Search Results (254)

Background/Objectives: Bud sports (somatic mutations) offer a quick way to develop new bougainvillea varieties by altering specific traits while keeping the desirable genetic background of the original cultivar. However, we still lack a comprehensive understanding of their genomic architecture and the molecular mechanisms behind their formation. This study aimed to characterize the population genomic characteristics of bud sports derived from the commercial variety Bougainvillea × buttiana ‘Miss Manila’. Methods: We employed genotyping by sequencing (GBS) on 39 accessions, including 27 bud sports and 12 conventional varieties. Population genomic analyses, such as principal component analysis (PCA), phylogenetic reconstruction, ADMIXTURE, and diversity statistics (π, He, Tajima’s D), were performed on 64,810 high-quality SNPs. Genome-wide scans for differentiation (FST) and selective sweeps (XP-CLR) were also conducted. Results: Bud sports showed significantly lower genetic diversity (π and He) than conventional varieties, which matches their clonal origin. PCA, phylogenetic, and ADMIXTURE analyses (optimal K = 4) revealed clear genetic differentiation and distinct population structures between the two groups. The bud sport population possessed fewer private alleles and a less negative Tajima’s D value. Genomic scans identified regions under selection in bud sports, with functional annotation pointed to genes involved in ubiquitin-mediated proteolysis and RNA transport. Notably, Bou_119143 (UDP-rhamnose rhamnosyltransferase 1) showed a high mutation frequency specifically in bud sports. Conclusions: We provide the first population-genomic evidence that bud sports of ‘Miss Manila’ are genetically distinct clonal lineages, shaped by somatic mutation and selection. These findings support bud sports as efficient sources for germplasm innovation. The identified genomic regions and candidate genes lay a foundation for future marker-assisted selection and molecular breeding in bougainvillea. Full article

This study provides a comparative analysis of phenotypic variability in the morphological traits of tench (Tinca tinca L.) reared under aquaculture conditions and those from a natural population in southern Kazakhstan. The aim of the study was to evaluate phenotypic plasticity and adaptive differentiation between populations shaped by contrasting ecological and trophic environments. Morphometric analysis revealed significant differences in indices associated with growth patterns and body shape. The aquaculture group demonstrated faster somatic growth and lower variability, whereas the wild population exhibited greater morphological diversity, likely reflecting the effects of natural selection and habitat heterogeneity. The results indicate pronounced phenotypic divergence between pond-reared and wild tench, which is likely driven by environmental conditions and aquaculture practices. These findings highlight the high adaptive plasticity of the species and support its potential for domestication and large-scale aquaculture in Kazakhstan. Overall, the data may contribute to the development of conservation and restocking programs for natural populations, as well as to selective breeding strategies and sustainable aquaculture practices. Full article

Rumination time is considered a sensitive behavioral indicator of physiological and metabolic status in dairy cows, yet its relationships with biochemical and milk quality parameters under commercial robotic milking conditions remain insufficiently described. This study combined precision monitoring technologies, serum biochemical profiling, and in-line milk analysis to evaluate physiological differences among early-lactation Holstein cows according to rumination time. A total of 88 cows were classified into three rumination time categories (>527, 412–527, and <412 min/day). Milk production traits, milk quality indicators, and blood biochemical parameters were compared among groups, and univariable regression analysis was performed to identify variables associated with rumination time. Cows in the low rumination group showed higher milk temperature, electrical conductivity, and somatic cell count, as well as lower milk protein percentage. They also showed higher concentrations of total protein, urea, gamma-glutamyl transferase, and lactate dehydrogenase, while triglyceride concentrations were lower. Regression analysis identified electrical milk conductivity, creatinine, magnesium, potassium, and chloride as variables associated with rumination time. These findings indicate that reduced rumination time is associated with changes in milk quality and biochemical parameters in early-lactation dairy cows, suggesting that rumination monitoring may provide useful information for identifying cows experiencing physiological and metabolic challenges under commercial farming conditions. Full article

