Genetic Architecture Research Articles

Exploring Meiotic Recombination and Its Potential Benefits in South African Beef Cattle: A Review

Meiotic recombination is a key evolutionary process that generates novel allele combinations during prophase I of meiosis, promoting genetic diversity and enabling the selection of desirable traits in livestock breeding. Although its molecular mechanisms are well-characterised in model organisms such as humans and mice, studies in African indigenous cattle, particularly South African breeds, remain scarce. Key regulators of recombination, including PRDM9, SPO11, and DMC1, play essential roles in crossover formation and genome stability, with mutations in these genes often linked to fertility defects. Despite the Bonsmara and Nguni breeds’ exceptional adaptability to arid and resource-limited environments, little is known about how recombination contributes to their unique genetic architecture and adaptive traits. This review synthesises the current knowledge on the molecular basis of meiotic recombination, with a focus on prophase I events and associated structural proteins and enzymes. It also highlights the utility of genome-wide tools, particularly high-density single nucleotide polymorphism (SNP) markers for recombination mapping. By focusing on the underexplored recombination landscape in South African beef cattle, this review identifies key knowledge gaps. It outlines how recombination studies can inform breeding strategies aimed at enhancing genetic improvement, conservation, and the long-term sustainability of local beef production systems.

Branched-chain amino acids and risk of major depressive disorder: a Mendelian randomization and colocalization study.

Depression is associated with numerous metabolic pathway abnormalities, and several studies have suggested a link between depression and branched chain amino acids (BCAAs) metabolic disorders. However, the precise causality and direction remain inconclusive. Consequently, this study aims to ascertain the relationship between the risk of depression and BCAAs levels using two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms associated with the BCAAs were extracted from the IEU OpenGWAS. Pooled level data for major depressive disorder (MDD) was obtained from the Psychiatric Genomics Consortium. We performed genome-wide linkage disequilibrium score regression, MR analyses, and colocalization analyses using summary genome-wide association study data across European population to probe genetic causality between BCAAs and MDD. Our results showed a causal effect of MDD risk on the increasing valine levels (IVW OR = 1.043, 95% CI = 1.006-1.082, P = 0.024) and a genetic correlation between MDD and valine. However, leucine, isoleucine, and total BCAAs were not causally associated with the risk of MDD (P > 0.05). The sensitivity analyses indicated that there was no heterogeneity or horizontal pleiotropy in our findings. The linkage disequilibrium score regression demonstrated significant evidence of shared genetic architecture between MDD and valine, with the genetic correlation estimated to be 0.112 (P = 0.002). Colocalization analysis did not provide any evidence of a shared causal variant between MDD and valine. It was revealed that valine metabolism may be significantly affected by depression through a two-sample MR analysis, while no significant connection was identified between other branched-chain amino acids and depression. This result provided new insights into the metabolic processes involved in depression.

From macro to micro: De novo genomes of Aedes mosquitoes enable comparative genomics among close and distant relatives.

The yellow fever mosquito (Aedes aegypti) is an organism of high medical importance because it is the primary vector for diseases such as yellow fever, Zika, dengue, and chikungunya. Its medical importance has made it a subject of numerous efforts to understand their biology. One such effort, was the development of a high-quality reference genome (AaegL5). However, this reference genome was sourced from a highly inbred laboratory strain with unknown geographic origin. Thus, the reference is not representative of a wild mosquito, let alone one from its native range in sub-Saharan Africa. To better understand the genetic architecture of Ae. aegypti and their sister species, we developed two de novo chromosome-scale genomes with sequences sourced from single individuals: one of Ae. aegypti formosus (Aaf) from Burkina Faso and one of Ae. mascarensis (Am) from Mauritius. Both genomes exhibit high contiguity and gene completeness, comparable to AaegL5. While Aaf exhibits high degree of synteny to AaegL5, it also exhibits several large inversions. We also conducted comparative genomic analyses using our genomes and other publicly available culicid reference genomes to find extensive chromosomal rearrangements between major lineages. The expanded gene families common to Aaf, AaegL5, and Am revealed that while the overarching category of genes that have expanded are similar, the specific genes that have expanded differ. Our findings elucidate novel insights into chromosome evolution at both microevolutionary and macroevolutionary scales. The genomic resources we present are additions to a growing arsenal for biologists in understanding mosquito biology and genome evolution.

