The aim of this study was to characterize clinical features, genetic architecture, treatment responses, and neurodevelopmental outcomes in neonatal epilepsy associated with KCNQ2 variants and to delineate genotype-phenotype correlations. We conducted a retrospective, two-center study of 30 neonates from 2019 to 2024. All patients underwent whole-exome sequencing with Sanger confirmation and, at last follow-up, were classified, according to International League Against Epilepsy criteria as having self-limited (familial) neonatal epilepsy (SeL[F]NE) or developmental and epileptic encephalopathy (DEE). Primary outcomes were seizure freedom by 6 months and milestone-based three-level neurodevelopment (normal/mild/severe). Clinical/EEG/MRI features and variant class/topology were compared across phenotypes. Most infants presented in the first week of life (median 3 days), typically with focal tonic seizures. EEG abnormalities were common (90%); burst-suppression/profound discontinuity consistently signaled adverse neurodevelopment. MRI was often normal (53%) or nonspecific. We identified 29 distinct variants (32 occurrences) across 30 patients. Twenty-eight carried a single heterozygous variant, and 2 carried 2 heterozygous variants (phase not determined); missense variants predominated (21/30, 70%). Clear topology-phenotype patterns emerged: transmembrane missense variants-especially S5-pore-S6-were enriched in DEE, whereas C-terminal/nontransmembrane variants were associated with SeL(F)NE and benign outcomes. At the last follow-up, SeL(F)NE accounted for 63% and DEE 37%. Seizure freedom reached 93%. Oxcarbazepine was often associated with seizure control after phenobarbital nonresponse, but this observational signal should not be interpreted as causal. Neurodevelopment was normal in 63%; delays occurred only within the DEE cohort. All 5 single-allele truncating/NMD lesions (CNV deletion, canonical splice-site, 2 nonsense, 1 frameshift) aligned with SeL(F)NE, whereas the 2 individuals with 2 heterozygous variants were classified as DEE with marked impairment; however, phase was not determined and 1 recurrent variant (p.E515D) was classified as likely benign, precluding inference of 2 pathogenic alleles. KCNQ2-related neonatal epilepsy shows robust, topology-dependent genotype-phenotype correlations with prognostic utility: early EEG patterns flag risk; transmembrane missense variants are associated with DEE, whereas single-allele truncating/NMD variants are associated with SeL(F)NE. Apparent benefits of oxcarbazepine reflect associations in an observational cohort and should not be interpreted as causal; prospective, phenotype-stratified studies are warranted. Long-term developmental surveillance remains essential, particularly for individuals with DEE and those with severe early EEG patterns or variants in transmembrane/pore regions.

Bipolar disorder (BD) is among the most heritable psychiatric disorders, with a genetic architecture likely consisting of both common genetic variants with small effects and rare variants with strong effects in certain families or populations. Genome-wide association studies (GWAS) with increasingly large sample sizes have identified many susceptibility genes, but common variants in these genes do not have a clear pathophysiological pathway to BD. Genetic linkage studies have the potential to identify rare causal variants in certain families. We sought to determine the chromosomal regions linked with BD in a specific family that has many members affected by the lithium-responsive subtype of BD. We performed genome-wide genetic linkage analysis of a family identified through a lithium-responsive BD index patient with many relatives also affected with lithium-responsive BD-related mood disorders: three with BD I, four with BD II, and one with a major depressive episode. WGS (whole genome sequence) data were obtained for 12 members of the lithium-responsive BD pedigree including the eight affected subjects. Both parametric and nonparametric linkage analyses with the narrow BD phenotype and the broader phenotype including all eight with mood disorders provided evidence of linkage to the same region of chromosome 19. The maximum nonparametric linkage score was 3.89 for the broad phenotype, which exceeds typical thresholds for genome-wide significance. We identified a region of chromosome 19 that has not previously been linked to BD. Nor have significant GWAS variants been found in this region. It is possible that this family has different genetic origins for lithium-responsive BD than other patients studied previously. The family we analyzed is part of a larger cohort of BD patients and their family members, and genetic linkage analysis of additional families could be informative. These results provide a starting point for investigating genes in this chromosomal region that may be involved in the pathophysiology of the lithium-responsive subtype of BD.

