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bioRxiv2024

Inbreeding and gallbladder cancer risk: Homozygosity associations adjusted for indigenous American ancestry, BMI and genetic risk of gallstone disease

Latin Americans have a rich genetic make-up that translates into heterogeneous fractions of the autosomal genome in runs of homozygosity (FROH), and heterogeneous types and proportions of indigenous American ancestry. While autozygosity has been linked to several human diseases, very little is known about the relationship between inbreeding, genetic ancestry and cancer risk in Latin Americans. Chile has one of the highest incidences of gallbladder cancer (GBC) in the world, and here we investigated the association between inbreeding, GBC, gallstone disease (GSD) and body mass index (BMI) in 4029 genetically admixed Chileans. We calculated individual FROH above 1.5 Mb and weighted polygenic risk scores for GSD, and applied multiple logistic regression to assess the association between homozygosity and GBC risk. We found that homozygosity was due to a heterogeneous mixture of genetic drift and consanguinity in the study population. Although we found no association between homozygosity and overall GBC risk, we detected interactions between FROH and sex, age, and genetic risk of GSD on GBC risk. Specifically, the increase in GBC risk per 1% FROH was 19% in men (P-value = 0.002), 30% in those under 60 years of age (P-value = 0.001), and 12% in those with a genetic risk of GSD above the median (P-value = 0.01). The present study highlights the complex interplay between inbreeding, genetic ancestry and genetic risk of GSD in the development of GBC. The applied methodology and our findings underscore the importance of considering the population-specific genetic architecture, along with sex- and age specific-effects, when investigating the genetic basis of complex traits in Latin Americans.

genetics↗

bioRxiv2024

Steep logarithmic increase of genetic variation in natural Arabidopsis thaliana accessions across geographic scales

Arabidopsis thalianas large native range across Eurasia and display of considerable genetic variation is key to its increasing use in eco-evolutionary studies. The structure and amount of this genetic variation has been studied on various geographic scales. On a continental scale, the genetic variation was postulated to follow an isolation by distance model, implying less genetic variation at smaller geographic distances. However, recent studies showed that the genetic variation is already high on small geographic scales, yet direct comparisons of the genetic variation across different geographic scales are rare. Here, we present a new local diversity panel covering 19 km2 with accessions of the Veluwe, the Netherlands. We compared the genetic variation of this local diversity panel to a national and a continental A. thaliana diversity panel. Direct comparison of these three geographic scales showed that local accessions harbour already 41.8% of the genetic variation found on a continental scale despite the substantial difference in geographic surface area covered. Moreover, a rapidly ascending logarithmic relationship between genetic and geographic distances was observed at continental, national and local scale and thus irrespective of the geographic scale considered. The high level of local genetic variation reported here poses new questions on which evolutionary forces are driving and maintaining this, and how much this constrains experimental design when using local A. thaliana populations in future eco-evolutionary studies.

genetics↗

bioRxiv2024

A novel expectation-maximization approach to infer general diploid selection from time-series genetic data

Detecting and quantifying the strength of selection is a main objective in population genetics. Since selection acts over multiple generations, many approaches have been developed to detect and quantify selection using genetic data sampled at multiple points in time. Such time series genetic data is commonly analyzed using Hidden Markov Models, but in most cases, under the assumption of additive selection. However, many examples of genetic variation exhibiting non-additive mechanisms exist, making it critical to develop methods that can characterize selection in more general scenarios. Here, we extend a previously introduced expectation-maximization algorithm for the inference of additive selection coefficients to the case of general diploid selection, in which the heterozygote and homozygote fitness are parameterized independently. We furthermore introduce a framework to identify bespoke modes of diploid selection from given data, a heuristic to account for variable population size, and a procedure for aggregating data across linked loci to increase power and robustness. Using extensive simulation studies, we find that our method accurately and efficiently estimates selection coefficients for different modes of diploid selection across a wide range of scenarios; however, power to classify the mode of selection is low unless selection is very strong. We apply our method to ancient DNA samples from Great Britain in the last 4,450 years, and detect evidence for selection in six genomic regions, including the well-characterized LCT locus. Our work is the first genome-wide scan characterizing signals of general diploid selection. Author SummaryNatural selection increases the likelihood that beneficial genetic variants are passed from parent to offspring and thus forms the basis of genetic adaptation to novel environments. Genomic data sampled at multiple timepoints, such as genetic material extracted from ancient remains (ancient DNA) or data from evolve and resequence experiments, can enable more precise identification of genetic variants subject to selective pressure than contemporary samples alone. However, most methods for identifying genetic variation under selection focus on additive selection, where the fitness of the heterozygote is exactly intermediate between the homozygotes. Leveraging genetic data at multiple timepoints, we develop a method to detect additive and non-additive selection as well as to infer the most likely dominance mechanism. We apply our methods to a dataset of ancient DNA from Great Britain dated less than 4,450 years before present and identify six regions with signals of recent selection, including one at the TFR2 locus that has not been previously reported as a target of selection. Our work enables more accurate quantification of non-additive selection dynamics and can be used to test more complex models of selection.

