Search Results (414)

Durum wheat, the world’s second most cultivated wheat species, is a staple crop, critical for global food security, including in Ethiopia where it serves as a center of diversity. However, climate change and genetic erosion threaten its genetic resources, necessitating genomic studies to support conservation and breeding efforts. This study characterized genome-wide diversity, population structure (STRUCTURE, principal coordinate analysis (PCoA), neighbor-joining trees, analysis of molecular variance (AMOVA)), and selection signatures (F_ST, Hardy–Weinberg deviations) in Ethiopian durum wheat by analyzing 376 genotypes (148 accessions) using an Illumina Infinium 25K single nucleotide polymorphism (SNP) array. A set of 7842 high-quality SNPs enabled the assessments, comparing landraces with cultivars and breeding populations. Results revealed moderate genetic diversity (mean polymorphism information content (PIC) = 0.17; gene diversity = 0.20) and identified 26 loci under selection, associated with key traits like grain yield, stress tolerance, and disease resistance. AMOVA revealed 80.1% variation among accessions, with no significant differentiation by altitude, region, or spike density. Landraces formed distinct clusters, harboring unique alleles, while admixture suggested gene flow via informal seed exchange. The findings highlight Ethiopia’s rich durum wheat diversity, emphasizing landraces as reservoirs of adaptive alleles for breeding. This study provides genomic insights to guide conservation and the development of climate-resilient cultivars, supporting sustainable wheat production globally. Full article

Introduction: Scattering of kernels due to angular dehiscence is a key bottleneck in mechanized harvesting of oilseed rape. Materials and Methods: In this study, a dual-track “genotype–phenotype” screening strategy was established by innovatively integrating high-throughput KASP molecular marker technology and a standardized random collision phenotyping system for the complex quantitative trait of angular resistance. Results: Through the systematic evaluation of 634 oilseed rape hybrid progenies, it was found that the KASP marker S12.68, targeting the cleavage resistance locus (BnSHP1) on chromosome C9, achieved a 73.34% introgression rate (465/634), which was significantly higher than the traditional breeding efficiency (<40%). Phenotypic characterization screened seven excellent resources with cracking resistance index (SRI) > 0.6, of which four reached the high resistance standard (SRI > 0.8), including the core materials NR21/KL01 (SRI = 1.0) and YuYou342/KL01 (SRI = 0.97). Six breeding intermediate materials (44.7–48.7% oil content, mycosphaerella resistance MR grade or above) were created, combining high resistance to chipping and excellent agronomic traits. For the first time, it was found that local germplasm YuYou342 (non-KL01-derived line) was purely susceptible at the S12.68 locus (SRI = 0.86), but its angiosperm vascular bundles density was significantly increased by 37% compared with that of the susceptible material 0911 (p < 0.01); and the material 187308 (SRI = 0.78), although purely susceptible at S12.68, had a 2.8-fold downregulation in expression of the angiosperm-related gene, BnIND1, and a 2.8-fold downregulation of expression of the angiosperm-related gene, BnIND1. expression was significantly downregulated 2.8-fold (q < 0.05), indicating the existence of a novel resistance mechanism independent of the primary effector locus. Conclusions: The results of this research provide an efficient technical platform and breakthrough germplasm resources for oilseed rape crack angle resistance breeding, which is of great practical significance for promoting the whole mechanized production. Full article

