic architecture. We simulate a population adapting to an optimum shift, modeling sequence variation for 20 QTL for each of 12 different demographies for 100 different traits varying in the effect size distribution of new mutations, the strength of stabilizing selection, and the contribution of the genomic background. We then use random forest regression approaches to learn the relative importance of input parameters in determining a number of aspects of the process of adaptation including the speed of adaptation, the relative frequency of hard sweeps and sweeps from standing variation, or the final genetic architecture of the trait. We find that selective sweeps occur even for traits under relatively weak selection and where the genetic background explains most of the variation. Though most sweeps occur from variation segregating in the ancestral population, new mutations can be important for traits under strong stabilizing selection that undergo a large optimum shift. We also show that population bottlenecks and expansion impact overall genetic variation as well as the relative importance of sweeps from standing variation and the speed with which adaptation can occur. We then compare our results to two traits under selection during maize domestication, showing that our simulations qualitatively recapitulate differences between them. Overall, our results underscore the complex population genetics of individual loci in even relatively simple quantitative trait models, but provide a glimpse into the factors that drive this complexity and the potential of these approaches for understanding polygenic adaptation.\n\nAuthor summaryMany traits are controlled by a large number of genes, and environmental changes can lead to shifts in trait optima. How populations adapt to these shifts depends on a number of parameters including the genetic basis of the trait as well as population demography. We simulate a number of trait architectures and population histories to study the genetics of adaptation to distant trait optima. We find that selective sweeps occur even in traits under relatively weak selection and our machine learning analyses find that demography and the effect sizes of mutations have the largest influence on genetic variation after adaptation. Maize domestication is a well suited model for trait adaptation accompanied by demographic changes. We show how two example traits under a maize specific demography adapt to a distant optimum and demonstrate that polygenic adaptation is a well suited model for crop domestication even for traits with major effect loci.

evolutionary biology↗
bioRxiv2018

Fast and general-purpose linear mixed models for genome-wide genetics

Linear mixed effect models are powerful tools used to account for population structure in genome-wide association studies (GWASs) and estimate the genetic architecture of complex traits. However, fully-specified models are computationally demanding and common simplifications often lead to reduced power or biased inference. We describe Grid-LMM (https://github.com/deruncie/GridLMM), an extendable algorithm for repeatedly fitting complex linear models that account for multiple sources of heterogeneity, such as additive and non-additive genetic variance, spatial heterogeneity, and genotype-environment interactions. Grid-LMM can compute approximate (yet highly accurate) frequentist test statistics or Bayesian posterior summaries at a genome-wide scale in a fraction of the time compared to existing general-purpose methods. We apply Grid-LMM to two types of quantitative genetic analyses. The first is focused on accounting for spatial variability and non-additive genetic variance while scanning for QTL; and the second aims to identify gene expression traits affected by non-additive genetic variation. In both cases, modeling multiple sources of heterogeneity leads to new discoveries.\n\nAuthor summaryThe goal of quantitative genetics is to characterize the relationship between genetic variation and variation in quantitative traits such as height, productivity, or disease susceptibility. A statistical method known as the linear mixed effect model has been critical to the development of quantitative genetics. First applied to animal breeding, this model now forms the basis of a wide-range of modern genomic analyses including genome-wide associations, polygenic modeling, and genomic prediction. The same model is also widely used in ecology, evolutionary genetics, social sciences, and many other fields. Mixed models are frequently multi-faceted, which is necessary for accurately modeling data that is generated from complex experimental designs. However, most genomic applications use only the simplest form of linear mixed methods because the computational demands for model fitting can be too great. We develop a flexible approach for fitting linear mixed models to genome scale data that greatly reduces their computational burden and provides flexibility for users to choose the best statistical paradigm for their data analysis. We demonstrate improved accuracy for genetic association tests, increased power to discover causal genetic variants, and the ability to provide accurate summaries of model uncertainty using both simulated and real data examples.

genomics↗
bioRxiv2018

Gut microbiota composition explains more variance in the host cardiometabolic risk than genetic ancestry

