Search Results (1,536)

Climate change poses a significant threat to agricultural productivity, particularly in low-input systems where resilient cultivars are crucial. Traditional pepper (Capsicum annuum L.) landraces represent a valuable genetic reservoir for adaptation, yet their agronomic and nutritional potential remains underexplored. In this study, twenty-five Greek pepper landraces and commercial varieties were comprehensively evaluated for morphological traits, early and total yield characteristics, and key fruit quality parameters. The results revealed substantial phenotypic diversity in both vegetative and reproductive traits, as well as considerable variation in fruit nutritional composition across the tested genotypes. Notably, ‘Skopos’, ‘Mesoropi’, and ‘Lygaria’ demonstrated superior yield performance, while ‘Pogoniou’, ‘Lyra’, and ‘Kantanou’ excelled in several nutritional quality traits, including high phenolic content, vitamin C, and antioxidant capacity. Heatmap analysis further identified ‘Pogoniou’, ‘Filuria’, ‘Lyra’, ‘Lagada’, and ‘Lygaria’ as consistently ranking among the top performers across yield and quality traits. These findings highlight the dual agronomic and nutritional value of traditional pepper landraces, underscoring their importance as a genetic resource for breeding programs. Overall, the study highlights the importance of conserving and utilizing local pepper germplasm as a sustainable approach to improve productivity, nutritional quality, and resilience in the face of climate change and low-input cultivation systems. Full article

Background/Objectives: Morphological defects such as limb malformations, cranial asymmetries, loin deviations, jaw misalignments, and navel irregularities are associated with early culling and reduced productivity in beef cattle. In Bos taurus indicus such as Nellore, the genetic basis of these traits remains poorly characterized. This study aimed to investigate the genetic architecture of six morphological defects in Nellore cattle, namely feet and legs malformation, chamfer asymmetry, fallen hump, loin deviation, jaw misalignment, and navel irregularities, via a genome-wide association study (GWAS) approach tailored for binary traits. Methods: Depending on the trait, the number of genotyped animals analyzed ranged from 3369 to 23,206, using 385,079 SNPs (after quality control). Analyses were conducted using a linear mixed model framework adapted for binary outcomes. Results: Significant associations were identified for four traits: feet and legs, chamfer, hump, and loin. No significant markers were detected for jaw or navel defects, likely due to lower sample sizes and trait incidence. Gene annotation revealed 49 candidate genes related to feet and legs, 4 for chamfer, 4 for hump, and 6 for loin. Conclusions: Candidate genes were enriched for biological functions, including bone remodeling, muscle development, lipid metabolism, and epithelial organization. Overlaps with QTL related to conformation, feed intake, reproductive traits, and carcass quality were also observed. These findings provide novel insights into the genetic control of morphological defects in Nellore cattle and may inform breeding strategies aimed at improving structural soundness. Full article

Piscine orthoreovirus (PRV) is a globally distributed viral pathogen that causes heart and skeletal muscle inflammation (HSMI) in Atlantic salmon (Salmo salar) and affects other salmonids, yet no commercial vaccines are currently available. Major barriers to vaccine development include the inability to propagate PRV in cell lines and the low, variable immunogenicity of its proteins, particularly the outer capsid protein σ1, which mediates viral attachment. This protein is hypothesized to be immunologically relevant due to its homology with Mammalian orthoreoviruses. Recombinant σ1 expressed in conventional systems exhibits poor antibody recognition, whereas structural modifications such as lipidation or fusion with molecular chaperones improve epitope exposure. Formalin-inactivated vaccines have shown inconsistent protection, often failing to elicit robust innate or adaptive responses, especially under cohabitation challenge. In contrast, DNA vaccines encoding σ1 and the non-structural protein μNS have demonstrated partial efficacy, likely due to enhanced intracellular expression and antigen presentation. Nonetheless, the considerable variability observed in immune responses among individual fish and viral genotypes, together with suggestions that PRV may interfere with antiviral pathways, represent additional barriers to achieving consistent vaccine efficacy. This review summarizes the current status of PRV vaccine development and discusses future directions for rational design based on optimized antigens and intracellular delivery platforms. Full article