Background: High-density lipoprotein cholesterol (HDL-C) is known for its cardiovascular and neuroprotective effects, but its association with cognitive function remains unclear, particularly in relation to genetic factors such as apolipoprotein E ε4 (APOE4). We aimed to investigate the association between serum HDL-C levels and cognition and to examine the moderating effect of APOE4 on this relationship. Methods: This cross-sectional study included 196 dementia-free older adults (aged 65–90) recruited from a memory clinic and the community. Cognitive function was assessed across multiple domains using the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) battery. Serum HDL-C levels were measured, and APOE4 genotyping was performed. Multiple linear regression analyses were conducted, adjusting for age, sex, APOE4 status, education, diagnosis, vascular risk, nutritional status, physical activity, and blood biomarkers. Results: Higher HDL-C levels were significantly associated with better episodic memory (B = 0.109, 95% confidence interval [CI]: 0.029–0.189, p = 0.008) and global cognition (B = 0.130, 95% CI: 0.001–0.261, p = 0.049). These associations were significantly moderated by APOE4 status. In APOE4-positive individuals, HDL-C was strongly associated with both episodic memory (B = 0.357, 95% CI: 0.138–0.575, p = 0.003) and global cognition (B = 0.519, 95% CI: 0.220–0.818, p = 0.002), but no such associations were observed in APOE4-negative participants. Conclusions: This study indicates a significant association between serum HDL-C levels and cognitive function, particularly in episodic memory and global cognition, with APOE4 status potentially moderating this relationship. While these findings may suggest a protective role of HDL-C in individuals at increased genetic risk due to APOE4, they should be interpreted with caution given the cross-sectional design. Future longitudinal and mechanistic studies are warranted to clarify causality and potential clinical implications. Full article

As high-CBD cannabis (Cannabis sativa L.) gains legal and commercial relevance in the United States, studies evaluating how external inputs impact critical traits remain limited. This study investigates the effects of methyl jasmonate (MeJA), ammonium bicarbonate (AB), and the genetic source (mother plant identity) on the growth and secondary metabolite traits of indoor cannabis. Plants were treated with 1 mM MeJA and/or AB under controlled conditions, and key traits, such as plant height, chlorophyll content, biomass, trichome density, and cannabinoid concentration, were measured. The MeJA treatment led to a significant 32% increase in trichome density. However, it did not significantly alter CBD or THC concentrations. The AB treatment enhanced vegetative growth, increasing chlorophyll content and plant height while reducing CBD concentrations, but the biomass gains could compensate for the lower cannabinoid in the total production. An interaction between MeJA and AB altered the CBD content, suggesting that MeJA may mitigate AB’s negative effect on cannabinoid synthesis. The genetic source significantly influenced most of the measured traits, highlighting the role of the genotype in trait expression and the importance of clonal consistency. These findings highlight the complex dynamics of external inputs and genetic factors in cannabis production, emphasizing the need for further research to optimize cultivation strategies. Future studies should refine input combinations and doses to improve both yield and cannabinoid profiles. Full article

Brassica napus is one of the most important oil crops. Rapid breeding of excellent genotypes is an important aspect of breeding. As a cutting-edge and reliable technique, genome-wide selection (GS) has been widely used and is influenced by many factors. In this study, ten phenotypic traits of two populations were studied, including oleic acid (C18:1), linoleic acid (C18:2), linolenic acid (C18:3), glucosinolate (GSL), seed oil content (SOC), and seed protein content (SPC), silique length (SL), days to initial flowering (DIF), days to final flowering (DFF), and the flowering period (FP). The effects of different GS models, marker densities, population designs, and the inclusion of nonadditive effects, trait-specific SNPs, and deleterious mutations on GS were evaluated. The results highlight the superior prediction accuracy (PA) under the RF model. Among the ten traits, the PA of glucosinolate was the highest, and that of linolenic acid was the lowest. At the same time, 5000 markers and a population of 400 samples, or a training population three times the size of an applied breeding population, can achieve optimal performance for most traits. The application of nonadditive effects and deleterious mutations had a weak effect on the improvement of traits with high PA but was effective for traits with low PA. The use of trait-specific SNPs can effectively improve the PA, especially when using markers with p-values less than 0.1. In addition, we found that the PA of traits was significantly and positively correlated with the number of markers, according to p-values less than 0.01. In general, based on the associated population, a GS system suitable for B. napus was established in this study, which can provide a reference for the improvement of GS and is conducive to the subsequent application of GS in B. napus, especially in the aspects of model selection of GS, the application of markers, and the setting of population sizes. Full article

