Search Results (859)

Juncus (Juncaceae) comprises over 300 species with high morphological plasticity, and its systematics remain incompletely resolved due to limited genomic resources. Here, we generated complete plastid genomes for two Korean Juncus species (J. decipiens and J. gracillimus) and incorporated plastid coding genes from an additional species to reconstruct phylogenetic relationships and examine plastome evolution within Juncaceae. Comparative analyses revealed substantial plastome size variation across Juncus and Luzula, largely driven by changes in inverted repeat (IR) length, with Luzula plastomes showing pronounced IR expansion. Within Juncus, extensive structural rearrangements were detected, including multiple inversion events, and closely related taxa shared conserved inversion patterns. Phylogenomic analyses recovered well-supported clades that were associated with structural traits such as extreme small single-copy (SSC) contraction and consistent loss of the plastid ndh, some rps and rpl gene families, indicating clade-specific plastome evolution in Juncaceae. To support applied molecular identification, we identified J. decipiens-specific plastid diagnostic SNPs (matK, rpl2) and validated allele-specific PCR markers using individuals from different species within the Juncus genus. In parallel, transcriptome sequencing of J. decipiens generated 133,559 transcripts and 66,324 unigenes, enabling discovery of high-confidence nuclear exonic SNP loci by mapping reads to a J. effusus nuclear genome. Collectively, our results provide new insights into plastome structural evolution and gene loss in Juncus and deliver validated plastid and nuclear markers for authentication and future conservation or utilisation studies on J. decipiens. Full article

Dynamic characterization of calcareous (carbonate) sands is essential for performance-based design of offshore foundations, coastal reclamation, and marine infrastructure in tropical and subtropical regions. In contrast to silica sands, carbonate sediments are biogenic and typically comprise angular, irregular grains with intra-particle voids and fragile skeletal microstructure. These traits promote grain crushing and fabric evolution at relatively low-to-moderate confinement, leading to pronounced stress dependency, strong nonlinearity with strain amplitude, and substantial scatter in laboratory stiffness and damping measurements. Consequently, empirical correlations calibrated primarily on quartz sands may yield biased estimates when transferred to carbonate environments. This study presents an ML-driven, leakage-aware benchmarking framework for predicting two key dynamic parameters of biogenic calcareous sands, damping ratio $D$ and shear modulus $G$, using standard tabular descriptors commonly available in geotechnical practice. Two consolidated experimental databases were curated from resonant column and cyclic triaxial measurements ($D$: $n=890$; $G$: $n=966$), spanning mean effective confining stress $25 \le {\sigma }_m^{\prime }\le 1600 \mathrm{k}$Pa and a wide range of density and gradation conditions. To emphasize transferability, explicit deposit/site labels were excluded, and missingness arising from heterogeneous reporting was handled through a consistent preprocessing pipeline (training-only imputation, categorical encoding, and scaling). Eleven regression algorithms were evaluated, covering linear baselines, regularized regression, neighborhood learning, single trees, bagging and boosting ensembles, kernel regression, and a feedforward neural network. Performance was assessed using $R^2$, RMSE, and MAE on training/validation/test splits, and engineering credibility was supported through explainability-based diagnostics to verify mechanically plausible sensitivities. Results show that ensemble-tree models (Extra Trees and Random Forest) provide the most reliable accuracy–robustness balance across both targets, consistently outperforming linear models and the tested SVR configuration and exhibiting stable validation-to-test behavior. The explainability audit confirms physically meaningful separation of governing controls: stiffness is primarily stress-controlled (${\sigma }_m^{\prime }$ dominant for $G$), whereas damping is primarily strain-controlled ($\gamma$ dominant for $D$). The proposed framework supports practical deployment as a fast surrogate for generating $G\hspace{0.17em}-\hspace{0.17em}\gamma$ and $D\hspace{0.17em}-\hspace{0.17em}\gamma$ curves within the training domain and for guiding targeted laboratory test planning in carbonate settings. Full article