Drought limits plant growth, development and productivity, leading to more than 50% crop loss globally. Drought-induced oxidative stress disturbs the plant’s metabolism; however, plants activate signaling pathways to respond and adapt to drought stress. Although drought response mechanisms are well reported in several crops, these mechanisms are poorly understood in Amaranthus. As a highly nutritious crop, rich in antioxidants with the ability to survive in extreme agro-climatic environments, Amaranthus has the potential to serve as a climate-smart future crop. This review provides evidence of some drought response traits in grain and vegetable Amaranthus species. Grain amaranths are the most tolerant species, mainly through improved osmoregulation, antioxidant capacity, and gene expression. While biomass partitioning, efficient water use, and membrane stability have been reported in both grain and vegetable amaranth, the molecular response of vegetable amaranth remains limited. Thus, future research must focus on integrated biochemical, molecular, and multi-omics applications to screen and identify resilient Amaranthus genotypes under drought for sustainable agriculture. Full article

Left ventricular non-compaction cardiomyopathy (LVNC) is an uncommon myocardial phenotype characterized by prominent trabeculae and deep blood-filled recesses. The expanding use of cardiac magnetic resonance (CMR) has increased detection, yet uncertainty persists about whether LVNC is a distinct disease or a phenotype that overlaps with other cardiomyopathies. LVNC expression reflects the interplay among genotype, sex, ancestry, and hemodynamic load and thus serves as a model for precision cardiology. We conducted a narrative review of literature published between January 2000 and April 2025 in major databases. We included clinical studies with at least 10 patients, meta-analyses, reviews, and consensus statements addressing pathophysiology, genetics, diagnosis, prognosis, and treatment. Sarcomeric variants account for a substantial fraction of cases and connect LVNC with dilated and hypertrophic cardiomyopathies. Echocardiographic and CMR criteria identify the phenotype but blur the boundary between physiological and pathological hypertrabeculation. Fibrosis on late gadolinium enhancement and systolic dysfunction are consistently associated with worse outcomes. Current management largely adapts heart-failure strategies, including neurohormonal blockade, SGLT2 inhibitors, and implantable cardioverter-defibrillators in selected high-risk patients. Optimal care integrates clinical, imaging, and genetic information. The lack of universal diagnostic criteria highlights the need for prospective studies and consensus to standardize diagnosis and treatment. Future algorithms that combine multi-omics, quantitative imaging, and AI-based risk prediction could individualize surveillance, pharmacotherapy, and device therapy. Full article

Heike 88, a new soybean variety developed through strategic hybridization of Heijiao 08-1611 × Heihe 43 followed by pedigree selection, was evaluated across seven locations in Heilongjiang Province from 2019 to 2022. The variety demonstrated stable performance with a 10.3% average yield advantage over regional check varieties and mean yields of 3188 kg ha⁻¹. Principal component analysis revealed that genetic variation accounted for 43.4% and 32.6% of performance variance in the first two components, indicating successful transgressive segregation where the pure line exceeded both parental lines through complementary gene action. Performance relative to parental averages ranged from −20% to +40% across the temperature gradient, demonstrating strong genotype-environment interaction effects. Machine learning analysis identified year effect (13% importance), accumulated temperature (7.6% importance), and oil content (4% importance) as primary yield drivers. Complete resistance to soybean mosaic virous (SMV) and cyst nematode attack was observed across all locations, with excellent gray leaf spot resistance (grades 0–1) maintained under natural pathogen pressure. Seed quality parameters remained stable across environments, with protein content ranging from 41.69% to 42.25% and oil content from 19.74% to 20.13%, indicating minimal environmental effects on compositional traits. Yield stability improved progressively over the evaluation period, with the coefficient of variation decreasing from 18.7% in 2019 to 6.7% in 2022, while absolute yields increased from 2550 to 3200 kg ha⁻¹. These results demonstrate successful exploitation of transgressive segregation for regional adaptation through strategic parent selection and pedigree breeding, supporting commercial deployment in northern China’s challenging production environments while providing methodological guidance for future breeding programs targeting environmental specificity. Full article