Background/Objective: Dyslipidemia significantly contributes to cardiovascular disease (CVD), with triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) as key components. While genetics play a key role in lipid levels, the interplay between genetic predisposition and modifiable lifestyle factors remains unexplored in population-based studies. We aimed to study the associations between weighted polygenic risk scores (wPRS) for TG and HDL-C, lifestyle, and metabolic factors with lipid traits and CVD. Methods: In this cross-sectional study, genotype, metabolic and lifestyle data from an Israeli cohort (n = 5584 adults) were analyzed. Individual wPRSs were constructed for TG and HDL-C based on SNPs associated with each trait. Gene-environment (lifestyle and metabolic factors) associations were evaluated by stratifying participants into high wPRS (≥90th percentile) vs. lower wPRS (<90th percentile). Results: High wPRSs were significantly associated with unfavorable lipid profiles (higher TG and lower HDL-C) and elevated TG/HDL-C ratios. Males and females in the high wPRS_HDL had 97- and 10-fold higher odds of CVD, respectively (p < 0.0001). Individuals with a combined high wPRS_HDL and wPRS_TG showed a 44-fold increase in CVD odds (p < 0.0001). Obesity (BMI > 30) and HbA1c ≥5.7% were significantly associated with elevated TG and reduced HDL-C levels, particularly in high wPRS_HDL and WPRS_TG individuals, while moderate wine (1–3 drinks/week) consumption and coffee intake (≥1 cup/day) mitigated these effects, particularly among individuals with high wPRS. Conclusions: Risk stratification based on genetic, lifestyle and metabolic profiles may inform personalized prevention strategies for dyslipidemia. Full article

Network-based GWAS (NetWAS) has advanced brain imaging research by identifying genetic modules associated with brain alterations. However, how imaging risk genes exert functions in brain diseases, particularly their mediation through imaging quantitative traits (iQTs), remains underexplored. We propose a module-level polygenic risk score (MPRS)-based NetWAS framework to uncover genetic modules associated with Alzheimer’s disease (AD) through the mediation of an iQT, using amygdala density as a case study. Our framework integrates genotype data, brain imaging phenotypes, clinical diagnosis of AD, and protein–protein interaction (PPI) networks to identify AD-relevant modules (ADMs) influenced by iQT-associated genetic variants. Specifically, we conducted a genome-wide association study (GWAS) of amygdala density ($N=1515$) to identify variants associated with iQT. These variants were mapped onto a PPI network and network propagation was performed to prompt amygdala modules. The meta-GWAS of AD ($N_1=63,926$; $N_2=455,267$) was used to calculate MPRS to further identify AD-relevant modules (ADMs). Four modules that showed significant differences in MPRS between AD and controls were identified as ADM. Post-hoc analyses revealed that these ADMs demonstrated strong modularity, showed increased sensitivity to early stages of AD, and significantly mediated the link between ADMs and AD progression through the amygdala. Furthermore, these modules exhibited high tissue specificity within the amygdala and were enriched in AD-related biological pathways. Our MPRS-based framework bridges genetics, intermediate traits, and clinical outcomes and can be adapted for broader biomedical applications. Full article

Autosomal trisomy, a genetic disorder characterized by the presence of an extra autosome, is a rare but important chromosomal abnormality in horses, often associated with infertility, developmental abnormalities, and reduced life expectancy. This study represents the largest population-level screening for autosomal trisomy in horses; the analysis used single nucleotide polymorphism (SNP) panel genotype intensity data from 17,078 horses, 6601 of which were juveniles (i.e., ≤12 months of age) when genotyped. Using methodologies adapted from similar screening studies in cattle, the only aneuploidy detected was trisomy 27 in two juvenile male Irish Sport Horses (ISH) (0.03% prevalence among juveniles or 0.01% prevalence in the overall population). One ISH colt was cytogenetically confirmed and displayed no overt external phenotypic abnormalities, while cytogenetics was not undertaken on the other ISH colt, nor was it phenotypically assessed. Parentage analysis revealed that one ISH colt inherited two different copies of chr27 from the sire, demonstrating heterodisomy, likely due to a nondisjunction event during meiosis I in the sire. The other ISH colt inherited two different copies of chr27 from the dam, also indicating heterodisomy; the dam was 23 years of age when the colt was born. Based on the observed prevalence of autosomal trisomy, it can be estimated that at least 3 foals per 10,000 live births are likely to have autosomal trisomy. Though, given that only 74 (i.e., 0.004%) of horses were genotyped within a month of birth, this is likely an underestimate. The economic consequence of undiagnosed trisomy in high-value breeding horses that are potentially infertile could be substantial. As horse genotyping for parentage verification and discovery is transitioning to medium-density single nucleotide polymorphism panels, routine genomic screening for autosomal aneuploidy could be readily undertaken and potentially should form a standard screening prerequisite along with other genetic defects at horse sales. Currently, thoroughbred horses registered for racing are not genotyped, and only a limited number of sport horse studbooks are using SNP genotyping. This highlights an opportunity for those already genotyping to expand their support for breeders through low-cost, high-value chromosomal screening at the time of registration rather than incurring additional costs over the horse’s life cycle to determine the root cause of certain phenotypes owing to the undiagnosed trisomy. Full article