Shifts in bee diet breadths are associated with gene gains and losses and positive selection across olfactory receptors.

Bees are palynivorous insects that vary widely in the number of plant families from which they collect pollen. Their evolutionary history has been marked by multiple transitions in diet breadth between specialists that only visit specific plant genera (narrow diet breadth) and generalists that visit multiple large plant families (broad diet breadth). Understanding the evolution of sensory systems associated with changes in the detection, discrimination, and gustation of different pollen in bees can shed light on the underlying genetic mechanisms associated with transitions between narrow and broad diet breadths. We conducted a comparative study of three families of insect olfactory receptor genes (odorant receptors (ORs), gustatory receptors (GRs), and ionotropic receptors (IRs)) linked to diet breadth across 51 bee species. We calculated rates of gene gains and losses and identified genes experiencing positive selection across specialist and generalist bees. Our results show that broad generalists exhibit high rates of OR gene losses and GR gene gains. We observed accelerated rates of evolution in seven orthologous groups of genes across specialists and one group in generalists. Several orthogroups showed diversification in putative ligand-binding domains of proteins, indicating potential shifts in functional properties of the receptors. Taken together, these results indicate that dietary specialization in bees requires chemosensory system diversification of existing genes while dietary generalization is associated with the loss of ORs and gain of GRs. Our study provides important insights into the genetic architecture underlying shifts in niche occupancy across insects.

Genome-wide association analysis reveals the genetic basis of ionomic variation in duck breast muscle.

Mineral elements are crucial for biological functions, with meat serving as a key dietary source. Despite advances in ionome analysis, the genetic mechanisms regulating mineral accumulation in meat remain poorly understood. Here, we analyze the ionome of 376 breast muscles from the large gradient consanguinity segregating population generated by Pekin duck×Liancheng white duck crosses, quantifying seven essential mineral elements (potassium (K), phosphorus (P), sodium (Na), magnesium (Mg), calcium (Ca), iron (Fe), and zinc (Zn)). Notably, Ca exhibited the most pronounced variation between Pekin duck and Liancheng white duck (fold change = 1.83, P < 0.01). Correlation analysis demonstrated significant positive relationships between Zn and Ca (r = 0.49), Na (r = 0.41), and (all P < 0.001), while negative correlations were observed between Na and K (r = -0.29) (P < 0.001). We then analyzed correlations between the ionomic profiles and growth and meat quality traits. Importantly, Ca concentrations showed strong negative correlations with both breast muscle thickness (r = -0.72) and body weight (r = -0.76) (both P < 0.01), but positively correlated with meat lightness (r = 0.54, P < 0.01). To elucidate the genetic architecture underlying the duck pectoralis muscle ionome, we first estimated its narrow-sense heritability, which ranged from 0.19 to 0.58 across different mineral elements. Through comprehensive genetic analyses incorporating Genome-wide association studies (GWAS), linkage disequilibrium (LD) mapping, gene annotation, and expression profiling, we identified two key genes (SLC25A25 and ATP2B2) on chromosomes 18 and 13 that collectively regulated Ca content. These lead SNPs in these loci explained 39.91% and 11.07% of the phenotypic variance, respectively. Notably, the lead SNP on Chr18 also demonstrated pleiotropic effects, contributing to both meat lightness (PVE = 14.79%) and breast muscle thickness (PVE = 1.79%). Furthermore, on chromosome 2, we discovered a significant SNP associated with both Na and Ca concentrations, accounting for 12.6% and 4.35% of phenotypic variation, respectively. Further analysis pinpointed gene SLC25A32 as the most promising candidate within this genomic region. These findings enhance our comprehension of the genetic basis underlying ion content in meat and offer valuable insights for refining breeding programs, while also providing a new direction for the combat hidden hunger through meat biofortification.

