Genetic diversity and genome-wide association mapping for salt stress tolerance in diverse parental lines of hybrid rice.

Imaging genetics links genetic variations to brain structures and functions, but the computational challenges posed by high-dimensional imaging and genetic data are significant. In voxel-level genome-wide association studies, we introduce a Representation learning-based Voxel-level Genetic Analysis (RVGA) framework that reduces computational time and storage burden by over 200 times. RVGA enhances statistical power by denoising images and shares minimal datasets of summary statistics for associations across the whole genome of the entire image for secondary analyses. Additionally, it introduces a unified estimator for voxel heritability, genetic correlations between voxels, and cross-trait genetic correlations between voxels and non-imaging phenotypes. Applying RVGA to hippocampus shape and white matter microstructure in the UK Biobank (n = 53,454) reveals 39 and 275 novel loci, respectively. We identify heterogeneity in heritability within images and subregions that share genetic bases with 14 brain-related phenotypes, such as the genetic correlation between the hippocampus and educational attainment, and between the anterior corona radiata and schizophrenia. RVGA replicates known genetic associations and uncovers new discoveries.

The high prevalence (>5%) of autoimmune hypothyroidism (AIHT) provides a unique opportunity to dissect genetic contributions to systemic and organ-specific autoimmunity. Here we performed a genome-wide association meta-analysis of 81,718 AIHT cases in FinnGen and the UK Biobank, identifying 418 independent signals (P < 5 × 10-8). At 48 of these loci, a protein-coding variant is, or is highly correlated (r2 > 0.95) with, the lead variant, including Finnish-enriched coding variants in LAG3, ZAP70 and TG. We demonstrated that ZAP70:T155M reduces T cell activation and broadly compare large-scale scans of nonthyroid autoimmunity and thyroid-stimulating hormone levels with a Bayesian classifier to assign loci into distinct groupings, estimating that 38% are involved in general autoimmunity whereas 20% are thyroid specific. We further identified substantial antagonistic pleiotropy, with 10% of AIHT loci showing a consistent protective effect against skin cancer. The AIHT results, including numerous genes encoding checkpoint proteins, support the causal role of natural immune variation influencing cancer outcomes.

Abstract Crop wild relatives provide valuable insights into trait diversity and the genetic basis of agronomic traits. In the genus Lactuca , domesticated lettuce ( Lactuca sativa ) and its wild progenitor, Lactuca serriola , have been extensively studied, yet broader wild species remain underrepresented. Here, we present a phenotypic dataset of 550 Lactuca accessions, including 20 wild relatives, capturing plant morphology, pigmentation, and pathogen resistance traits derived from images and genetic resource collections. To investigate the genetic basis of these traits, we used a jointly processed SNP set for L. sativa and L. serriola , applying an iterative two-step GWAS approach, enabling the dissection of multiple loci per trait. We identified both known and novel QTLs associated with anthocyanin accumulation, leaf morphology, and pathogen resistance in L. sativa and L. serriola . Importantly, we identified L. serriola -specific QTLs undetected in L. sativa , revealing unique genetic architectures underlying anthocyanin biosynthesis and leaf morphology in the wild progenitor. These findings expand the knowledge of Lactuca beyond cultivated varieties, highlighting the potential of wild species for breeding applications. Our dataset and results provide a foundation for further investigations into the evolutionary and agronomic significance of Lactuca diversity.

Genome-wide association analysis of ecologically essential traits in Picea crassifolia

The content and composition of fatty acids are crucial determinants of soybean nutritional quality. In this study, we conducted an expression genome-wide association analysis (eGWAS) using 298 soybean germplasm accessions. We identified 904,984 high-quality SNP markers (MAF > 0.02, missing data ≤ 10%). Thirty-three association signals were identified that correlated with to the expression levels of very long chain fatty acid (VLCFA) genes. Integrating KEGG pathway enrichment analysis with gene haplotype analysis, we identified GmLACS11 as the candidate gene that potentially involved in regulating long-chain fatty acid biosynthesis. We performed subcellular localization, bioinformatics analysis, and functional validation of the GmLACS11 gene. The fatty acid content was measured following GmLACS11 gene expression in Saccharomyces cerevisiae eukaryotic expression, Arabidopsis thaliana, and in soybean overexpression and knockout lines. The results demonstrated that both overexpression and knockout of GmLACS11 gene altered soybean fatty acid composition. Overexpression significantly increased the levels of the polyunsaturated fatty acids, linoleic acid and linolenic acid, and a corresponding rise in the total fatty acid content was observed. These findings provide insights into the regulation of soybean very long chain fatty acids biosynthesis and the genetic mechanisms underlying soybean fatty acids composition.

