Search Results (293)

Winter durum wheat combines the benefits of autumn sowing with high grain quality but remains poorly adapted to temperate regions due to low frost tolerance. To elucidate the genetic basis of winter hardiness and support breeding for improved cold adaptation, a segregating multi-family F₂ panel (n = 270) was developed from crosses among frost-tolerant and frost-susceptible lines. GWAS identified four loci significantly associated with winter survival on chromosomes 1B, 5A, 5B, and 7B, collectively explaining 7.6–21.5% of phenotypic variance. These loci jointly improved model performance (ΔMcFadden R² = 0.230, p-value = 4.76 × 10⁻¹⁷) without evidence of epistasis, indicating additive inheritance. Predicted survival increased nearly linearly with the number of favorable alleles, highlighting the potential for pyramiding through marker-assisted or genomic selection. Three significant SNPs were converted to KASP assays, providing validated molecular tools for breeding applications. Overall, the study broadens understanding of frost-tolerance genetics in winter durum wheat beyond canonical Fr regions and delivers practical markers for improving winter hardiness in breeding programs targeting continental climates. Full article

To address issues such as attitude instability, insufficient adaptability, and poor operational quality of precision operation equipment caused by complex terrain conditions in hilly orchards, this study designed an electric carrier Self-Leveling Platform based on the 3-RRS parallel configuration. Focusing on the stability requirements of the operation plane, an automatic leveling control strategy was proposed with the constant center height of the moving platform as an additional constraint condition. Based on the inverse kinematics solution of the 3-RRS Parallel Mechanism, the analytical mapping relationship between the fuselage attitude and the compensation angle of the leveling leg crank was derived, and based on this, the working space of the Self-Leveling Platform and the maximum compensation angles of the moving platform in the pitch and roll directions were calculated. Key structural parameters were optimized using a multi-objective genetic algorithm, followed by the completion of a 3D model design and modal simulation analysis to verify the effectiveness of the structural design. Finally, leveling performance tests were conducted on a prototype. The results showed that the platform can achieve omnidirectional automatic leveling, with a maximum leveling time of 1.593 s and a maximum steady-state error of 0.62° under typical slope and load conditions. Analysis of variance results further indicated that there are significant differences in the leveling performance of the 3-RRS parallel configuration of the Self-Leveling Platform in the pitch and roll directions, demonstrating anisotropic characteristics. This study provides an effective solution for attitude stability control of orchard operation equipment in hilly areas and offers theoretical reference and technical support for the application of the 3-RRS parallel configuration in the agricultural equipment field. Full article

Background: Rhodiola quadrifida (Pall.) Fisch. & C.A. Mey. (Crassulaceae) is a rare medicinal species in the Kazakh Altai, yet information on its population structure and genetic diversity remains limited. This study presents findings from an investigation of natural R. quadrifida populations. Methods: The morphometric characteristics, population age structure, and genetic diversity of the plants were analysed using PCR-based genome profiling. Genetic diversity within R. quadrifida populations was assessed using PCR primers for binding sites complementary to a specific region at the 3′ terminus of a particular tRNA. Results: The populations exhibited variations in morphological traits, age structures, and reproductive strategies. The IVA-1, IVA-2 and KOK populations represent the most mature stages, characterized by a dominance of vegetative reproduction and a disturbed age structure, with a predominance of senile and virgin individuals. In contrast, the LIN-1 and LIN-2 population is characterized by a balanced age structure, encompassing all ontogenetic groups, and a mixed reproductive system that includes both sexual and vegetative propagation. Genetic diversity, as measured by Shannon’s information index, ranged from 0.194 to 0.247, indicating low genetic diversity in R. quadrifida. Analysis of molecular variance (AMOVA) revealed significantly greater variation within populations (62%) than among populations (38%). Genetic diversity was higher in the LIN-1 and LIN-2 populations, which employs a mixed reproductive system (clonal and seeds), than in populations dominated by vegetative reproduction. Both LIN populations, characterized by a mixed reproductive system, exhibited higher genetic diversity than the KOK, IVA-1 and IVA-2 populations, where vegetative reproduction predominated. Conclusions: These results underscore the necessity for priority conservation measures, including monitoring population size and age structure in populations with low levels of seed reproduction and disturbed age structure. Additional measures include supporting in situ and ex situ conservation, such as clonal collection, seed banks, and tissue cultures, as well as restricting the harvesting of medicinal raw materials. Full article