Admixed and single-continental genome segments of the same ancestry have distinct linkage disequilibrium patterns

BackgroundAdmixed populations offer valuable insight into the genetic architecture of complex traits. Many studies have proposed methods for genome-wide association study (GWAS) in admixed populations and various simulation studies have evaluated their performances. In this work, we propose another direction of comparison of recently proposed methods for admixed GWAS from a population genetic viewpoint.ResultsOur theoretical approach mathematically and directly compares the power of methods given that the causal variant is tested. This is done by deriving the variance formula of the methods from the population genetic admixture model. Our results analytically confirm previous observation that the standard GWAS test is more powerful than alternative tests due to leveraging allele frequency heterogeneity in which alternatives do not. As a by-product, we obtain a simple method to improve the power of multi-degrees-of-freedom tests only using summary statistics. We further investigate the problem when the causal variant is not directly known but is detected by tagging variants in linkage disequilibrium (LD). The analysis shows that a genetic segment from admixed genomes may exhibit distinct LD patterns from the single-continental counterpart of the same ancestry.ConclusionsWhile the classic admixture model is successful in predicting GWAS power, its popular extension in the literature falls short in explaining the LD patterns found in simulations and real data, warranting an improved model for LD in admixed genomes.

Genome-wide association studies and candidate genes networks affecting reproductive traits using Iranian Holstein sequence data

BackgroundThe reproduction process in domestic animals is one of the most important challenges of animal husbandry. Fertility is an important trait that contributes to herd profitability and can be improved by genomic information. One of the best ways to investigate the association between single nucleotide polymorphisms (SNPs) and phenotypic performance is the genome-wide association study (GWAS). The aim of our study was to identify the genomic regions affecting reproductive traits, interval between first and last insemination (IFL), days open (DO), days from calving to first service (DFS), number of services per conception (NSPC), age at first calving (AFC) and age at first insemination (AFI) using SNP chip data in Iranian Holstein cows.ResultsGWAS analysis for all reproductive traits based on the significant-association threshold P < 1 × 10–8, led to the identification of 55 single nucleotide polymorphisms (SNPs) for IFL (n = 3), DFS (n = 0), DO (n = 5), NSPC (n = 5), AFI (n = 33), and AFC (n = 9) traits. Based on the results of gene ontology analysis, 54 different candidate genes for reproductive traits were identified in this study. For IFL, NSPCC, DO, AFC, and AFI traits 4, 8, 11, 10, and 21 candidate genes were identified in the vicinity of significant SNPs, respectively. Key genes with biologically important positions for heifers (ATG7, PTPN5, STAC, GAD2, PLXDC2, KARS1, PRIM2, and ZNF597) and cows (LPL, SERP2, BIRC6, CENPU, PIK3C3, and MYLK3) can be mentioned.ConclusionsOur results identified 55 marker-trait associations (MTAs) and 54 different candidate genes associated with reproductive traits. As a result, the SNPs and candidate genes discovered in this study can be used in genomic experiments to improve the reproductive performance of Iranian Holstein dairy cows and provide new information about the genetic architecture of these traits.

Utilising genomic association data for causal inference in anorexia nervosa.

Anorexia nervosa (AN) is a prevalent psychiatric disorder with high rates of mortality and limited treatment options. AN is a complex disorder, for which common variation contributes to disorder risk. To dissect the genetic architecture of AN, a variety of statistical methods can be applied. Many of these utilise genome-wide association study (GWAS) datasets to investigate biological mechanisms within disease progression in addition to broader associations between complex traits. GWAS for AN have revealed important biological insights, however, these have not translated into new pharmacotherapies. Here, we review the application of statistical methods that use GWAS, to investigate the relationship between genetic variation, biochemical compounds and complex traits to identify potential relationships which could advance our understanding of disease biology. We discuss genetic variant association data for AN, the application of gene-based and complex trait level correlation methods and approaches for establishing evidence of causality between complex traits and AN. These methods all contribute to the growing literature regarding the genetic influences of AN risk and demonstrate that statistical analysis utilising genetic data is a valuable tool to progress our understanding of this disease.

Molecular epidemiology and clinical characteristics of carbapenem-resistant Klebsiella pneumoniae bloodstream and pneumonia isolates.

