Huoxiang Zhengqi (HXZQ) is a classical polyherbal formulation used to treat gastrointestinal disorders. It exerts multi-targeted therapeutic effects, yet its phytochemical complexity hinders standardization and modern pharmacological development. This challenge is further exacerbated by the lack of comprehensive resources covering its diverse natural components, particularly as most previous research neglected peptides and small RNAs, which possess emerging therapeutic potential. There is an urgent need for novel research models to explore polyherbal formulations such as HXZQ. Here, we present the Huoxiang Zhengqi Component Galaxy (HXZQCG), a dedicated database for the HXZQ. HXZQCG integrates over seven million natural components through artificial intelligence-assisted mining, including 15 811 metabolites, 7 597 212 small peptides, and 152 342 small RNAs. To demonstrate its utility, we applied HXZQCG to screen for ligands of the histamine H2 receptor (H2R), a well-established and druggable G Protein-Coupled Receptor (GPCR) target widely implicated in gastrointestinal pathologies. Through high-throughput screening of potential ligands for H2R based on the HXZQCG, we identified 125 candidates. Candidates identified through virtual screening were validated via cell membrane chromatography, ultimately identifying two putative binding small molecules. Furthermore, our results demonstrated that naringenin chalcone is a ligand of H2R, and it can inhibit the downstream accumulation of cyclic adenosine monophosphate (cAMP). In sum, HXZQCG stands as a representative case study for polyherbal formulation research. It provides data-based resources for discovery of active component and elucidation of pharmacological mechanisms, serving as a fundamental data-driven platform to support the secondary development of HXZQ. HXZQCG is available at https://cbcb.cdutcm.edu.cn/HXZQCG/.

The widespread adoption of hybrid rice has played a pivotal role in ensuring food security in China. However, the heavy reliance on wild-abortive (WA) cytoplasmic male sterility (CMS) systems raises potential biosafety concerns. In this study, we screened a global collection of wild rice (Oryza rufipogon) accessions using orf182-specific molecular markers to characterize the geographic distribution patterns of this gene. Mitochondrial sequencing and assembly of 11 representative wild rice species harboring orf182 revealed 16 novel genes. A total of 469 mitochondrial genes were classified into 23 gene families, with nine families containing single-copy homologous genes, indicating significant gene duplication in mitochondria. We observed a strong positive correlation between mitochondrial genome size and the quantity and size of repetitive sequences. Collinearity analysis revealed extensive mitochondrial variation and large-scale inversions in Guangdong wild rice. Comparative genome analysis uncovered inversions, translocations, and several variations surrounding orf182, with a 71 bp repeat sequence mediating the formation of the orf182-nad6 chimeric gene. Gene copy number analysis (GCNV) revealed variable orf182 gene copy counts (1, 2, and 3) in wild rice species. Additionally, successful transformation of orf182 from various sources into sterile lines was achieved. These findings provide valuable resources for advancing hybrid rice development in China, thus contributing to enhanced food security.

Polygonaceae is a globally distributed angiosperm family rich in anthraquinones (AQs), which contribute to diverse medicinal properties and species-specific chemical defenses. Despite their ecological and pharmacological significance, the evolutionary dynamics and transcriptional regulation of AQ biosynthesis genes in Polygonaceae remain largely unexplored. In this study, we combined comparative genomics and multi-omics analyses to investigate these processes. Phylogenomic reconstruction indicated that Polygonaceae diverged from its sister family approximately 66.26 million years ago. A total of 206 polyketide synthase (PKS) genes were identified, with lineage-specific tandem duplication driving substantial expansion. Polyketide biosynthetic gene clusters with dense PKS aggregation were detected in three species, primarily shaped by tandem duplication. By integrating gene expression and synteny analyses, candidate PKS genes likely involved in AQ biosynthesis were identified. Multi-level gene regulatory networks constructed from root transcriptomes of Fallopia multiflora across different growth years revealed hierarchical regulatory relationships and divergence among candidate PKS genes. Weighted gene co-expression network analysis further identified co-expression modules and transcription factors potentially associated with AQ biosynthesis, while machine learning approaches prioritized transcription factors regulating the glycosyltransferase involved in AQ modification. These results reveal the evolutionary expansion, diversification, and functional specialization of PKS genes, as well as the hierarchical transcriptional regulation underlying AQ biosynthesis in Polygonaceae. The identified candidate genes and regulatory networks provide a valuable resource for metabolic engineering and molecular breeding strategies aimed at enhancing medicinal AQ production.