Environmental metagenomics and microbial taxonomy provide essential frameworks to evaluate how population structures shape the evolution of antimicrobial resistance and microbial community dynamics within densely populated environments. To evaluate microbial community composition and pathogenic potential, high-touch surfaces at high-traffic sites on and off campus were analyzed using metagenomics and characterization of 188 bacterial isolates, including antibiotic susceptibility testing, hemolytic assays, and whole-genome sequencing. Off-campus sites showed significantly higher bacterial richness and more complex communities enriched with diverse potential pathogens. Notably, high-risk carbapenemase genes were predominantly identified in these off-campus urban environments. In contrast, on-campus environments harbored less diverse communities dominated by opportunistic, antibiotic-resistant Staphylococcus species, with metagenomic analysis confirming a concentrated enrichment of β-lactam resistance determinants associated with methicillin-resistant staphylococci. Phenotypic profiling revealed extensive antimicrobial resistance, with 84.7% of isolates exhibiting resistance to at least one antibiotic and 35.1% of Staphylococcus showing hemolytic activity. Whole-genome sequencing further revealed that these resistance and pathogenic traits are predominantly localized on mobile plasmids, highlighting a high potential for horizontal gene transfer. These findings indicate that population activities shape distinct microbial communities in closely adjacent environments and highlight the importance of monitoring high-risk resistance determinants in densely populated university settings. Full article

The genus Capsicum comprises several species that are vital vegetable and spice crops cultivated worldwide, possessing significant economic, nutritional, and ornamental value due to their diverse fruit morphologies, colors, spiciness levels, and stress resistance. Historically, the large genome size (approximately 3 Gb) and high proportion of repetitive sequences (over 80% transposable elements) have constrained in-depth analysis of structural variations and functional genes within Capsicum species. However, recent advances in long-read sequencing, Hi-C scaffolding, and genome assembly have enabled the production of multiple high-quality and telomere-to-telomere (T2T) Capsicum genomes, which have ushered in a new era of research at the nuclear, organellar, and pan-genome levels. The publication of these omics resources has greatly expanded our understanding of the evolution of agronomically and environmentally relevant traits in peppers and their wild relatives. This review systematically summarizes recent progress in reference genomes, pan-genomes, and organellar genomes of the genus Capsicum, highlighting the enhancement of key breeding trait analyses through omics data, and outlines future integrated breeding strategies to provide theoretical and methodological references for genetic improvement and molecular breeding in pepper. Full article

Vicia villosa Roth var. glabrescens (smooth vetch) is an economically important legume cover crop valued for its nitrogen-fixing capacity, high biomass yield, and adaptability across diverse agroecosystems. Here, we present a chromosome-scale, high-quality genome assembly of V. villosa var. glabrescens, constructed using PacBio HiFi sequencing combined with Hi-C scaffolding. The assembly spans 3.70 Gb with a scaffold N50 of 4.69 Mb and exhibits lower heterozygosity (0.9%) compared to V. villosa Roth (3.1%). Genome analysis revealed significant expansion of long terminal repeat retrotransposons (LTR-RTs), as well as lineage-specific proliferation of miniature inverted-repeat transposable elements (MITEs) in V. villosa var. glabrescens. Comparative genomics with V. villosa Roth highlighted gene family expansions associated with trichome development, providing insights into the genetic basis of morphological and adaptive differences within the Vicia species. This reference genome provides a foundational resource for accelerating the breeding of V. villosa varieties with enhanced agronomic traits and contributes to a broader understanding of legume genomics and plant genome evolution. Full article

