This study investigated the performance of various triticale cultivars and the impact of glutamic acid application on key physiological traits. We found significant differences among cultivars in nearly all measured parameters, underscoring the importance of genetic selection. Notably, Sara consistently excelled in vegetative growth, including plant height and flag leaf area, while Rizan demonstrated superior stomatal conductance, tillering capacity, and relative growth rate. Exogenous application of glutamic acid consistently improved plant performance across multiple traits. Specifically, a concentration of 500 mg L⁻¹ generally enhanced stomatal conductance, plant height, and tiller number, while 250 mg L⁻¹ was optimal for boosting relative growth rate and net photosynthesis. This underscores the importance of glutamic acid as an advantageous biostimulant. The study indicated strong connections between genetics and environment. The ideal reaction to glutamic acid was frequently particular to the cultivar. Sara and Rizan exhibited significant synergistic advantages from glutamic acid, frequently attaining optimal performance at certain dosages. Conversely, several cultivars demonstrated no enhancement or deterioration without optimum glutamic acid. In conclusion, to get the most out of triticale, you need to do two things: choose genetically better cultivars like Sara and Rizan and use glutamic acid at levels that are right for each cultivar and attribute you want. You need to use this focused method to get the most performance out of triticale in your area.

ABSTRACTWars impose unprecedented environmental damage that has rarely been studied in real time. Domestic dogs are an accessible model species during war times, because they enable data collection without specialised equipment and skills, which can be performed without creating additional danger to humans or animals involved. We compared phenotypic traits in Ukrainian dogs living close to the front line with those from other regions of Ukraine. We found significant differences in frequencies and diversity of multiple morphological traits, consistent with mortality‐based selection at the front line. We also found differences in age structure and frequency of diseases and injuries, consistent with high mortality of old and ill individuals. The front‐line population had low average BMI and stable isotope analysis suggested malnutrition and low trophic level. Our study shows that wars can be factors of strong and fast natural selection, with the effects comparable to large‐scale natural or anthropogenic disasters.

Studies indicate a high psychiatric burden in autoimmune hepatitis (AIH) patients, yet research on their genetic links remains unclear. This study comprehensively explores their genetic connections. The correlation metric, genetic correlation (rg), can measure the shared biological basis and explore the genetic architecture. We used the summary statistics from genome-wide association studies (GWAS) to accurately calculate the global and bivariate local genetic correlations between AIH and psychiatric disorders. Cross-trait GWAS meta-analysis for multiple traits can efficiently evaluate single nucleotide polymorphism (SNP) level summary statistics. We employ molecular characteristics to conduct unit tests in various tissues and annotate the corresponding loci. Through multiple genetic covariant tests, we identified 314 unique regions out of 1185 bivariate regions, including chr1p31.1, chr15q25.1, and chr3p14.1. Furthermore, it was discovered that AIH and psychiatric disorders share co-enrichment in multiple brain tissues, including the cerebellum hemisphere, cortex, pituitary, and nucleus accumbens basal ganglia, with PTRHD1, ANKK1, RPS26, YJEFN3, and C2orf69 identified as potential functional genes. The results of the above analyses were verified through multiple colocalization and functional enrichment assessments. Our study has identified pleiotropic genomic regions linking AIH and psychiatric disorders, providing effective strategies for the treatment of diseases.

