Search Results (533)

Pumpkin (Cucurbita spp.) is a globally significant vegetable crop known for its high nutritional value and remarkable phenotypic diversity. Yet, the surge in new cultivar releases has overwhelmed traditional morphological descriptors, creating critical gaps in variety purity control and breeders’ rights enforcement. Despite the established utility of SNP markers as the gold standard for genetic analysis, a dedicated high-resolution molecular database for modern pumpkin cultivars remains unavailable. To address this gap, we conducted whole-genome resequencing (WGS) on 94 representative pumpkin cultivars (spanning C. moschata, C. maxima, and C. pepo). Clean reads were mapped to the Cucurbita maxima reference genome. We employed a stringent pipeline to identify genomic variants and utilized STRUCTURE software, Principal Component Analysis (PCA), and Neighbor-Joining (NJ) trees to evaluate population stratification. Linkage disequilibrium (LD) decay and DNA fingerprinting barcodes were also developed. A total of 8,873,150 high-quality variants were identified, including 7,345,007 SNPs and 1,528,143 InDels, with an average SNP density of 21,281.50 SNPs/Mb. Population analysis consistently categorized the 94 cultivars into two primary subpopulations (G1 and G2). The first two PCs accounted for 74.06% of the total genetic variance. Further analysis revealed that G1 possessed a more complex genetic architecture and slower LD decay compared to G2, suggesting distinct selection histories. Finally, we screened for highly informative biallelic SNPs to construct a DNA fingerprinting database, enabling precise sample discrimination through unique chromatic barcodes. This study fills a critical gap in pumpkin genomics by establishing a high-density SNP database and a robust fingerprinting system. These resources provide a definitive tool for variety certification, seed purity testing, and the advancement of molecular-assisted breeding in pumpkin. Full article

Ductal carcinoma in situ (DCIS) is a non-invasive precursor to invasive breast cancer. DCIS incidence continues to rise, yet its clinical management remains constrained by the absence of reliable biomarkers that can adequately distinguish indolent lesions from those with high invasive potential, to circumvent over- or under-treatment. Black women with DCIS are significantly more likely to progress to invasive breast cancer, are disproportionately diagnosed with high-grade, hormone receptor-negative lesions, and experience elevated risk of recurrence and mortality relative to White women with DCIS. These disparities persist despite comparable access to screening and treatment, suggesting underlying biological and tissue microenvironmental factors. This review synthesizes emerging evidence implicating early molecular and systemic changes that may be driving the disparity in DCIS progression. We highlight racial distinctions in interconnected pathways involving Wnt/β-catenin signaling, metabolic and nutritional dysregulation, immune microenvironment remodeling, and cellular tolerance of genomic instability. We further discuss how epigenetic alterations, obesity-associated inflammation, and immune dysregulation may arise during the pre-invasive stage that intersect with social and environmental exposures to influence racial differences in lesion fate. We spotlight candidate biomarkers disproportionately associated with aggressive disease in Black women—including KIFC1, a mediator of centrosome clustering and genomic instability tolerance, and ACKR1/DARC, a regulator of chemokine gradients and immune trafficking—as potential drivers of progression-permissive states. This review advances an integrated, equity-informed framework for DCIS progression that links early tumor evolution to coordinated alterations in genomic instability, immune regulation, metabolic signaling, and stress-adaptive pathways. Importantly, we propose that DCIS progression is governed not by isolated molecular alterations but by coordinated programs that enable survival under genomic and immunologic stress. Current clinical risk assays, which primarily capture tumor-intrinsic proliferation and hormone signaling, do not fully resolve these pathways and may therefore incompletely reflect biologically meaningful racial disparities. This synthesis underscores the need for pathway-level, microenvironment-informed, and population-representative approaches to DCIS risk stratification. Advancing such frameworks will be essential for identifying actionable biomarkers, refining early intervention strategies, and ultimately reducing racial disparities in breast cancer outcomes. Full article