Appropriate antibiotic therapy in patients with carbapenem-resistant Klebsiella pneumoniae (CRKp) infections often requires knowledge of resistance mechanisms. Therefore, we aimed to define the clonal diversity, mechanisms of carbapenem resistance, potential for carbapenem resistance transmissibility, virulence gene repertoire, and potential clinical impact of these genetic elements in patients with CRKp bloodstream infection and/or pneumonia, which are associated with high mortality. Clinical data and CRKp isolates at a site in Singapore and in the United States were examined. Whole-genome sequencing and bioinformatic analysis of CRKp isolates were performed. In total, 125 patients (n = 118 from Singapore; n = 7 from the United States) were included. Clonal diversity was high as 58 sequence types were identified. Carbapenemases were present in 109 (87%) of the CRKp isolates; KPC-, OXA-, and NDM-type enzymes were identified in significant quantity. The majority (87%) of carbapenemases were encoded on conjugative or mobilizable plasmids and thus potentially transmissible to other strains. Of the 16 CRKp isolates without a carbapenemase, the predominant predicted mechanism of carbapenem resistance was extended-spectrum β-lactamases along with truncation of porins ompK35 and/or ompK36. Patients with carbapenemase-producing CRKp strains had increased in-hospital mortality. Recurrent CRKp infections were primarily due to either the same CRKp genomic group or similar carbapenemase-encoding conjugative plasmids within a different K. pneumoniae strain. Our findings suggest that in CRKp isolates causing serious infections, carbapenem resistance arises through diverse mechanisms, is easily transmissible between isolates, and impacts patient outcomes. These findings highlight the importance of diagnostic tools to identify mechanisms of carbapenem resistance in the clinical setting.IMPORTANCETo design more effective therapies and better understand treatment failure in patients with carbapenem-resistant Klebsiella pneumoniae (CRKp) infections, we must identify the mechanisms of carbapenem resistance and their impact on patient outcomes. However, prior studies are often limited by the inclusion of CRKp that are colonizers or from non-severe infections, a focus on a single general mechanism (i.e., presence of carbapenemases), lack of whole-genome sequencing to fully characterize the underlying genetic architecture of CRKp strains, and no analyses of associations between resistance mechanisms and clinical outcomes. Here, we attempt to address some of these gaps by sequencing a large set of invasive CRKp isolates to characterize the underlying clonal diversity, mechanisms of carbapenem resistance, potential carbapenemase transmissibility, virulence gene repertoire, and the possible impact of these genetic elements on patient mortality.

Identification of novel MYO19 variants in neonatal hypertrophic cardiomyopathy: a familial analysis revealing oligogenic contributors to disease severity

BackgroundPediatric hypertrophic cardiomyopathy (HCM) is a rare condition, particularly in neonates, and is characterized by rapid and extensive myocardial hypertrophy, often leading to severe clinical outcomes. HCM can arise from variants in sarcomeric genes, which are essential for myocardial contractions, as well as non-sarcomeric gene variants. Although genetic modifiers and oligogenic inheritance have been implicated in congenital heart disease and cardiomyopathy, their complexity in HCM has not been fully elucidated, especially in familial cases with variable phenotypes. Hence, this study aims to investigate the genetic architecture in a family with a history of cardiac disease and neonatal HCM, focusing on oligogenic inheritance of non-sarcomeric variants.MethodsClinical data and blood samples were collected for genetic analysis. Whole genome sequencing (WGS) and bioinformatic analyses identified compound heterozygous variants in the MYO19 gene. Maternally inherited variants were analyzed because the proband’s mother was also diagnosed with HCM. WGS was performed on the patient’s maternal grandfather and aunt, who have cardiac disease, revealing candidate genetic variants that may contribute to the cardiac phenotype.ResultsCompound heterozygous MYO19 variants were identified in the neonatal patient. Missense c.203C > G (p.A68G) and frameshift c.275_276del (p.E92Vfs*19) variants were identified, which were located in the myosin motor domain, a functionally crucial region of the MYO19 protein. Maternally inherited missense variants were identified in SURF1 and ETFDH. All three genes are associated with mitochondrial function, and in silico prediction tools suggest that these variants are likely damaging. Other candidate genetic variants possibly contributing to the cardiac phenotype were also detected in the extended maternal family.ConclusionsTo the best of our knowledge, this study represents the first report proposing MYO19 as a candidate gene for HCM and highlights the potential role of oligogenic inheritance in the etiology of the disease. Furthermore, plausible candidate variants of other mitochondria-related genes, such as MYO19, SURF1, and ETFDH, were identified, and other family members were investigated to support the pathogenesis of HCM further. Given the limited understanding of the genetics of pediatric HCM, these findings contribute valuable insights into its genetic basis in pediatric patients.