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

Mithun (Bos frontalis): Evolutionary origin, genetic architecture, and emerging omics insights

The ESX-3 secretion system in mycobacteria: Evolution, structure, and multifunctional roles in pathogenesis.

Genotypic diversity and genome-wide association study of gelatinization and retrogradation properties of potato starch.

Drought is a major environmental factor limiting maize (Zea mays L.) production worldwide. Unraveling the genetic basis of drought tolerance and pinpointing key loci and candidate genes are fundamental to the molecular breeding of maize with enhanced drought resistance. In this research, 200 maize inbred lines were evaluated under two contrasting water conditions-water-stressed (WS) and well-watered-across two consecutive years (2022 and 2023). Grain yield and drought resistance index (DRI) at maturity were determined, with DRI serving as a yield-based index that provides a more comprehensive measure of drought tolerance. A genome-wide association study based on the FarmCPU model was conducted. A total of 126 significant single nucleotide polymorphisms were detected, including 43 associated with yield under WS conditions (phenotypic variance explained [PVE]=4.64%-10.67%) and 55 related to DRI (PVE=1.47%-10.67%). By combining two independent RNA-seq data collections, 43 core candidate genes were identified, 29 of which were functionally annotated. Gene Ontology enrichment and protein-protein interaction analyses demonstrated that these genes were primarily associated with biological processes related to metabolic regulation, signal transduction, and environmental stress responses. Notably, several transcription factors, including NAC35 (GRMZM5G813651), a MADS-box protein (GRMZM2G148693), and a C3HC4-type RING finger protein (GRMZM2G147319), have been previously implicated in drought response pathways. These findings provide new insights into the genetic architecture of drought tolerance in maize by using a mature-plant, yield-based DRI, which more directly reflects drought tolerance under field conditions.

Improving end-use quality in bread wheat (Triticum aestivum) requires dissecting the genetic basis of complex processing traits and deploying robust prediction pipelines in breeding. We performed genome-wide association studies (GWASs) using 1767 high-quality single-nucleotide polymorphisms generated by genotyping-by-sequencing in a diverse Canada Western Red Spring panel phenotyped near Swift Current, SK, from 2009 to 2019 for grain protein content, milling yield, mixing energy, water absorption, and doughextensibility. The analysis detected significant marker-trait associations on 13 chromosomes, recovering signals at Rht-B1 and Glu-1 and revealing multiple additional signals that may represent previously unreported loci in this germplasm and environmental context, consistent with polygenic control. We then evaluated genomic selection using GBLUP (Genomic Best Linear Unbiased Predictor) and BayesB with and without including significant GWAS hits as fixed effects; gains in predictive accuracy were generally negligible, although water absorption showed modest improvement, compatible with fewer, larger effect loci. Functional annotation of genes near associated variants implicated stress responses, protein metabolism, and grainfilling. Together, these results refine the genetic architecture of Canadian wheat quality and support integrating GWAS-informed biology with genome-wide prediction to accelerate quality-by-design breeding.

Angular leaf spot (ALS), caused by Xanthomonas fragariae, is a bacterial disease that limits strawberry (Fragaria × ananassa) productivity worldwide. Although major resistance loci have been identified in wild Fragaria species, their introgression into elite germplasm remains constrained by linkage drag and inconsistent inheritance. To dissect the genetic architecture of ALS resistance, we evaluated a diverse panel of n=241 greenhouse-tested and n=468 field-tested strawberry accessions representing elite cultivars, breeding materials, and heirloom varieties of cultivated strawberry (F. × ananassa). Plants were evaluated under controlled inoculations and natural field infection using a standardized phenotypic scale and genotyped with 50K single nucleotide polymorphism array. Broad-sense heritability was moderate (H2=0.45), whereas narrow-sense heritability was low (h2=0.10), reflecting the contribution of nonadditive genetic effects such as epistasis. Genome-wide association studies (GWAS) identified two loci on chromosomes 1D and 2D, explaining 4%-5% of phenotypic variance, respectively. A segregating F1 population validated the 2D locus, confirmed by co-localization with the GWAS signal explaining 11.3% of the phenotypic variance. Two-dimensional genome wide scan in this F1 population revealed a significant epistatic interaction between locus on chromosome 2D and an additional locus on chromosome 6B, collectively explaining 27% of the phenotypic variance. Together, these results demonstrate that nonadditive effects in these populations control ALS resistance. Understanding this complexity provides a foundation for developing elite cultivars with durable resistance, such as UCD Royal Royce. Our findings underscore the need for predictive breeding strategies that capture epistatic and environmental variance to accelerate genetic gain for ALS resistance in strawberry.