Glycogen synthase kinase 3 (GSK3/SHAGGY-like kinase) plays a pivotal role in regulating plant growth, development, and stress responses. To elucidate the characteristics of the GSK family in Glycine max, this study employed whole-genome data combined with bioinformatic and gene expression analyses to investigate the gene structure, chromosomal localization, collinearity, phylogenetic evolution, promoter cis-elements and differential gene expression analysis. Additionally, the expression patterns of GmGSK genes under manganese (Mn) stress and their associated phenotypic alterations were analyzed. A total of 22 GmGSK family members were identified, all harboring the characteristic GSK kinase domain. These members are distributed across 16 chromosomes, encoding proteins ranging from 380 to 802 amino acids (aa) in length. Phylogenetic analysis classified the GmGSK family into four evolutionary clades, consistent with patterns observed in Arabidopsis and Oryza sativa. Members within the same clade share identical exon-intron structures and conserved motifs. Collinearity analysis revealed that segmental duplication events have been crucial in the functional expansion of the GmGSK family through intraspecific collinearity. In recent years, alongside industrial development and fertilizer imbalance, the effective manganese concentration in agricultural soils has risen abnormally in some regions of China, leading to toxic effects on crops. Soybean, an oilseed crop relatively sensitive to manganese, has been adversely impacted. Clarifying the response mechanisms of soybean seedlings to manganese stress is therefore of significant importance for improving both yield and quality. Manganese stress treatment induced significant up-/down-regulation of specific GmGSK members in soybean, concomitant with pronounced inhibition of root elongation and leaf growth. This study provides a theoretical framework for deciphering the molecular regulatory mechanisms by which the GmGSK gene family mediates plant responses to Mn stress, offers insights into soybean Mn tolerance mechanisms, and establishes a foundation for genetic improvement of Mn-tolerant traits in crops. Full article

Bivalves possess a diverse array of photoreceptive organs that are significant for their evolutionary success and systematic classification. Giant clams are the largest bivalve mollusks, with mantle tissue permanently extended in nature to maintain symbiosis with zooxanthellae and perceive environmental cues. Eyes serve as critical sensory organs for these organisms, yet the structural and functional characteristics of tridacnine eyes remain inadequately understood. This study systematically investigated the ocular traits and visual resolution of three ecologically distinct giant clam species (Tridacna crocea, T. squamosa, T. maxima) using morphometric analysis, hematoxylin-eosin (HE) staining, transmission electron microscopy (TEM), and grating stimulation assays. Significant interspecific differences were observed in eye count, diameter, and pupil-to-eye ratio (PER): T. maxima exhibited the highest mean eye count (221 ± 8), T. squamosa the largest mean eye diameter (0.490 ± 0.082 mm), and T. crocea the highest mean PER (0.363 ± 0.041). Eyes were numerically symmetric on the left and right mantles but positionally asymmetric, showing random distribution patterns along the mantle margin without fixed corresponding locations across species. All three species possessed typical pinhole eyes lacking lenses and retinas, primarily composed of filler cells, receptor cells, and sparse neurons, with symbiotic zooxanthellae distributed in the surrounding mantle tissue. Grating stimulation assays revealed resolvable stripe periods of 5.82–11.64° (T. crocea), 8.62–13.16° (T. squamosa), and 10.15–12.26° (T. maxima), confirming T. crocea as the species with the highest visual resolution. These ocular variations are inferred to reflect adaptive evolution driven by ecological niches and habitat-specific factors (water depth or light intensity), while the simplified pinhole morphology is consistent with their sedentary lifestyle and metabolic dependence on symbiotic zooxanthellae. These ocular variations provide potential morphological markers for the systematic classification of Tridacninae and offer valuable insights for researchers studying the evolutionary plasticity of bivalve visual systems. Full article

Silk production is a classic example of a domestication trait, yet the cell-type-specific driver of its enhancement in the silkworm Bombyx mori remains unresolved. To address this, we integrated extensive bulk RNA-seq data with a single-nucleus RNA-seq atlas of silk glands (SGs) from domestic B. mori and wild B. mandarina for deconvolution analysis. This identified phenotype-associated cell subpopulations (Scissor+ and Scissor− cells) that enrich in B. mori and B. mandarina, respectively. Transcriptomic characterization revealed that B. mori SG cells exhibit a pervasive “pro-synthesis” transcriptional state, with concerted upregulation of silk protein genes and metabolic pathways. Conversely, B. mandarina cells maintained a “protective–adaptive” state, enriched for stress response and xenobiotic metabolism genes. Pseudotime analysis further delineated the cell state transitions, pinpointing key dynamic gene expression linked to high silk yield. Our findings demonstrate that domestication reshaped the silk gland cellular landscape, promoting a systemic shift toward a synthesis-optimized cell state. This study offers a new framework at the cellular level to elucidate the evolution of complex traits under selection. Full article