The objective of the present study is to evaluate the effects of lactation stage, age, somatic cell count (SCC), and daily milk yield on plasmin–plasminogen (PL–PG) system activity and physicochemical milk traits in intensively reared Chios and Frizarta ewes. A total of 52 purebred ewes (26 ewes per breed and farm) were randomly selected and prospectively monitored during the 3rd, 5th, and 6th month post-lambing. Daily milk yield and body condition score (BCS) were recorded, and individual milk samples were collected for the assessment of PL–PG activities using enzymatic assays, SCC, electrical conductivity (EC), refractive index (RI), and pH. Correlation analysis and mixed linear regression models were used for the assessment of the effects. Lactation stage significantly affected PL–PG system traits in both breeds, but in opposite direction; plasmin and plasminogen plus plasmin declined toward late lactation in Chios ewes, whereas it increased in Frizarta ewes. Lower SCC was associated with reduced plasmin system activity in Chios ewes, whereas no effect was observed in Frizarta ewes. The plasminogen-to-plasmin ratio remained stable across lactation, breeds, and SCC classes, indicating coordinated regulation of the system. BCS was positively associated with plasmin activity during late lactation, suggesting a stage-dependent metabolic modulation. EC and pH were closely associated with SCC, while RI mainly reflected compositional variation. Our findings underline that, although the PL–PG system is primarily affected by lactation stage and mammary health status in sheep, there are breed-specific regulatory patterns which should be further investigated. Full article

Starvation resistance is a critical fitness trait for the olive fruit fly, Bactrocera oleae (Rossi) (Diptera: Tephritidae), influencing survival and reproductive success in fluctuating environments. This study investigates how age (15, 30, and 45 days), diet (full vs. restricted), and mating status (virgin vs. mated) affect the species’ capacity to withstand food deprivation. A multifactorial experiment was conducted on 3600 adults, with survival data analyzed using Kaplan–Meier curves, Log-Rank tests, and Tukey’s HSD. The findings indicate that 15-day-old individuals generally exhibit superior starvation resistance compared to older cohorts. However, these patterns vary by sex and nutritional history. In virgin males on a restricted diet, resistance does not decline linearly with age, while in mated males on a full diet, age has no significant influence on survival. Conversely, in mated females on a full diet, a significant decline in resistance is observed only between the ages of 15 and 45 days. Additionally, for mated adults on a restricted diet, age was found to have a significant influence on survival. These results suggest that starvation resistance in B. oleae is not merely a function of chronological age but emerges from complex resource allocation trade-offs between somatic maintenance and reproductive investment. Full article

This critical and selective review synthesizes the accumulating body of biological evidence supporting a process we term epigenetic–genetic coupling as a mechanistic basis for Lamarckian inheritance of somatically acquired adaptations. We propose that evolutionary processes in mammals and higher vertebrates can involve deaminase-driven, reverse transcriptase-mediated, RNA-templated targeted homologous recombination. We contrast well-established examples of “Soft”, reversible epigenetic inheritance with historical and contemporary evidence suggestive of stable, DNA-integrated “Hard” Lamarckian transgenerational inheritance. Our analysis indicates that the establishment of “Hard” Lamarckian inheritance may require specific population dynamics, including inbreeding or interbreeding among phenotypically affected offspring, together with sustained and defined environmental stimuli over one or more generations to consolidate the acquired traits at the genomic level. We also present molecular and cellular evidence supporting RNA-to-DNA genetic feedback mechanisms involving targeted genomic integration, primarily mediated by the DNA repair–associated reverse transcriptase activity of DNA polymerase η. Finally, we review diversification mechanisms in molecular and cellular immunology that now routinely employ single-molecule, real-time, long-read genomic sequencing (6–8 kb). We recommend the broader application of these technologies in future breeding and experimental programs across other somatic systems. Their deployment offers a robust strategy for securing definitive “Hard” molecular evidence of Lamarckian acquired inheritance in diverse biological contexts; including somatically acquired immunity, as well as adaptive behavioral and central nervous system phenotypes. This is compatible with our over-arching goal—to provide an experimental road map of conceptual options to drive future experimentation in acquired inheritance breeding programs. Full article