The beneficial fungus Trichoderma enhances plant growth and stress tolerance through poorly understood mechanisms. Here, we show that Trichoderma harzianum swollenin ThSWO contributes to efficient root colonization and plant growth promotion. ThSWO traverses the plant cell wall and localizes to the plasma membrane, where it interacts with ABC transporter AtABCB5, which we establish as a bona fide auxin efflux carrier. ThSWO binding to NBD2 and R-domain faces of AtABCB5 prosmotes phosphorylation at Ser640 and Ser644, enhancing indole-3-acetic acid (IAA) efflux and triggering auxin-associated responses, including cell wall acidification, membrane potential transitions, and accelerated cytoplasmic streaming. Structure-guided substitutions at the AtABCB5-ThSWO interface differentially affected transporter binding and lateral root promotion, supporting the conclusion that host auxin transport is a primary effector target. These findings reveal a molecular mechanism by which a fungal effector co-opts host auxin transport machinery to promote plant development, with implications for microbe-assisted crop improvement.

Grain size and leaf angle are closely related to the final yields of rice (Oryza sativa). Brassinosteroids (BRs) are plant-specific steroid hormones that play a crucial role in regulating grain size and leaf angle; however, the underlying molecular mechanisms require further investigation. Here, we report on OsbHLH186, which encodes an atypical bHLH transcription factor. OsbHLH186 influences grain size and leaf angle by affecting cell expansion. The cr-osbhlh186 mutants exhibit smaller grains and erect leaves, whereas overexpressed OX-OsbHLH186 plants display larger grains and increased leaf angle. OsbHLH186 acts as a positive regulator in response to BR signaling, with the cr-osbhlh186 mutant being insensitive to exogenous BR treatment, while OX-OsbHLH186 plants are hypersensitive. Biochemical and genetic analyses demonstrate that OsbHLH186 interacts with BRASSINOSTEROID UPREGULATED 1-LIKE1 (OsBUL1) and OsBC1, functioning within a common pathway. Further transient expression assays indicate that OsbHLH186 and OsBUL1 mediate the transcriptional activity of OsBC1. Overall, these findings suggest that OsbHLH186 is associated with a potential transcriptional complex that mediates BR signaling and rice development, indicating that OsbHLH186 could serve as a promising target for improving plant architecture and grain shape in rice.

Accurate identification of the geographical origin of tea leaves is crucial for ensuring quality assurance and traceability within the tea industry. This study introduces Origin-Tea, a novel lightweight convolutional neural network that innovatively combines depthwise separable convolutions with squeeze-and-excitation (SE) attention mechanisms to effectively capture subtle phenotypic variations while minimizing computational costs. Unlike prior approaches that depend on heavy architectures or handcrafted features, Origin-Tea is explicitly designed for efficiency and interpretability in agricultural applications. Comprehensive ablation studies confirm the significant contribution of each architectural component to the model’s robust performance. The dataset comprises 900 high-resolution RGB images of Yunkang 10 tea leaves, independently collected from seven distinct regions in Yunnan Province. A 10-fold stratified nested cross-validation (CV) was employed, with one-fold designated for testing, one for validation, and the remaining eight for training in each iteration. Data augmentation techniques, including flipping, rotation, and exposure adjustments, were applied solely to the training set to enhance model robustness without compromising the intrinsic phenotypic features. Origin-Tea achieved an average overall accuracy (OA) of 0.92 ± 0.03 and a Kappa coefficient of 0.90 ± 0.03, outperforming the best-performing baseline, CoAtNet (OA = 0.89 ± 0.03), by 3.37