Aquaculture has become a crucial component of global food production, yet catfish (10.8% of global finfish production) breeding programs often lack sufficient genetic data to fully utilize their production potential. In the last 15 years, there have been improvements in this field as two high-density (HD) single nucleotide polymorphism (SNP) arrays (250K and 690K) and low-density panels have been developed for North American channel catfish (Ictalurus punctatus) and blue catfish (Ictalurus furcatus). This lack of genomic tools hinders genetic improvement efforts in other commercially relevant catfish species besides them. Therefore, this review investigated the reason behind the lack of SNP chip usage in genetic-based selections in most catfish breeding programs and the cross-species applicability of the already existing high-density SNP arrays for genotyping members of the Clariidae, African catfish (Clarias gariepinu), and Siluridae, European catfish (Silurus glanis), families. This paper systematically reviews the literature of more than 16 SNP arrays, with 66 non-target species, and assesses the possibility of adapting catfish SNP arrays to the catfish families of interest. With lowered filtering (e.g., MAF > 0) thresholds, the Affymetrix Axiom 250K and Axiom Catfish 690K Genotyping Array could potentially be used on important market species like African and European catfishes. In the long term, chip development would be the solution for these species, but, until then, cross-application is a viable alternative. Despite low polymorphic SNPs (~1%) and call rates (~0%), this SNP array could aid researchers and breeders, improving catfish aquaculture and management. Full article

The abiotic stresses associated with spring/fall freezes and extreme winter cold cause significant economic losses in blueberry production. These problems are exacerbated by climate change and increasingly erratic weather patterns. Developing freeze-tolerant blueberry cultivars with optimized cold hardiness, chilling requirement, and flowering and fruiting phenology holds promise for mitigating the risk of these weather-related damages. These weather-resilient cultivars will ensure the long-term productivity and sustainability of the blueberry industry. The focus of this review is to present the current understanding of the major components of genetic breeding for blueberry freeze tolerance, i.e., phenotyping, genotyping, genetic association analysis, and marker development. The advancement in gene regulation and corresponding proteomic changes upon cold acclimation, dormancy, de-acclamation, and flowering and fruiting aids in the understanding of the adaptive stress response in blueberries. A wide range of genetic diversity in freeze tolerance and phenological traits has been identified among cultivated and wild blueberry relatives. Significant efforts have been made to phenotype freeze tolerance, chilling requirement, and flower and fruit development in both field and controlled environmental conditions. Recent studies emphasize the need for high-throughput, image-based phenotyping of blueberry flower development to improve the precision and efficiency of selecting freeze-resilient genotypes. In addition, advancements in blueberry genomics and pangenome resources expanded the potential of variant calling and high-density linkage map construction. Genetic association studies have identified QTL regions linked to freeze tolerance in blueberries, providing valuable targets for selection. The implementation of these advanced genomic tools and high-throughput phenotyping methodology will accelerate the development of weather-resilient blueberry cultivars. Full article