Phenome-wide association study identifies multiple traits associated with a polygenic risk score for colorectal cancer

BackgroundMany factors, including environmental and genetic variables, contribute to Colorectal Cancer (CRC) risk. The genetic components of risk can be divided into monogenic and polygenic factors. Just as monogenic factors can increase risk for more than one condition, polygenic factors may also underlie multiple phenotypes, including behavioral traits. In order to understand the biology of CRC risk better, it is important to understand the shared polygenic genetic architecture contributing to CRC risk and other phenotypes, including CRC associated risk factors.MethodsWe investigated potential shared genetics by performing a Phenome-wide association study (PheWAS) with a multi-ancestry CRC polygenic risk score (PRS). The discovery cohort (N = 426,464) consisted of ancestrally diverse participants from the United Kingdom Biobank. The replication cohort (N = 87,271) consisted of ancestrally diverse participants from the electronic Medical Records and Genomics Network phase 3. We used a mixed-effects model to adjust for the presence of related individuals. To preserve power, we limited the number of tests by restricting analysis to ancestor phecodes derived from the electronic health record (EHR) that were not likely to be a result of CRC or its treatment.ResultsWe discovered and replicated associations between the CRC PRS and breast cancer, prostate cancer, obesity, smoking and alcohol use (discovery p < 1.1e-4; replication p < 0.0019). The association between CRC risk and prostate cancer may be a novel finding, whereas the association with breast cancer has been previously observed using orthogonal methods. The association between CRC risk and behavioral risk factors corroborate previous studies, also using orthogonal methods, and may reveal potential prevention or treatment strategies.ConclusionsAs these results corroborate findings from other studies using orthogonal methods, we demonstrate that a CRC PRS can be used as a proxy for genetic risk for CRC when investigating shared genetics between CRC and other phenotypes. Further study of the relationship between PRS from multiple traits with EHR data may reveal additional shared genetic factors. Ultimately, understanding these underlying genetic correlations may identify prevention and treatment strategies for CRC.

High burden of variants of uncertain significance in early-onset colorectal cancer among indigenous African patients: a call for global research equity in cancer genetics

BackgroundColorectal cancer (CRC) remains a significant global health challenge, with rising incidence among early-onset cases in low- and middle-income countries, including South Africa. However, comprehensive germline genetic data from indigenous African populations remain scarce. This study aimed to explore germline genetic factors contributing to early-onset CRC (eoCRC) in Indigenous African patients using whole exome sequencing (WES).Methods and resultsWe performed WES on blood-derived genomic DNA from 32 Indigenous African patients diagnosed with eoCRC (< 50 years), who previously tested negative on a multigene CRC panel. While preliminary but definitive, pathogenic variants were identified in only 5 patients (16%) across genes such as C6, FAT1, LZTR1, PYCR1, and UGT1A7. A substantial proportion (47%, n = 15) carried variants of uncertain significance (VUS) with strong pathogenic potential (“leaning pathogenic”) in genes ASXL1, CHEK2, ERBB2, ERCC4, INSR, KIT, MITF, NOTCH1, NOTCH2, PDGFRA, RAD51B, RAD54L, RASA1, RECQL, SUFU, VEGFA, and WT1. Comparative analysis with public datasets and recurrent findings suggests these leaning pathogenic VUSs may represent true disease-associated variants, currently may be misclassified due to limited representation of African genomes in reference databases.ConclusionsOur findings reveal a high burden of potentially pathogenic VUSs in indigenous African patients with eoCRC, reflecting both unique genetic architecture and a critical gap in global genomic equity. These variants may contribute to future variant reclassification and improved understanding of CRC predisposition in African populations. This study underscores the urgent need for population-specific genomic research and the development of inclusive variant databases to support accurate diagnosis and personalised care.