Onion (Allium cepa L.) is a globally important vegetable crop where yield improvement depends on multiple morphological, quality, and resistance traits. The study investigated 18 onion (Allium cepa L.) genotypes in order to determine correlations and path coefficient associations between yield, quality, and resistance parameters under short-day circumstances. Genotypic correlations were frequently larger than phenotypic correlations, indicating that genetic relationships were somewhat obscured by environmental factors. The number of leaves had substantial positive connections with polar diameter, equatorial diameter, bulb weight, and yield features, indicating its role in assimilate production. Among bulb features, equatorial diameter had the strongest relationship with bulb weight and yield, with bulb weight exhibiting a nearly perfect connection (r > 0.95) with both marketable and total yield. Neck diameter correlated positively with days to maturity but negatively with reducing sugars, total sugars, and pyruvic acid, indicating a maturity-quality trade-off. Quality characteristics like reducing sugars and total sugars were substantially connected (r > 0.90), although pyruvic acid had a somewhat favourable relationship with yield traits. Biotic stress measures had a considerable impact on production, with thrips infestation and Stemphylium blight incidence showing strong negative associations with bulb size and yield. A positive correlation between thrips and illness severity demonstrated their combined negative influence. Average bulb weight was shown to be the most significant characteristic with the greatest direct positive impact on yield (1.036), followed by bulb diameter (0.734) and number of leaves (0.793). On the other hand, Stemphylium blight (–0.649) and thrips infestation (–0.738) had significant detrimental direct impacts. The results indicate that onion yield may be increased by selecting for higher bulb weight, more leaves, larger bulb diameter, and resistance to key pests and diseases.

Breeding objectives for turfgrass species include continued improvement of aesthetics and persistence while minimizing inputs such as water, fertilizers, and fungicides. In order to achieve the objectives, breeders must evaluate large amounts of germplasm for multiple traits in multiple environments to develop resilient grasses suitable for sport, lawn, and landscape uses. Fungal endophytes of the genus Epichloë develop a mutualistic relationship with many turfgrass species, including ryegrass (Lolium spp.) and fescues (Festuca spp.), imparting a high tolerance to biotic and abiotic stresses. The development of improved turfgrasses with endophyte is of great value to reduce maintenance costs and conserve resources. It has been reported that red thread disease (caused by the pathogen Laetisaria fuciformis) and dollar spot disease (caused by Sclerotinia homoeocarpa) can be suppressed in fine fescues that are infected with endophytes. Grasses colonised by Epichloë endophytes have shown high tolerance to foliar feeding insects such as billbugs (Sphenophorus spp.). Several studies have also demonstrated that endophytes confer protection to perennial ryegrass and tall fescue from water stress by increasing the availability of primary metabolites, e.g. concentrations of glucose and fructose. Breeders can use established immunological tests to determine if Epichloë endophytes are present in plant seed, but there is no guarantee that the endophyte is viable. To determine viability, the same immunological tests (commonly known as growouts) can be performed on grass seedlings to determine viable endophyte infection frequencies across grass populations. To deliver grass cultivars with high (>70%) endophyte infection frequencies, these cultivars must be developed with endophyte infection frequencies near 100%. Many grass breeders in the United States maintain high endophyte frequencies in the live plant material to ensure the mutualistic relationship between the plant genotype and endophyte genotype is maintained throughout the breeding cycle. However, viable endophyte infection frequencies can decrease over time depending on the environment and cultural practices deployed. Maintaining breeder seed of a cultivar with a high endophyte infection frequency requires cold storage with low humidity in addition to an established endophyte assessment protocol. However, delivering this quality endophyte-seed product for commercial production requires a quality assurance program that is not currently available on an industry wide scale in the United States.

Lead (Pb) contamination poses a serious threat to soil ecosystems, crop productivity, and food safety. The use of Pb-resistant plant growth-promoting bacteria (PGPB) offers a sustainable and eco-friendly strategy for soil bioremediation. In this study, a novel Pb-tolerant PGPB strain, Pseudomonas mendocina L1, was isolated from phosphate rock-contaminated soil. Strain L1 exhibited high Pb resistance (MIC = 1000mg/L) and multiple plant growth-promoting traits, including phosphate solubilization, indole-3-acetic acid (IAA) and siderophore production, as well as ACC deaminase activity. Whole-genome sequencing (WGS) revealed that strain P. mendocina L1 harbors a 5.54Mb circular chromosome with a GC content of 62.39% and 5136 predicted coding sequences. Genomic analysis identified key genes involved in plant-beneficial functions, such as phosphate transport (pstA, pstB, pstC, pstS), siderophore-mediated iron uptake (fhuB, fhuC, fhuD), and IAA biosynthesis (trpEDCBA operon, trpF). Furthermore, a soil-pakchoi (Brassica chinensis L.) system was employed to evaluate its bioremediation potential, demonstrating that inoculation with P. mendocina L1 significantly improved plant growth while reducing Pb accumulation in edible tissues. These findings highlight P. mendocina L1 as a promising candidate for the bioremediation of Pb-contaminated soils, offering an eco-friendly and cost-effective strategy for sustainable agriculture and environmental restoration.