Resistance genes are critical for plant defence against biotic stresses, and building a comprehensive, integrated data resource platform for these genes holds great significance for plant research and agriculture. Here, we developed PlantRG (http://plantrg.bio2db.com), a user-friendly plant resistance gene database, which is built on 2 163 397 resistance genes identified from 1062 plant species. These genes were mined from all accessible plant genomic resources-systematically curated from 794 peer-reviewed publications and 107 public databases-to ensure data breadth and reliability. All resistance genes in PlantRG were further functionally annotated using five major reference databases, enhancing their utility for targeted studies. Additionally, 207 353 SSR markers and 141 582 miRNAs associated with these resistance genes were detected, providing insights into their regulatory networks and genetic markers. Key bioinformatic results, including gene duplication patterns, protein-protein interaction predictions and CRISPR guide sequences, were also generated and stored in the database. PlantRG allows free browsing and downloading of all resistance gene sequences, annotations and bioinformatic data. It also offers practical tools such as Blast (for homology search), CasViewer (for CRISPR guide visualization), Circos (for genomic landscape analysis), HmmerSearch (for domain-based identification) and Primer Design, to facilitate user-friendly comparative genomic analysis. Notably, PlantRG is the comprehensive platform to complete large-scale collection and bioinformatic analysis of plant resistance genes. It will support in-depth studies on the structure, function and evolutionary patterns of resistance genes, thereby contributing to agricultural development-for example, breeding stress-resistant crop varieties. In the future, PlantRG will be continuously updated to incorporate new data and features, maintaining its value for the global plant research community.

The plasma proteomic signatures of sleep disturbance remain poorly characterized. Using data from 43,709 predominantly European-ancestry, middle-aged and older UK Biobank participants, we depict a large-scale atlas of plasma proteomic signatures of seven self-reported sleep traits (sleep duration, chronotype, insomnia symptoms, daytime napping, daytime sleepiness, snoring, and ease of getting up in the morning) and a derived sleep health score. We identify 935 proteins associated with at least one sleep trait, converging on lipid metabolism, immune function and inflammation, cell adhesion, and neurochemical signaling. Leveraging genomic structural equation modeling to define three latent sleep factors, namely circadian preference, daytime sleep burden, and nighttime sleep adequacy, bidirectional Mendelian randomization (MR) identifies one protein (LTA) with robust cis-instrument and strong colocalization support (PP.H4 = 0.98) for a putative causal effect on nighttime sleep adequacy. Sixteen additional genetically supported candidate proteins rely primarily on trans-pQTL instruments or weaker colocalization. These genetically supported candidates are prospectively associated with incident cardiovascular disease, stroke, type 2 diabetes, dementia, chronic kidney disease, depression, and mortality over a median 13.6-year follow-up, with the strongest per-SD hazard ratio (HR) associations observed for chronic kidney disease (e.g., BTN2A1: HR = 2.33) and type 2 diabetes (e.g., RBP5: HR = 1.58). Collectively, these findings highlight the potential of large-scale proteomics in elucidating sleep pathogenesis, and generate testable hypotheses for validation in independent cohorts and experimental models.

Bacillus subtilis was widely used for enzyme production and was gradually engineered to biosynthesize value-added chemicals with the development of genetic parts for it. Compared to other genetic parts for expression, the identified integration sites were fewer, which limits the development of B. subtilis. Here, a library of integration sites was developed for B. subtilis. All candidate sites were selected at the 3′-untranslated region of two opposite nonessential genes and separated by essential genes among genome to avoid the destruction for coding sequence of genes and eliminate the homologously recombined strains with the loss of essential genes. The expression of GFP and cell growth were detected for candidate sites to evaluate the gene expression strength and the influence on cell growth. As a result, 12 loci revealed higher gene expression level and cell growth compared with control site amyE, the highest expression site spxA was 1.89 times as high as amyE. Using the developed integration sites library, threefold gene expression range could be achieved without the replacement of promoter and RBS. When the integration site library was used to construct cell factories, the production of lacto-N-triose II and lycopene was increased by 95% and 83%, respectively. In addition, integration site library was also successfully used to increase the enzymatic activity of secretory β-galactosidase by 101% when the strain using spxA locus compared with that using amyE. The developed integration site library could accelerate the construction of stable and plasmid-free cell factories for B. subtilis in the future.