Understanding how complex biological forms emerge and evolve remains a central question in evolutionary and developmental biology. To explore this complexity, we introduce a minimal two-dimensional, cellular automaton (CA)-based model that captures key features of biological development—such as spatial growth, self-organization, and differentiation—while remaining computationally tractable and evolvable. Unlike most abstract genotype–phenotype mapping models, our approach generates emergent morphological complexity through spatially explicit rule-based interactions governed by a simple genetic vector, resulting in self-organized patterns reminiscent of biological morphogenesis. Using simulations, we show that, as observed in empirical studies, the resulting phenotypic distribution is highly skewed: simple forms are common, while complex ones are rare. The model exhibits a strongly non-linear genotype-to-phenotype mapping in such a way that small genetic changes can lead to disproportionately large morphological shifts. Notably, transitions toward complexity are less frequent than regressions to simplicity, reflecting evolutionary asymmetries observed in natural systems. We further demonstrate that, by allowing for mutations in the generative rules, our model is capable of adaptive evolution and even reproducing generic features of tumoral growth. These findings suggest that even minimal developmental rules can give rise to rich, hierarchical patterns and complex evolutionary dynamics, positioning our CA-based model as a powerful tool for investigating how developmental constraints and biases shape morphological evolution. Full article

Wild potato relatives are vital for breeding programs to tackle rising temperatures. This study proposes a methodological approach based on the examination of genetic variation among 19 accessions belonging to Solanum chacoense and Solanum commersonii from the Embrapa Potato Genebank under heat stress (HS). Heat tolerance coefficient (HTC) was calculated using genotypic values predicted through mixed models. After 15 days of heat stress (DHS), a significant variation in gas exchange and chlorophyll fluorescence indicates strong breeding potential and photosystem resilience. By 35 DHS, increased pigment variation suggests acclimation. Based on predicted genotypic values, S. chacoense outperforms S. commersonii in tuber production and gas exchange under HS, and principal component analysis (PCA) performed using the HTC shows early resistance driven by photosynthesis, mid-term by tuber yield, and long-term by gas exchange and tuber production. Genotypes BRA00167017-3, BRA00167023-1, BRA00167025-6, and BRA00167028-0 excel in heat comprehensive evaluation values (HCEVs)/comprehensive principal component value (F) rankings, demonstrating robust photosynthesis, thermoregulation, and tuber yield. Cluster analysis identifies these as highly tolerant, ideal for breeding heat-resilient potatoes. These PCA-derived weights and genotype clustering system provide a precise tool for selecting heat-tolerant wild potato germplasm, categorizing them into highly tolerant, moderately tolerant, sensitive with late recovery, and highly sensitive groups acquired for specific objectives of the breeding programs to climate change. Full article

In Uganda, rain-fed crops frequently encounter cycles of drought stress followed by rewatering. Thus, with escalating fluctuations in water supply, drought recovery has become a critical focus for future sorghum drought phenotyping, genetics, and breeding research. However, there is currently a low knowledge of the drought recovery potential of prospective genotypes in Uganda’s National Sorghum Improvement Program. The present study aimed to assess the response of selected genotypes to rewatering after drought. Sixteen sorghum genotypes and two check varieties were evaluated under two contrasting moisture regimes: well-watered and drought stress-rewatering in a split-plot layout using a randomized complete block design (RCBD). Watering regimes were assigned to whole plots, while sorghum genotypes were assigned to subplots, with three replications. The results showed highly significant effects (p < 0.05) of drought stress on key agronomic traits, decreased dry weight, grain weight, and biomass yield by 39%, 43% and 37%, respectively, and delayed flowering by an average of 11 days. Key genotype-specific traits associated with drought recovery included rapid rehydration, compensatory growth, and maintenance of high relative chlorophyll content, all of which were essential for optimizing yields after stress. Leveraging drought tolerance indices, genotypes were ranked by their recovery potential and further classified into four distinct groups (A–D) based on their yield performance and stability under the two watering regimes. Genotypes in category A demonstrated high yield stability and strong recovery potential. Conversely, genotypes in category D exhibited the poorest recovery response. Overall, the information generated from this study will support future sorghum breeding efforts for drought resilience. Full article