Clarifying the complex interaction between climate risks and the new energy industry chain is of key significance to advancing the energy transition and strengthening industrial chain robustness. This research pairwise-matches the climate physical risk and the climate transition risk with the entire range of the new energy industry chain segments, comprehensively examining the pairwise interactive relationships. By applying the MF-ADCCA series of methods, it was revealed that there are prevalent asymmetric cross-correlated multifractal characteristics between climate risks and the new energy industry. The long-term memory under the upward trend of the market is distinctly stronger than that under the downward trend. Given that this correlation can indirectly reflect market efficiency differences, this paper constructs the Hurst Volatility Sensitivity Index (HVI) and the Hurst Asymmetry Index (HAI) and further proposes the Unified Market Efficiency Index (UMEI). Its innovative advantage resides in the balanced integration of volatility efficiency and structural symmetry, in turn enabling a comprehensive assessment of the new energy market efficiency under climate risk perturbations. Static analysis reveals that the overall market efficiency of the new energy industry under the climate transition risk is generally higher than that under the climate physical risk, and the market efficiency of mature upstream and midstream new energy segments is significantly superior to that of the downstream. Dynamic evolution characteristics indicate that market efficiency has typical time-varying traits, the evolution of which is often driven by significant policies or extreme events. The climate transition risk tends to trigger aperiodic structural adjustments, while the climate physical risk mostly induces periodic efficiency fluctuations. This study furnishes solid evidence for the new energy market in coping with climate risks. Full article

Body size is a key trait influencing life history and ecological adaptation, and sexual size dimorphism (SSD) reflects divergent selective pressures acting on males and females. In morphologically conserved insect groups such as Cassidinae leaf beetles, the external similarity between sexes often impedes accurate dimorphism assessment. To address this, we conducted a systematic morphometric study of ten Cassidinae species from the Nanling Mountains—the largest east–west mountain system in southern China—where we definitively assigned sex via genital dissection. We measured body weight, body length, body width, length–width ratio, and corresponding wing traits. Across all species, SSD was consistently female biased, with statistically significant but subtle differences in most traits; body weight exhibited the greatest relative disparity. While this pattern aligns with the fecundity advantage hypothesis, direct fecundity data were not collected. Crucially, interspecific allometric analyses revealed that the scaling of male and female body sizes was statistically indistinguishable from that of isometry, providing no significant support for Rensch’s rule in this female-biased system. Our findings offer foundational insights into SSD evolution in cryptically dimorphic, herbivorous beetles and highlight the need for phylogenetically informed studies across broader geographic and taxonomic scales. Full article

Cyberbullying demonstrates notable metaphorical and contextual traits, characterized by a high-dimensional sparse semantic space and dynamic evolution. Pre-trained models utilize extensive textual data for learning and employ transformer-based word vector generation techniques to accurately capture intricate semantics and nuanced syntax in text. However, although a single pre-trained model demonstrates strong performance in contextual modeling, it still faces challenges including inadequate feature representation and limited generalization capability in classifying cyberbullying texts. This study proposes a cyberbullying detection model employing BERT-BiGRU-CNN (BBGC) to address this issue. The BBGC model initially employs BERT to produce word embeddings, subsequently inputs them into a BiGRU layer to acquire sequence features, and finally utilizes a CNN for the extraction of local features. The features derived from BERT, BiGRU, and CNN are integrated, followed by the application of the softmax function to yield the final outcome of cyberbullying detection. Experimental findings indicate that the BBGC fusion model surpasses individual pre-trained models in the task of detecting cyberbullying text. Furthermore, in comparison to hybrid neural network models utilizing RoBERTa, ALBERT, DistilBERT and other pre-trained models, the BBGC model demonstrates considerable advantages. Full article