Next-generation sequencing (NGS) has transformed the diagnostic landscape for inherited metabolic diseases by enabling high-resolution detection of pathogenic variants across genetically heterogeneous lysosomal pathways. This is particularly impactful for lysosomal diseases (LDs), including the mucolipidoses (ML I–IV), and for disorders involving lysosomal membranes, transporters, and lysosome-related organelles (LROs). These conditions often present with overlapping biochemical and clinical features that historically complicated accurate diagnosis. This review synthesizes current knowledge on the application of next-generation sequencing (NGS) technologies in the detection and interpretation of variants underlying mucolipidoses types I-IV and selected LRO and lysosomal membrane transport disorders. We summarize expanded variant catalogues, genotype–phenotype correlations, and functional evidence informing pathogenicity classification. In addition, we discuss the integration of NGS into newborn screening and population-level genomics. Collectively, these advances have refined disease definitions, resolved diagnostically challenging cases, and reshaped clinical workflows across the LD and LRO disease spectra. Full article

Diaphorencyrtus aligarhensis parasitizes the Asian citrus psyllid (ACP), Diaphorina citri, the primary insect vector responsible for transmitting Huanglongbing (HLB), a severe citrus disease. Screening of appropriate reference genes is a critical prerequisite for reliable RT-qPCR analysis, which is essential for investigating the functions of target genes in D. aligarhensis across diverse experimental conditions. However, to date, no validated reference genes have been reported for this species. This study assessed seven housekeeping genes in D. aligarhensis under six conditions (developmental stage, body tissue, population, temperature, diet, and starvation) using five stability algorithms (geNorm, BestKeeper, NormFinder, RefFinder, and ∆Ct). The results identified the most suitable reference genes for specific experimental conditions: EIF5A and RPL32 for the developmental stage; RPL13 and H3 for population comparisons; RPS6 and GAPDH for different feeding diets; RPL32 and RPS6 for starvation; RPL7A and RPS6 for different body tissues (head, thorax, abdomen) and temperature gradients (5 °C, 15 °C, 25 °C, 35 °C). Furthermore, the expression profiles of HSP70 were markedly different when normalized to the most versus the least stable reference genes across body tissues, diets, starvation durations, and temperatures. Our findings establish the first set of RT-qPCR reference genes for D. aligarhensis, providing a useful foundation for functional genomics research on this biological control agent. Full article

The Northwest soybean production region (covering Shanxi, Shaanxi, Gansu, Ningxia, Xinjiang, central and western Inner Mongolia and northern parts of Hebei) possesses vast cultivated land resources and advantageous light–temperature conditions, endowing soybean with substantial yield potential. In this study, two natural soybean populations originating from this region were used to systematically investigate the phenotypic variation in two important agronomic traits, plant height (PH) and main stem node number (NN). The results showed abundant genetic variation for both traits. Through genome-wide association analysis (GWAS) and employing a joint detection across multi-environments (control false positives), 5 SNPs significantly associated with PH and 18 SNPs significantly associated with NN were identified, among which four SNPs were detected associated with both traits. Candidate genes were further screened within the ±100 kb intervals flanking lead SNPs at association peaks. By integrating gene expression levels of different soybean tissues and their correlations with the phenotypes, two candidate genes associated with both PH and NN were determined. These findings provide a theoretical basis for the identification and utilization of soybean germplasm resources in Northwest China, and lay a solid foundation for breeding high-yield and high-quality soybean varieties through molecular breeding. Full article

Verticillium wilt of hop (Humulus lupulus L.), caused by the soil-borne pathogen Verticillium nonalfalfae, is a devastating disease with no effective chemical control. In European hop-growing regions, breeding resistant cultivars is the most effective strategy. The lack of response differences in earlier studies suggests constitutive resistance. We therefore conducted a genome-wide association study (GWAS) using a phased hop genome assembly to improve detection of Verticillium resistance loci. A bi-parental population of 142 genotypes, derived from a cross between resistant Wye Target and susceptible BL2/1, was phenotyped for Verticillium wilt resistance and genotyped by sequencing. Association analyses with five statistical models (MLM in TASSEL 5, MLM, MLMM, FarmCPU and BLINK in GAPIT) did not identify any significant SNPs; however, several candidate loci were identified using exploratory threshold, particularly in the phase 2 genome assembly, including a wall-associated kinase (WAK) consistently detected across both genome phases and all models. GWAS results were further assessed with a Random Forest model, which identified SNPs of high feature importance and showed adequate predictive power (accuracy ≈ 0.4, correlation ≈ 0.8) for preliminary breeding screening. These findings provide an initial set of candidate markers and exploratory prediction models for Verticillium wilt resistance in hop, representing a valuable genomic resource for future marker-assisted selection and breeding strategies. Full article

