Horticulture Research

Climate change poses an increasing threat to the cultivation of deciduous fruit trees, placing greater demands on modern pear breeding. Using pear germplasm adapted to diverse environments, we assembled 11 chromosome-level genomes. In combination with 13 publicly accessible pear genomes, we analyzed presence-absence variations (PAVs) and constructed a graph-based pangenome for pear. By performing a PAV-eQTL analysis of the fruit of 123 pear accessions, we identified PAVs significantly associated with expression levels of genes that may be involved in regulating agronomic traits. Population analysis of 268 pear accessions revealed two stop-gained variants in DAM1 of independent origin, which may function in advancing the blooming date and reducing the chilling requirement. We detected complex PAVs at the NOR1 locus, including two copy-number variations and one deletion. These PAVs contributed to the rapid diversification of the NOR1 locus and the fruit development period through regulating ARF5 and other ripening-related genes. We revealed the selection history of the NOR1 locus and developed novel pear individuals that accumulated alleles for low chilling requirement, early blooming date, and short fruit development period. The results provide valuable resources for pear genomics research and offer a guideline for breeding modern pears with climate resilience.

Tomato wild relatives are valuable genetic resources for trait discovery and understanding the genetic basis of fruit metabolism and quality. Yet, only a fraction of naturally occurring variation has been exploited. Here, we performed metabolite profiling of two large Backcross Inbred Line populations derived from crosses between the wild species S. pennellii accession LA5240 (Lost) and cultivated genotypes LEA (determinate) and TOP (indeterminate), including [~]1400 and [~]500 lines, respectively. High-resolution mapping identified enormous metabolic quantitative trait loci (mQTL), including a new locus on chromosome 12 associated with fruit sucrose accumulation that harbours INVERTASE INHIBITOR 3 (SlINVINH3) protein. Comparative analysis indicated that SlINVINH3 is highly expressed in wild S. pennellii 0716 fruit, whereas a six-amino acid deletion is present in its coding sequence compared with S.pennellii LA5240 and S. lycopersicum. We further demonstrated that in SlINVINH3-overexpressing tomato plants, only the S. pennellii LA5240 allele led to increased sucrose, accompanied by reduced fructose and glucose levels. Furthermore, the large population size enabled us to assess the epistatic interactions, with approximately 40% of interactions being more-than-additive and 60% less-than-additive. Our results demonstrate the power of permanent exotic populations to reveal hidden metabolic diversity and provide an approach for improving fruit quality through targeted breeding and metabolic engineering.

This study integrated morphometric characterization and machine-learning modelling to identify key predictors of yield in Annona reticulata under semi-arid conditions. Thirty-one canopy, fruit, seed, and biochemical traits were evaluated across 62 genotypes, revealing substantial phenotypic diversity, particularly in structural attributes such as tree growth nature and branch angle. Principal Component Analysis and hierarchical clustering differentiated genotypes into three ideotypes representing high-yielding, structurally stable, and quality-oriented groups. Random Forest modelling and SHapley Additive exPlanations (SHAP) interpretation consistently highlighted leaf breadth, leaf length, fruit shape, and pulp-associated traits as dominant yield predictors, underscoring the coordinated influence of source-sink balance. Integration of SHAP importances with trait stability (CV%) further revealed that moderately variable traits provide reliable selection indices. These findings demonstrate that yield performance is governed by multivariate trait networks rather than isolated descriptors. The proposed framework provides a robust basis for precision phenotyping and strategic parent selection to develop high-yielding, nutritionally enriched, and climate-resilient custard apple cultivars.