3D genome editing reconfigures chromatin loops to fine-tune gene expression for coordinated improvement of multiple crop traits.

The current study was conducted at ICAR-Indian Agricultural Research Institute, New Delhi, India, in the year 2023. Plant Protein Isolates (PlPIs) derived from sesame, mung bean, peanut, chickpea and spirulina have attracted widespread attention due to their high nutritional value, the popularization of vegan diets and broad availability. However, their relatively poor functional properties compared to animal proteins limit their wider use in food formulations. This study investigates the effect of sonication pretreatment on the functional properties of lab-made PlPI blends compared to Commercial Plant Protein Isolates (CPlPIs). Functional attributes such as solubility, dispersibility, swelling capacity, foaming and gelation behaviour were evaluated. PlPI blends exhibited significantly higher solubility (up to ~48 % at pH 11) and oil-holding capacity (~339 %) than commercial isolates. Dispersibility in PlPI blends ranged narrowly from 61–63 %, whereas CPlPIs varied widely between 16 % and 100 %, depending on formulation. Swelling capacity was also notably improved in PlPI blends (13.3–426.9 %) compared to CPlPIs (12.1–122.2 %). Rheological analysis (flow properties) indicated shear-thinning behaviour (less viscous when stirred or subjected to force) for both PPI-blends and CPPIs, with PPI-blend 2 showing the highest viscosity due to its greater swelling capacity. PPI-blends demonstrated higher oil-holding capacity (330.6–339.7 %) than CPPIs (66.7–139.5 %). However, unlike CPlPIs, which formed gels at low concentrations (1–3 %), all PlPI blends required a higher concentration (12 %) to gel. This is the first study to systematically compare sonicated PlPI blends with CPlPIs across multiple functional traits using diverse plant sources. Overall, sonication pretreatment improved hydration and functional properties, making sonicated PlPI blends promising ingredients for developing plant-based dairy alternatives, meat analogues and other functional food products requiring improved solubility, foaming and texture.

Pleiotropy is the phenomenon by which a genetic variant affects multiple independent traits. Human genetics studies have identified pervasive pleiotropy throughout the genome and multitrait genome-wide association studies are growing in scale, such that dissecting pleiotropy is an increasingly important step in linking disease-associated variants to specific mechanisms. Dissecting pleiotropy entails using one of several statistical approaches to define clusters of genetic associations reflecting biological processes that are distinct and shared across traits, which must then be validated with orthogonal datasets. In this Review, we outline the various approaches to pleiotropy dissection, describing exemplary applications throughout, and discuss the remaining challenges and limitations to elucidating the shared mechanisms of disease.