Genomic prediction is now routine in crop improvement, but its main bottleneck has shifted from marker density to environmental complexity. Breeders rarely need predictions for one fixed environment; they need to rank genotypes across target populations of environments that differ in weather, soils, management, and stress timing. This makes genotype-by-environment interaction a primary breeding problem rather than a secondary statistical nuisance. This review examines how genomic, environmental, and phenomic information can be integrated to improve multi-environment prediction in crop breeding pipelines. The review is narrative rather than PRISMA-style, but the literature search and selection logic were structured and explicitly defined. Peer-reviewed English-language studies were identified through structured searches of Web of Science Core Collection and Scopus, supplemented by backward citation screening, with emphasis on literature published from January 2023 to March 2026. Four conclusions emerge. First, environmental information is most useful when it is developmentally aligned, biologically interpretable, and matched to the target population of environments. Second, strong structured statistical baselines remain highly competitive, especially in moderate-sized or highly unbalanced datasets, whereas gains from more flexible machine-learning and deep-learning approaches are most evident in large, sparse, heterogeneous, and multimodal settings. Third, phenomic markers often improve prediction for complex traits, especially yield, because they capture realized crop responses not fully represented by markers alone. Fourth, practical value depends less on isolated gains in predictive accuracy than on evaluation under realistic deployment scenarios, including untested genotype and untested environment settings. Progress therefore requires transparent reporting, benchmark design, stage-aware envirotyping, multimodal integration, uncertainty reporting, and cost-aware deployment. Full article

Chinese Simmental cattle are a high-quality breed developed through long-term crossbreeding and selection after their introduction into China and have become the main dual-purpose cattle population in the Xinjiang region. To deeply dissect the population structure, characteristics of the population structure, and the genetic basis of the twinning trait, this study focused on Xinjiang Chinese Simmental cattle as the main research subject. It integrated genomic data from global public databases to systematically conduct population structure analysis, genetic relationship analysis, and genome-wide selection signature analysis. Population genetic analysis revealed that the IBS matrix and G matrix indicated that some individuals from different geographical origins exhibited distant genetic relationships; the Xinjiang population showed the fastest LD decay, suggesting abundant genetic diversity; the inbreeding coefficient based on Runs of Homozygosity (ROH) across populations ranged from 0.036 to 0.063; principal component analysis and phylogenetic tree showed that some individuals from different geographical origins had certain genetic interconnections; admixture analysis indicated that K = 5 was the optimal model, with each population exhibiting clear genetic differentiation and admixture characteristics. Furthermore, by combining F_st and θπ analysis (comparing the Xinjiang population with other geographical populations), a total of 89 candidate genes associated with the twinning trait in Xinjiang Chinese Simmental cattle were screened, including CYP19A1, HORMAD1, GRB14, CADM2, CXCR4, and others that have been reported to be closely related to oogenesis and reproductive function. In summary, this study explores genome-wide genetic differences among Simmental cattle populations from different regions, deepens our understanding of their population structures, and offers new candidate genes and molecular markers for high-fecundity breeding in Simmental cattle. Full article

To assess the current genetic status of cultured populations of the speckled blue grouper (Epinephelus cyanopodus) in China and to provide a scientific basis for the selective breeding of superior strains, this study utilized single nucleotide polymorphism (SNP) loci screened via whole-genome resequencing technology to analyze the genetic diversity and population genetic structure of 90 E. cyanopodus samples collected from six cultured populations in southeastern China. Comprehensive evaluation of various genetic diversity parameters indicated that all populations exhibited moderate genetic diversity with minor differences among them. Population structure analysis revealed weak genetic differentiation among populations, suggesting that anthropogenic introduction and translocation practices may be the primary factors contributing to the unclear population genetic structure. Additionally, this study identified a number of key genes associated with energy metabolism, muscle development, and environmental adaptation. The findings provide important theoretical foundations for the broodstock selection and scientific aquaculture of E. cyanopodus. Full article