genetics↗

bioRxiv2024

Optimising future rhino population management strategies using insights from genetic health assessments across India

Various species conservation paradigms are facing enormous challenges during the ongoing Anthropocene. While the widely-used reintroduction/translocation-based approaches have supported many endangered species population recoveries, they seldom use detailed genetic information during initial planning. The Indian greater one-horned rhino typifies such assisted migration-driven species recovery, but currently facing long-term survival concerns due to their mostly small, isolated populations reaching respective carrying capacities. We assessed nation-wide rhino genetic health, identified suitable source populations and provided future translocation scenarios for all extant and proposed rhino habitats. Analyses with 504 unique rhino genotypes across all seven Indian rhino-bearing parks revealed six genetically-isolated populations with overall moderately low genetic diversity. Our results showed that Kaziranga and Manas NPs (Assam) to have the best rhino genetic health, whereas Jaldapara and Gorumara NPs (West Bengal) undergoing strong genetic erosions. Forward genetic simulations suggested that annual supplementation efforts from only few Assam rhino populations (Kaziranga NP, Orang NP and Pobitora WLS) are best suited for genetic rescue of most of the extant populations. Overall, the genetic diversity and differentiation patterns mimics the complex evolutionary history and individual recovery histories. We suggest park-specific management solutions (ranging from protection measures, grassland restoration, livestock and conflict management, regular supplementation events etc.) to ensure the species long-term persistence and prevent the alarming loss of grassland habitats and its associate biodiversity. We insist on utilising such genetic health indices-driven population management solutions to identify targeted mitigative measures in other species.

genetics↗

bioRxiv2025

Genetic Insights of Image-Based Traits: Analysis Pipeline for AI-based Phenotyping, Combined-GWAS, and Federated Learning with Application to the Human Face

Biological images capture rich morphological information and understanding their genetic basis is crucial for elucidating underlying molecular mechanisms, relevant in biomedical, evolutionary, and forensic research and applications. However, progress in understanding the genetic basis of image-based complex traits is hindered by key limitations in the current methodology, regarding both, the degree of which the large image complexity is captured with the phenotyping methods and how the analysis methods deal with the underlying large genetic complexity. Here, we present a robust, scalable, privacy-preserving computer pipeline for analysing image-based complex traits and unveiling their genetic basis by integrating (i) AI-based phenotyping for large-scale extraction of image-based traits across cohorts in a federated learning framework, without sharing individual images; (ii) Combined-GWAS (C-GWAS) for identifying genetic variants underlying the numerous AI-derived image-based traits; and (iii) Explainable AI (XAI)-based image visualization of the identified genetic association effects. In its first application to the example of the human face, we analysed 3D facial images and genomic data from two European cohorts (N=7,309), extracted 200 AI-derived facial traits, identified 43 significantly face associated genetic loci, including 12 novel ones, and replicated 70% of them in an independent European dataset (N=8,246). XAI-based visualization of the identified genetic effects shows the involvement of many of these loci in different parts of the face. Our study provides a privacy-aware and extensible pipeline for investigating the genetic basis of image-based complex traits implemented in a computationally efficient python package available at GitLab and its first application yielded new insights into the genetic architecture of facial shape variation.

genetics↗

bioRxiv2025

Back to the future 2: the implications of germplasm structure on thebalance between short and long-term genetic gain in a changingtarget population of environments