BackgroundCardiometabolic affections greatly contribute to the global burden of disease. The susceptibility to these conditions associates with the ancestral genetic composition and gut microbiota. However, studies explicitly testing associations between genetic ancestry and gut microbes are rare. We examined whether the ancestral genetic composition was associated with gut microbiota, and split apart the effects of genetic and non-genetic factors on host health.\n\nResultsWe performed a cross-sectional study of 441 community-dwelling Colombian mestizos from five cities. We characterized the host genetic ancestry using 40 ancestry informative markers and gut microbiota through 16S rRNA gene sequencing. We measured variables related to cardiometabolic health (adiposity, blood chemistry and blood pressure), diet (calories, macronutrients and fiber) and lifestyle (physical activity, smoking and medicament consumption). The ancestral genetic composition of the studied population was 67{+/-}6% European, 21{+/-}5% Native American and 12{+/-}5% African. While we found limited evidence of associations between genetic ancestry and gut microbiota or disease risk, we observed a strong link between gut microbes and cardiometabolic health. Multivariable-adjusted linear models indicated that gut microbiota was more likely to explain variance in host health than genetic ancestry. Further, we identified 9 OTUs associated with increased disease risk and 11 with decreased risk.\n\nConclusionsGut microbiota seems to be more meaningful to explain cardiometabolic disease risk than genetic ancestry in this mestizo population. Our study suggests that novel ways to control cardiometabolic disease risk, through modulation of the gut microbial community, could be applied regardless of the genetic ancestry of the intervened population.

microbiology↗
bioRxiv2018

Population genomic analyses reveal a highly differentiated genetic cluster of northern goshawks (Accipiter gentilis laingi) in Haida Gwaii

Accurate knowledge of geographic ranges and genetic relationships among populations is important when managing a species or population of conservation concern. In the western Canadian province of British Columbia, a subspecies of the northern goshawk (Accipiter gentilis laingi) is designated as Threatened under the Canadian Species at Risk Act. Historically, the range of this bird of prey has been ambiguous and its genetic distinctness from the other North American subspecies (Accipiter gentilis atricapillus) has not been well established. Given the uncertainty in using morphological traits to assign individual goshawks to these two subspecies, we analyzed genomic relationships in tens of thousands of single nucleotide polymorphisms identified using genotyping-bysequencing of high-quality genetic samples. This genome-wide analysis revealed a genetically distinct population of northern goshawks on the archipelago of Haida Gwaii and subtle genetic structuring among the remainder of our sampling sites within North America. Following from this analysis, we developed targeted genotyping assays for ten loci that are highly differentiated between the two main genetic clusters, allowing the addition of hundreds of low-quality samples to our analysis. This additional information confirmed that the distinct genetic cluster on Haida Gwaii is restricted to that archipelago. As the laingi form was originally described as being based in Haida Gwaii, where the type specimen of that form is from, further study (especially of morphological traits) may indicate a need to restrict this name to the Haida Gwaii genetic cluster. Regardless of taxonomic treatment, our finding of a distinct Haida Gwaii genetic cluster along with the small and historically declining population size of the Haida Gwaii population suggests a high risk of extinction of an ecologically and genetically distinct form of northern goshawk. Outside of Haida Gwaii, sampling regions along the coast of BC and southeast Alaska (often considered regions inhabited by laingi) show some subtle differentiation from other North American regions. We anticipate that these results will increase the effectiveness of conservation management of northern goshawks in northwestern North America. More broadly, other conservation-related studies of genetic variation may benefit from the two-step approach we employed that first surveys genomic variation using high-quality samples and then genotypes low-quality samples at particularly informative loci.

genomics↗
bioRxiv2019

The role of genetic diversity in the evolution and maintenance of environmentally-cued, male alternative reproductive tactics

BackgroundAlternative reproductive tactics (ARTs) are taxonomically pervasive strategies adopted by individuals to maximize reproductive success within populations. Even for conditionally-dependent traits, consensus postulates most ARTs involve both genetic and environmental interactions (GEIs), but to date, quantifying genetic variation underlying the threshold disposing an individual to switch phenotypes in response to an environmental cue has been a difficult undertaking. Our study aims to investigate the origins and maintenance of ARTs within environmentally disparate populations of the microscopic bulb mite, Rhizoglyphus robini, that express fighter and scrambler male morphs mediated by a complex combination of environmental and genetic factors. ResultsUsing never-before-published individual genetic profiling, we found all individuals across populations are highly inbred with the exception of scrambler males in stressed environments. In fact within the poor environment, scrambler males and females showed no significant difference in genetic differentiation (Fst) compared to all other comparisons, and although fighters were highly divergent from the rest of the population in both poor or rich environments (e.g., Fst, STRUCTURE), fighters demonstrated approximately three times less genetic divergence from the population in poor environments. AMOVA analyses further corroborated significant genetic differentiation across subpopulations, between morphs and sexes, and among subpopulations within each environment. ConclusionOur study provides new insights into the origin of ARTs in the bulb mite, highlighting the importance of GEIs: genetic correlations, epistatic interactions, and sex-specific inbreeding depression across environmental stressors. Asymmetric reproductive output, coupled with the purging of highly inbred individuals during environmental oscillations, also facilitates genetic variation within populations, despite evidence for strong directional selection. This cryptic genetic variation also conceivably facilitates stable population persistence even in the face of spatially or temporally unstable environmental challenges. Ultimately, understanding the genetic context that maintains thresholds, even for conditionally-dependent ARTs, will enhance our understanding of within population variation and our ability to predict responses to selection.

