Search Results (424)

While silage maize (Zea mays L.) remains the dominant biogas feedstock crop in Germany, concerns about landscape homogenization and ecological risks have stimulated the search for more diverse energy crops. This study evaluated twelve amaranth genotypes (GT01–12; Amaranthus spp.) in southwest Germany using field experiments combined with biomass composition analysis and laboratory batch biogas assays. In contrast to earlier studies focusing primarily on the cultivar ‘Baernkraft’ (GT04), a broader set of genetic material was examined. Significant differences among GTs were observed for plant density, dry matter yield (DMY), dry matter content (DMC), and biomass composition. The most productive genotypes (GT09 and GT11) exceeded 10 Mg ha⁻¹ DMY, clearly outperforming Baernkraft. However, even these GTs did not reach the ≈28% DMC threshold considered necessary for reliable ensiling. Lignin concentrations ranged from 4.7% to 7.2% of dry matter. Methane concentrations remained relatively stable (54–55%), resulting in an average methane yield of 1788 ± 441 m³ CH₄ ha⁻¹ (maximum: 2677.8 m³ CH₄ ha⁻¹) across all genotypes and harvest dates. These findings indicate that amaranth may contribute to diversification of biogas cropping systems, although its agronomic and substrate-related performance remains inferior to that of maize under the conditions studied. Full article

Tomato landraces possess distinct flavors, colors, textures and aromas, making them suitable for traditional cuisine. Tomato landraces contain a wide range of genes, including those involved in fruit quality, that can be isolated and used in local breeding programs. In regions recognized as centers of origin, domestication and diversification, traditional farmers play an important role in the preservation of tomato landraces adapted to local conditions and agricultural practices, on the whole maintaining high genetic diversity. This work aimed to evaluate the effects of the crop cycle (C), genotype (G) and C × G interactions on the contents of soluble solids, reducing sugars, lycopene, total polyphenols, flavonoids, and vitamin C, as well as the pH and antioxidant activity, in fifteen tomato landraces (genotypes) undergoing phenotypic selection and a commercial tomato variety (control). All the varieties were grown in two crop cycles under uniform greenhouse management using a randomized block design with four repetitions. Fruit composition was analyzed with AOAC and spectrophotometric methods. Significant differences (p ≤ 0.01) were detected in the soluble solid content, pH, flavor and maturity indices, polyphenol and flavonoid contents, and antioxidant activity between C, G and C × G interactions. In contrast, titratable acidity, reducing sugars, lycopene and vitamin C did not differ between cycles. Coefficients of phenotypic and genotypic variation and broad-sense heritability (H²) ranged from 4.3 to 33.7, 2.0 to 19.0, and 3.2 to 63.5%, respectively. H² for bioactive compounds ranged from moderate to slightly high (16.3–38.8%). These findings, supported by laboratory analyses, suggest that genotypes under agronomic selection have potential as parents to enhance fruit quality in current and future breeding programs. Full article

The remarkable ecological success of fungi is supported by their capacity for rapid and often reversible molecular responses to fluctuating environments. While conventional evolutionary theory has largely emphasized mutation and selection as central drivers of adaptation, many environmentally responsive fungal traits are also shaped by molecular processes that generate reversible phenotypic variation on ecological or developmental timescales. This review synthesizes current knowledge on reversible genetic and epigenetic mechanisms underlying fungal phenotypic plasticity by integrating insights from programmed genetic rearrangements such as mating-type switching, transposable element activity, variation in tandem repeats and the behavior of accessory chromosomes, together with dynamic epigenetic processes including histone modifications, DNA methylation, chromatin remodeling and RNA mediated regulation. Together, these mechanisms form an interconnected framework that enables rapid and, in many cases, reversible phenotypic diversification, although their consequences range from transient regulatory shifts to partially or fully irreversible sequence-level changes. We highlight the molecular machinery that governs reversibility and its evolutionary implications for fungal pathogenesis, symbiosis, and biotechnology. By uniting genetic and epigenetic perspectives, this review advances a holistic framework in which reversibility is treated as a key property of fungal phenotypic plasticity, helping fungi balance stability with flexibility under environmental challenge. Understanding these mechanisms provides new insights into fungal evolution, and opens new avenues for antifungal intervention and the rational design of industrially valuable fungal strains. Full article