Identifying biological and clinical factors associated with response to mood-stabilizing medications is critical for improving bipolar disorder (BD) treatment. The Mood Stabilizer Genomics (MoStGen) Consortium was established to investigate pharmacogenomic and clinical predictors of response to treatment of BD with antiepileptic drug mood stabilizers (AMS). Here we present the first pharmacogenomic analyses of AMS treatment outcomes based on MoStGen Consortium data, including 917 individuals across contributing sites. We performed genome-wide association analyses in subcohorts followed by meta-analyses, with AMS treatment response measured quantitatively using the Alda scale. Medication-stratified analyses were performed for valproic acid (VPA) and lamotrigine (LTG) treatment response. Additionally, polygenic score (PGS) analyses were used to evaluate the overall genetic contribution to AMS response across cohorts and to test whether genetic liability for various neuropsychiatric illnesses impacts AMS response. We detected genome-wide significant associations with LTG treatment response for SNPs in the gene ROBO2 (top SNP: rs985123, p = 1.9E-10) and for POLR1E at the gene-level (p = 2.53E-06). No significant associations were found for overall AMS or VPA treatment response. Leave-one-out PGS analyses provided significant evidence for a polygenic signal for AMS treatment response. Furthermore, the epilepsy PGS was nominally significantly associated with AMS response (p = 0.024), suggesting higher genetic liability to epilepsy predicts a better response to treatment with AMS. These findings provide insights into the genetic contribution to AMS treatment outcomes, and in particular LTG response, and may contribute to the development of more precise treatments for BD.

Studies have shown that substance use liability is associated with novelty seeking, anxiety-like behavior, and pain sensitivity. We examined whether common genetic variation in outbred Sprague-Dawley rats explained variation in behavioral measures from three assays with established links to substance use: locomotor response to a novel environment, elevated plus maze, and tail flick. We estimated single-nucleotide polymorphism heritability and performed genome-wide association analyses using permutation-derived significance thresholds (N=534-654 rats across traits). Heritability estimates ranged from 0.14-0.38 across eleven traits. Three independent loci were identified: chromosome 1 for elevated plus maze open-arm behavior (α=0.05), chromosome 14 for elevated plus maze immobility (α=0.10), and chromosome 17 for tail flick latency (α=0.05). Candidate genes included Slc18a2, Gfra1 , and Pdzd8 (chromosome 1); Rel and Bcl11a (chromosome 14); and Eci2 and Eci3 (chromosome 17). We compared these loci with our genome wide association study of a F 2 intercross of selectively bred high- and low-responder rats, originally derived from Sprague-Dawleys, that model individual differences in externalizing and internalizing behavior. The current loci are distinct from the ones identified in the bred lines. This difference likely reflects selection history in the high- and low-responder F 2 s, which focused on facets of exploratory locomotion, while loci for anxiety and pain sensitivity traits were identified in the outbreds. This highlights the benefit of using both outbred and selectively bred rats to probe causal variants contributing to individual differences in substance use liability. The current outbred findings implicate monoaminergic signaling, transcriptional control, and lipid metabolism as testable mechanisms for addiction-relevant behaviors.

Background: Although elevated triglyceride (TG) levels are consistently associated with hypertension in observational studies, whether TGs have a causal effect on hypertension remains uncertain, and evidence in East Asian populations is limited. Methods: We analyzed 2159 Korean adults (20-86 years) whose individual-level genetic and phenotypic data were obtained from a cross-sectional health check cohort. Candidate TG-associated genetic variants were identified using genome-wide association analysis and evaluated as instrumental variables (IVs). An individual-level, two-stage IV Mendelian randomization (MR) framework was applied to assess the potential effect of TGs on hypertension, alongside conventional observational analyses using logistic regression. Results: Three candidate TG-associated single-nucleotide polymorphisms (SNPs)-rs78115082 (TRPC7), rs117867615 (TTLL1), and rs34463296 (LINC03019)-were identified and combined to construct a weighted genetic risk score (GRS). Although all the instruments met the conventional strength criteria (F statistics > 10), they explained only a modest proportion of the variance in TG levels (partial R2, 0.008-0.020). Observational analyses showed a strong positive association between TG levels and hypertension (crude odds ratio [OR] = 2.12; 95% confidence interval [CI]: 1.76-2.54; adjusted OR = 1.43; 95% CI: 1.16-1.75). In contrast, MR estimates based on individual SNPs and the GRS were directionally positive but statistically nonsignificant, with wide CIs crossing the null, indicating limited precision. Conclusions: In this Korean cohort, observational analyses demonstrated a robust association between TG levels and hypertension, whereas individual-level MR provided inconclusive genetic evidence for a causal effect under the available instruments. The difference between the observational and genetic estimates is compatible with the finding that TG levels reflect broader cardiometabolic dysregulation rather than acting as an isolated causal determinant of hypertension. These findings underscore the need for larger studies with stronger, externally derived instruments to refine the causal inference in East Asian populations.