Plant breeding operates within a highly complex genetic landscape determined by gene effects emerging through biological networks and their interactions with the environment. This environment is not constant but subject to short-term fluctuations and long-term shifts. This significantly complicates the task of plant breeders in finding a balance between adapting their germplasm for the short- and long-term. Here we build on previous work of us that investigated the implications of genetic complexity on breeding program design, by adding an environmental dimension in the form of the E(NK) model to the simulation framework. We found that the addition of environmental interactivity and change creates greater uncertainty associated with pursuing any specific selection trajectory, as compared to a static environment. This advantages preserving genetic variability and genetic landscape exploration over quickly exposing additive variation by constraining genetic space around a particular and temporary local optimum. Nonetheless, we found that also in a dynamically changing environment, a structure in which several breeding programs explore genetic space while maintaining constant germplasm exchange, finds the best balance between short and long-term objectives, as opposed to isolated programs or one large undifferentiated program, which exclusively emphasize short respectively long-term objectives. We furthermore highlight the difficulty of exchanging germplasm to restore genetic variability with non-stationary and germplasm context dependent genetic effects. In summary we found that also with addition of environmental complexity and change, the structural features that characterized breeding operations hitherto and allowed them to navigating biological complexity apply. Namely the necessity to constraining genetic space in order for heritable additive variation to emerge. We end by arguing that optimal breeding program design depends on the level of genetic and environmental complexity, which should be appropriately reflected when modeling the long-term behavior of selection programs and the implications of specific interventions into these.

genetics↗

bioRxiv2018

Genetic analyses in UK Biobank identifies 78 novel loci associated with urinary biomarkers providing new insights into the biology of kidney function and chronic disease

BackgroundUrine biomarkers, such as creatinine, microalbumin, potassium and sodium are strongly associated with several common diseases including chronic kidney disease, cardiovascular disease and diabetes mellitus. Knowledge about the genetic determinants of the levels of these biomarker may shed light on pathophysiological mechanisms underlying the development of these diseases.\n\nMethodsWe performed genome-wide association studies of urinary levels of creatinine, microalbumin, potassium, and sodium in up to 326,441 unrelated individuals of European ancestry from the UK Biobank, a large population-based cohort study of over 500,000 individuals recruited across the United Kingdom in 2006-2010. Further, we explored genetic correlations, tissue-specific gene expression and possible causal genes related to these biomarkers.\n\nResultsWe identified 23 genome-wide significant independent loci associated with creatinine, 20 for microalbumin, 12 for potassium, and 38 for sodium. We confirmed several established associations including between the CUBN locus and microalbumin (rs141640975, p=3.11e-68). Variants associated with the levels of urinary creatinine, potassium, and sodium mapped to loci previously associated with obesity (GIPR, rs1800437, p=9.81e-10), caffeine metabolism (CYP1A1, rs2472297, p=1.61e-8) and triglycerides (GCKR, rs1260326, p=4.37e-16), respectively. We detected high pairwise genetic correlation between the levels of four urinary biomarkers, and significant genetic correlation between their levels and several anthropometric, cardiovascular, glycemic, lipid and kidney traits. We highlight GATM as causally implicated in the genetic control of urine creatinine, and GIPR, a potential diabetes drug target, as a plausible causal gene involved in regulation of urine creatinine and sodium.\n\nConclusionWe report 78 novel genome-wide significant associations with urinary levels of creatinine, microalbumin, potassium and sodium in the UK Biobank, confirming several previously established associations and providing new insights into the genetic basis of these traits and their connection to chronic diseases.\n\nAuthor SummaryUrine biomarkers, such as creatinine, microalbumin, potassium and sodium are strongly associated with several common diseases including chronic kidney disease, cardiovascular disease and diabetes mellitus. Knowledge about the genetic determinants of the levels of these biomarker may shed light on pathophysiological mechanisms underlying the development of these diseases. Here, we performed genome-wide association studies of urinary levels of creatinine, microalbumin, potassium and sodium in up to 326,441 unrelated individuals of European ancestry from the UK Biobank. Further, we explored genetic correlations, tissue-specific gene expression and possible causal genes related to these biomarkers. We identified 78 novel genome-wide significant associations with urinary biomarkers, confirming several previously established associations and providing new insights into the genetic basis of these traits and their connection to chronic diseases. Further, we highlight GATM as causally implicated in the genetic control of urine creatinine, and GIPR, a potential diabetes drug target, as a plausible causal gene involved in regulation of urine creatinine and sodium. The knowledge arising from our work may improve the predictive utility of the respective biomarker and point to new therapeutic strategies to prevent common diseases.