Signatures of selective sweeps in urban and rural white clover populations

Abstract Urbanization is increasingly recognized as a powerful force of evolutionary change. However, anthropogenic sources of selection can often be similarly strong and multifarious in rural habitats, and whether selection differs in either strength or its targets between habitats is rarely considered. Despite numerous examples of phenotypic differentiation between urban and rural populations, we still lack an understanding of the genes enabling adaptation to these contrasting habitats. In this study, we conducted whole genome sequencing of 120 urban, suburban, and rural white clover plants from Toronto, Canada and used these data to identify urban and rural signatures of positive selection. We found evidence for selection in genomic regions involved in abiotic stress tolerance and growth/development in both urban and rural populations, and clinal change in allele frequencies at SNPs within these regions. Patterns of allele frequency and haplotype differentiation suggest that most sweeps are incomplete and our strongest signals of selective sweeps overlap known large-effect structural variants. These results highlight how both urban and rural habitats are driving ongoing selection in Toronto white clover populations, and motivate future work disentangling the genetic architecture of ecologically important phenotypes underlying adaptation to contemporary anthropogenic habitats.

Identification, characterization, and associations with agronomic traits and early vigor of mature wheat embryo size loci.

Although the mature wheat (Triticum aestivum L.) embryo constitutes only a small proportion of kernel weight, it plays a significant role in seed germination and seedling establishment. However, the genetic basis underlying wheat embryo size remains poorly understood. In this study, we measured the embryos of mature kernels from 199 recombinant inbred lines (RILs) across up to nine environments. Using linkage maps constructed with the Wheat 55K SNP array, we identified genetic loci associated with embryo size, including embryo length (EL), embryo width (EW), embryo area (EA), and their respective ratios to kernel dimensions (EL/KL, EW/KW, and EL/EW). Nine stable quantitative trait loci (QTL) were detected within three co-located chromosomal intervals, six of which are likely novel. The major, stably expressed, and novel QTL-QEL.sicau-2CN-2D.1 and QEW.sicau-2CN-2D-were successfully validated in a natural population comprising 165 Sichuan wheat cultivars and 57 Sichuan wheat landraces across two environments. By leveraging the genomic assemblies of the two parental genotypes, we identified candidate genes for this locus on chromosome 2D. Furthermore, significant correlations were observed between embryo size and early vigor, as well as kernel traits. Collectively, these findings provide critical insights into the genetic architecture of embryo size and facilitate the fine mapping and breeding applications of this promising locus.

Unveiling genetic architecture of white matter microstructure through unsupervised deep representation learning of fractional anisotropy images.

Fractional anisotropy (FA) derived from diffusion MRI is a widely used marker of white matter (WM) integrity. However, conventional FA based genetic studies focus on phenotypes representing tract- or atlas-defined averages, which may oversimplify spatial patterns of WM integrity and thus limiting the genetic discovery. Here, we proposed a deep learning-based framework, termed unsupervised deep representation of white matter (UDR-WM), to extract brain-wide FA features-referred to as UDIP-FA, that capture distributed microstructural variation without prior anatomical assumptions. UDIP-FAs exhibit enhanced sensitivity to aging and substantially higher SNP-based heritability compared to traditional FA phenotypes ( P < 2.20e-16, Mann-Whitney U test, mean h 2 = 50.81%). Through multivariate GWAS, we identified 939 significant lead SNPs in 586 loci, mapped to 3480 genes, dubbed UDIP-FA related genes (UFAGs). UFAGs are overexpressed in glial cells, particularly in astrocytes and oligodendrocytes (Bonferroni-corrected P < 2e-6, Wald Test), and show strong overlap with risk gene sets for schizophrenia and Parkinson disease (Bonferroni-corrected P < 7.06e-3, Fisher exact test). UDIP-FAs are genetically correlated with multiple brain disorders and cognitive traits, including fluid intelligence and reaction time, and are associated with polygenic risk for bone mineral density. Network analyses reveal that UFAGs form disease-enriched modules across protein-protein interaction and co-expression networks, implicating core pathways in myelination and axonal structure. Notably, several UFAGs, including ACHE and ALDH2 , are targets of existing neuropsychiatric drugs. Together, our findings establish UDIP-FA as a biologically and clinically informative brain phenotype, enabling high-resolution dissection of white matter genetic architecture and its genetic links to complex brain traits.