The objectives of this study were (i) to analyze the ClassyFarm welfare scores in loose housing system (LHS) and tied housing system (THS) Rendena herds, and (ii) to investigate the influence of the housing on individual milk yield and quality traits in Rendena cows. The dataset consisted of 3761 individual milk samples from 750 Rendena cows, collected between August 2022 and November 2023 from 17 single-breed herds of the Veneto region. Available data included days in milk (DIM), parity, and milk yield, as well as fat, protein, casein, and lactose contents, somatic cell count, differential somatic cell count, and urea concentration. For milk traits, a linear mixed model included housing system, DIM, and parity as fixed effects, while cow, herd-test-date, and residual variability were random effects. In both housing systems, a good level of welfare was observed, although shortcomings in biosecurity measures were identified in both LHS and THS. Milk quality (in terms of protein % and casein %) and yield were higher in LHS compared to THS. The observed differences cannot be explained by the housing system alone, as other management and nutritional factors may have played a role, highlighting the need for further studies to clarify these contributions. Full article

Background: 47,XYY syndrome is a relatively common sex chromosome aneuploidy that remains largely underdiagnosed. While its somatic phenotype is often mild, growing evidence indicates a substantial burden of neurodevelopmental and psychiatric morbidity. However, the characterization of the neuropsychiatric phenotype across development, particularly during adolescence, and the associated treatment challenges remain incomplete. Objectives: To provide a comprehensive narrative review of the neuropsychiatric phenotype of 47,XYY syndrome and to illustrate clinical complexity and treatment response through a case series of adolescents. Methods: A narrative review of the literature was conducted focusing on genetics, neurodevelopmental and psychiatric features, neuroimaging and neurophysiology findings, clinical course, and management strategies in 47,XYY syndrome. This review is complemented by a case series of adolescents with confirmed 47,XYY karyotype, evaluated for developmental history, psychiatric comorbidity and response to pharmacological and non-pharmacological interventions. Results: The literature consistently describes increased risks of language impairment, executive dysfunction, ADHD, autism spectrum traits, and emotional and behavioral dysregulation in males with 47,XYY syndrome. Psychiatric vulnerability appears to increase during adolescence and adulthood, with elevated rates of mood, psychotic, and substance use disorders. The presented cases illustrate a convergent clinical trajectory marked by early developmental delays, progressive behavioral dysregulation in adolescence and limited or inconsistent response to multiple classes of psychotropic medications, suggesting a pattern of pharmacoresistance in a subset of patients. Conclusions: 47,XYY syndrome is associated with a distinct and heterogeneous neuropsychiatric phenotype that extends beyond early neurodevelopmental disorders. Early diagnosis alone may be insufficient to prevent severe psychiatric outcomes, highlighting the need for long-term monitoring and integrated, multidisciplinary management. Further research is required to identify early predictors of high-risk trajectories and to optimize treatment strategies for this population. Full article

The purpose of this study was to examine the use of portable spectroscopy technologies for rapid milk composition and hygiene quality assessment in ovine milk. Two portable analyzers, namely SmartAnalysis (UV/Vis absorbance) and SpectraPod (NIR transmittance), were used to obtain spectral data of raw milk samples. Additionally, reference values of the milk’s compositional, physical, and hygienic traits were measured. Machine learning algorithms were used to explore the correlations between spectral data and milk traits. The initial results indicated a promising potential of utilizing spectral technologies to predict milk quality and hygienic parameters. Regression models presented a moderate predictive accuracy, with R² values between 0.55 and 0.34, respectively, regarding fat (RF-NIR) and protein (LR-UV/Vis). Classification models indicated high accuracy for hygienic parameters, with the highest accuracy and AUC values up to 0.87 and 0.83, respectively, predicting increased levels of total bacterial count (TBC), while somatic cell count (SCC) level was less accurately predicted by the model, with AUC values lower than 0.70. The results demonstrate the applicability potential of UV/Vis and NIR portable devices in milk quality assessment, enabling its rapid evaluation, including milk composition and hygiene parameters at the point of service. Full article