Age-related cognitive decline and individual differences in dementia susceptibility are increasingly explained through the concept of cognitive reserve (CR). CR reflected the brain’s adaptive capacity to sustain cognitive performance despite Alzheimer’s disease (AD)-related pathology, extending beyond traditional biomarkers that captured the molecular or structural changes, but often failed to account for clinical heterogeneity. This review provided a comprehensive synthesis of how CR was operationalized through three major methodological approaches: sociobehavioral proxies, residual variance frameworks, and neurobiological indicators within the context of longitudinal study designs. The review included evidences from a structured PubMed and Scopus search restricted to English-language studies examining the incidence of mild cognitive impairment (MCI) or AD. Findings consistently demonstrated that higher CR, most commonly estimated through sociobehavioral proxies, such as educational level, occupational complexity, bilingualism, and engagement in cognitively stimulating activities, was associated with a delayed onset of impairment, lower dementia risk, and better clinical outcomes, despite a comparable neuropathological burden. Residual variance approaches provided complementary insights by quantifying cognitive performance that exceeded the predicted levels from underlying pathology, thereby capturing unexplained variance by structural or molecular disease markers. These residual-based methods extend CR concept beyond life-course experiences, offering statistical evidence of resilience within longitudinal trajectories of aging and disease. Additional evidence from electrophysiological and genetic investigations further suggested that CR enhanced the neural efficiency, flexibility, and the recruitment of compensatory networks. Finally, neuroimaging studies provided the mechanistic evidence that CR was supported by alterations in brain structure, functional connectivity, and activation patterns, though findings on long-term trajectories remained inconsistent. Overall, CR emerged as a multidimensional and modifiable construct that enhanced resilience to aging and dementia. Future research should prioritize the integrative longitudinal designs, combining sociobehavioral, residual variance, genetic, electrophysiological, and neuroimaging approaches to clarify mechanisms, establishing robust measurement frameworks and advance clinical translation. Full article

Shendao3^# (SD3^#) exhibits perennial characteristics. Identifying the QTLs underlying the yield-related traits in SD3^# provides a theoretical basis for future perennial rice breeding. In this study, SD3^# and an F₂ population derived from a cross between SD3^# and XieqingzaoB (XQZB) and its bi-parents were selected as experimental materials. A total of fifteen yield-related traits including plant height, effective panicle per plant and thousand-grain weight in the SD3^#-population and its bi-parents were investigated for both phenotypic analysis and QTL mapping. Results indicated that the fifteen yield-related traits in the SD3^#-population exhibited quantitative genetic characteristics suitable for QTL analysis. Altogether, 25 QTLs underlying the yield-related traits and 26 pairs of epistatic QTLs were identified; these explained phenotypic variances ranging from 4.21% to 27.30% and 1.24% to 19.30%. Of these, nine novel QTLs underlying unfilled grain per panicle (UGP), spikelet per panicle (SP), seed setting density (SSD), grain yield per plant (GYP) and thousand-grain weight (TGW) with additive effects derived from SD3^# were detected on the first, second, fourth, eighth, ninth, and tenth chromosomes. Six pleiotropic QTLs underlying two or more traits were detected on the first, fourth, seventh, eighth, and eleventh chromosomes. This work lays a good foundation for both the yield-related gene mined from SD3^# and future perennial Chinese rice breeding. Full article