Etiological basis for chronic pain genetic variation in brain and dorsal root ganglia cell types.

Chronic pain is a complex clinical problem comprising multiple conditions that may share a common genetic profile. Genome-wide association studies (GWAS) have identified many risk loci whose cell-type context remains unclear. Here, we integrated GWAS data on chronic pain ( N = 1,235,695) with single-cell RNA sequencing (scRNA-seq) data from human brain and dorsal root ganglia (hDRG), and single-cell chromatin accessibility data from human brain and mouse dorsal horn. Pain-associated variants were enriched in glutamatergic neurons; mainly in prefrontal cortex, hippocampal CA1-3, and amygdala. In hDRG, the hPEP.TRPV1/A1.2 neuronal subtype showed robust enrichment. Chromatin accessibility analyses revealed variant enrichment in excitatory and inhibitory neocortical neurons in brain and in midventral neurons and oligodendrocyte precursor cells in the mouse dorsal horn. Gene-level heritability in the brain highlighted roles for kinase activity, GABAergic synapses, axon guidance, and neuron projection development. In hDRG, implicated genes related to glutamatergic signaling and neuronal projection. In cervical DRG of patients with acute or chronic pain ( N = 12), scRNA-seq data from neuronal or non-neuronal cells were enriched for chronic pain-associated genes (e.g., EFNB2 , GABBR1 , NCAM1 , SCN11A ). This cell-type-specific genetic architecture of chronic pain across central and peripheral nervous system circuits provides a foundation for targeted translational research.

Understanding genetic architecture overcomes tradeoffs between seed quality and insect resistance.

The sunflower (Helianthus annuus) pericarp protects the seed within from both abiotic and biotic stresses. Achenes with stronger pericarps are less susceptible to damage from insect feeding. Complicating the genetic improvement of pericarp strength is the negative correlation between pericarp thickness (a component of strength) and oil content. As breeding efforts have increased oil content, there has been a concomitant decrease in pericarp thickness. One breeding goal is to improve oil content while preserving pericarp strength through genetic mechanisms independent of the tradeoffs with pericarp thickness. To determine the genetic basis of oil content, pericarp strength, and thickness, we identified QTL in two populations: the Sunflower Association Mapping panel (Mandel et al. in Theor Appl Genet 123:693-704, 2011) and a recombinant inbred line (RIL) population derived from a thin pericarp oilseed inbred (HA 467) crossed to a thick pericarp open-pollinated variety from Türkiye (PI 170415). A region on chromosome 15 was associated with neighboring QTL for banded moth resistance, oil content, and pericarp thickness, partially underlying the trade-offs among these traits. Additional QTL on chromosome 5 and 14 for pericarp strength provide fewer trade-offs with oil content. QTL for pericarp strength on chromosome 5 and pericarp thickness on chromosome 16 were associated with large structural variants on chromosome 5 and putative structural variation on chromosome 16, with candidate gene presence/absence variation between the haplotypes on chromosome 5. Understanding the origin and nature of phenotypic tradeoffs is beneficial to plant biologists and sunflower breeders as they seek to understand the origin and genetic architecture of adaptive and maladaptive traits.

Genomic structural equation study reveals links between anorexia nervosa and delay discounting and lack of perseverance but not other facets of impulsivity