The silkworm (Bombyx mori) is essential to sericulture and is also becoming a key model organism in genomics and agriculture. For decades, genetic studies of the silkworm were limited by inefficient and inflexible genome tools. CRISPR genome editing allows precise and scalable alterations to genes regulating development, physiology, and industrial traits. This review summarizes silkworm genome-editing breakthroughs, highlighting CRISPR’s evolution from simple gene knockouts to large-scale genome-wide screening. We highlight how these advancements contribute to disease resistance, higher yields, and the development of new silk-based materials, as well as how they influence the development and growth rate of the sericulture. The creation of high-quality reference genomes, pangenomes, and genome-wide screening systems has made the silkworm a major model for integrating multiple biological datasets and approaches, such as genomic, transcriptomic, and proteomic. By considering the unique biological characteristics of the silkworm, this provides new insights for research on silk biology, piRNA synthetic biology, and hormonal signaling regulation. Finally, we examine new areas at the intersection of CRISPR, pangenomics, and artificial intelligence (AI) and suggest future paths for molecular breeding, pest control, and synthetic biology. Moreover, AI-assisted prediction of CRISPR outcomes is utilized to inform the design of targeted trait modifications, representing an approach to enhancing biomanufacturing efficiency and eco-friendly silk production. Together, these advances have made the silkworm a flexible genetic platform and an important part of sustainable agriculture and biomanufacturing. Full article

Chenopodium album L. is a highly problematic weed in agricultural systems, exhibiting resistance or tolerance to multiple herbicides. This weed significantly impacts crop growth and yield, threatening global agricultural production. Since the introduction of genetically modified herbicide-resistant crops, glyphosate has become a primary option for controlling C. album. However, the continuous application of glyphosate has led to shifts in weed community composition, favoring species that are more challenging to manage, and thus complicating weed control efforts. Although glyphosate resistance in C. album has not been confirmed, varying tolerance among populations brings practical problems to weed evolution. This review provides a synthesis of the progress on the mechanisms of glyphosate tolerance in C. album. Key factors influencing plant responses to glyphosate are examined, including target proteins, encoding genes, morphological and physiological traits, transport capacity, and metabolic detoxification processes. The existing evidence indicates that glyphosate tolerance in C. album is driven primarily by non-target-site adaptations or morpho-physiological changes, not target-site mutations. The insights gained from this review will aid in designing precision approaches to manage glyphosate-tolerant weeds in agricultural systems. Full article

Polygenic adaptation in response to natural selection on a quantitative trait has become an important topic in population genetics and evolution. We modeled a scenario in which a population was assumed to be in equilibrium between mutation, selection and genetic drift, when a sudden shift in the fitness optimum occurred. It is well known that after an environmental shift the trait mean may approach the new optimum very quickly at a rate proportional to the equilibrium genetic variance. Here, we analyze the dynamics of the allele frequencies at individual loci, using diffusion theory. We show that genetic drift slows down the speed of polygenic adaptation. We also found that, while the frequencies of rare and very common alleles decrease during the adaptive phase, alleles starting at intermediate equilibrium frequencies at the time of the optimum shift change most quickly and thus may substantially modify the shape of the allele frequency distribution. Finally, we explain how these properties of the allele frequency spectrum may be utilized in statistical tests of polygenic selection. Full article

This study presents integrated zircon U-Pb geochronology, whole-rock geochemistry, and Sr-Nd-Hf isotopic investigations of quartz diorite and gneissic quartz diorite from the Datian Complex along the western Yangtze Block, elucidating their petrogenesis and tectonic implications. Key findings reveal: (1) The crystallization ages of the Datian Complex (~770–755 Ma) record episodic magmatic activity over a ~16 Ma period, indicating a multi-stage tectonic evolution; (2) Both rock types exhibit intermediate SiO₂ (57–64.58 wt.%), high Al₂O₃ (15.44–17.80 wt.%), and MgO (2.18–3.67 wt.%; Mg# = 47.41–52.65) with calc-alkaline signatures (Na₂O/K₂O = 1.14–2.65), coupled with adakitic traits including pronounced LREE/HREE fractionation (La_N/Yb_N = 3.83–26.4), negative Eu anomalies (δEu = 0.61–1.05), elevated Sr (372–701 ppm), and Sr/Y ratios (24.6–56.2), collectively classifying the complex as high-Si adakite; (3) The isotopic homogeneity (whole-rock Sr-Nd: ⁸⁷Sr/⁸⁶Sr(i) = 0.7038–0.7048, εNd(t) = −1.5 to–3.8; zircon Hf: εHf(t) = 1.24–6.88) supports a two-stage petrogenetic model involving partial melting of subducted oceanic slab, followed by mantle wedge metasomatism during magma ascent. These results position the Datian Complex as a Neoproterozoic arc-related adakitic magmatic system within the active continental margin of the Yangtze Block. Full article