evolutionary biology↗
bioRxiv2019

Limits to environmental masking of genetic quality in sexual signals

There is considerable debate over the value of male sexual ornaments as signals of genetic quality. Studies alternately report that environmental variation enhances or diminishes the genetic signal, or leads to crossover where genotypes perform well in one environment but poorly in another. A unified understanding is lacking. We conduct the first experimental test examining the dual effects of distinct low and high genetic quality (inbred versus crossed parental lines) and low, through high, to extreme environmental stress (larval diets) on a condition-dependent male ornament. We find that differences in genetic quality signalled by the ornament (male eyespan in Diasemopsis meigenii stalk-eyed flies) become visible and are amplified under high stress but are overwhelmed in extreme stress environments. Variance among distinct genetic lines increases with environmental stress in both genetic quality classes, but at a slower rate in high quality outcrossed flies. Individual genetic lines generally maintain their ranks across environments, except among high quality lines under low stress conditions, where low genetic variance precludes differentiation between ranks. Our results provide a conceptual advance, demonstrating a unified pattern for how genetic and environmental quality interact. They show when environmental conditions lead to the amplification of differences in signals of genetic quality and thereby enhance the potential indirect genetic benefits gained by female mate choice.

evolutionary biology↗
bioRxiv2019

Artificial selection on male size depletes genetic variance but not covariance of life history traits in the yellow dung fly

The evolutionary potential of organisms depends on the presence of sufficient genetic variation for traits subject to selection, as well as on the genetic covariances among them. While genetic variation ultimately derives from mutation, theory predicts the depletion of genetic (co)variation under consistent directional or stabilizing selection in natural populations. We estimated and compared additive genetic (co)variances for several standard life history traits, including some for which this has never been assessed, before and after 24 generations of artificial selection on male size in the yellow dung fly Scathophaga stercoraria (Diptera: Scathophagidae) using a series of standard half-sib breeding experiments. As predicted, genetic variances (VA), heritabilities (h2) and evolvabilities (IA) of body size, development time, first clutch size, and female age at first clutch were lower after selection. As independent selection lines were crossed prior to testing, we can rule out that this reduction is due to genetic drift. In contrast to the variances, and against expectation, the additive genetic correlations between the sexes for development time and body size remained strong and positive (rA = 0.8-0.9), while the genetic correlation between these traits within the sexes tended to strengthen (but not significantly so). Our study documents that the effect of selection on genetic variance is predictable, whereas that on genetic correlations is not.

evolutionary biology↗
bioRxiv2025

Causal modelling reveals lower coral genetic diversity in more heterogenous reef environments

Conserving genetic diversity is crucial for maintaining species evolutionary potential and resilience to environmental change. Yet, directly measuring genetic diversity across large spatial scales remains resource-intensive and impractical for conservation planning. Identifying reliable, accessible, and cost-effective spatial predictors of genetic diversity would significantly enhance our ability to incorporate genetic diversity into conservation efforts. Caribbean coral reefs represent a compelling system for investigating such predictors, as these ecosystems face unprecedented threats from disease outbreaks and climate change. Here, we investigate the utility of several environmental proxies as surrogates for genetic diversity, which may be useful for conservation planning in resource- or data-poor regions. To achieve this goal, we used reduced-representation genomic sequencing to estimate intraspecific genetic diversity, and in doing so, identified two genetically distinct and sympatric cryptic coral species in the Agaricia tenuifolia species complex. We employed a causal inference approach to assess the relationships between genetic alpha diversity and habitat area and connectivity, habitat heterogeneity, and temperature. Statistical investigations revealed that increased habitat heterogeneity, derived from remotely sensed habitat maps, was associated with lower genetic diversity within coral populations, suggesting that habitat characteristics promoting species diversity may not maintain high genetic diversity within a single species. Habitat area and connectivity, and temperature have predominantly negative effects on genetic diversity with coral habitat area and connectivity showing markedly contrasting responses in two cryptic taxa. Thus, our findings reveal that context matters greatly, as results differ between cryptic species, across variables, and among spatial scales.