Anorexia nervosa (AN) is a heritable condition, characterized by a fear of weight gain and a distorted body image, for which treatments are only limited. AN is characterized by excessive control over feeding behaviors, which has been hypothesized to indicate that low impulsivity, including low emotional impulsivity (urgency), may place certain individuals at risk for AN; however, this has not been fully genetically evaluated. We used genomic structural equation modeling and genome-wide association studies (GWASs) based on individuals of European ancestry (n = 72,517–903,147) to examine the latent genetic architecture between AN and several measures of impulsivity. Because AN is positively genetically associated with substance use disorders (SUDs), which are also strongly associated with impulsivity, we conditioned our analyses using GWAS data from four SUDs (alcohol, tobacco, cannabis, and opioid use disorders). AN was not significantly genetically correlated with impulsivity latent factors as indices of Barratt Impulsiveness Scale (BIS) or Urgency, Premeditation, Perseverance, Sensation Seeking, and Positive Urgency (UPPS) subscales (common impulsivity, rg = −0.07; urgency-specific impulsivity, rg = 0.14; and sensation seeking, rg = −0.07) but was significantly negatively genetically correlated with delay discounting (rg = −0.19) and lack of perseverance (rg = −0.15), even after controlling for SUDs (rg = −0.32 or rg = −0.25, respectively). This work suggests that delay discounting and lack of perseverance capture genetically informative dimensions of AN; clarifying shared etiologies could inform AN diagnosis and treatment mechanisms.

Shared genetic architecture between eating disorders, mental health conditions, and cardiometabolic diseases: a comprehensive population-wide study across two countries

Eating disorders arise from a complex interaction of genetic and environmental influences. Here we provide comprehensive population-level estimates of the heritability of eating disorders and their genetic relationships with various mental health and cardiometabolic disorders (CMDs), expanding beyond genome-wide association studies. We examined the heritability of three eating disorders—anorexia nervosa (AN), bulimia nervosa (BN), and other eating disorders (OED)—and investigated shared familial and genetic risk factors with mental health disorders and CMDs. Using national register data from Denmark and Sweden (1972–2016), we analysed clinical diagnoses for over 67,000 individuals with eating disorders, their first-degree relatives, and matched controls from populations totalling 17 million. Heritability estimates were moderate, h2AN = 36%, h2BN = 39%, and h2OED = 30% and genetic correlations revealed substantial overlap between AN and obsessive-compulsive disorder (rg = 0.65) and moderate correlations with other mental health disorders such as autism (rg = 0.36). Significant genetic associations were also identified between eating disorders and CMDs, showing strong replication across both countries. These findings emphasise the genetic foundations of eating disorders and their shared genetic architecture with mental health and CMDs. This research enhances our understanding of comorbidity patterns and has important implications for developing integrated treatment approaches.

Mapping QTLs for Stripe Rust Resistance and Agronomic Traits in Chinese Winter Wheat Lantian 31 Using 15K SNP Array

Wheat stripe rust (Puccinia striiformis f. sp. tritici, Pst) resistance and agronomic traits are crucial determinants of wheat yield. Elucidating the quantitative trait loci (QTLs) associated with these essential traits can furnish valuable genetic resources for improving both the yield potential and disease resistance in wheat. Lantian 31 is an excellent Chinese winter wheat cultivar; multi-environment phenotyping across three ecological regions (2022–2024) confirmed stable adult-plant resistance (IT 1–2; DS &lt; 30%) against predominant Chinese Pst races (CYR31–CYR34), alongside superior thousand-kernel weight (TKW) and kernel morphology. Here, we dissected the genetic architecture of these traits using a total of 234 recombinant inbred lines (RILs) derived from a cross between Lantian 31 and the susceptible cultivar Avocet S (AvS). Genotyping with a 15K SNP array, complemented by 660K SNP-derived KASP and SSR markers, identified four stable QTLs for stripe rust resistance (QYrlt.swust-1B, -1D, -2D, -6B) and eight QTLs governing plant height (PH), spike length (SL), and kernel traits. Notably, QYrlt.swust-1B (1BL; 29.9% phenotypic variance) likely represents the pleiotropic Yr29/Lr46 locus, while QYrlt.swust-1D (1DL; 22.9% variance) is the first reported APR locus on chromosome 1DL. A pleiotropic cluster on 1B (670.4–689.9 Mb) concurrently enhanced the TKW and the kernel width and area, demonstrating Lantian 31’s dual utility as a resistance and yield donor. The integrated genotyping pipeline—combining 15K SNP discovery, 660K SNP fine-mapping, and KASP validation—precisely delimited QYrlt.swust-1B to a 1.5 Mb interval, offering a cost-effective model for QTL resolution in common wheat. This work provides breeder-friendly markers and a genetic roadmap for pyramiding durable resistance and yield traits in wheat breeding programs.