The objective of this study was to compare the proportion of explained genetic variance (EXGV) and the reliability of genomic breeding values (GBVs) predictions for milk yield (MY), fat yield (FY), protein yield (PY) fat percentage (FP), protein percentage (PP), and somatic cell score (SCS) in Holstein cattle. Three types of genomic information were evaluated. (a) SNP-ALL: this analysis included 88,911 single nucleotide polymorphisms (SNP) from 8290 animals. (b) HAP-PSEUDOSNP: haplotypes, defined based on high linkage disequilibrium (LD, r² ≥ 0.80) between SNPs, which were encoded as pseudo-SNPs, with a total of 35,552 pseudo-SNPs and 8331 animals included. (c) SNP-HAP: analysis using only individual SNPs included in the haplotypes (without recoding); for this analysis, 33,010 SNPs and 8192 individuals were retained. All analyses were conducted using the single-step genome-wide association study method implemented in the BLUPF90 software package. The results showed that the inclusion of SNPs with high LD (SNP-HAP) increases the reliability of GBVs’ predictions compared to the SNP-ALL analysis; average reliability increased between 0.05 and 0.11. Moreover, the SNP-HAP analysis resulted in a twofold increase in the EXGV for all traits, likely due to increased estimates of individual marker effects compared to the SNP-ALL analysis. Full article

This study investigates the reliability and potential genetic utility of data recorded by automatic milking systems by comparing them with official milk recording data. Analyses focused on phenotypic distributions, correlations, systematic differences, and heritability estimates for milk production and quality traits including milk yield, fat and protein percentage, somatic cell count, and electrical conductivity. Automatic milking system data and official milk recording data shared similar distributions. Correlations between the two systems were high for milk yield (r = 0.93), but moderate for fat (r = 0.52) and protein percentage (r = 0.48), and somatic cell count (r = 0.62), suggesting that while the former provides consistent data for quantity traits, quality-related ones may be less reliable. Systematic deviations between automatic milking systems and official milk recordings emerged across different lactation stages. Heritability estimates based on automatic milking system data were generally higher than the official control for production traits, supporting their use in genetic evaluations. Electrical conductivity displayed a similar heritability to somatic cell count, but its measure is insufficiently detailed and its use as an indirect indicator of udder health is not recommended. Automatic milking system data demonstrates potential for integration into genetic selection programs, although further refinement of sensor accuracy is recommended. Full article

Clubroot disease, caused by Plasmodiophora brassicae, is a major global threat, causing severe yield losses of up to 100% in heavily infested fields. Interspecific hybridization is essential for the transfer of clubroot resistance genes among the Brassica species. This review aimed to describe the sources of clubroot resistance, categorize their types in Brassica crops, and identify the most effective techniques and underutilized sources for both intergeneric and interspecific hybridization. A systematic literature review served as the foundation for expert analysis, encompassing a comprehensive list of known sources of resistance and a detailed description of their characteristics, including monogenic, polygenic, dominant, and recessive traits. In addition, this review specifies techniques suitable for gene transfer, such as markers, embryo rescue, somatic hybridization, and CRISPR/Cas. Based on the literature, underutilized directions for genetic crosses have been proposed. These conclusions suggest that combining biotechnological methods, including markers, CRISPR/Cas, and embryo rescue, with intergeneric crosses offers the potential to transfer resistance genes from previously untapped sources. Full article