Here, we present a comprehensive multiomics analysis of anthocyanin biosynthesis in Rubus armeniacus, known for its dark fruits. A phased genome sequence of the tetraploid blackberry was generated, achieving an N50 of 34 Mb with an assembly size of 1.2 Gbp based on Oxford Nanopore Technology sequencing (ONT). The BUSCO score for the total assembly shows a high completeness of 99.1%. The assembly was separated into 4 pseudohaplophases, with the pseudohaplophase A representing the R. armeniacus genome in 7 chromosome scale contigs, with an N50 of 46 Mbp and 98.8% conserved BUSCO genes. A total of 118,183 protein coding genes were annotated within the genome assembly and all relevant genes encoding enzymes and transcriptional regulators of the anthocyanin biosynthesis pathway were identified within each pseudohaplophase. To further understand the underlying cause of dark pigmentation, the gene expression was analysed during different stages of berry development revealing a strong induction of anthocyanin biosynthesis genes including the anthocyanin activating subgroup 6 MYB transcriptions during the berry ripening process. Further, a quantification of cyanidin-3-O-glucoside in methanolic berry extract, utilizing a UHPLC-HRAM-MS analysis, revealed an approximately 500-fold increase of cyanidin-3-O-glucoside from green to black fruit, indicating that dark pigmentation in R. armeniacus results from high anthocyanin accumulation. Significance statementThis study provides a multiomics analysis of the dark pigmentation of Rubus armeniacus, including a high quality phased assembly and an in-depth analysis of the anthocyanin biosynthesis pathway. A transcriptional and metabolomic analysis revealed that dark berry pigmentation is caused by a high accumulation of cyanidin-3-O-glucoside during fruit ripening.

Obtaining tomato plants with firm and intact fruit is one of the main goals in tomato breeding programs. Achieving these goals through conventional breeding is time-consuming and can lead to the loss of unwanted traits. In other hand, consumers are concerned about the presence of transgenic elements in plants acquired through RNA interference. The use of CRISPR/Cas9 technology has made it possible to overcome the above-mentioned shortcomings. In this study, the {beta}-D-N-acetylhexosaminidase ({beta}-hex) gene, which is involved in tomato fruit ripening, was knocked out using CRISPR/Cas9. In the resulting mutant plant genome, an indel mutation was found in exons 1 and 2 of the {beta}-hex gene. Plants with a mutation in their genome were observed to have increased fruit firmness and shelf life compared to control plants without affecting fruit quality.

Potato crop is highly vulnerable to abiotic stresses like salinity and low nutrient availability. Rapid identification of stress-resilient genotypes is therefore essential for breeding, yet conventional phenotyping is often slow, space-demanding and expensive. We present LOCOPOTS -- a LOw-COst high-throughput screening platform for in vitro POTatoes under abiotic Stress -- which combines individual in vitro plant culture, low-cost RGB imaging and machine-learning-based automatic segmentation using a trained model of a convolutional neural network, based on U-Net architecture. LOCOPOTS enabled the automated extraction of growth, colour, and vegetation-index traits and demonstrated robust performance across independent phenotyping rounds. We screened 30 potato varieties under control, low-nutrient and saltinity conditions, identifying contrasting growth and physiological responses. Integrated traits such as final area and height, Area_AUC and height_AUC, together with GLI, Chol, cive and chlorophyll fluorescence parameters, discriminated genotype performance under stress. Metabolic profiling further revealed genotype-specific reprogramming in carbon and nitrogen metabolism under low nutrition and salt stress, including changes in fructose, myo-inositol, {beta}-aminobutyric acid, {gamma}-aminobutyric acid, proline, and certain polyamines, identifying them as specific chemical biomarkers of plant stress responses. LOCOPOTS provides a scalable, affordable and space-efficient platform for early screening of potato genetic diversity and identification of candidate traits associated with stress resilience.

Banana (Musa spp.) is a vital staple food and cash crop cultivated in over 140 countries, providing nourishment and livelihoods to more than 400 million people worldwide. In this context, Bhimkol (Musa balbisiana, BB genome), a diploid banana variety native to Northeast India holds significant nutritional and commercial value. Its high iron and nutrient content have already been commercially validated through products like Bhimvita and Bhimshakti, which utilize fresh fruit pulp as nutrient-rich food for infants. However, Bhimkol fruits typically contain 100-150 seeds, an undesirable trait for product development. The manual removal of these seeds significantly increases production time and labour costs. Furthermore, because bananas are recalcitrant to traditional breeding, there is a constant need for rapid in vitro transformation protocols. To address these challenges, as a proof of concept, our research aims to knockout the INNER NO OUTER (INO) gene, which is responsible for ovule development. Using CRISPR/Cas12a technology, we established an efficient and reproducible in vitro regeneration and transformation system using Embryogenic Cell Suspensions (ECS). The resulting CRISPR-edited plantlets exhibited various mutations, including insertions and deletions (INDELs) within the targeted INO gene. These INDELs resulted in frameshift mutations that triggered premature stop codons. While these genetic changes are expected to render the banana seedless, phenotypic verification is currently underway to confirm the absence of seeds in mature fruit. Significance StatementDespite its superior nutritional profile, the commercial viability of the Bhimkol banana (Musa balbisiana) is restricted due to abundance of seeds (100-150 per fruit). This study employs CRISPR/Cas12a-mediated knockout the INNER NO OUTER (INO) gene in Bhimkol and expected to develop seedless fruits. The resulting plantlets exhibit targeted indels that trigger frameshift mutations, effectively disrupting ovule developmental INO gene.