Capsicum spp. support diverse fresh and processing value chains, yet integrated assessments of phenotypic stability and genome-enabled prediction remain limited. In this study, 32 representative accessions, selected from a panel of 235 genotyped entries from the Colombian Capsicum germplasm collection, were evaluated across three contrasting environments to characterize physicochemical traits (texture, pH, soluble solids, color) and biochemical attributes (total carotenoids, capsaicin, dihydrocapsaicin, phenolics, antioxidant capacity). Variance partitioning and AMMI models quantified the contributions of genotype (G), environment (E), and G × E interactions (GEIs). Significant effects were detected for most traits. The AMMI analysis identified stable genotypes across locations for pH, moisture, firmness, and cohesiveness. In contrast, color attributes, total carotenoids, and phenolic compounds showed greater environmental responsiveness. Texture-related and solid content traits showed broad adaptability and high phenotypic stability, making them reliable targets for selection under variable production conditions. For the genomic component, we analyzed 235 accessions genotyped with 68,481 high-quality SNPs obtained through GBS. These data were used to estimate genomic heritability and prediction accuracy with Bayesian and semi-parametric models. Among them, BayesC showed the best performance. Prediction accuracy reached r = 0.94 within the training environment and ranged from r = 0.64 to 0.73 when tested across contrasting environments. Genomic heritability was highest for pH (h² = 0.48) and pungency-related traits, including capsaicin (h² = 0.39) and dihydrocapsaicin (h² = 0.48), indicating strong additive genetic control. Finally, by integrating AMMI-based stability analysis and BayesC genomic prediction, we identified genotypes exhibiting both high performance and environmental robustness. This combined selection approach provides a comprehensive framework for genomic-assisted breeding to enhance fruit quality, carotenoid content, and pungency stability in Capsicum spp. under heterogeneous environments. Full article

Background/Objectives: Cochlear implantation (CI) has been shown to be effective in children with inner ear malformations (IEMs). However, outcomes vary with malformation type and anatomical complexity. Advances in radiological classification may improve the understanding of such variability to better guide patient counseling. We aimed to assess one-year post-implant auditory outcomes in children with IEMs using radiology-based classifications, and to explore genetic and perinatal predictors. We also propose a preliminary severity score derived from the INCAV system. Methods: Out of 303 pediatric CI recipients assessed at a tertiary center, we retrospectively analyzed 41 children (82 ears) diagnosed with IEMs. Malformations were categorized with the Sennaroğlu system and re-coded using INCAV, from which a severity score was derived. Postoperative outcomes were assessed in 56 implanted ears, including pure-tone average (PTA), word recognition score (WRS), and post-surgical complications. Statistical analyses included Spearman’s correlation, linear regression, and exploratory discriminant MANOVA. Results: The most frequent malformation was enlarged vestibular aqueduct (33%), followed by incomplete partition type II (22%). CI was performed in 56 malformed ears with a complication rate of 10.7%. PTA and WRS correlated with the INCAV-derived severity score, with higher severity linked to poorer thresholds and lower WRS. Linear regression showed severity explained ~20% of PTA variance, with outcomes more frequently impaired in ears with scores > 3. Exploratory analysis revealed inter-subject variability, with partial separation of mild versus moderate/severe groups mainly driven by PTA and WRS. Conclusions: CI in pediatric IEMs is safe and consistently improves hearing thresholds. PTA was the most robust predictor of performance, while the INCAV-derived severity score, though exploratory, may provide additional value for anatomical stratification, prognostic counseling, and rehabilitation planning. Full article