genetics↗

bioRxiv2018

Genetic correlations between pain phenotypes and depression and neuroticism

Correlations between pain phenotypes and psychiatric traits such as depression and the personality trait of neuroticism are not fully understood. The purpose of this study was to identify whether eight pain phenotypes, depressive symptoms, major depressive disorders, and neuroticism are correlated for genetic reasons. Eight pain phenotypes were defined by a specific pain-related question in the UK Biobank questionnaire. First we generated genome-wide association summary statistics on each pain phenotype, and estimated the common SNP-based heritability of each trait using GCTA. We then estimated the genetic correlation of each pain phenotype with depressive symptoms, major depressive disorders and neuroticism using the the cross-trait linkage disequilibrium score regression (LDSC) method integrated in the LD Hub. Third, we used the LDSC software to calculate genetic correlations among pain phenotypes. All pain phenotypes were heritable, with pain all over the body showing the highest heritability (h2=0.31, standard error=0.072). All pain phenotypes, except hip pain and knee pain, had significant and positive genetic correlations with depressive symptoms, major depressive disorders and neuroticism. The largest genetic correlations occurred between neuroticism and stomach or abdominal pain (rg=0.70, P=2.4 x 10-9). In contrast, hip pain and knee pain showed weaker evidence of shared genetic architecture with these negative emotional traits. In addition, many pain phenotypes had positive and significant genetic correlations with each other indicating shared genetic mechanisms. Pain at a variety of body sites is heritable and genetically correlated with depression and neuroticism. This suggests that pain, neuroticism and depression share partially overlapping genetic risk factors.

genetics↗

bioRxiv2019

Genome-wide Association study of facial morphology identifies novel genetic loci in Han Chinese

Human face is a heritable surface with many complex sensory organs. In recent years, many genetic loci associated with facial features have been reported in different populations, yet there is a lack for the Han Chinese population. We report a genome-wide association analysis of 3D normal human faces in 2659 Han Chinese with two groups of phenotypes, the partial and whole face phenotypes and the distance and angle phenotypes. We found significant signals in five genomic regions with traits related to nose or eyes, including rs970797 in 2q31.1 near HOXD1 and MTX2, rs16897517 in 8q22.2 at intron of VPS13B, rs9995821 in 4q31.3 near DCHS2 and SFRP2, rs12636297 in 3q23 near PISRT1, and rs12948076 in 17q24.3 near SOX9 and CASC17. We visualized changes in facial morphology by comparing the volume of local areas and observed that these nose-related loci were associated with different features of the nose, including nose prominence, nasion height, and nostril shape, suggesting that the nose underlies precise genetic regulation. These results provide a more comprehensive understanding of the relationship between genetic loci and human facial morphology.\n\nAuthor SummaryHuman face as a combination of delicate sensory organs has a strong genetic component, as evidenced by the identical appearance in twins and shared facial features in close relatives. Although facial genetics have been studied in different populations, our knowledge between genetic markers with facial features is still limited. In this paper, we found genetic variants associated with nose and eyes through a large-scale high-resolution 3D facial genetic study on the Han Chinese population. We observed that these nose-related loci were associated with different features of the nose, including nose prominence, nasion height, and nostril shape, which suggests the nose underlies precise genetic regulation. Intriguingly, we noted that genes (DCHS2 and SFRP2) related to one of these loci are differentially expressed in human and chimp cranial neural crest cells, which plays a crucial role in the early formation of facial morphology. The ongoing genetic studies of facial morphology will improve our understanding of human craniofacial development, and provide potential evolution evidence of human facial features.

genetics↗

bioRxiv2019

Alternate approach to stroke phenotyping identifies a genetic risk locus for small vessel stroke