Apples (Malus x domestica) are popular fruits grown in temperate regions of the world. The various genotypes must meet a specific threshold amount of cold exposure before they are competent to break dormancy, a quantity approximated as "chill hours". Several varieties have been identified that exhibit an ultra-low-chill requirement, or more precisely shallow dormancy, breaking vegetative and floral buds early in spring in response to minimal cold exposure. These ultra-low-chill genotypes originated from the Bahamas ( Dorsett Golden,1960s), Israel ( Anna, 1950s) and Alabama, USA ( Shell of Alabama, 1880s). The separation in time and space implies that each would feature distinct genetic lesions that govern dormancy control, providing discrete mechanisms to incorporate a low-chill trait in variety improvement. However, analysis of microsatellites and ultimately genome sequence indicates that Dorsett Golden and Anna share strong concordance with the Shell of Alabama genotype, as well as other ultra-low-chill varieties. Kinship analysis confirms that all are closely related, despite differences in year and place of origin. All three low-chill genotypes share common mutations in the DORMANCY ASSOCIATED MADS-BOX1(DAM1) gene, a known repressor of vegetative growth during dormancy. Genomic sequence diversity is observed among Shell of Alabama individuals, including differences in DAM1 that match differences in flowering time. The results of this study call into question the pedigrees of the ultra-low-chill apple germplasm and indicate variation in an otherwise narrow genetic base for use in future breeding efforts.

RNA-seq datasets from medicinal yews are crucial for studying paclitaxel biosynthesis. However, cross-study data analyses are hindered by pronounced batch effects. Here, we compiled 45 RNA-seq samples from three studies across four tissues (bark, leaf, root, stem) and assessed 35 preprocessing pipelines combining six normalization strategies with five batch-effect correction approaches. Unsupervised clustering (HCA, k-means, Grade-of-Membership), evaluated using Jaccard and Adjusted Rand indices, revealed significant variability in batch effect removal. Supervised classification of tissue and project labels (Random Forest and linear/radial SVM) demonstrated improved accuracy in tissue type prediction, highlighting the effectiveness of correction methods. The processed data facilitated the identification of 189 putative ABC transporters across samples, six of which showing a strong correlation to the gene encoding 10-deacetylbaccatin-III-10{beta}-O-acetyltransferase, a key biosynthetic enzyme in the taxol pathway. High expression levels in leaf and bark further support their role in taxane intermediates trafficking in taxol biosynthesis. Structural analysis and molecular docking further supported the selection of these candidates, and the agreement between transcriptomic ranking and docking-based prioritization suggests that these transporters may participate in taxane intermediate recognition, trafficking, or export. These findings demonstrate the importance of normalization and batch effect correction in RNA-seq analysis to advance gene discovery in Taxus species and, more broadly, in plant research. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/723993v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1469162org.highwire.dtl.DTLVardef@1f2c4deorg.highwire.dtl.DTLVardef@15ad821org.highwire.dtl.DTLVardef@123676d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Plants produce specialized metabolites that function in plant defense and as attractants to pollinators and symbionts. One class of specialized metabolites are terpenoids that are synthesized from universal C5 building blocks via activities including terpene synthases, cytochromes P450, and glycosyl transferases. Some terpenes are highly valued for their use as insect repellants, fragrances, antimicrobial compounds, low calorie sweeteners, flavors, and medicines. Low abundance in target tissues, present in complex mixtures, as well as challenging extraction logistics are barriers to economic sustainable production of these compounds from their native species. While heterologous expression of terpenoid biosynthetic genes is feasible, the potential derivation of the products into conjugates via endogenous cytochromes P450 and glycosyl transferases limits this approach. In this project, we used multiplex gene editing technologies to overcome these challenges by creating novel tomato chassis with altered terpenoid biosynthetic capacity in fruit. Excluding central metabolic genes to minimalize impacts on growth and development, we selected 23 known and potential terpene-related genes expressed specifically in the fruit for gene editing. Fruit production and metabolic profiles of three chassis lines with alterations in the major classes of fruit specialized metabolites indicate loss of these genes is tolerated for fruit production. These combinatorial knockouts also showed modulation of native carbon reallocation toward endogenous sinks beneficial for a biosynthetic chassis. Establishing metabolite-modified fruit chassis demonstrates efficient combinatorial editing of entire branches of plant specialized metabolism, facilitating engineering of heterologous terpenes of industrial interest in tomato fruit.