The grand jackknife clam, Solen grandis, is a crucial mariculture bivalve with high economic value. To investigate the genetic variation of S. grandis in China, the whole-genome resequencing was carried out on 81 individuals from three S. grandis geographical populations (Huludao [HLD], Rizhao [RZ], and Dongtai [DT]) to develop the genome-wide SNPs. Generally, all three populations indicated low genetic diversity. For each population, the observed heterozygosity (HO) ranged from 0.097 to 0.101, the expected heterozygosity (HE) from 0.105 to 0.109, the number of effective alleles (Ne) from 1.329 to 1.343, nucleotide diversity (π) between 0.0107 and 0.0111, the polymorphism information content (PIC) from 0.156 to 0.160, and the inbreeding coefficient (FIS) values of 0.042 to 0.053. Meanwhile, the fixation index pairwise (FST) values among the three S. grandis populations ranged from 0.008 to 0.023, which were low differentiation. Additionally, population structure analysis revealed that the RZ and DT populations first clustered together and were further grouped with the HLD population. Moreover, the genome-wide outlier analysis identified 32 candidate selected regions with a total size of 5.50Mb, as well as 10 candidate genes including ACE (Angiotensin-converting enzyme), KIAA1161 (Myogenesis regulating glycosidase), CES1 (Carboxylesterase 1), RPS13 (Ribosomal protein S13), APOD (Apolipoprotein D), PPP1R13B (Protein phosphatase 1 regulatory subunit 13B), and CHDH (Choline dehydrogenase), etc. Overall, this study enriches the genetic resources of S. grandis and improves our understanding of its population genetic structure and selection signatures, providing a useful reference for future genetic resource conservation and management.

Predicting internal biological states and nutrient requirements from simple, non-invasive morphometric traits remains challenging due to small sample sizes, strong non-linearity, and the need for interpretability. Using only carapace length and condition factor, we propose a hierarchical multi-task deep neural network with cross-attention that explicitly models the pathway “morphometry → metabolism → development”. The model simultaneously predicts gonadosomatic index (GSI), ovarian arachidonic acid (ARA) content, and ARA intake. A multi-objective optimization step selects seven intermediate metabolites that bridge external morphology to reproductive status. We compare three attention mechanisms (Multi-Head, Additive, Dot-Product) under identical conditions. Multi-Head attention achieves test-set Pearson correlation (average r = 0.756), outperforming Additive (r = 0.745) and Dot-Product (r = 0.733). Compared with conventional models (Random Forest, SVR, single-hidden-layer ANN), our network also shows superior performance (average r = 0.758 vs. 0.732, 0.569, 0.137). Cross-attention heatmaps and Shapley Additive exPlanations (SHAP) analysis suggest that the embedded metabolites—linked to ARA metabolism and sphingolipid signaling—are associated with the predictions, providing computational plausibility without sacrificing accuracy. This is the first attention-based framework for non-destructive prediction of ARA-related ovarian development in crustaceans. The model should be viewed as a proof-of-concept research prototype for small-sample, cross-modal biological prediction tasks, requiring prospective multi-site validation before farm application.

The metabolome is highly diverse and the closest layer to phenotype; therefore, it is commonly regarded as a bridge between the genome and phenome in plants. Here, we performed large-scale metabolome analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and 33 grain-related traits in a diverse panel of natural accessions and a recombinant inbred line (RIL) population. We identified a new network of 2286 associations between 947 metabolites and 33 grain-related traits. Systematic integration of metabolic genome-wide association study (mGWAS) and metabolic quantitative trait locus (mQTL) analyses identified 33 566 significant single-nucleotide polymorphisms (SNPs) and 3128 mQTL. Thirteen annotated metabolites co-localized within a physical interval on 7A. Integration of metabolite-based and phenotype-based GWAS and QTL revealed an overlapped region for gibberellin A4 (GA4) content and grain roundness on 4A. Phenotyping of an ethyl methanesulfonate (EMS)-induced mutant confirmed the role of TaSDR in regulating GA4 content and grain morphology. These findings provide novel insights into the metabolic pathways influencing key grain-related traits and advance our understanding of the complex molecular mechanisms regulating grain metabolites and phenotypes in wheat. The identified metabolic markers and candidate genes provide valuable targets for molecular breeding programs aimed at improving wheat yield and quality.