Bringing a new drug to market is a complex, costly, and lengthy process, averaging $2.6 billion and about ten years of research and development. It involves multiple stages, from target discovery to post-approval monitoring, and relies heavily on innovation driven by collaboration among pharmaceutical sciences, biology, biochemistry, engineering, and artificial intelligence. Drug discovery can be divided into four main stages: target selection and validation; compound screening and optimization; preclinical studies; and clinical trials. First, researchers identify and validate a biological target associated with a disease using genomic, proteomic, and bioinformatic approaches. Next, potential compounds (“hits”) are identified through methods such as high-throughput and virtual screening, followed by iterative chemical optimization and functional testing. Promising candidates undergo preclinical in vivo studies to assess pharmacokinetics, pharmacodynamics, and toxicity. Clinical development proceeds in three phases: Phase I evaluates safety in healthy volunteers; Phase II assesses efficacy in patients; and Phase III confirms efficacy and safety in larger populations. After successful trials, regulatory agencies review the data for approval. While small molecules have long dominated due to their stability and oral bioavailability, biologics—such as monoclonal antibodies and mRNA-based therapies—have grown rapidly, highlighted by COVID-19 vaccine development and increasing FDA approvals. Full article

Objectives: To facilitate the innovation and efficient utilization of specialty maize germplasm, this study aimed to systematically evaluate a panel of 222 inbred lines. The objective was to comprehensively characterize phenotypic variation, genetic diversity, and genotype–phenotype associations to screen for representative germplasm resources. Methods: We integrated Best Linear Unbiased Prediction (BLUP) values derived from multi-environment field trials with high-density whole-genome single-nucleotide polymorphism (SNP) data. Population structure and genetic diversity were analyzed, Mantel tests were conducted to assess genotype–phenotype correspondence, and a genome-wide association study (GWAS) was performed to identify significant loci. Results: The population exhibited substantial phenotypic variation, particularly in plant height and tassel traits, with distinct morphological differentiations among specialty types. Genetic diversity analyses revealed varying diversity levels among subpopulations. While Mantel tests indicated a weak overall genotype–phenotype correspondence, specific traits showed significant associations with genetic distance. GWAS successfully identified significant loci associated with plant height and tassel traits. Furthermore, population structure analysis revealed distinct genetic stratification corresponding to specialty types, albeit with a certain degree of admixture. Conclusions: By integrating multi-dimensional phenotypic and genomic profiles, a panel of highly diverse and representative candidate germplasm was identified. These findings provide a crucial theoretical basis for specialty maize breeding and the optimized utilization of germplasm resources. Full article

Psoriasis is an immune-mediated inflammatory disease with a genetic component, characterized by dysregulation of cytokine signaling and activation of T lymphocytes. This study investigated genetic variants associated with psoriasis, psoriatic arthritis (PsA), and response to tumor necrosis factor alpha (TNF-α) inhibitors (adalimumab, infliximab, and etanercept) in a Russian cohort. A genome-wide association study (GWAS) was conducted in 1026 psoriasis patients and 9212 controls using Infinium Global Screening Array-24 v3.0 microarrays. Exploratory analyses of treatment response (n = 48) and PsA (n = 96) were performed without covariate adjustment or explicit modeling of population structure. Polygenic risk scores (PRS) were derived from internally estimated effect sizes in a split-sample design. The GWAS replicated a robust association in the major histocompatibility complex (MHC) region (rs12189871 near HLA-C, p = 3.2 × 10⁻⁵⁰, OR = 2.99 [2.59–3.45]). Additional loci included variants in ZC3H8 and PLCL2. Nominal signals were observed for IL18R1/IL18RAP in treatment response (including rs17027071) and for RCL1 and FBLIM1 in PsA; these findings remain exploratory. PRS demonstrated moderate predictive performance (AUC = 0.6355) and should be interpreted with caution given the study design. Overall, the results highlight a strong MHC signal in psoriasis, while findings for PsA and treatment response remain hypothesis-generating and require independent validation. Full article