Phyllosphere microorganisms play a vital role in supporting host plant health and adaptability. Although previous research on the effects of host performance and their phylogenetic associations on phyllosphere microbial communities has predominantly focused on tropical, subtropical, and temperate forestry ecosystems, the responses of these microbial communities to plant phylogeny and functional traits in temperate desert environments remains poorly understood. In this study, we conducted a quantitative analysis of bacterial and fungal community structures in the phyllosphere of 39 plant species from the Gurbantunggut Desert, a typical temperate desert in Central Asia. Variation partitioning analysis revealed that plant phylogeny, leaf physicochemical properties, and leaf morphological characteristics collectively explained the variation in phyllosphere microbial communities. Specifically, these factors accounted for 19.26%, 14.53%, and 2.32% of the variance in bacterial communities, and 11.55%, 8.36%, and 2.19% of the variance in fungal communities, respectively. A significant hierarchical pattern emerged: plant phylogeny > leaf physicochemical properties > leaf morphological characteristics, highlighting the dominant role of plant filtering effects in community assembly. Linear mixed-effects model analysis further confirmed the significant influence of multiple plant attributes, including phylogeny and functional traits, on microbial community structure. Plant-microbe interaction analysis revealed distinct host preferences of microbial taxa across different plant taxonomic levels. Co-evolutionary analysis also indicated a significant phylogenetic association between host plants and their phyllosphere amplicon sequence variants (ASVs). Overall, our findings demonstrate that plant attributes, particularly plant phylogeny and functional traits, are key factors driving the assembly of phyllosphere microbial communities in deserts. This study provides new insights into species coexistence mechanisms in fragile habitats and enhances our understanding of plant-microbe interactions in global desert ecosystem.

Background: Urinary tract infections (UTIs) during pregnancy are a significant public health concern due to their potential risk to maternal and child health. Among other prevalent organisms, Enterococcus faecalis has emerged as a key pathogen, with virulence genes, biofilm-forming ability, and multidrug resistance as significant pathogenic properties. Objective: This review examines the pathogenic mechanisms, diagnostic innovations, treatment challenges, and alternative therapeutic strategies for E. faecalis-induced UTIs during pregnancy. Methods: A literature review was conducted to examine virulence factors, diagnostic advancements, conventional antibiotic therapies, and emerging alternatives. Results: E. faecalis exhibits multiple virulence traits, including adhesion proteins (Agg, Ace), gelatinase, hemolysin, and surface proteins (Esp), which facilitate colonisation, immune evasion, and biofilm formation. Diagnostic innovations such as molecular assays, metabolomics-based biomarkers, microfluidic platforms, and AI-assisted urinalysis have improved the accuracy of rapid detection. While nitrofurantoin has remained a reliable antimicrobial agent, because of its low resistance profile, emerging antimicrobial resistance necessitates the exploration of alternative approaches. These include phage therapy, antimicrobial peptides, immunotherapy, probiotics, and herbal adjuncts. Effective campaigns towards antibiotic stewardship and combination therapy are also critical in managing recurrent and resistant infections. Conclusion: Effective management of urinary tract infections caused by E. faecalis during pregnancy requires a multidisciplinary approach that incorporates advanced technologies, targeted therapeutics, and preventive strategies to improve outcomes and combat antimicrobial resistance.

Abstract The association between dominance and phenotypic traits (‘badges of status’) has been recently questioned, since it has been found to show more variation across populations and time than expected. Using an eleven-year dataset, encompassing more than 1,800 individuals, we studied the association between the size of a melanin-based plumage trait (a black patch under the beak or ‘bib’), individual attributes (age and sex) and dominance. Our study model, the sociable weaver (Philetairus socius), is a small passerine, which lives year-round in colonies of varying size. Bib sizes were obtained from pictures and automatically pre-processed with an object segmentation deep learning network. We recorded 36,346 dominance-related interactions to estimate dominance hierarchies. We then investigated the effect of sex and age on bib size, and the overall and between-year association of bib size and age with dominance for each sex. We found that bib size increased with age within individuals of both sexes. Age was a strong and consistent predictor of dominance in males, but not in females. Nevertheless, dominance was not correlated with bib size in males and in females. Finally, these relationships did not strongly vary between years. Our results suggest that males and females may use different factors to regulate dominance interactions. Furthermore, our longitudinal dataset allowed us to show that bib size is not a badge of status in our population even though its growth encodes information on age. These results highlight the importance of considering multiple traits over time when studying morphological signalling of dominance hierarchy.