Sweet corn (Zea mays L. saccharata) has emerged as a valuable crop not only for its economic potential but also for its role in sustainable food systems due to its high consumer demand and adaptability. As global agricultural systems face increasing pressure from climate change, resource scarcity, and nutritional challenges, a strategic synthesis of research is essential to guide future innovation. This review aims to critically assess and synthesize major advancements in sweet corn (Zea mays L. saccharata) research from 2010 to 2025, with the objectives of identifying key genetic improvements, evaluating agronomic innovations, and examining sustainable production strategies that collectively enhance crop performance and resilience. The analysis is structured around three core pillars: genetic improvement, agronomic optimization, and sustainable agriculture, each contributing uniquely to the enhancement of sweet corn productivity and environmental adaptability. In the genetics domain, recent breakthroughs such as CRISPR-Cas9 genome editing and marker-assisted selection have accelerated the development of climate-resilient hybrids with enhanced sweetness, pest resistance, and nutrient content. The growing emphasis on biofortification aims to improve the nutritional quality of sweet corn, aligning with global food security goals. Additionally, studies on genotype–environment interaction have provided deeper insights into varietal adaptability under varying climatic and soil conditions, guiding breeders toward more location-specific hybrid development. From an agronomic perspective, innovations in precision irrigation and refined planting configurations have significantly enhanced water use efficiency, especially in arid and semi-arid regions. Research on plant density, nutrient management, and crop rotation has further contributed to yield stability and system resilience. These agronomic practices, when tailored to specific genotypes and environments, ensure sustainable intensification without compromising resource conservation. On the sustainability front, strategies such as reduced-input systems, organic nutrient integration, and climate-resilient hybrids have gained momentum. The adoption of integrated pest management and conservation tillage further promotes sustainable cultivation, reducing the environmental footprint of sweet corn production. By integrating insights from these three dimensions, this review provides a comprehensive roadmap for the future of sweet corn research, merging genetic innovation, agronomic efficiency, and ecological responsibility to achieve resilient and sustainable production systems. Full article

The identification of causal genomic regions for liver fat accumulation in the context of metabolic dysfunction remains a challenging goal. This study aimed to identify potential endophenotypes for liver fat content and employ them in bivariate linkage searches for pleiotropic genetic regions where targeted association analysis is more likely to reveal significant variants. Multiple metabolic risk and adiposity distribution traits were assessed using the endophenotype ranking value. The top-ranked endophenotypes were then used in a bivariate linkage analysis, paired with liver fat content. Quantitative trait loci (QTLs) identified as significant or suggestive were targeted for measured genotype association analyses. The highest-ranked endophenotypes for liver fat accumulation were insulin resistance (IR), visceral adipose tissue (VAT), and high-density lipoprotein cholesterol (HDL-C). The univariate linkage analysis for liver fat content identified one significant QTL at chromosome 17p13.2 (Logarithm of odds score (LOD) = 2.90, p = 1.29 × 10⁻⁴). The bivariate linkage analysis pairing liver fat with IR and VAT improved the localization of two suggestive QTLs at 13q21.31 (LOD = 2.11, p = 9.03 × 10⁻⁴), and 6q21 (LOD = 2.35, p = 5.07 × 10⁻⁴), respectively. Targeted association analyses within the -1-LOD score regions of these QTLs revealed 17 marginally significant single nucleotide polymorphisms (SNPs) associated with liver fat content or its combination with the selected endophenotypes. The endophenotype-informed linkage analysis successfully identified regions suitable for the targeted association analysis of liver fat content, either alone or in combination with IR or VAT, leading to the discovery of marginally significant variants with potential for future functional studies. Full article

Evaluating the genetic variability of germplasms is essential for enhancing and developing superior cultivars. However, there is limited information on cultivated germplasm diversity for Australian passion fruit breeding programs. The genetic diversity of Australian passion fruit (Passiflora spp.), including 94 rootstocks and 95 scions, was evaluated to support breeding programs aimed at enhancing productivity, fruit quality, and overall crop resilience. Rootstocks were genotyped using high-density 24k Diversity Arrays Technology (DArT)-based single-nucleotide polymorphism (SNP) markers, while genetic characterization of scions was conducted using eight simple sequence repeat (SSR) markers. The resulting genetic relationships revealed significant variation within rootstock populations. Bayesian cluster analysis in STRUCTURE showed that the rootstock population was divided into six distinct genetic groups, whereas only two subpopulations were identified among the scion accessions. SNP-based genotyping further highlighted the allelic diversity of Australian rootstocks, suggesting a rich reservoir of genetic traits for rootstock improvement. These findings underscore the importance of preserving and utilizing genetic diversity in Australian passion fruit germplasm to drive the development of superior cultivars with enhanced adaptability and performance under diverse environmental conditions. Full article