Despite the importance of the gut microbiome to health, the role of human genetic variation in shaping its composition remains poorly understood. Here we report genome-wide association analyses of harmonized metagenomic data from 16,017 adults in four Swedish population-based studies, with replication in 12,652 people from the Norwegian HUNT study. We identified variants in the OR51E1-OR51E2 locus, encoding sensors for microbiome-derived fatty acids, associated with microbial richness. We further identified 15 study-wide significant genetic associations (P < 5.4 × 10-11) involving eight loci and 14 common bacterial species, of which 11 associations at six loci were replicated. The results confirm previously reported associations at LCT, ABO and FUT2, and provide evidence for new loci MUC12, CORO7-HMOX2, SLC5A11, FOXP1 and FUT3-FUT6, with supporting data from metabolomics and gene expression analyses. Our findings link gut microbial variation genetically to gastrointestinal functions, including enteroendocrine fatty acid sensing, bile composition and mucosal layer composition.

In non-alcoholic steatohepatitis, there is a compensatory increase in monocyte-derived Kupffer cells (MoKCs) due to the loss of resident Kupffer cells. However, the mechanisms behind MoKCs recruitment and their impact on steatohepatitis development remain unclear. We aimed to elucidate the contribution of continuously recruited MoKCs and the interaction between MoKCs and other cells in macrophage-mediated metabolic dysfunction associated steatotic liver disease (MASLD) to disease exacerbation. We utilized snRNA-seq analysis parallel to characterize the transcriptomes of hepatocytes and non-parenchymal cells (NPCs) in the MASLD progression of steatosis to fibrosis livers in mice and humans, integrating multi-omics analyses among the program. We used spatial transcriptome analysis to discover key functional compartments to recruit MoKCs in MASLD progression. Further performed the critical cytokine validation by genome-wide association analysis combine with genetic risk scores construction in 5,936 individuals. The signal that recruited MoKCs damaging hepatocytes was explored by cell-cell communication analysis and co-culture system. We confirmed through difference cytokine screening and spatial transcriptome that serum amyloid A1 (SAA1) is significantly involved in the pathogenesis of MASLD as evidenced by periportal hepatocytes (PPHs) recruiting MoKCs through the secretion of SAA1. The polygenetic risk score also indicated SAA1 significantly increased MASLD risk in UK Biobank cohort. The recruited MoKCs can in turn disrupt liver microenvironment homeostasis through abnormal cell-cell interactions with hepatocytes, endothelial cells (ECs) and hepatic stellate cells (HSCs). Of these, the recruited MoKCs damaging hepatocytes via CADM1 signal was validated through co-culture system. These findings enhance our comprehension of MoKCs recruitment and turnover in humans and mice, emphasizing their critical role in the multiple-hit injury process during MASLD development.

Genome-wide association analysis to identify candidate genes for growth rate traits in Chinese endemic geese.

Dry age-related macular degeneration (dAMD) is the leading cause of blindness among elderly people in developed countries. The main objective of this study is to investigate the causal relationship between gut microbiota (GM), blood metabolites, and dAMD among European participants. Based on the genome-wide association analysis database, double sample Mendelian randomization (MR) analysis was performed on GM, blood metabolites, and dAMD. The inverse-variance weighted method is used to estimate the causal relationship between GM, blood metabolites, and dAMD, while multiple methods are employed to eliminate pleiotropy and heterogeneity. A 2-step MR analysis quantitatively assessed the effect of metabolite-mediated GM on dAMD. In MR analysis, 15 GM were found to be associated with increased or decreased risk of dAMD, and 18 blood metabolites were found to be associated with increased or decreased risk of dAMD. Our research also found that the potential association between GM and dAMD may be mediated by blood metabolite levels, specifically, ADpSGEGDFXAEGGGVR levels accounted for 38.9% of the causal pathway from genus Parasutterella to dAMD. Our research findings indicate that certain GM and blood metabolites can affect the onset of dAMD, and increasing the abundance of genus Parasottella can increase the risk of dAMD through the mediation of ADpSGEGDFXAEGGGVR levels.

Fusarium head blight (FHB) is a devastating fungal disease in wheat, causing significant yield losses and deterioration of grain quality under severe conditions. In this study, a genome-wide association study was conducted with 448 accessions using genotyping data generated by the 660K SNP array. Nine relatively stable FHB resistance loci were identified on chromosomes 1B, 1D, 2D, 5B, 7A, and 7B. Each QTL accounted for 4.1 to 10.4% of the phenotypic variation. Among them, QFhb.nwafu-7BS and QFhb.nwafu-7BL are novel loci. Polymorphisms of the flanking AQP marker AX-94527414 were developed for QFhb.nwafu-7BL, which could be useful for marker-assisted selection of FHB resistance. Correlation analysis indicated that variation in FHB response was independent of plant height, spike length, and uppermost internode length across the three environments. These results offer new resistance resources for FHB resistance breeding and insights for marker-assisted selection and gene cloning.