Tomato (Solanum lycopersicum) is the most important vegetable crop globally; however, its production is often hindered by soil-borne biotic and abiotic stresses. The use of rootstocks provides an effective strategy to mitigate these soil-related challenges. Hence, the development of new rootstock cultivars remains crucial to meet the demands of rapidly changing environmental conditions. Wild tomato species represent valuable genetic resources for rootstock improvement and are increasingly utilized in rootstock breeding programs. Nevertheless, the genetic mechanisms, particularly quantitative trait loci (QTL), underlying rootstock–scion interaction, remain poorly understood. In this study, 38 introgression lines (ILs) derived from S. lycopersicoides were used as rootstock and grafted with the commercial cultivar ‘Torry F₁’ to evaluate their effects on morphological and fruit quality traits under greenhouse conditions. The evaluations included assessments of morphological and fruit quality traits for QTL analysis. A total of 19 QTLs were identified, associated with 11 traits such as yield, antioxidant capacity, flavonoid content, and fruit color parameters (L*, a*, b*, C*, h°), with the phenotypic variance explained ranging from 12% to 61%. Of these QTLs, seven favorable alleles originated from S. lycopersicoides, notably including a major yield-associated locus (Fy5.1). In addition, the identification of a QTL for scion stem thickness (Tsc3.1) highlights the genetic contribution of the rootstock to scion development. This study represents the first evaluation of the rootstock potential of S. lycopersicoides ILs and provides novel insights into the genetic basis of rootstock–scion interaction in tomato. The identified QTLs offer valuable information for future breeding efforts aimed at developing improved rootstock cultivars for sustainable tomato production. Full article

Background: Leukemia comprises heterogeneous hematologic malignancies, and whether circulating metabolites contribute causally to subtype-specific risk remains uncertain. Objectives: The aim of this study was to assess the causal effects of plasma metabolites for acute myeloid leukemia (AML), chronic myeloid leukemia (CML), acute lymphoblastic leukemia (ALL), and chronic lymphocytic leukemia (CLL). Methods: A two-sample Mendelian randomization (MR) using summary-level genome-wide association study statistics was conducted. For each metabolite, a single variant showing the strongest association with the metabolite that had the largest variance explained (R²) among the independent genome-wide significant (p < 5 × 10⁻⁸) SNPs assigned to effector genes was selected as sentinel. Multiple comparisons using Bonferroni correction (0.05/83 = 6.02 × 10⁻⁴) were applied to minimize the risk of obtaining false positive results. Results: Totally, 83 metabolites and metabolite ratios were analyzed for AML, CML, ALL, and CLL. Lithocholate sulfate (1), instrumented by the rs10425975 variant in the SULT2A1 gene, was significantly associated with an increased risk of CLL (OR = 2.19; 95% CI: 1.45–3.31; p = 2 × 10⁻⁴). An additional 17 metabolite-leukemia associations showed suggestive evidence of significance. Approximately 300 drug entries linked to candidate metabolites were curated to provide a basis for mechanistic follow-up. Conclusions: Our MR result supports a causal link between higher genetically proxied lithocholate sulfate (1) and increased CLL risk. The discovery of these “metabolite-gene-drug” relationships suggests a central role in leukemia pathogenesis and warrants further functional investigation for their therapeutic potential. Full article

Reproductive performance in rabbits is highly sensitive to seasonal environmental variation and management practices, while the proportion of variance attributable to additive genetics for litter-level traits is typically low. The objective of this study was to evaluate the effects of year and season on litter size at birth (BR), litter size at weaning (WR), and weaning rate (WT), and to estimate the heritability of these traits in a commercial rabbit farm. A total of 770 kindling events recorded between 2015 and 2021 were analyzed. The mixed model for BR included the fixed effects of year and season, and the random effects of sire and residual error. The model for WR included the same structure, with BR added as a covariate. Least-squares means for fixed effects were used for pairwise comparisons using Tukey’s test. Year and season effects were significant for BR (p < 0.005), and the year effect was also significant for WR (p < 0.021). Litter size at birth ranged from 7.80 (dry season) to 9.21 (year 2020), with higher means observed during the semi-dry (8.52) and humid (8.56) seasons compared to the dry season (7.80). Litter size at weaning varied between 4.65 and 5.81 kits depending on the year. Weaning rate showed interannual variation (56.1–68.2%), but seasonal differences did not reach statistical significance (p < 0.075). Heritability estimates from the sire variance component were low: 0.01 for BR, 0.04 for WR, and 0.05 for WT. These results indicate that phenotypic variation in prolificacy in this population was predominantly driven by interannual and seasonal environmental factors, as well as perinatal management practices, while the additive genetic contribution was marginal. Full article