Stroke causes approximately 1 in every 20 deaths in the United States. Most strokes are ischemic, caused by a blockage of blood flow to the brain. While neurologists agree on the delineation of ischemic stroke (IS) into the three most common subtypes (cardioembolic stroke (CES), large artery stroke (LAS), and small vessel stroke (SVS)), several different subtyping systems exist. The two most commonly-used clinical subtyping systems are TOAST (Trial of Org 10172 in Acute Stroke Treatment) and CCS (Causative Classification System for Stroke), but agreement between these two systems is only moderate. Here, we have compared two approaches to combining the existing subtyping systems for a phenotype suited for a genome-wide association study (GWAS).\n\nWe used the NINDS Stroke Genetics Network dataset (SiGN, 13,390 cases and 28,026 controls), which includes cases with both CCS and TOAST subtypes. We defined two new phenotypes: 1) the intersect, for which an individual must be assigned the same subtype by CCS and TOAST; and 2) the union, for which an individual must be assigned a subtype by either CCS or TOAST. The union yields the largest sample size while the intersect may yield a phenotype with less potential misclassification.\n\nWe performed GWAS for all subtypes, using the original subtyping systems, the intersect, and the union as phenotypes. In each subtype, heritability was higher for the intersect phenotype compared to the union, CCS (alone), and TOAST (alone) phenotypes. We observed stronger effects at known IS variants with the intersect compared to the other phenotype definitions. In GWAS of the intersect, we identify rs10029218 as an associated variant with small vessel stroke. We conclude that in the absence of a golden standard for phenotyping, taking this alternate approach yields more power to detect genetic associations in ischemic stroke.\n\nAuthor summaryAround one in five people will have a stroke at some point in their life. Most strokes (~80%) are ischemic, caused by a blockage of blood supply to the brain. Ischemic stroke risk is partly influenced by lifestyle, and partly by genetics. There are different ischemic stroke subtypes, and genome-wide association studies (GWAS) indicate that the genetic risk for these subtypes is influenced by different genetic factors. Genetic studies of ischemic stroke are therefore typically performed by analyzing each subtype separately. There are several methods to determine someones subtype based on clinical features. To find more genetic factors that influence ischemic stroke risk, we aimed to find a group of patients that are phenotypically similar by using information from all subtyping methods. We compared a group of patients assigned the same subtype by all subtyping methods (the intersect) to a group of patients assigned that subtype by at least one subtyping method (the union). Even though the intersect sample size is smaller, we find genetic factors in the intersect GWAS have stronger genetic effects, likely explained by the fact that we are more certain of the subtype in the intersect. Using the intersect, we find new risk-associated genetic factors.

genetics↗

bioRxiv2019

The genetic landscape of Ethiopia: diversity, intermixing and the association with culture

The rich linguistic, ethnic and cultural diversity of Ethiopia provides an unprecedented opportunity to understand the level to which cultural factors correlate with -- and shape -- genetic structure in human populations. Using primarily novel genetic variation data covering 1,214 Ethiopians representing 68 different ethnic groups, together with information on individuals birthplaces, linguistic/religious practices and 31 cultural practices, we disentangle the effects of geographic distance, elevation, and social factors upon shaping the genetic structure of Ethiopians today. We provide evidence of associations between social behaviours and increased genetic differences among present-day peoples. We show that genetic similarity is broadly associated with linguistic classifications, but indicate pronounced genetic similarity among groups from disparate language classifications that may in part be attributable to recent intermixing. We also illustrate how groups reporting the same culture traits are more genetically similar on average and show evidence of recent intermixing, suggesting how shared cultural traits may promote admixture. In addition to providing insights into the genetic structure and history of Ethiopia, these results identify the most important cultural and geographic proxies for genetic differentiation and provide a resource for designing sampling protocols for future genetic studies involving Ethiopians.

genetics↗

bioRxiv2019

Subthreshold psychosis symptoms associated with molecular genetic risk in a population-based cohort: Findings from Generation Scotland