Miscanthus lutarioriparius exhibits strong potential for cadmium (Cd) accumulation, making it a promising candidate for the phytoremediation of Cd-contaminated soils. However, its full remediation potential remains underexploited, highlighting the need for targeted genetic improvement This study presents a comprehensive genome-wide identification and systematic characterization of 20 Ml4CL (4-coumarate: CoA ligase genes) in the M. lutarioriparius. Results indicate that the Ml4CL gene family has undergone substantial evolutionary divergence and expansion. Phylogenetic classification is highly consistent with gene structures ad conserved motifs suggesting potential functional diversification. Promoter analysis revealed a complex cis-regulatory landscape enriched in n ABA- and light-responsive elements, frequently co-occuring with hormone-responsive elements associated with jasmonic acid (JA), gibberellins (GAs), salicylic acid (SA), and strigolactones (SLs) signaling. This pattern suggests that the Ml4CL family may function as an integrative regulatory node linking multiple stress and hormonal signaling pathways. Importantly, under Cd stress, Ml4CL genes exhibited diverse expression dynamics, including gene-specific repression and dose-dependent biphasic responses. Notably, Ml4CL4 showed strong repression, while other members displayed “induction-then-repression” or “repression-then-induction” patterns, suggesting a staged or hierarichical transcriptional response. These findings further suggest that Cd-responsive signaling networks may involve non-linear or threshold-dependent mechanismsthat activate distinct transcriptional programs depending on stress levels. Collectively, this study highlights the regulatory role of the Ml4CL family in plant adaptation to complex environments and identifies candidate dose-resonsive regulatory elements and key allelic variations. These findings provide valuable targets for molecular breeding and synthetic biology aimed at improving crop stress resilience. Full article

Glucosinolates (GSLs) are unique sulfur-containing secondary metabolites in Brassica crops that critically influence stress resistance, nutritional quality, and economic value. This review systematically summarizes the chemical classification, tissue-specific distribution, and conserved three-phase biosynthetic pathway of GSLs in Brassica species. We dissect the core MYB–MYC–WRKY transcriptional regulatory network, elucidate how whole-genome duplication-driven gene functional diversification shapes species-specific GSL accumulation patterns, and outline the multi-layered regulatory system integrating endogenous and exogenous signals. Furthermore, we consolidate recent advances in the genetic dissection of GSL traits and molecular breeding strategies for targeted trait improvement. Finally, we propose a three-tiered regulatory cascade model for GSL metabolism and highlight future research priorities to address current breeding bottlenecks. This work provides a systematic theoretical framework for functional research and precision breeding of GSL metabolism in Brassica crops. Full article

Observations suggest that headwater streams have lower species diversity within a site than larger streams, but higher beta diversity, and thus gamma diversity, across a catchment. This pattern of diversity includes taxonomic richness and genetic diversity, as well as a high degree of endemism. I review several mechanisms that potentially contribute to the overall high diversity of freshwater organisms in headwaters, although these mechanisms are interdependent. These include the high numbers of headwater streams, heterogeneity of habitats and resources, founder effects, colonization dynamics, isolation, and strong selection, all leading to diversification of forms. However, riverscape diversity patterns vary across taxonomic and functional groups, highlighting that patterns of diversity are driven by different processes for different organisms. More explicitly structured sampling designs will better address patterns of taxonomic richness and for a broader range of taxa. It will be interesting to find ways to partition the relative importance of different mechanisms in contributing to the variation in diversity among headwaters. The great importance of headwater streams to global biodiversity conservation is clear, but will be more evident when better assessments of diversity patterns across these small systems are available. Full article