Background/Objectives: This study was designed to investigate the potential causal relationship between uterine fibroids (UF) and breast cancer (BC) using genetic data in East Asian populations. Methods: We conducted a bidirectional two-sample Mendelian randomization (MR) analysis of UF and BC, selecting exposure-associated single-nucleotide polymorphisms (SNPs) from Biobank Japan and extracting outcome associations from the China Kadoorie Biobank for both directions. The primary estimator was inverse-variance-weighted (IVW), with robustness assessed using the weighted median, MR-Egger regression, and the MR-pleiotropy residual sum and outlier (MR-PRESSO). Results: The SNPs with (p < 5.0 × 10⁻⁸) were selected as instrumental variables for UF (n = 16) and BC (n = 7). There was no evidence of heterogeneity in either direction. Genetically predicted UF was positively associated with BC risk (odds ratio, 1.33; 95% confidence interval, 0.99–1.79; p = 0.063), although the association did not reach statistical significance in IVW. In addition, the causal effect of BC on UF was significant (odds ratio, 1.19; 95% confidence interval, 1.08–1.32; p < 0.001 in IVW). Conclusions: Our study suggested a borderline significant causal effect of UF on BC. Moreover, BC demonstrated a significant causal association with UF, underscoring the need for further research into the role of various mechanisms including estrogen in the relationship between the two diseases. Full article

White leg markings in horses are phenotypic traits influenced by genetic and environmental factors. This study analyzed their prevalence, symmetry, and genetic parameters in 38,825 Pura Raza Española (PRE) horses registered in the official studbook. White markings were scored using a binary (affected/unaffected) and a four-level ordinal scale. Most horses (38,341 out of 38,825; 98.8%) had at least one limb without white markings. The prevalence of white markings was higher in the hindlegs (17.9% LH; 14.5% RH) than in the forelegs (5.3% LF; 4.6% RF). Markings were most frequent above the fetlock (≈64%), chestnut horses showed the highest prevalence, whereas black coats showed the lowest. Genetic analyses using Bayesian animal models revealed moderate-to-high heritabilities, ranging from 0.488 for Right hindlegs to 0.574 for Left hindlegs in the multinomial model, which outperformed the dichotomous model (h² = 0.030–0.515 for all legs and left foreleg, respectively). Additive genetic variance was highest in the left hindleg (σ²_u = 7.904). Genetic correlations were high between contralateral homologous limbs (0.991 forelegs; 0.995 hindlegs), confirming strong bilateral genetic control, while diagonal correlations were lower (≈0.886). These findings confirm a substantial genetic component underlying white leg markings in PRE horses and highlight the importance of refined phenotyping and genetic evaluations for breeding strategies, particularly when markings are penalized as in the PRE breeding program. Full article

Background/Objectives: Previous studies suggest that nutrient deficiencies can alter immune responses in animals. However, the impact of micronutrients on autoimmune diseases like type 1 diabetes (T1D) in humans remains unclear since the described associations are based on observational data and they cannot establish causality. This study aims to examine the causal relationship between various micronutrients and T1D using Mendelian randomization (MR). Methods: We performed a two-sample MR analysis using genetic variants from genome-wide association studies (GWASs) of 17 micronutrients as instrumental variables (IVs). We analyzed T1D GWAS datasets of European (18,942 cases/520,580controls), multi-ancestry (25,717 cases/583,311 controls), Latin American/Hispanic (2295 cases/55,134 controls), African American/Afro-Caribbean (6451 cases/109,410 controls), and East Asian (1219 cases/132,032 controls) ancestries. We applied the inverse variance weighted (IVW) method in our main analysis, and additional MR estimators (MR-Egger, weighted median, weighted mode, MR-PRESSO) to address pleiotropy, and the Steiger test to test directionality in sensitivity analyses. Results: Following Bonferroni correction (p < 0.05/17), we found positive association between potassium levels and T1D risk (OR = 1.098, 95% CI [1.075, 1.122] p = 5.5 × 10⁻¹⁸) in the multi-ancestry analysis. Zinc, vitamin B12, retinol, and alpha tocopherol showed nominal associations. Vitamin C, D, K1, B6, beta- and gamma-tocopherol, magnesium, iron, copper, selenium, carotene, and folate showed no significant effects on T1D risk. For the multi-ancestry analysis, we had sufficient power to detect ORs for T1D larger than 1.065. Conclusions: Higher serum potassium levels were associated with increased T1D risk in our MR study, though supporting observational evidence is currently limited. Other micronutrients are unlikely to have large effects on T1D. Full article