High-frequency longitudinal RNA sequencing has emerged as a powerful approach for capturing dynamic transcriptional responses to therapeutic interventions, yet traditional differential expression analysis fails to identify genes with temporal variability that lack static expression differences. We used our previously developed computational framework for identifying Temporally Varying Genes (TVGs) from daily blood samples collected over 10-21 days in Sprague-Dawley rats treated with hepatotoxic compounds including tetracycline, isoniazid, carbon tetrachloride, and valproate. Our methodology employs variance-based scoring to detect genes exhibiting significant temporal fluctuations under treatment conditions. Unsupervised hierarchical clustering of TVGs identified three distinct temporal patterns: early-transient responses, sustained activation, and late-phase upregulation, each enriched for specific biological processes. Principal component analysis demonstrated clear treatment-induced transcriptomic shifts from baseline "Healthy Region" clusters to treatment-adapted "Response Region" states, with sample trajectories reflecting dose-dependent temporal dynamics. Cross-compound analysis revealed 186 commonly regulated genes across all treatments, representing conserved hepatotoxicity signatures, while compound-specific responses highlighted distinct mechanistic pathways. This approach enables kinetic-pharmacodynamic modeling that distinguishes primary drug targets from secondary adaptive responses, advancing precision medicine applications through dynamic molecular portraits of drug action and individual treatment variability.

Plant epicuticular waxes (EW) play a critical role in defending against biotic and abiotic stresses. Notably, onions (Allium cepa L.) present a distinctive case where the mutant with defect in leaf and stalk EW showed resistance to thrips compared with the wild type with integral EW. We identified a premature stop codon mutation in the AcCER2 gene, an ortholog of CER2 gene in Arabidopsis thaliana that has been proved essential for the biosynthesis of very long-chain fatty acids (VLCFAs), in the onions with glossy leaf and stalks in our experiments. The data hinted at the possibility that this mutation might impede the elongation process of VLCFAs from C28 to C32, thereby hindering the production of 16-hentriacontanone, a primary constituent of onion EW. Transcriptomic analysis revealed substantial alterations in expression of genes in the pathways related not only to lipid synthesis and transport but also to signal transduction and cell wall modification in glossy mutants. Meanwhile, metabolomic profiling indicates a remarkable increase in flavonoid accumulation and a significant reduction in soluble sugar content in glossy mutants. These findings suggested that the enhanced resistance of glossy mutants to thrips might be a consequence of multiple physiological changes, and our integrated multiomics analysis highlighting the regulatory role of AcCER2 in these processes. Our study has yielded valuable insights into the biosynthesis of onion EW and has provided an initial hypothesis for the mechanisms underlying thrip resistance. These findings hold significant promise for the breeding programs of thrip-resistant onion.

Ring Box Protein-1 (RBX1) is an essential component of the Skp1-cullin-F-box protein (SCF) E3 ubiquitin ligase, which is involved in the regulation of oocyte maturation in the form of ubiquitination substrate modification. In this study, a sequence of RBX1 (Sp-RBX1) was identified and analyzed using bioinformatics methods from the transcriptome data of Scylla paramamosain. The length of Sp-RBX1 cDNA sequence was 1247 bp, consisting of a 336 bp open reading frame (ORF). Sequence analysis revealed that the protein contained a C-terminal modified RING-H2 finger domain, with two zinc binding sites and a Cullin binding site, classifying it as a member of the RBX1 superfamily. The results of real-time fluorescence quantitative PCR (RT-qPCR) showed that Sp-RBX1 expression in the ovary was low at stages I and II, then significantly increased from stage III to V (p < 0.05), which indicated that it might be closely related to the maturation of oocytes. It also peaked at stage II in the hepatopancreas, then sharply declined from stages III to V. The expression pattern might be related to the accumulation of fat in the early development of hepatopancreas. Furthermore, we characterized the expression of Sp-RBX1 induced by follicle-stimulating hormone (FSH) and estradiol (E2) hormones. The results showed that the expression in the ovary was up-regulated by FSH and significantly inhibited by E2. The expression in the hepatopancreas increased only at 0.5 µmol/L concentration of FSH, and decreased in other groups. Conversely, it was up-regulated by E2. Thus, the expression of Sp-RBX1 was influenced by FSH in a concentration-dependent manner. These findings could offer valuable insights for further research on ovarian maturation in crustaceans.