The sucrose synthase (SUS) gene family plays a pivotal role in plant carbon metabolism, growth, and development. In this study, we identified 65 SUS genes across six Brassica species (B. rapa, B. nigra, B. oleracea, B. juncea, B. napus, and B. carinata), and systematically analyzed their structural characteristics, evolutionary history, and expression profiles. Phylogenetic analysis classified these genes into three subfamilies (SUSI, SUSII, and SUSIII). SUS4 orthologs (from SUSI subfamily) are completely lost in Brassica, and total SUS gene numbers are just 6–7 in Brassica diploid species, though the SUSIII subfamily exhibits significant expansion in Brassica polyploid species. Selection pressure analysis (Ka/Ks) revealed that the Brassica SUS family has primarily undergone purifying selection, although certain members show evidence of adaptive evolution. Comprehensive expression profiling and qRT-PCR validation demonstrated the functional diversification of BnSUS genes in tissue specificity and responses to hormonal and abiotic stimuli. SUSI genes BnSUS1-1/2/3/4 are predominantly expressed in vegetative tissues and flowers; SUSII genes BnSUS2-1/2 and BnSUS3-1/2 are reproductive-organ-specific, while SUSIII genes BnSUS5-1/2 and BnSUS6-1/2/3/4 show young-plant-specific weak expression. BnSUS family genes are generally upregulated by ABA, TZ and GA but downregulated by IAA, ACC, BL and JA. Salt, drought, freezing and cold mainly upregulate the BnSUS family, heat downregulates it, and osmotic stress exerts both effects. Correspondingly, Brassica SUS promoters are enriched with light-responsive (G-box, Box-4), hormone-responsive (ABRE, CGTCA-motif) and anaerobic-induction (ARE) elements. Functional characterization demonstrated that the ABA-responsive gene BnSUS3-2 significantly improved tolerance to osmotic and ionic stresses by promoting root growth in transgenic A. thaliana seedlings. These findings underscore the essential roles of BnSUS genes in maintaining cellular homeostasis and provide a theoretical foundation for the genetic improvement of carbon metabolism and stress resilience in Brassica crops. Full article

Yersinia pestis is the etiological agent of plague, a severe and often fatal disease in humans when left untreated. Because of the high genetic clonality of Y. pestis, high-resolution genotyping assays are necessary to differentiate between individual strains. Here, we report on the development and validation of a robust and reproducible core-genome multilocus sequence typing (cgMLST) assay for Y. pestis comprising 3139 gene targets, enabling high-resolution typing at the strain level. The assay was validated using 222 publicly available Y. pestis genomes, including 45 recently sequenced outbreak isolates from Madagascar and 21 isolates from Mongolia. The cgMLST analysis revealed primary clustering aligned with known biovar-associated branches and sub-branches. Additional geographically structured sub-clusters illustrate its application for regional diversification analysis. Yersinia pestis strains from different geographic regions were clearly distinguished, consistent with spatial clustering. Within the analyzed dataset, closely related or epidemiologically linked strains differed by zero to three alleles, suggesting this range as an operational reference for identifying highly similar isolates. The cgMLST showed clustering patterns concordant with previously described single-nucleotide polymorphism (SNP) assays. It therefore provides a standardized high-resolution typing approach, with demonstrated applicability for outbreak investigations, source tracking, and comparative genomic surveillance of Y. pestis. Full article

Climate change threatens crop yields and farming profitability, especially in drought-prone regions, requiring a transition to climate-resilient farming systems. Concurrently, growing demand for health-promoting and bio-based materials is creating new market opportunities for farmers. Sulla (Sulla coronaria Medik; syn. Hedysarum coronarium L.), a Mediterranean forage crop, may represent a strategic resource for sustainable intensification by simultaneously providing high-value commodities and a wide range of ecosystem services. This review explores the multifunctional potential of sulla following a holistic approach and is structured in thematic chapters, exploring: i. agronomy, ii. ecosystem services and agroecological value, iii. plant biochemical profile, iv. emerging applications for the bio-based industry, v. genetic diversity (including rhizobia diversity) and breeding perspectives for target environments and end-use. A SWOT analysis synthesizes strengths, research gaps and bottlenecks hindering large-scale adoption and valorization. The review proposes a strategic framework matching research priority with specific, actionable goals. The review aims to increase awareness of the multifaceted value of sulla as a promising model legume to increase sustainability in agriculture, promote product diversification and farming profitability, while assuring important ecosystem benefits. Full article