Salinity is a major crop production constraint in dry pea (Pisum sativum L.), making the development of salt-tolerant varieties essential to improve crop productivity and land-use efficiency. The genetic mechanisms of salt tolerance in dry pea is largely unknown, and research on salt-tolerant genes is limited. In this study, we established comprehensive genomic and transcriptomic resources, along with a robust screening protocol, to dissect the genetic basis of salinity tolerance using two germplasm sets: the USDA pea diversity panel, consisting of approximately 200 globally sourced accessions, and a set of 300 modern elite lines from the NDSU Pulse Crops Breeding Program. Genetic variation for the salinity response was assessed based on ten phenotypic traits, with root dry weight, shoot dry weight, and specific root length identified as key indicators based on their heritability. Genome-wide association mapping uncovered significant genomic regions and several candidate genes linked to salt stress, with the strongest association found on chromosome 6. Overlapping QTL signals across traits suggest a shared genetic architecture underlying salinity tolerance. Field-based transcriptomic analysis further identified five putative genes involved in salinity response conserved across multiple crop species. Notably, Psat5g000800, encoding a glycosyl hydrolase gene, was markedly upregulated under salinity stress. These findings highlight the complex, multi-gene regulatory nature of salinity tolerance in dry pea and underscore the importance of functional validation of candidate genes. This study provides key insights and practical tools to support breeding efforts aimed at improving salt tolerance in dry pea.

Accurate modeling of genotype-by-environment (GxE) interaction is critical for genomic prediction in plant breeding but remains challenging due to complex interaction structures. Conventional models often use the Hadamard product of genotype and environment covariance matrices to capture joint similarity, which may not fully represent GxE complexity. Here we propose a novel framework that derives covariance structures from the matrix multiplication of genotype and environment kernels, decomposing these into symmetric components incorporated as random effects in mixed models. Evaluated for 11 wheat and rice multi-environment datasets and across, this approach consistently outperformed the traditional Hadamard-based model, improving prediction accuracy by up to 13.2% in Pearsons correlation and enhancing top-selection accuracy. Combining both methods yielded the highest performance, indicating complementary information capture. This framework offers a flexible, interpretable, and computationally feasible extension for modeling GxE interaction, potentially enhancing genomic selection effectiveness under diverse environmental conditions.

Prenylated isoflavonoids are widely distributed specialized metabolites within the Fabaceae and contribute to various characteristic biological activities for both plants and humans. Several aromatic prenyltransferases (PTs) have been identified in Glycyrrhiza species, which are the most widely consumed crude drugs in traditional Chinese medicine. However, these enzymes do not sufficiently explain the structural diversity of prenylated flavonoids produced in the Glycyrrhiza genus. To identify additional novel PTs, we used elicited cultured Glycyrrhiza glabra roots as source material, in which elicitor treatment of cultured roots increased the accumulation of multiple prenylated flavonoids. To identify the responsible enzyme, PT candidates were screened using G. uralensis transcriptomes, currently the sole publicly available transcriptomic resource within the genus, and a homolog designated GgBSPT1 (BSPT; a broad-substrate prenyltransferase) was subsequently isolated from elicited cultured G. glabra roots. GgBSPT1 differed from previously identified Glycyrrhiza PTs in both amino acid sequence and enzymatic properties. GgBSPT1 catalyzed 3'-prenylation of isoliquiritigenin and 6-prenylation of five flavonoids, i.e., this PT displayed broad substrate acceptance across 20 distinct flavonoid structures. Overall, elicited cultured G. glabra roots enabled the identification of a previously unrecognized PT that is functionally distinct from earlier reported Glycyrrhiza PTs. This study provides a new insight into the metabolic plasticity of Glycyrrhiza species and expands the enzymatic toolkit for future metabolic engineering of prenylated phytochemicals by the unusually broad substrate specificity of GgBSPT1. Main conclusionUsing cultured Glycyrrhiza glabra roots, we identified a new prenyltransferase involved in the formation of a variety of flavonoids, thereby revealing novel prenylated isoflavonoid pathways in licorice.