Durum wheat productivity in Mediterranean regions faces growing challenges from drought and heat stress. Understanding the genetic architecture of diverse germplasm is therefore essential to support pre-breeding efforts and enhance stress adaptation. In this context, 125 durum wheat genotypes were evaluated for agro-morphological traits across two contrasting Algerian locations over two growing seasons. A subset of 94 genotypes, selected on the basis of phenotypic characterization, was genotyped using the Illumina 7K SNP array. Population structure analysis revealed two to four subgroups, with linkage disequilibrium decaying at 4.09 Mb. Genome-wide association analysis identified 27 distinct significant SNPs associated with eight traits, with most associations detected for spike length, thousand-kernel weight, and plant height. The marker TGWA25K-TG0010 on chromosome 4A showed pleiotropic effects on plant height and peduncle length and co-localized with the Dwarf8 and gibberellic-acid-insensitive genes. Additionally, wsnp_Ex_c2033_3814035 on chromosome 2A was associated with heading earliness and the number of fertile spikelets per spike, and wsnp_Ku_c51039_56457361 on chromosome 5A with plant height and peduncle length in a single site and season. Several other environment-specific associations were also identified. These results support future studies in which the identified markers may be deployed in breeding strategies aimed at improving yield stability and stress adaptability in durum wheat under Algerian conditions.

The rhizosphere microbiome plays a crucial role in determining plant performance and fitness. Nevertheless, regulatory mechanisms linking host genetic variation, root gene regulation and microbiome assembly-and their collective influence on plant nutritional traits-remain poorly understood. Here we generated and integrated 1,341 paired datasets, including root transcriptomes, rhizosphere bacterial 16S rRNA profiles and root ionomes, across 175 resequenced Brassica napus ecotypes grown at two contrasting field sites. We identified 203 highly heritable bacterial amplicon sequence variants (ASVs), many of which were significantly associated with root nitrogen (N) levels. Host transcriptome-wide gene expression and these microbial features together explained up to 45% of natural variation in N uptake while genome-wide association analyses revealed host loci regulating ASV abundance, many of which were under the control of eQTL hotspots linked to carbon and N metabolism. Isolate-level inoculation, whole-genome sequencing, metabolite profiling and confocal imaging demonstrated that the dominant, genetically regulated bacterial genus Sphingopyxis modulates auxin biosynthesis and promotes lateral root development to enhance N acquisition under stress. This study therefore identifies Sphingopyxis as a functionally relevant taxon with potential for microbiome-assisted breeding of nutrient-efficient crops.

Comparative study of the Dof gene family in buckwheat: FtDof34's function in sugar biosynthesis and response to salt and drought stress.

The Taizhou Longitudinal Study: a population-based biobank resource of genetic and biochemical biomarkers for precision medicine in China.

Plumage coloration is an economically important trait in poultry. Although PMEL mutations cause systemic pigmentation defects in vertebrates, their role in localized melanin deposition remains unclear. Wuhua yellow chickens, exhibiting black-spotted (BS) tails on a white background, provide a model system to address this knowledge gap. We integrated whole-genome sequencing of 47 roosters (24 solid white [SW] and 23 BS) with data from 100 black-tailed samples and transcriptomic profiling of follicles. Genome-wide association analysis identified 38 significant SNPs on chromosome 33 within PMEL and related genes, overlapping with selective sweep regions. Transcriptomics revealed 2702 differentially expressed genes, with PMEL significantly upregulated in BS follicles, which was confirmed by quantitative real-time PCR. Gene set enrichment analysis highlighted melanogenesis pathways (GO:0043473; normalized enrichment score = 1.81, false discovery rate = 0.037), with PMEL as a core gene. Kompetitive allele-specific PCR genotyping of the synonymous PMEL variant (chr33:7,093,765) showed a near-perfect genotype-phenotype concordance in males: SW were AA (476/476), BS were predominantly GA (98/115), and black-tailed breeds were GG (107/107). Critically, genotyping of 315 SW hens identified 14 G-allele carriers, confirming cryptic carriers and sex-dimorphic expression. The A allele was absent in diverse populations but present in commercial broilers (A = 0.105) according to the Global Chicken Reference Panel database. These results indicate that the G allele is strongly associated with melanin deposition, with the GA genotype linked to localized spotting and GG to systemic pigmentation. This study provides multi-omics insights into avian pigmentation and offers a kompetitive allele-specific PCR marker for precision breeding.

Genome-wide association analysis reveals natural genetic variations controlling canopy architecture traits in bread wheat.