Studying the nutritional components and accumulation patterns in colored wheat grains is essential for improving wheat nutritional quality and advancing the development of functional foods. Through a comprehensive high-throughput metabolomics and ionomics analysis of grains from 16 colored wheat varieties at various growth stages, 501 essential nutrients were identified. The findings revealed that colored wheat exhibited higher levels of anthocyanins, vitamins, iron, and zinc compared to white wheat. Anthocyanin levels increased in colored wheat varieties post-21 d after flowering, while other nutrients decreased as the grains matured. Interestingly, green wheat kernels were found to be more nutrient-rich than mature kernels, containing beneficial compounds such as polyphenols, flavonoids, amino acids, and vitamins, which make them ideal for functional food development. Transcriptome analysis identified key synthetic genes and transcription factors responsible for anthocyanidin accumulation in colored wheat. This study offers valuable insights for utilizing colored wheat varieties to improve crop nutrition and innovate in the field of functional foods.

Wheat (Triticum aestivum) production is vital for global food security, providing energy and protein to millions of people worldwide. Recent advancements in wheat research have led to significant increases in production, fueled by technological and scientific innovation. Here, we summarize the major advancements in wheat research, particularly the integration of biotechnologies and a deeper understanding of wheat biology. The shift from multi-omics to pan-omics approaches in wheat research has greatly enhanced our understanding of the complex genome, genomic variations, and regulatory networks to decode complex traits. We also outline key scientific questions, potential research directions, and technological strategies for improving wheat over the next decade. Since global wheat production is expected to increase by 60% in 2050, continued innovation and collaboration are crucial. Integrating biotechnologies and a deeper understanding of wheat biology will be essential for addressing future challenges in wheat production, ensuring sustainable practices and improved productivity.

Nothapodytes nimmoniana is known to produce the highest content of the anticancer compound camptothecin (CPT) in the plant kingdom. We present the chromosome-level allotetraploid genome of N. nimmoniana, marking the first genome sequence from the order Icacinales. This 5-Gb genome encodes 92,630 genes, with subgenome B exhibiting dominant gene expression. Through genome mining, we identified and characterized four key enzymes involved in CPT biosynthesis, revealing that N. nimmoniana shares a similar prestrictosidine pathway with most monoterpene indole alkaloid-producing plants. Notably, homoeologous pairs of all characterized enzymes maintained their functions across both subgenomes, suggesting that gene duplication from allotetraploidization likely enhances CPT production in this species. Phylogenetic and syntenic analyses revealed that strictosidine synthase and strictosamide epoxidase were independently recruited in N. nimmoniana, Camptotheca acuminata, and Ophiorrhiza pumila, supporting the hypothesis that CPT biosynthesis evolved independently at least three times within the asterid clade.

The synergistic action of GH18 chitinase and GH20 beta-N-acetylhexosaminidase (Hex), two glycosylated hydrolase families, is crucial in the molting process of the Asian corn borer (Ostrinia furnacalis) and are regarded as important target for the development of green pesticides. Herein, two series of compounds A (15 compounds) and B (14 compounds) were synthesized to inhibit chitin degrading enzyme by the strategy of the multitarget. Enzyme activity experiments showed that the enzyme activity of B-series compounds was superior to A-series compounds, attributing to the strong hydrogen bond interaction between Glu328 and 1,3,4 thiadiazoline as well as hydrophilicity of 1,3,4 thiadiazoline. Thereinto, B12 was shown to exhibit inhibitory activities against all four chitinolytic enzymes as C-glycoside thiadiazole inhibitors with K-i of 23.21 mu M, 40.20 mu M, 28.32 mu M and 15.21 mu M for OfChtI, OfChtII, OfChi-h and OfHex1, respectively, and possessed a favourable insecticidal activity (similar to 70 %) against P. xylostella and O.furnacalis. What's more, the hydrophobic effect and polar interaction played significant roles in the combination between B12 with OfHex1. Particularly, preliminary biological tests revealed that B12 possessed certain inhibitory effect on the growth and development of O.furnacalis and P. xylostella. This study provides an example of using a multitarget strategy to develop C-glycoside thiadiazole as an insecticide precursor for the biodegradation of chitin.

Dear Editors, Wheat(Triticum aestivum)faces significant threats from diseases such as powdery mildew(Blumeria graminis)and Fusarium head blight(FHB;caused by Fusarium graminearum),which cause se-vere yield losses.Moreover,the antagonism between yield-related traits and disease resistance makes yield resistance coor-dination a major challenge in wheat breeding.