Dioscorea polystachya (Chinese yam) is a crop valued for both medicinal and edible purposes, and exhibits rich genetic diversity. However, research into its germplasm resources remains understudied, and molecular breeding efforts lag behind. To bridge this gap, this study employed an integrated approach, combining the analysis of 23 phenotypic traits (17 qualitative and 6 quantitative) with genotyping using 19 polymorphic SSR markers. This combined strategy was applied to 53 accessions collected across 16 Chinese provinces to assess genetic diversity, population structure, and marker–trait associations. Phenotypic analysis revealed high diversity, with the Shannon diversity index (I) ranging from 0.09 to 1.15 for qualitative traits and from 1.45 to 1.79 for quantitative traits. Tuber traits exhibited the highest variability (with a CV up to 71.45%), indicating significant potential for yield improvement. Principal component analysis distilled phenotypic variation into eight principal components (accounting for 73.13% of the cumulative variance), and elite germplasm (e.g., DP24, DP52) was selected for breeding based on this analysis. Stepwise regression prioritized eight core evaluation traits (e.g., flowering rate, tuber length). SSR markers amplified 80 alleles (mean 4.211/locus), showing moderate genetic diversity (He = 0.529, PIC = 0.585). Population structure analysis divided accessions into two subpopulations, correlated with geographic origins: Group 1 (northern/southwestern China) and Group 2 (central/eastern China), reflecting adaptation to local climates and human selection. Association analysis identified 10 SSR loci significantly linked (p < 0.01) to key traits, including YM07_2 (flowering, R² = 13.94%), YM37_2 (leaf margin color, R² = 19.03%), and YM19_3 (leaf width, R² = 19.34%). This study establishes a comprehensive genetic framework for Chinese yam, offering molecular tools for marker-assisted breeding and strategies to conserve high-diversity germplasm, thereby enhancing the utilization of this orphan crop. Full article

‘Pera’ sweet orange is a key variety for the Brazilian citrus industry, but orchards rely on a limited number of clonal selections, which restricts adaptability and productivity across diverse environments. This study assessed the agronomic performance of 13 ‘Pera’ selections grafted on Rangpur lime, cultivated under rainfed conditions in subtropical Brazil. From 2002 to 2010, trees were assessed for vegetative growth, cumulative yield, alternate bearing, and fruit quality. Market-specific performance indices were calculated to determine suitability for fresh fruit or juice processing. Substantial genotypic variation was observed across traits, particularly during early orchard stage. Selections such as ‘Morretes’, ‘Seleção 11’, ‘Seleção 27’, ‘Seleção 37’, and ‘IPR 153’ demonstrated high cumulative yield, stable productivity, and favorable canopy traits, supporting their use in both conventional and high-density systems. ‘IPR 153’ combined compact growth with high yield efficiency and excellent fruit quality, while ‘Morretes’ had the highest juice content and broad market adaptability. In contrast, ‘IPR 159’ showed low vigor and yield under rainfed conditions. The results emphasize the value of regionally targeted clonal selection to improve orchard performance and market alignment. The identification of dual-purpose genotypes offers a pathway to diversify citrus production and improve profitability under subtropical growing conditions. Full article

We consider optimization for different production requirements from the viewpoint of a bio-inspired framework for system flexibility that allows us to study the ability of an algorithm to transfer solutions from previous optimization tasks, which also relates to dynamic evolutionary optimization. Optimizing manufacturing process parameters is typically a multi-objective problem with often contradictory objectives, such as production quality and production time. If production requirements change, process parameters have to be optimized again. Since optimization usually requires costly simulations based on, for example, the Finite Element method, it is of great interest to have a means to reduce the number of evaluations needed for optimization. Based on the extended Oxley model for orthogonal metal cutting, we introduce a multi-objective optimization benchmark where different materials define related optimization tasks. We use the benchmark to study the flexibility of NSGA-II, which we extend by developing two variants: (1) varying goals, which optimizes solutions for two tasks simultaneously to obtain in-between source solutions expected to be more adaptable, and (2) active–inactive genotype, which accommodates different possibilities that can be activated or deactivated. Results show that adaption with standard NSGA-II greatly reduces the number of evaluations required for optimization for a target goal. The proposed variants further improve the adaption costs, where on average, the computational effort is more than halved in comparison to the non-adapted baseline. We note that further work is needed for making the methods advantageous for real applications. Full article