Isoflavone hydroxylases (IFHs, CYP81E) convert isoflavone aglycones into their respective hydroxylated intermediates, which direct legume isoflavones into specialized defense pathways. In soybean, their functions have been studied mostly in the context of the daidzein-derived glyceollin biosynthesis. Here we combine metabolomics-guided feature mining, phylogenetic analysis, heterologous enzymology, structural elucidation, and in planta metabolite validation to determine the functional landscape of the soybean IFH family. Analysis of a soybean isoflavonoid-enriched metabolomic dataset revealed unidentified hydroxyisoflavone features that co-accumulated with glyceollins, indicating branch chemistry that is not well-recognized. The systematic characterization of the repertoire of soybean CYP81E has demonstrated that 9 out of 11 GmIFHs are catalytically active and collectively span both 2'- and 3'- hydroxylation of the major soybean isoflavone aglycones. Among them, GmIFH9A showed broad substrate scope and regioselectivity, yielding canonical and previously unknown hydroxylated isoflavone products. NMR and LC-MS/MS were used to identify and validate the hydroxylated isoflavone products as 2'-hydroxyglycitein and 2'-hydroxyformononetin, whose presence was also confirmed in soybean roots, thus confirming two of the hidden soybean isoflavonoid network metabolites. Kinetic studies also indicated that, although the majority of GmIFHs prefer daidzein and genistein as substrates, a few isoforms are active towards methoxylated isoflavones as well, indicating functional divergence in this expanded family. Our findings collectively redefine soybean IFHs as a multi-functional enzyme module that expands the hydroxyisoflavone chemical space and reveals new biosynthetic entry points beyond canonical glyceollin pathway.

Plants continuously develop shoot branches derived from axillary meristems. In rice (Oryza sativa), TILLERS ABSENT1 (TAB1), an ortholog of Arabidopsis WUSCHEL, plays an essential role in axillary meristem formation by promoting stem cell proliferation. Although several genes associated with TAB1 function have been identified, the molecular mechanisms underlying stem cell proliferation during axillary meristem formation remain poorly understood. Here we identify ABERRANT SPIKELET AND PANICLE1 (ASP1), a TOPLESS-like transcriptional corepressor, as a novel regulator of axillary meristem formation, and investigate downstream mechanisms regulated by TAB1 and ASP1. In asp1, the stem cell region was expanded, indicating that ASP1 negatively regulates stem cell proliferation. Notably, WOX4, a paralog of TAB1, was precociously expressed in asp1, possibly in association with expansion of the stem cell region. Genetic analysis further revealed that asp1 mutation rescued the loss of axillary meristems in tab1. Transcriptome analysis showed that several type-A RESPONSE REGULATOR (OsRR) genes, encoding negative regulators of cytokinin signaling, were upregulated in tab1 relative to wild type, asp1, and the tab1 asp1 double mutant. Consistently, fluorescence of the synthetic cytokinin reporter was absent during axillary meristem formation in tab1 but was detected in wild type and tab1 asp1. Moreover, overexpression of OsRR10 inhibited axillary meristem formation, phenocopying tab1. Collectively, these findings suggest that TAB1 activates cytokinin signaling by repressing type-A OsRR expression, whereas ASP1 negatively regulates cytokinin signaling by promoting the expression of these genes. Thus, rescue of the tab1 phenotype by asp1 mutation probably reflects restoration of cytokinin signaling.