ImportanceSubthreshold psychosis symptoms in the general population may be associated with genetic risk for schizophrenia. In this analysis, empirically-derived symptom factor scores led to a detection of significant and robust polygenic signal.\n\nObjectiveThis study sought to optimize genetic association with data-driven symptom factor scores, accounting for cohort factor structure and sex differences.\n\nDesignEFA-derived symptom factor scores were regressed onto PRS for schizophrenia in models accounting for age and genetic ancestry principal components. Follow-up examination of symptom factor score associations with other related genetic risks included ADHD, autism, bipolar disorder, major depression, and neuroticism.\n\nParticipantsThis study examined the newly expanded symptom dataset from the Northern European ancestry cohort, Generation Scotland: Scottish Family Health Study (N = 9,105 individuals 18-65 years of age) comprising common variant and subthreshold psychosis symptom data. A total of 5,391 females and 3,713 males with age M[SD] = 45.2 [13] were included in the final analyses.\n\nMain Outcome and MeasureSubthreshold psychosis symptoms were measured using the Schizotypal Personality Questionnaire-Brief (SPQ-B). Primary phenotypic factor scores and genome-wide polygenic risk scores (PRS) reflected weighted sum scores and were examined as continuous measures. Polygenic risk scores were calculated from genome-wide association summary statistics using 7,358,674 imputed common genetic variants passing quality control.\n\nResultsIn males, symptom factor scores were positively associated with polygenic risk for schizophrenia alone and implicated primarily interpersonal/negative symptoms. In females, symptom factor scores were positively associated with polygenic risks for ADHD and autism but not schizophrenia. Scores were robustly associated with genetic risk for neuroticism across both males and females.\n\nConclusions and RelevanceThis study detected a significant association of subthreshold psychosis symptoms with genetic risk for schizophrenia and neuroticism in a population-based sample. Furthermore, important sex differences suggest a need for better understanding of schizophrenia risk assessment in females.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat molecular genetic risks are associated with subthreshold psychosis symptoms in the general population?\n\nFindingsIn a large population-based cohort (N = 9,084), significant associations of polygenic risks with symptoms were observed. Symptoms were associated with genetic risk for schizophrenia in males, for ADHD and autism spectrum disorder in females, and for neuroticism across both males and females.\n\nMeaningAssociations of genetic risk with symptoms in the general population are highly significant and suggest important sex differences.

genetics↗

bioRxiv2026

A Bayesian multidimensional approach to decipher the genetic basis of dynamic phenotypes in multiple species

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.

genetics↗

bioRxiv2026

Long-term realized genetic gain and population dynamics under genomic selection in Brazilian cassava germplasm

Genomic selection has become an important strategy in cassava breeding, enabling faster selection cycles and sustained genetic progress. Despite its widespread adoption, long-term evaluations integrating predictive performance, realized genetic gain, and genetic diversity remain scarce, particularly in clonally propagated crops. We present a comprehensive assessment of genomic selection outcomes in the Brazilian cassava breeding program across four recurrent selection cycles (C0 to C3) implemented between 2011 and 2024, using historical phenotypic and genomic data from 210 multi-environment trials. Predictive ability of genomic best linear unbiased prediction models ranged from low to moderate, depending on the traits genetic architecture and heritability. Prediction accuracies were highest in early cycles (C0 and C1) and showed modest declines in later cycles (C2 and C3). Root yield, shoot yield, plant height, starch content, and dry matter content exhibited stable predictive performance across cycles, with a gradual reduction in RMSE, indicating improved model calibration as training populations expanded. Regression analyses of genomic estimated breeding values revealed significant realized genetic gains for most yield-related traits. In contrast, dry matter content and starch content exhibited small, non-significant negative trends, consistent with known unfavorable genetic correlations with yield. Targeted reductions in plant architecture scores reflected deliberate selection for ideotypes suited to mechanized production systems. At the same time, analyses of genetic diversity revealed a slight decrease in observed heterozygosity, with higher values in the most advanced selection cycle. These results provide an integrated framework for monitoring predictive performance, realized genetic gain, and population genetic dynamics under long-term genomic selection. Collectively, they offer valuable insights into balancing short-term genetic improvement with long-term sustainability and support the development of strategies to optimize selection decisions, breeding planning, and population management in Brazilian cassava breeding programs.

genetics↗

bioRxiv2026

Genetic diversity within and between polyploid sugarcane (Saccharum spp.) families obtained via caryopsis using microsatellite markers and multicategory model

Genetic diversity analyses are essential for sugarcane (Saccharum spp.) breeding programs. Crossbreeding, based on genetic distances between parental plants, is a tool used to increase genetic variability and enhance plant selection; however, quantifying variation in highly polyploid species remains a challenge. The present study aimed to evaluate the diversity within and between 12 families of sugarcane derived from caryopses, analyzing 120 individual seedlings arranged in an augmented block design. Genotyping was performed using primers for 16 microsatellite loci, five simple sequence repeat (SSR) loci, and 11 expressed sequence tag-SSR (EST-SSR) loci. To accurately account for polyploidy, similarity calculations were performed using Bruvos distances among individuals and RST distances among the families. Analysis of molecular variance (AMOVA) indicated that most of the genetic variability was within families (72%), with only 28% found between them. This high level of intra-family variation demonstrates that a significant reservoir of genetic diversity remains available within the crosses. The highest genetic similarity was observed between the families RB986952 x RB986960 and RB036122 x RB03611, whereas the lowest genetic similarity was observed between the families RB97319 x RB966928 and RB106802 x RB855036. Although the evaluated families shared high genetic similarity, the pronounced genetic variation within them demonstrates a robust recombination potential, indicating that the genetic basis of sugarcane can be better explored using the high variability that already exists in the selection of desirable morpho-agronomic characteristics within the families. Furthermore, this study highlights the importance of using appropriate distances for diversity studies with codominant markers, such as microsatellites, in polyploid species.