Despite its long history of cultivation and diverse applications, Cannabis sativa remains underexplored at the genomic level, particularly in landrace populations that harbor untapped genetic diversity. In this study, we investigated the genetic architecture of 145 Iranian cannabis landrace accessions, including both male and female plants, using 233K common SNPs and genome-wide association studies. Our analysis revealed three genetically distinct subpopulations shaped by geography, climate, and traditional cultivation practices. We identified 91 significant genomic regions associated with 40 phenological, morphological, and phytochemical traits, including 15 key loci with pleiotropic effects linked to multiple traits, including flowering time, plant architecture, biomass accumulation, and cannabinoid biosynthesis. These findings highlight the complex interplay between developmental and metabolic pathways in cannabis. The high heritability of most traits and rapid linkage disequilibrium decay underscore the potential of these landraces for high-resolution mapping and genetic improvement. This work provides a valuable genomic resource for marker-assisted selection, supporting the development of improved cultivars with tailored cannabinoid profiles and agronomic traits.

Coffee is one of the world's most widely consumed beverages, derived mainly from Coffea arabica, known for its superior flavor, and Coffea canephora (Robusta/Conilon), valued for its resilience and higher caffeine content. Functional breeding aims to develop cultivars that combine productivity and stress tolerance with improved health-related traits and flavor quality. Because carbohydrate polymers account for more than 50% of green coffee bean dry weight and act as key precursors of aroma and bioactive compounds, we hypothesized that elucidating the genetic architecture underlying carbohydrate metabolites would create new opportunities for molecular breeding in coffee. To test this hypothesis, we integrated cell wall carbohydrate profiling with genomic analyses in a genetically diverse coffee collection encompassing both Coffea canephora and Coffea arabica. Genome-wide association studies identified 14 major genomic loci associated with variation in cell wall polysaccharide composition. Using cup quality as a functional trait endpoint, we further linked carbohydrate profiles with sensory evaluations and propose a framework for implementing marker-assisted selection to accelerate flavor improvement in coffee breeding programs.

Crown rust (CR), caused by Puccinia coronata f. sp. avenae, is a major constraint to oat (Avena sativa L.) production in the southern United States. We dissected the genetic architecture of CR resistance and assessed genomic prediction in 234 winter and facultative oat lines adapted to the southern United States. Using multi-environment phenotyping across five CR-prone sites and 8,234 high-quality single-nucleotide polymorphisms, we conducted genome-wide association study (GWAS) and genomic prediction analyses. GWAS detected 13 significant loci, nine of which co-localized with reported quantitative trait loci or contained plausible resistance candidates such as leucine-rich repeat (LRR), nucleotide-binding site-LRR, and serine/threonine kinases. A stable locus on chromosome 3D was repeatedly identified in Baton Rouge, LA (2016); Castroville, TX (2016); Winnsboro, LA (2017); and in the combined analysis, indicating cross-environment consistency. Additional loci were supported on chromosome 4C (Citra and Quincy, FL, in 2017, and the combined analysis) and 2A (Winnsboro, LA, in 2017 and the combined analysis). Allele stacking was associated with large phenotypic gains. Lines with five or more favorable alleles showed >56% lower crust and 63% lower Crust_Per than lines with none, supporting marker-assisted pyramiding. Genomic prediction models achieved high prediction accuracy. Parametric models, particularly BayesA and RRBLUP, performed strongly across cross-validation schemes; random forest was broadly comparable; and gradient boosting was lower. These results underscore the effectiveness of using GWAS and genomic prediction to enhance breeding for durable CR resistance in oat and provide a genomic framework for developing resilient cultivars suited to southern United States growing conditions.