Achieving high-throughput and precise phenotypic quantification and imaging modalities of stomatal and epidermal cells across diverse species remains a primary bottleneck in elucidating the mechanisms of stomatal dynamics, epidermal patterning, and environmental adaptation of plants. Here, we developed EpiReasoner, an artificial intelligence framework comprising a vision module, EpiVision, and a knowledge-based reasoning module, EpiBrain, for the quantitative phenotypic analysis and domain-specific knowledge reasoning of stomatal complexes and pavement cells in plants. Operating across bright-field, scanning electron microscopy, and differential interference contrast modalities, EpiVision achieves precise instance segmentation in various monocotyledonous, dicotyledonous, and fern species. Its performance significantly surpasses current state-of-the-art models. Moreover, we defined 23 quantitative indices describing stomatal cell morphology and spatial distribution. For domain-specific tasks such as phenotype prediction, genotype deduction, and molecular mechanism reasoning, EpiBrain demonstrates a human preference rate significantly higher than that of general-purpose large language models, including GPT-5 and Claude Sonnet 4. The application of EpiReasoner to phenotypic data of stomatal density derived from a tomato natural population of 170 accessions successfully identified a major quantitative trait locus on chromosome 8. The candidate gene, SKP1-interaction partner 19L (SKIP19L), encoding an F-box family protein, exhibited severe allele frequency drift during tomato domestication, which is highly consistent with the adaptive trend of reduced stomatal density under artificial selection. EpiReasoner provides a novel paradigm that unifies visual phenomics and knowledge-driven reasoning for the biology of stomata and pavement cells, thereby significantly accelerating scientific discovery in plant science.

Key message Characterized and unknown septoria nodorum blotch susceptibility/resistance genes were identified in contemporary U.S. hard winter wheat. The necrotrophic fungus Parastagonospora nodorum is the causal agent of septoria nodorum blotch (SNB) of wheat. To determine the prevalence of SNB sensitivity genes in a contemporary U.S. hard winter wheat (HWW), we evaluated a panel of 619 breeding lines and cultivars against five P. nodorum isolates and five necrotrophic effectors (NEs), SnToxA, SnTox1, SnTox3, SnTox267 and SnTox5, and genotyped the panel using genotyping-by-sequencing (GBS) markers and diagnostic Kompetetive-allele specific PCR (KASP) markers for the sensitivity genes Tsn1-B1, Snn1-B1, and Snn3-B1/B2. GBS analysis identified 34,357 GBS-single nucleotide polymorphism (SNP) markers. Evaluations against P. nodorum isolates showed that 40-67% of the genotypes were susceptible in the panel. Toxin infiltration assays showed that 54%, 2%, 37%, 13%, and 15% of the genotypes were sensitive to SnToxA, SnTox1, SnTox3, SnTox267, and SnTox5, respectively. Diagnostic KASP markers for Tsn1-B1, Snn1-B1, and Snn3-B1/B2 showed prediction accuracies of 98%, 75%, and 92% for the corresponding effectors SnToxA, SnTox1, and SnTox3, respectively. Genome-wide association studies (GWAS) not only confirmed the presence of the previously characterized sensitivity genes Tsn1-B1, Snn1-B1, Snn2, Snn3-B1/B2, and Snn5-B1, but also identified new loci to be associated with responses to P. nodorum isolates and NEs. Of which, Qsnb.osu-2AS on chromosome 2AS was associated with responses to all five isolates. We developed KASP markers KASP_S4B_643615365, KASP_ S2D_16184991, and KASP_S2A_9833162 linked to Snn5-B1, Snn2, and Qsnb.osu-2AS, respectively. These findings should guide breeding for SNB resistance in hard winter wheat.