Background/Objectives: Multidrug-resistant Salmonella enterica serovar Enteritidis, especially those isolated from humans, remains a public concern. In the present study, S. Enteritidis strain 31404 was obtained clinically from a fecal sample of a fifteen-year-old girl, who was positive for bla_NDM-13. Methods: Antibiotic susceptibility testing and whole genome sequencing were performed. Core genome MLST and hierarchical clustering (HierCC) were performed using EnteroBase. Population structure analysis of 57 S. Enteritidis isolates collected between 2023 and 2025 in Jiaxing city was conducted. A comparative structure analysis of bla_NDM-13-positive plasmids was also performed. Results: S. Enteritidis strain 31404 was resistant to 13 antimicrobial agents. We found that strain 31404 belonged to ST11 and carried resistance genes, such as bla_NDM-13, bla_CTX-M-14, ble_MBL, fosA3, qnrS, and tet (A). bla_NDM-13 was located on an IncI1-I (α) plasmid designated as p31404-NDM13. S. Enteritidis isolate 31404 was closely related to PNUSAS514422, which was isolated from the United States in 2025. Comparative genetic environment related to bla_NDM-13-positive plasmids available in the NCBI database indicates that ΔTn125-mediated contexts were commonly associated with bla_NDM-13. IS1294 (IS91 family), which replaces ISAba125, is likely to mobilize bla_NDM-13. Conclusions: The findings in this study provide insights into the molecular characterization and diversification of bla_NDM-13. The identification of bla_NDM-13-containing transferable plasmids in different serotypes of Salmonella isolates (such as S. Rissen, S. Typhimurium, and S. Enteritidis) in different cities in China highlights the risk of the spread of carbapenem-resistant genes among Salmonella isolates. Full article

High-quality training data are essential for the performance and generalization of artificial intelligence systems, particularly in dynamic environments such as adaptive stream processing for disaster response. However, constructing large and representative datasets remains costly and time-consuming, especially in domains where real data are scarce or difficult to obtain. Large Language Models (LLMs) provide powerful capabilities for synthetic text generation, yet the quality of generated data strongly depends on the design of input prompts. Prompt engineering is therefore critical, but it remains largely manual and difficult to scale, particularly in black-box settings where model internals are inaccessible. This work introduces EVOLMD-MO, a multi-objective evolutionary framework for automated prompt learning aimed at generating high-quality synthetic text datasets using black-box LLMs. The proposed approach formulates prompt optimization as a multi-objective search problem in which candidate prompts evolve through genetic operators guided by two complementary objectives: semantic fidelity to reference data and generative diversity of the produced samples. To support scalable optimization, the framework integrates a modular multi-agent architecture that decouples prompt evolution, LLM interaction, and evaluation mechanisms. The evolutionary process is implemented using the NSGA-II algorithm, enabling the discovery of diverse Pareto-optimal prompts that balance semantic preservation and diversity. Experimental evaluation using large-scale disaster-related social media data demonstrates that the proposed approach consistently improves prompt quality across generations while maintaining a stable trade-off between fidelity and diversity. Compared with a single-objective baseline, EVOLMD-MO explores a significantly broader semantic search space and produces more diverse yet semantically coherent synthetic datasets. These results indicate that multi-objective evolutionary prompt learning constitutes a promising strategy for black-box LLM-driven data generation, with potential applicability to adaptive data analytics and real-time decision-support systems in highly dynamic environments, pending broader validation across domains and models. Full article

Stevia rebaudiana Bertoni is a strategically important perennial crop because it is the main botanical source of steviol glycosides, a group of high-intensity, non-caloric sweeteners increasingly demanded by the global food and beverage industry. Despite the rapid expansion of stevia cultivation, commercial production remains strongly dependent on a narrow genetic base, particularly on clonally propagated cultivars such as ‘Morita II’, which has long served as the industrial benchmark because of its favourable rebaudioside A profile and processing consistency. This dependence has raised concerns about limited adaptive capacity, genetic erosion and restricted long-term breeding progress. In this review, we provide an integrated and critical synthesis of current knowledge on the genetic diversity of S. rebaudiana, the biosynthetic and regulatory architecture of steviol glycosides, and the conventional and emerging strategies available for crop improvement. Unlike previous reviews, this article explicitly connects domestication-driven genetic bottlenecks, wild germplasm mobilisation, metabolic pathway regulation, advanced analytical phenotyping and precision breeding into a single systems-oriented framework. We examine the roles of wild germplasm, somaclonal variation, polyploidy, molecular markers, omics-assisted approaches and transgene-free genome editing as complementary tools to broaden the stevia breeding base while preserving industrial quality standards. We finally propose an integrative roadmap for the sustainable genetic improvement of stevia, positioning ‘Morita II’ not as an endpoint, but as a benchmark within a broader diversification strategy. Full article