evolutionary biology↗
bioRxiv2025

Genetic Diversity and Phylogenetic Relationships of Cultivated and Wild Urochloa Species Conserved in the ILRI Forage Genebank

Understanding the genetic diversity and evolutionary relationships within the genus Urochloa is essential for effective germplasm conservation and the development of improved forage cultivars. In this study, we assessed the genetic diversity, population structure, and phylogenetic relationships of 545 accessions representing 17 Urochloa species conserved in the ILRI Forage Genebank for the last four decades at its Zway field site in Ethiopia. Large numbers of genome-wide SNP and SilicoDArT markers were generated by the GBS based Diversity Arrays Technology (DArT)seq platform, providing valuable resources for genetic analysis in Urochloa spp. From these, we filtered a subset of high-quality SNP and SilicoDArT markers suitable for cross-species analysis, which was then used to characterize species differentiation and to detect admixture patterns across wild and cultivated species. Hierarchical clustering grouped all 545 accessions into two major groups, clearly separating the brizantha complex (U. brizantha, U. decumbens, and U. ruziziensis) from the rest of the species, which were primarily wild and less domesticated relatives. The analysis further identified four well-defined phylogenetic clades, largely consistent with previously reported evolutionary relationships within the genus. The three clades, primarily composed of wild species, exhibited clear genetic separation, high diversity, and strong geographic structuring with limited admixture, reflecting reproductive isolation (their apomictic nature) and differing ploidy levels that have driven local adaptation. In contrast, the brizantha complex exhibited extensive admixture and comparatively lower genetic variation, consistent with their historical polyploidization events, shared ancestry, and domestication (particularly in the key forage species U. brizantha and U. decumbens). Population structure analysis using the admixture model revealed multiple genetically distinct clusters and populations across clades, including species-specific clusters, mixed-species groups, and within-species populations, highlighting substantial genetic variation within and among species shaped by historical gene flow (particularly among diploid and sexual types), differences in ploidy levels, and adaptive divergence. The identification of genetically differentiated populations in wild species underscores their potential as reservoirs of unique adaptive traits such as drought tolerance, waterlogging and disease resistances, and nutrient-use efficiency. Meanwhile, the genetically diverse cultivated gene pool provides valuable resources for improving biomass productivity, nutritional quality, and resilience to environmental stress. Our findings provide a comprehensive genetic overview of one of the most important tropical forage genera and offer strategic insights for the conservation and utilization of Urochloa genetic resources.

plant biology↗
bioRxiv2026

Use of SNPs in a low diversity system for genetic monitoring and identifying a successful translocation event in the Paiute Cutthroat Trout (O. henshawi seleniris)

ObjectiveMaintaining genetic diversity in small, isolated populations is a key goal in conservation genetics. Genetic monitoring can guide management decisions, but comparisons across studies and time points are often complicated by differences in genetic markers and data sets. We aimed to develop a consistent, replicable set of genetic markers to support long-term monitoring of Paiute Cutthroat Trout (Oncorhynchus henshawi seleniris), a federally threatened subspecies persisting in a network of isolated refuge populations in California, USA. MethodsWe used RAD (Restriction site-associated DNA) sequencing to identify single nucleotide polymorphisms (SNPs) from 476 individuals representing eight extant refuge populations. Filtering steps included the removal of paralogous loci and exclusion of FST outliers associated with sequencing batch effects. We selected a panel of 1,114 SNPs that were shared across all populations and validated the panel in silico by comparing population structure and genetic diversity estimates to those derived from the full RAD sequencing dataset. ResultsThe candidate panel SNPs captured key patterns of genetic differentiation and diversity consistent with previous studies and the larger RAD dataset. We present updated baseline genetic metrics for each refuge population, providing a consistent reference point for future monitoring efforts. We also demonstrate the ability of our candidate panel SNPs to detect successful spawning after a translocation event. ConclusionThis study provides a set of SNPs tailored for monitoring genetic diversity and structure in Paiute Cutthroat Trout refuge populations. Future work should include development of a high-throughput genotyping assay to implement these candidate panel SNPs for ongoing management. This would enable consistency over time with genetic studies and be a foundational tool for repeated evaluation of conservation actions such as reintroductions and augmentations. Lay SummaryWe identified genetic markers to help track and protect one of the rarest trout in the United States. This work supports long-term conservation by making it easier to monitor isolated populations and measure the success of efforts to restore the species.

genomics↗