Background: Drought is one of the most limiting environmental stresses affecting both early seedling establishment and later developmental stages of agricultural crops. Its frequent occurrence, intensified by irregular rainfall and rapid climate shifts, severely disrupts the productivity of oilseed crops and contributes to substantial yield reductions. These challenges highlight the urgent need to identify drought-resilient and locally adapted Brassica germplasm that can withstand water-deficit conditions and support sustainable crop improvement programs. Objective: This study aimed to evaluate the performance of ten Brassica genotypes under varying levels of polyethylene glycol (PEG-6000)–induced drought stress and identify drought-tolerant candidates suitable for future breeding initiatives. Methods: A controlled-environment Petri dish experiment was conducted using a Completely Randomized Design with three replications. Four treatments were applied: a non-stressed control and PEG-6000 concentrations of 5%, 10%, and 20% to simulate mild, moderate, and severe drought stress. Ten genotypes were assessed for germination percentage, shoot length, root length, root-to-shoot ratio, shoot and root fresh weight, shoot and root dry weight, seedling fresh weight, and seedling dry weight. Data were recorded eight days after sowing and analyzed using analysis of variance to determine significance across genotypes, treatments, and genotype-by-treatment interactions. Results: Highly significant differences (p < 0.001) were observed among genotypes, treatments, and their interactions. Values ranged widely across traits, including germination percentage (40–100%), shoot length (0.33–8.30 cm), root length (0.20–5.37 cm), and root-to-shoot ratio (0.28–0.93). Biomass parameters also showed considerable variation, with shoot fresh weight (0.002–0.54 mg), root fresh weight (0.01–0.04 mg), shoot dry weight (0.0005–0.0134 mg), and root dry weight (0.0003–0.010 mg). The 5% PEG-6000 treatment consistently enhanced seedling performance compared to higher stress levels. Among genotypes, RBN-08003 showed superior performance across multiple traits, whereas UAF-11 ranked lowest under most treatments. Conclusion: Mild drought simulated through 5% PEG-6000 proved most favorable for seedling growth in the evaluated Brassica genotypes. The genotype RBN-08003 demonstrated strong drought tolerance and appears promising for incorporation into future breeding programs focused on water-limited environments.

GmUbiE3 as a novel regulator of soybean seed size and weight identified via cross-population QTL analysis and functional validation.

Pugionium cornutum PcHARBI1-5 (Harbinger Transposase Derived 1-5) facilitates early flowing and seed development in in Arabidopsis thaliana.

A fundamental goal of genetics is to identify which and how genetic variants are associated with a trait, often using the regression results from genome-wide association (GWA) studies. Important methodological challenges account for inflation in GWA effect estimates as well as in investigating more than one trait simultaneously. We leverage machine learning approaches for these two challenges, developing a computationally efficient method called ML-MAGES. First, we shrink the inflation in GWA effect sizes caused by nonindependence among variants using neural networks. We then cluster variant associations among multiple traits via variational inference. We compare the performance of shrinkage via neural networks to regularized regression and fine-mapping, two approaches used for addressing inflated effects but dealing with variants in focal regions of different sizes. Our neural network shrinkage outperforms both methods in approximating the true effect sizes in simulated data. Our infinite mixture clustering approach offers a flexible, data-driven way to distinguish different types of associations—trait-specific, shared across traits, or nonprioritized—among multiple traits based on their regularized effects. Clustering applied to our neural network shrinkage results also produces consistently higher precision and recall for distinguishing gene-level associations in simulations. We demonstrate the application of ML-MAGES on association analyses of two quantitative traits and two binary traits in the UK Biobank. Our identified associated genes from single-trait enrichment tests overlap with those having known relevant biological processes to the traits. Besides trait-specific associations, ML-MAGES identifies several variants with shared multitrait associations, suggesting putative shared genetic architecture.