Background/Objectives: Paspalum nicorae Parodi is a native subtropical grass species with promising agronomic attributes, such as persistence, drought and cold tolerance, and rapid establishment. However, the species remains underutilized in breeding programs due to the absence of well-characterized germplasm and limited studies on its genetic variability and agronomic potential. This study aimed to estimate genetic parameters, predict genotypic values, and identify superior ecotypes with desirable forage traits, integrating stability and adaptability analyses. Methods: A total of 84 ecotypes were evaluated over three consecutive years for twelve morphological and forage-related traits. Genetic parameters, genotypic values, and selection gains were estimated using mixed models (REML/BLUP). Stability was assessed through harmonic means of genotypic performance, and the multi-trait genotype–ideotype distance index (MGIDI) was applied to identify ecotypes with balanced performance across traits. Results: Substantial genetic variability was detected for most traits, particularly those related to biomass accumulation, such as total dry matter, the number of tillers, fresh matter, and leaf dry matter. These traits exhibited medium to high heritability and strong potential for selection. Ecotype N3.10 consistently showed superior performance across productivity traits while other ecotypes, such as N4.14 and N1.09, stood out for quality-related attributes and cold tolerance, respectively. The application of the MGIDI index enabled the identification of 17 ecotypes with balanced multi-trait performance, supporting the simultaneous selection for productivity, quality, and adaptability. Comparisons with P. notatum suggest that P. nicorae harbors competitive genetic potential, despite its lower level of domestication. Conclusions: The integration of REML/BLUP analyses, stability parameters, and ideotype-based multi-trait selection provided a robust framework for identifying elite P. nicorae ecotypes. These findings reinforce the strategic importance of this species as a valuable genetic resource for the development of adapted and productive forage cultivars in subtropical environments. Full article

Climate change poses serious challenges to Mediterranean crops such as the olive tree (Olea europaea L. subsp. europaea), underscoring the need for cultivars with improved drought tolerance and disease resistance. This study investigates variability in leaf and wood traits among Moroccan and introduced olive cultivars and their crossbreed genotypes grown under similar conditions. Specifically, we assessed (1) variation in key functional traits, (2) the effects of crossbreeding combinations, and (3) trait syndromes shaped by selection. Results showed substantial intraspecific variation in leaf traits, including specific leaf area (SLA), specific leaf water content (SLWC), stomatal size (SS), and density (SD), indicating diverse strategies for resource use and plasticity. Crossbreed genotypes generally displayed higher SLWC and lower SLA, reflecting adaptation to water stress. Wood traits, particularly vessel size (SVS) and number (NVS), also varied, revealing trade-offs between hydraulic efficiency and safety. Notably, an increase in vessel size and hydraulic conductivity was correlated with oil content (OC%), while OC% increased with higher vessel and stomatal densities. Larger stomata increased conductance and fruit growth, while lower SLA was linked to higher yield. Multivariate analysis distinguished two genotype groups, consistent with parental combinations. Overall, crossbreeding generated novel functional diversity that may enhance adaptive potential. These findings highlight the value of integrating functional and anatomical traits into olive breeding programs to improve resilience and productivity under climate change. Full article

Analysis of selection signatures in the genomes of farm animals enables the detection of genomic regions affected by selection and contributes to the identification of genes underlying adaptive and productive traits. This research aimed to identify loci under selection pressure and to detect candidate genes in Dzhalgin Merino sheep by performing a comparative genomic analysis with the related Australian Merino and Rambouillet breeds. A total of 293 animals were included in the analysis, comprising Dzhalgin Merino (n = 53), Australian Merino (n = 50), Australian Industry Merino (n = 88), and Rambouillet (n = 102). Whole-genome SNP genotyping data for Dzhalgin Merino were generated within this study, while data for Australian Merino, Australian Industry Merino, and Rambouillet were obtained from the SheepHapMap project. For the purposes of analysis, Australian Merino and Australian Industry Merino were combined into a single group (n = 138). To enhance the reliability of the results, three independent methods were employed to detect selection signatures: the fixation index (FST), analysis of linkage disequilibrium variation (varLD), and the cross-population number of segregating sites by length (xp-nSL). The study showed that Dzhalgin Merino have unique genetic signatures potentially associated with adaptation and productivity, which opens up new opportunities for their selection. The identified genes can become the basis for developing new breeding programs aimed at improving both the productive qualities and the adaptive abilities of the breed. Further research should be aimed at a detailed investigation of gene structure within loci under selection pressure and at clarifying the mechanisms by which these genes influence animal phenotypes. A total of 185 genes were identified within genomic regions exhibiting selection signatures. Among these, particular attention was given to EPHA6, MLLT3, ROBO1, KIAA0753, MED31, SLC13A5, and ELAVL4, which are involved in biological processes such as growth, development, and reproduction. The identified genes represent potential targets for breeding programs aimed at increasing productivity and adaptive capacity of the breed. Full article