The present study aimed to determine the Genotype × Environment interaction (GEI), yield stability, and agronomic performance of 24 “Pinto” bean lines under semi-arid conditions in Central-West Mexico. All the lines possess a slow-darkening seed coat, a trait that prolongs visual quality and increases market value. The lines, which exhibit an indeterminate prostrate growth habit, were evaluated in three contrasting environments: irrigated, rainfed, and drought-stressed. A combined analysis of variance, Tukey’s test, and the additive main effects and multiplicative interaction (AMMI 2) model were applied to assess seed yield and agronomic traits. Average seed yield declined markedly across environments, from 2279 kg ha⁻¹ under irrigation to 593 kg ha⁻¹ under drought stress, with different lines performing best in each environment. AMMI 2 biplot analysis showed that the first two principal components explained 100% of GEI variability for seed yield, dry shoot biomass, total biomass, harvest index, pods per plant, and seeds per pod. Both genetic and environmental effects were significant, with notable GEI patterns. Despite pronounced environmental influence, several lines exhibited stable performance across environments. Line 11 consistently combined high yield and stability, positioning it as a strong candidate for cultivar registration and as a parent in breeding programs targeting semiarid regions. These results underscore the importance of multi-environment evaluation for identifying genotypes with broad or specific adaptation, contributing to genetic improvement and sustainable bean production under variable moisture regimes. Full article

The accuracy of genomic selection has a significant impact on the selection of superior individuals in livestock. Studies have reported that integrating GWAS information can improve the accuracy of genomic prediction. In this study, phenotypic data, systematic environmental data, and genotypic data of important economic traits (cashmere yield, cashmere diameter, body weight, and cashmere length) of Inner Mongolia cashmere goats were utilized. Based on the results of a previous genome-wide association study that considered additive and dominance effects, the top 5%, top 10%, top 15%, and top 20% of loci were extracted as prior marker information. The genomic breeding values for each trait were estimated using the GBLUP–GA method based on GWAS prior information, and the accuracy of genomic prediction was further evaluated using a five-fold cross-validation method. The results showed that the contribution of significant loci to the genetic variance of each trait gradually increased with an increase of the number of integrated loci. The genetic variance contribution rates of significant loci to cashmere yield, cashmere diameter, body weight, and cashmere length were 64–71%, 47–57%, 76–82%, and 66–80%, respectively. The additive heritability estimates for cashmere yield, cashmere diameter, body weight, and cashmere length using GWAS prior information were 0.252–0.266, 0.297–0.580, 0.305–0.330, and 0.107–0.117, respectively. These values were higher than those obtained using the traditional G matrix constructed from all loci, with increases of 0.052–0.066, 0.007–0.29, 0.134–0.159, and 0.015–0.025, respectively. The results of genomic prediction accuracy showed that when 5% of the GWAS prior information was integrated, the highest genomic prediction accuracy was achieved for cashmere yield (0.8156), body weight (0.8361), and cashmere length (0.7571). When 20% of the GWAS prior information was integrated, the genomic prediction accuracy for cashmere diameter was 0.8074, which was significantly higher than that at other levels. Additionally, it was found that the dominance heritability for cashmere diameter, body weight, and cashmere length was very small and could be ignored when integrating GWAS prior information. Therefore, when integrating prior information for genomic selection of these traits, the influence of dominance effects can be disregarded. Full article