Hyperspectral remote sensing is a powerful, high-throughput phenotyping tool that quantifies physiologically and structurally relevant wavelengths across diverse genotypes and over varying temporal scales. In this study, we combined tower-based continuous hyperspectral sensing with genome-wide association studies to analyze 1,423 wavebands (400-900 nm) and derivative vegetation indices across 505 genotypes and the genetic architecture of hyperspectral phenotypes over time in Populus trichocarpa Torr. & Gray grown under field conditions. Wavelengths related to chlorophyll and carotenoid absorption spectra exhibited the strongest genetic variation resulting in 98 significant SNP associations. Notably, we found substantial overlap in genetic association between the blue and red spectral regions, indicative of carotenoids and chlorophyll, respectively, and identified more than 10 candidate genes associated with chloroplast function, underpinning photosynthetic activity. Furthermore, fluctuations in associations for vegetative indices, such as the chlorophyll:carotenoid index (CCI), across the growing season reveal a temporally dynamic genetic architecture of physiological traits associated with fall senescence of this temperate tree species. Finally, we also observed correlations (⍴=0.3, p<1x10 -8 ) between individual wavebands or vegetative indices and growth rate, assessed as the relative change of tree height over the growing season. The growth rate prediction was substantially improved by a regularization multivariate model (⍴>0.5, p<1x10 -16 ), reinforcing the value of hyperspectral measurements for predicting traits linked to tree productivity. These findings highlight the potential of high-throughput, rapid, hyperspectral genome wide association studies GWAS to uncover physiologically meaningful genetic variation and offer promising insights for future acceleration for plant breeding.

Genome-wide association analysis to identify novel candidate genes and genomic model optimization to predict acute low-temperature stress resilience in olive flounder (Paralichthys olivaceus).

Autism spectrum disorder (ASD) has a complex genetic etiology, with limited data from Indian populations. This study delineates the genetic architecture of ASD in Indian children using whole exome sequencing (WES) and exploratory genetic association studies (GASs). WES was performed on 142 Indian children with ASD, diagnosed per the Diagnostic and Statistical Manual V criteria. GAS compared cases to 180 age- and ethnicity-matched Indian controls (aged 4-8 years) who exhibited normal neurological development. Variants were annotated using annotate variation, classified per the American College of Medical Genetics and Genomics guidelines, and analyzed for gene ontology, Kyoto Encyclopedia of Genes and Genomes pathways, and GAS associations. Chromosomal microarray 750K was used to confirm the copy number variations. WES identified pathogenic/likely pathogenic variants in 20 cases (14.08%) (12 autosomal dominant, five autosomal recessive, and three X-linked) and variants of uncertain significance in 107 cases (75.35%). Chromosomal microarray analysis revealed six pathogenic variants in 49 autism cases. Functional enrichment implicated neurotransmitter function, synaptic transmission, chromatin remodeling, and glutamatergic/GABAergic imbalances. GAS revealed significant variants (rs2014562 and rs7730228) and a chromosome 11 hotspot ( MUC6 , ZDHHC13 , OR8U1 , OR9G1 ), with chr5 : 130-131 Mb single nucleotide polymorphisms (SNPs) interacting with ADAMTS19 . This study highlights genetic heterogeneity in Indian ASD cases, identifying novel variants and pathways of potential biological relevance. Moderate GAS sample size and high variants of uncertain significance burden warrant further validation.

The study by Hegemann etal. advances understanding of the genetic architecture underlying early neurodevelopmental traits by distinguishing direct and indirect genetic effects using Trio-GCTA and polygenic score models. Findings reveal that indirect genetic effects are particularly pronounced for hyperactivity and restricted and repetitive behaviors, while direct effects dominate in language and motor development. Notably, associations between parental cognitive and educational attainment polygenic scores and child outcomes suggest potential protective genetic influences. However, several methodological considerations may affect interpretation. Excluding closely related individuals could limit the detection of extended familial effects, and reliance on polygenic scores derived from predominantly European GWAS may constrain generalizability. Furthermore, current PGS explain only a portion of trait heritability, possibly underrepresenting true genetic contributions. Future studies incorporating extended family structures, diverse populations, and alternative methods to model gene-environment interplay are essential for refining insights into early neurodevelopmental processes.

Incorporating GWAS-derived prior information enhances genomic prediction for body size traits in the mud crab (Scylla paramamosain).

Genetic risk modeling approaches to resolve phenotypic and molecular heterogeneity in psychiatric disorders.

Hierarchical and sex-dependent genetic architecture of familial fingerprint similarity revealed by a multi-dimensional kinship cohort analysis.

Shared genetic architecture between major depressive disorder and inflammatory bowel disease: Insights from large-scale genome-wide cross-trait analysis.