Polyploid genome assembly presents unique challenges due to extensive heterozygosity and complex haplotype structure. We report a haplotype-resolved, chromosome-scale assembly of Regen-SY27x, a genotype of autotetraploid alfalfa (Medicago sativa), which is widely used for genetic modification because of its excellent regenerative capacity in tissue culture. Using PacBio HiFi long reads, Omni-C scaffolding, and linkage map guided phasing, we generated a 3.2 GB assembly comprising four haplotypes with high contiguity and completeness. Kmer-based validation confirmed accurate haplotype separation, while linkage map integration and dotplot analysis identified and corrected chimeric scaffolds. Gene annotation yielded 221,688 protein-coding genes, with more than 99% assigned to pseudochromosomes. Repetitive elements accounted for 62.7% of the genome, dominated by long terminal repeat retrotransposons and a high fraction of Helitrons. The spatial enrichment of Helitrons within gene-dense distal chromosome arms underscores their pivotal role as key drivers of genomic innovation and gene family expansion. We identified 3,696 nucleotide-binding leucine-rich repeat R genes, with Toll/interleukin-1 receptor-like and Rx-type subclasses forming large tandem clusters across haplotypes. Comparative analyses revealed strong macrosyntenic conservation among Regen-SY27x and the publicly available Chinese alfalfa genomes but extensive structural variation both within Regen-SY27x haplotypes and between Regen-SY27x and the Chinese genotypes with tens of thousands of duplications, inversions, and translocations detected. These results demonstrate that a single autotetraploid individual captures extensive structural diversity, but individuals from different populations vary greatly. The Regen-SY27x assembly provides a foundational genomic resource for investigating polyploid genome evolution and identifying genetic variation relevant to biological and agronomic improvement in alfalfa. Article SummaryThis study presents the first chromosome-scale, haplotype-resolved genome assembly of the US alfalfa germplasm, Regen-SY27x, a key alfalfa genotype used widely for genetic engineering. We integrated HiFi long reads, Omni-CTM scaffolding, and linkage map-guided phasing to reconstruct all four haplotypes of this complex autotetraploid. Our results identified 221,688 protein-coding genes and reveal immense intra-individual structural variations dominated by small duplications. This high-quality reference serves as a foundational tool for the alfalfa community, enabling researchers to link complex structural diversity with agronomic traits and further enhance the biotechnological potential of this essential forage crop.

Licorice (Glycyrrhiza) is a medicinal plant widely used in approximately 70% of traditional Japanese Kampo formulations and is known to produce a wide array of specialized metabolites with diverse pharmacological properties. Although hundreds of metabolites have been reported, the overall chemical diversity of Glycyrrhiza remains poorly characterized. Here, using mass spectrometry data obtained from fully 13C-labeled leaves and roots of Glycyrrhiza uralensis and Glycyrrhiza glabra, we determined the carbon number, followed by molecular formula and substructure prediction in combination with MS/MS similarity-based molecular networking. After excluding redundant ions, including isotopic peaks, adducts, and in-source fragments, we extracted 3,060 unique metabolite features with assigned carbon numbers. Among these, substructure information was assigned to 1,015 features (33%) across the four plant tissues, revealing the tissue-specific metabolome profiles. Furthermore, we discovered five previously unreported alkaloids, homopipecolic acid-conjugated flavonoids, in the roots of G. uralensis and G. glabra, and Glycine max, another member of the Fabaceae family. Two of these structures were validated using nuclear magnetic resonance spectroscopy. We further proposed a biosynthetic route involving a spontaneous reaction between 1-piperideine and malonyl glycoside substrates and confirmed the formation of the conjugated product using authentic standards.

Punicalagin, an ellagic acid polyphenol from pomegranate, has been proposed as an antagonist of protein disulfide isomerase (PDI) and endoplasmic reticulum resident protein 57 (ERp57), thiol oxidoreductases that regulate protein folding and extracellular thrombotic signaling. Here, biochemical oxidase and reductase assays on PDI show that punicalagin inhibits both activities with micromolar potency, thereby extending earlier work that described only disulfide reductase inhibition. In parallel, thiol labeling of catalytic cysteines revealed no change in the redox state, supporting a noncovalent, allosteric of inhibition. Molecular docking and molecular dynamics simulations showed that punicalagin binds stably and preferentially to defined sites on the Nterminal domains of PDI through extensive hydrogen bonding and van der Waals contacts, which is an alternative binding mode to previously reported C-terminal binding. Finally, artificial intelligence-driven network analysis identified PDI as a high-confidence target of punicalagin and related galloylated polyphenols, alongside additional signaling proteins. Together, these findings provide further mechanistic framework for punicalagin-mediated antagonism of PDI and highlight galloylated polyphenols as promising scaffolds for protein disulfide isomerase-targeted therapeutics. HighlightsO_LIPunicalagin, a galloylated polyphenol, antagonizes not only the reductase activity but also the oxidase activity of protein disulfide isomerase C_LIO_LIProtein disulfide isomerase inhibition by punicalagin is through N-terminal binding C_LIO_LIPunicalagin inhibits conformationally rather than catalytic cysteine modification C_LIO_LIArtificial intelligence network analysis reveals pathway inhibition by punicalagin C_LI