Plant height is a key component of sunflower (Helianthus annuus L.) plant architecture. It strongly influences lodging resistance, mechanized harvestability, and yield stability. However, the genetic basis of plant height in sunflowers remains underexplored. This study aimed to develop an F₂ population consisting of 715 individuals from a cross between the dwarf inbred line 150A and the tall inbred line PT326. Bulked segregant analysis coupled with whole-genome resequencing was employed to identify loci associated with plant height. Using three complementary analytical methods, a major quantitative trait locus, qPH15, was identified on chromosome 15. This locus was subsequently fine-mapped, using Kompetitive Allele Specific PCR (KASP) markers and recombinant screening in F₂ and F₃ populations, narrowing it to a 64.66-kb region containing three annotated genes. Among these, HanXRQr2_Chr15g0707451, which encodes an NAC transcription factor designated HaNAC7, was identified as the most promising candidate gene. Haplotype analysis of HaNAC7 across 148 sunflower accessions revealed 4 polymorphic sites defining 6 haplotypes with substantial differences in plant height. The shortest haplotypes, Hap2 and Hap3, were associated with reduced plant height and were predominantly found in Asian germplasm. These findings suggest that HaNAC7 is a strong candidate gene underlying qPH15 and provide useful molecular markers and favorable allelic resources for improving sunflower plant architecture. Full article

Asymptomatic pharyngeal Neisseria meningitidis (Nm) carriage is seen in >30% of sexually transmitted infection (STI) clinic attendees. With increasing reports of Nm urethritis and STI-related invasive disease outbreaks, longitudinal assessment and genomic characterization of Nm among patients at an urban STI clinic population in Columbus, Ohio, was undertaken. This study determined the genomic basis of oropharyngeal, urogenital and rectal Nm isolates carried by patients presenting for care. Cultures using media selective for Neisseria spp., Nm-specific PCR screening of colonies with oxidase-positive Gram-negative diplococci, PCR-based genogrouping and whole-genome sequencing of confirmed Nm were performed. Overall, genomic data of 453 oropharyngeal, 10 urethral, 5 rectal and 1 cervical Nm isolate were obtained between January 2018 and December 2019. Among oropharyngeal Nm isolates, genogrouping identified 37.7% as cnl (capsule null locus), 28% B, 13.5% E, 10.8% Z, 2.6% C and 2.6% Y. However, the cps locus was inactivated in ≥80% of isolates with specified genogroups. The major clonal complexes (ccs) were cc53, cc32, cc41/44, cc1157, cc198 and cc4821. Two oropharyngeal, one rectal and three urethral isolates belonged to the ST-11 Nm urethritis clade (NmUC). Group Y ST-1466 Nm, recently linked to global urogenital and systemic infections, was also identified in the oropharynx. Full article

Neurodegenerative diseases (NDDs) in children represent a heterogeneous group of rare but collectively significant disorders characterized by progressive neurological decline, developmental regression, and substantial morbidity and mortality. Unlike adult-onset neurodegeneration, pediatric conditions are predominantly genetic and frequently arise from defects in fundamental cellular pathways, including lysosomal degradation, mitochondrial oxidative phosphorylation, peroxisomal lipid metabolism, and myelin maintenance. This comprehensive review synthesizes current knowledge regarding the epidemiology, molecular classification, pathophysiology, and emerging therapeutic strategies of major pediatric neurodegenerative disorders. Epidemiological data indicate a “rare-but-many” landscape, where individually uncommon diseases collectively impose a measurable population burden. Mechanistically, disease progression reflects converging processes such as toxic substrate accumulation, impaired autophagy–lysosome flux, mitochondrial bioenergetic failure, oxidative stress, neuroinflammation, and glial dysfunction. Representative groups discussed include lysosomal storage disorders, leukodystrophies, mitochondrial encephalopathies, peroxisomal disorders, and other monogenic neurodegenerative syndromes. Advances in next-generation sequencing, metabolic profiling, and neuroimaging have substantially improved diagnostic accuracy and enabled earlier detection, including through newborn screening programs. Therapeutic paradigms are shifting from primarily supportive care toward mechanism-based interventions, including enzyme replacement therapy, hematopoietic stem cell transplantation, substrate reduction strategies, and gene therapy approaches. Early molecular diagnosis is increasingly recognized as critical for optimizing outcomes, particularly in disorders amenable to presymptomatic intervention. Continued integration of genomic medicine, standardized epidemiologic surveillance, and translational research will be essential to refine disease classification, improve prognostication, and expand access to targeted therapies. Collectively, pediatric neurodegenerative diseases exemplify the intersection of developmental neurobiology and inherited metabolic dysfunction, underscoring the need for multidisciplinary, precision-based clinical strategies. Full article