The spice Ferula assa-foetida L., also known as asafoetida, is widely recognized for its medicinal and culinary applications. The non-native status of the plant and the prolonged dormancy of its seeds pose significant challenges for large-scale cultivation in India. In vitro organogenesis offers an effective solution to these obstacles. Establishing reliable in vitro regeneration protocols requires standardized statistical methods to evaluate univariate and multivariate data for optimizing specific traits. However, these methods have limitations when handling complex, nonlinear inputs, often producing large prediction errors that reduce the reliability of trait optimization. This study developed an in vitro regeneration system for F. assa-foetida L. and identified optimal PGRs for somatic embryogenesis and shoot organogenesis through image-based morphological analysis. Predictive models were created using DL and ML algorithms. Calli induced from leaf explants was cultured on the Murashige and Skoog medium supplemented with various combinations and concentrations of thidiazuron (TDZ), 6-benzylaminopurine (BAP), and α-naphthaleneacetic acid (NAA), as experimental variables. Seven ML approaches, namely random forest (RF), support vector machine (SVM), k-nearest neighbours (kNN), decision tree (DT), extreme gradient boosting (XG Boost), naïve bayes, and logistic regression, alongside five DL models—convolutional neural network (CNN), MobileNet, region-based convolutional neural network (RCNN), residual neural network (ResNet), and visual geometry group (VGG19)—were employed to predict the best PGRs for somatic embryogenesis and shoot organogenesis. Among them, the convolutional neural network (CNN) achieved the highest accuracy (87%), outperforming baseline ML models such as logistic regression and decision tree (82%). This pioneering study in F. assa-foetida L. presents an AI-driven, image-based framework for predicting optimal PGRs, offering a scalable approach to enhance micropropagation in endangered medicinal plants. Full article

Climate change and widespread micronutrient deficiencies threaten food security in the semi-arid tropics. Finger millet (Eleusine coracana (L.) Gaertn.) is a climate-resilient “nutri-cereal” rich in calcium, zinc, iron and dietary fiber. Finger millet is a promising crop for addressing climate stress and nutrient deficiencies. However, it remains under-explored and relatively neglected in breeding and genetic improvement programs compared to major cereals. This review synthesizes recent biotechnological advances and outlines future directions for finger millet improvement. Foundational resources now include a chromosome-scale reference genome, expanding transcriptome, diverse global germplasm panels, and growing reports of genome-wide association studies (GWAS) and quantitative trait loci (QTL) for key traits including yield, stress tolerance, blast resistance, and mineral contents. Tissue culture studies reported both somatic embryogenesis and direct regeneration. Stable genetic transformation has been achieved in finger millet via Agrobacterium-mediated methods, particularly using shoot apical meristem (SAM) and by biolistics (gene gun) methods. Genome editing has not yet been reported, but we propose a practical roadmap leveraging reported tissue culture genetic transformation protocols for applying the CRISPR/Cas system for trait improvements. Using new biotechnological methods, along with pangenome, speed breeding, and helpful microbiomes, will make finger millet a strong and reliable food source for the future. Full article

We evaluated four candidate SNPs (GC-NPFFR2 rs137147462, GC-NPFFR2 rs109452259, BRCA1 rs134817801, and DGAT1 p.K232A) previously reported in relation to mastitis or milk production traits, using 10,729 test-day phenotypic records collected over 10 years from 269 Japanese Holstein cows (Bos taurus) enrolled in the national Dairy Herd Improvement (DHI) program. Linear mixed models were used to estimate genotypic effects on somatic cell score (SCS) and to test multiple inheritance models. To assess clinical relevance, mastitis severity was further analyzed using categories defined by somatic cell counts (SCC). Among the SNPs tested, GC-NPFFR2 rs137147462 showed the clearest and most consistent association with SCS under a recessive model, with GG cows exhibiting higher SCS throughout lactation. Ordinal logistic regression confirmed a higher probability of progression to severe mastitis in GG cows. DGAT1 p.K232A showed additive effects, with the A allele increasing milk yield while lowering fat and protein percentages. AA cows also showed higher SCS under a modest recessive effect. BRCA1 rs134817801 and GC-NPFFR2 rs109452259 had minimal effects. These findings support GC-NPFFR2 rs137147462 as a promising marker for mastitis resistance and indicate the importance of considering not only additive but also recessive genetic models in genomic selection strategies. Full article