In recent decades, ships’ ballast water and associated sediments have been recognized globally as significant vectors for the dissemination of non-indigenous species, which has attracted extensive attention due to its ecological and economic impacts. The characteristics of production of resting cysts in the dinoflagellate life cycle further increases the risk of biological invasions through ballast tank sediments. Despite extensive research which has characterized the species diversity of dinoflagellate cysts within ballast tank sediments, the possibility and importance of invasions caused by different ribosomal types of the same species have been paid little attention. In this study, two cultures of dinoflagellates were established through cyst germination from the ballast tank sediments collected from two ships (“THETIS” and “WARIYANAREE”) arriving at the Jiangyin Port (China) and identified as Wangodinium sinense Z. Luo, Zhangxi Hu, Yingzhong Tang and H.F. Gu by comprehensive phylogenetic analysis of rDNA sequences (including LSU, SSU, and ITS1-5.8S-ITS2). Despite the rDNA sequences of the isolates showing a generally high similarity to reference sequences, the LSU D1-D6 sequences contained up to 11 stable single nucleotide polymorphisms (SNPs), while SSU and ITS1-5.8S-ITS2 sequences exhibited up to five and two divergence sites, respectively. Moreover, phylogenetic analyses based on partial LSU and SSU rDNA sequences further indicated that strains germinated from ships’ ballast tank sediments formed a strongly supported sister clade to the strains previously isolated from Chinese and Korean waters, representing a novel ribo-type distinct from Chinese and Korean strains. Detailed morphological observations using light microscopy (LM) and scanning electron microscopy (SEM) did not find differences between our isolates and the holotype of the species in key diagnostic characteristics including the position and shape of the nucleus and chloroplasts, as well as the ASC structure, which suggested that no significant morphological divergence has occurred among these ribo-types. Acute toxicity exposure assays indicated that this ribo-type of W. sinense posed no lethal effect on rotifers at concentrations ≤ 10⁴ cells/mL, yet it remains necessary to maintain vigilance regarding the potential risk of algal blooms resulting from higher cell density or environmental changes in the invaded ecosystems. This study reports the first successful germination of W. sinense cysts from ballast tank sediments, indicating that its cysts may be widely transferred through ballast tank sediments, and presents a potential risk of bio-invasions of new genotypes of species to a region where other genotypes of the same species have been present as indigenous species. Full article

The proliferation of harmful cyanobacteria, particularly Microcystis, poses significant risks to drinking and recreational water resources, especially under the influence of climate change. Conventional monitoring methods based on microscopy for harmful cyanobacteria management systems are limited in detecting toxigenic genotypes, hindering accurate risk assessment. In this study, we developed a digital droplet PCR (ddPCR)-based method for the simultaneous quantification of total and toxigenic Microcystis in freshwater environments. We targeted the secA gene, specific to the Microcystis genus, and the mcyA gene, associated with microcystin biosynthesis. Custom-designed primers and probes showed high specificity and sensitivity, enabling accurate detection without cross-reactivity. The multiplex ddPCR assay allowed for concurrent quantification of both targets in a single reaction, reducing the analysis time and cost. Application to field samples demonstrated good agreement with microscopic counts and revealed seasonal shifts in toxigenic genotype abundance. Notably, ddPCR detected Microcystis at very low densities—down to 7 cells/mL in the mixed cyanobacterial communities of field samples—even when microscopy failed, highlighting its utility for early bloom detection. This approach provides a reliable and efficient tool for monitoring Microcystis dynamics and assessing toxin production potential, offering significant advantages for the early warning and proactive management of harmful cyanobacterial blooms. Full article