genetics↗

bioRxiv2026

Phantom genetic nurture: assortative mating accounts for most of the apparent association between parental genotypes and childhood cognitive performance

Parental genotypes may influence offspring outcomes through the environments parents provide, a process known as genetic nurture, but estimating such effects from polygenic scores is complicated jointly by measurement error, unobserved genetic variation, and assortative mating. Here, we introduce RAVEL, a structural equation modeling framework that uses two independently constructed polygenic scores for the same trait to estimate latent genetic liability associations in parent-offspring trios and to distinguish direct and non-transmitted genetic associations. Through analytic derivations and simulations, we show that naive trio regressions can produce spurious non-zero parental coefficients, attenuate genuine genetic nurture effects, and obscure asymmetric parental effects, whereas RAVEL recovers unbiased estimates of the underlying coefficients when the assortative mating history and the extent of unobserved genetic variation are correctly specified. Applying RAVEL to national test scores in the Norwegian Mother, Father and Child Cohort Study using polygenic scores for educational attainment, we find that parental genetic liabilities explain less than 0.5% as much variance in childhood cognitive performance as the child's own genetic liability (substantially lower than the 10% observed with naive trio regressions) once assortative mating is modeled, with only a small paternal association significantly surviving the correction. In contrast, we find a maternal-specific non-transmitted association with offspring premature birth. RAVEL provides a general framework for interpreting trio polygenic score analyses of direct and non-transmitted genetic effects, clarifying the contribution of parental genetic liabilities to offspring traits.

genetics↗

bioRxiv2015

When three traits make a line: Evolution of phenotypic plasticity and genetic assimilation through linear reaction norms in stochastic environments

Genetic assimilation results from selection on phenotypic plasticity, but quantitative genetics models of linear reaction norms considering intercept and slope as traits do not fully incorporate the process of genetic assimilation. We argue that intercept-slope reaction norm models are insufficient representations of genetic effects on linear reaction norms, and that considering reaction norm intercept as a trait is unfortunate because the definition of this trait relates to a specific environmental value (zero) and confounds genetic effects on reaction norm elevation with genetic effects on environmental perception. Instead we suggest a model with three traits representing genetic effects that respectively (i) are independent of the environment, (ii) alter the sensitivity of the phenotype to the environment, and (iii) determine how the organism perceives the environment. The model predicts that, given sufficient additive genetic variation in environmental perception, the environmental value at which reaction norms tend to cross will respond rapidly to selection after an abrupt environmental change, and eventually become equal to the new mean environment. This readjustment of the zone of canalization becomes completed without changes in genetic correlations, genetic drift or imposing any fitness costs on maintaining plasticity. The asymptotic evolutionary outcome of this three-trait linear reaction norm generally entails a lower degree of phenotypic plasticity than the two-trait model, and maximum expected fitness does not occur at the mean trait values in the population.

Evolutionary Biology↗

bioRxiv2016

No evidence for the positive relationship between genetic correlations and heritabilities

Quantitative genetics predicts, that traits subjected to strong selection should show low heritability and may yield biased estimates of genetic correlations (rg). Similar pattern may also appear if genetic sources of variation are confounded with non-genetic sources. Thus, a positive relationship between genetic correlations and heritabilities (h2) of underlying traits might be observed. Here we test this prediction using a large dataset of published estimates of genetic correlations and employing a powerful meta-analytical approach. We considered both between-traits and cross-sex genetic correlations. We failed to find support for the prediction about a positive rg - h2 relationship: our analysis based on nearly 1000 published estimates of genetic parameters indicates that the predicted relationship is weak and statistically non-significant. Thus, low heritability does not preclude the possibility of detecting substantial genetic correlations. Our meta-analysis indicates that published estimates of genetic parameters coming from various experimental designs and obtained using different statistical techniques are not significantly biased in case of weakly-heritable traits.

Evolutionary Biology↗