This study develops and evaluates an equity selection pipeline that converts quarterly fundamentals into a monthly frequency, constructs profitability, leverage, liquidity, and growth characteristics, and learns a linear ranking model via a genetic algorithm (GA). The GA is trained to maximize either (i) mean monthly NDCG@30 using 12-tile relevance labels or (ii) mean monthly Spearman information coefficient (IC). The learned ranker is tested out-of-sample using monthly forward returns, benchmarked against the S&P 500, with different types of allocation weights, and further evaluated under sector concentration limits. In the last layer, the monthly-selected stock universe is used in a daily dynamic allocation which is solved by the penalized Max-Sharpe or Min-Variance optimization problems under only long positions and transaction fees. Performance is examined across Pre-COVID, COVID, Post-COVID (Train), and Final Test regimes, demonstrating how ranking objectives and diversification constraints impact performance and stability. Results show that TTM-based accounting signals, when optimized through genetic learning and disciplined allocation, yield economically meaningful stock selection and robust portfolio performance across market regimes. Full article

This study investigates the genetic diversity, population structure, and adaptive differentiation of Yunnan native cattle (YNC) using whole-genome SNP data from 457 individuals, representing eight cattle populations and two closely related bovine species (Zhongdian yak and Dulong gayal). Genetic diversity analyses revealed a distinct latitudinal gradient from north to south, with the highest diversity observed in the northern Diqing (DQC) and Zhaotong (ZTC) populations. The observed population structure was largely consistent with geographic distribution, identifying distinct ancestral components and complex admixture patterns. Genome-wide selective sweep scans revealed several key candidate genes underlying local adaptation. Notably, GRIA4 and DUOXA2 were associated with cold tolerance in northern populations, and ST3GAL3 and MST1 were implicated in heat stress adaptation in southern populations. Genome-wide balancing selection analyses further detected significant loci, such as MGST1 and SLC36A1, where divergent haplotype frequencies reflected differential selective pressures on milk-related traits between northern and southern populations. Additionally, we detected signals of historical introgression from Zhongdian yak into DQC cattle, highlighting the introgressed gene SLIT3 as a potential candidate associated with high-altitude thermogenesis. Collectively, these results provide a comprehensive genomic framework for the management and conservation of indigenous bovine genetic resources in Southwest China. Full article

Copy number variants (CNVs) are large-scale genomic alterations that contribute substantially to genetic diversity and may influence phenotypic variation in livestock. This study investigated the genome-wide CNV landscape of three Vietnamese indigenous chicken breeds. Whole-genome sequencing on the Illumina platform (3–5× coverage) was performed on 24 individuals from Dong Tao (DT), Cay Cum (CC), and Ri (RI) breeds. A total of 1743 CNVs were detected, clustering into 315 copy number variation regions (CNVRs). Most CNVRs were rare, with 31.7% present in only one animal among breeds. Across the genome, 122 unique CNVRs were distributed over 28 chromosomes, predominantly the first five. Losses were the most frequent type (45.9%), followed by gains (39.3%), and mixed events (14.8%). Within these CNVRs, 3633 genes were identified. In DT and RI, CNVR-embedded genes included several candidates, potentially related to adaptability, development, and phenotypic diversification. Notably, DT harbored genes such as EGLN1, OASL, GPX1, DUOX1/DUOXA2 (adaptation, stress/immune response) and LRP4, ZIC1, ZIC4, JARID2, KMT2C, OGN, OMD, and PLOD2 (developmental and skeletal traits), whereas in RI they included genes such as CACNA1S, CALCR, CAPN3, and MAPK13/MAPK14, which may contribute to muscle, bone, and physiological regulation. Functional enrichment analysis revealed numerous genes and Quantitative Trait Loci (QTLs) associated with metabolic, developmental, and immune-related pathways. This study provides the first comprehensive genome-wide CNV profile of Vietnamese indigenous chickens and offers a valuable genomic resource for investigating the genetic basis of breed-specific and adaptive phenotypes. Full article