Genomic and functional analysis of Pseudomonas protegens CS11 reveals multifaceted biocontrol mechanisms against Sclerotinia sclerotiorum via antifungal metabolites, root colonisation and plant defence induction in tomato.

The Meta-Analysis of Glucose and Insulin-related traits Consortium (MAGIC) identified 242 loci associated with glycaemic traits fasting insulin (FI), fasting glucose (FG), 2h-Glucose (2hGlu), and glycated haemoglobin (HbA1c). However, for the majority, the causal variant(s) remain(s) unknown. Modelling multiple traits and integrating functional annotations have each been shown to improve fine-mapping resolution. Here, we aimed to determine whether combining these techniques would further improve fine-mapping resolution. Using single-trait fine-mapping results from FINEMAP as input, we performed multi-trait fine-mapping with flashfm at 50 loci significantly associated with more than one glycaemic trait. We used fGWAS to build models of enriched annotations by considering 32 cell-type specific and 28 static annotations. We used these models to define prior probabilities to perform annotation informed fine-mapping with both FINEMAP (single-trait) and flashfm (multi-trait). Multi-trait fine-mapping of 106 locus-trait associations significantly (P= 1.23 × 10-17) reduced the median size of the credible sets accounting for 99% of the posterior probability of being causal (99CS) to 21.5 variants compared to the 60.5 variants in single-trait fine-mapping. Annotation informed single-trait fine-mapping of 211 locus-trait associations reduced (P= 4.24 × 10-12) the median 99CS size from 72 in agnostic single-trait fine-mapping to 52 variants. Annotation informed multi-trait fine-mapping of 110 locus-trait associations led to a further significant (P= 2.69 × 10-18) decrease in median 99CS size to 14.5 variants compared to 51.0 in annotation informed single-trait fine-mapping. In conclusion, by applying combined multi-trait and annotation informed fine-mapping to 50 loci, we refined the number of potential causal variants by 71.1% compared to single-trait agnostic fine-mapping.

Water scarcity is a major constraint to agricultural productivity, particularly in arid and semi-arid regions. This study evaluated the effects of gardening waste-based compost and compost tea (CT) on tomato (Solanum lycopersicum L.) plants subjected to osmotic and water deficit stress. The first experiment assessed seed germination and early growth under polyethylene glycol (PEG)-induced osmotic stress. An inverse correlation between PEG concentration and seed and plant development was found. CT improved the germination rate and early seedling development under moderate stress (2% PEG). The second experiment examined the effect of compost and CT on tomato growth in a 45-day pot trial under three irrigation levels: 100%, 60%, and 40% field capacity (FC). Compost-treated plants consistently showed significantly greater growth and biomass accumulation across all FC levels, especially under moderate water stress. In contrast, CT-treated plants showed a general reduction in growth parameters. In addition, there was a positive association between compost treatment and multiple growth traits, particularly under reduced irrigation conditions. These findings underscore the beneficial effects of compost on plant performance under drought conditions.

Endophytic bacteria living within the medicinal plants are increasingly recognized for their ability to support plant growth and contribute to sustainable agriculture. In present study, fifteen endophytic bacteria were isolated from healthy Aloe vera tissues and evaluated their plant growth-promoting potential. Each isolate was screened for PGP traits such as phosphate solubilization, indole-3-acetic acid (IAA) production, ammonia production, siderophore production and nitrogen fixation. The majority of isolates demonstrated at least one of these beneficial activities, and several displayed notably strong performance across multiple traits particularly in phosphate solubilization and IAA production. Among them, isolate AV11 exhibited the highest PGP efficiency across assays and was identified as Brevibacillus borstelensis by 16S rRNA gene sequencing. Hence, present study suggests that B. borstelensis can serve as an effective plant growth-promoting endophyte with potential applications in sustainable agriculture. The findings highlight the functional diversity of endophytic bacteria associated with Aloe vera and their potential role in sustainable agriculture.