Drought stress severely restricts global rice production, making the improvement of drought tolerance a central goal in rice breeding. Here, we identify the rice FCS-like zinc finger protein 20 (OsFLZ20) as a previously unrecognized client of the 14-3-3 protein OsGF14f, a recently characterized and promising target for engineering drought-tolerant rice cultivars. OsFLZ20 transcription is rapidly and robustly induced by drought, and transgenic analyses show that it does not affect normal growth or yield but instead acts as a positive regulator of drought tolerance by increasing soluble sugar accumulation and alleviating oxidative damage. OsGF14f and OsFLZ20 co-regulate a broad suite of drought-responsive genes, with OsGF14f serving as a positive modulator of OsFLZ20-driven transcriptional reprogramming. Mechanistically, OsGF14f interacts with OsFLZ20 at Ser-64 and increases its protein abundance. In parallel, the OsGF14f-OsbZIP23 module enhances the transcriptional activation of OsFLZ20 under drought stress. Further genetic analyses reveal that full OsFLZ20 function in drought tolerance requires a functional OsGF14f, whereas loss of OsFLZ20 compromises the drought tolerance conferred by OsGF14f, indicating mutual interdependence of these two regulators within the drought response network. Collectively, these findings establish the OsGF14f-OsbZIP23-OsFLZ20 module as a previously unrecognized determinant of rice drought tolerance and provide valuable genetic resources and molecular insights for crop improvement under water-limited conditions.
Gene duplication promotes the generation of novel gene functions and trait diversity across species. Here, we present DupHIST, a computational pipeline that reconstructs the hierarchical timing of gene duplications by integrating maximum likelihood (ML)-based phylogeny with substitution-derived timing via statistical smoothing. Applied to over 4.5 million genes from 114 plant genomes, we successfully inferred duplication histories across nearly 130,000 orthogroups. This large-scale analysis showed that 53.0% of genes arose from recent, lineage-specific duplications, with high concentrations in particular multi-copy families. Among these, NLR, C48, and P450 families exemplified how recently duplicated genes undergo rapid stepwise structural remodeling. This process was primarily driven by small-scale mutations, including insertions, deletions, and frameshifts, that rapidly accumulated shortly after duplication. By resolving the precise duplication order, we reconstructed these architectural changes, thereby enabling both the inference of putative ancestral structures and the exploration of functional diversification arising from structural remodeling. Structure-based clustering further uncovered that recently duplicated, uncharacterized genes retain core domain structures resembling known functional proteins even across phylogenetically distant species lacking sequence homology. Our findings reveal that recent gene duplications and subsequent structural remodeling represent a widespread and lineage-specific force driving rapid diversification of gene families in plants.
The specification and commitment of lateral root founder cells (LRFCs) from postembryonic pericycle cells are critical steps in LR development, yet their earliest molecular determinants remain unclear. Using single-cell transcriptomics, we resolved transcriptional transitions guiding LRFC fate in Arabidopsis thaliana and identified five distinct phases of transcriptional progression during LRFC specification. Through differentially expressed gene analysis and phenotypic observation, we showed that application of exogenous GA (20 and 50 μM) promoted the nuclear migration and division in LRFCs independently of DELLA signaling, and revealed that Gibberellic acid-stimulated Arabidopsis 1 (GASA1) functions as a key mediator of gibberellin (GA) to accelerate the LRFC progression. Further histochemical staining and cytological observations demonstrated that GASA1 mediated the GA-triggered reactive oxygen species (ROS) accumulation to reinforce the LRFC commitment. The GA-GASA1-ROS module is evolutionarily conserved, with GA-ROS-driven LRFC commitment being fundamental across angiosperms. Notably, GASA1 emerged with root evolution in early land plants and diversified alongside lateral and shoot-borne root systems, revealing a conserved GA-ROS axis in plant organogenesis.
Fleshy fruit ripening involves broadly convergent physiological changes across phylogenetically distinct species, yet the extent to which shared chromatin-level mechanisms underlie this convergence remains poorly understood, partly due to technical challenges posed by metabolite-rich fruit tissues. Here, we develop iCUT&Tag, an improved chromatin profiling method requiring as few as 500 nuclei, and apply it to generate histone modification profiles across 12 fruit species spanning 9 botanical families, demonstrating its broad application in metabolite-rich fruit tissues. Comparative profiling of climacteric (tomato, apple) and non-climacteric (citrus, strawberry) fruit identifies H3K9 acetylation (H3K9ac) as a recurrently enriched chromatin feature associated with ripening-linked gene activation, regardless of the dominant hormonal system. In tomato, SlHDA1 loss is accompanied by premature H3K9ac accumulation at ripening-associated loci, whereas in strawberry, FaHDA19 silencing is associated with increased H3K9ac at transcriptionally activated ripening-related loci. Mechanistically, comparative genetic analyses suggest a bipartite regulatory architecture: H3K9ac-mediated permissive chromatin state appears conserved across lineages, yet productive transcription additionally requires species-specific transcription factor activity—SlNOR in tomato and FaMYB10 in strawberry—to drive phenotypically convergent ripening. Our study provides a validated technological framework for plant epigenomics and identifies a recurrent associated chromatin-level feature that may underlie the convergent evolution of fleshy fruit ripening.
SHORT SUMMARY:TeroSeek is an AI-powered platform that converts terpenoid literature into a structured knowledge base of over 3 million entries and an expert Q&A agent. By coupling knowledge-graph retrieval with large language models, it delivers evidence-based, fully cited answers that reduce hallucination and bypass knowledge cutoffs. The framework is readily transferable to other scientific domains.
In maize hybrid breeding, synergic multi-trait selection of elite hybrids in specific target environments remains a major challenge. Enviromic data and functional gene knowledge are rapidly increasing; however, they have not been effectively integrated into crop breeding decisions. Here, we present TOPlus, a multi-trait hybrid prioritization framework comprising predictive and selective modules. The predictive module uses environmental information to improve phenotype prediction for untested genotypes and environments, whereas the selective module incorporates functional gene priors and multiple predicted traits to prioritize hybrids for target environments. Across 17 agronomic traits, TOPlus improved average cross-environment prediction accuracy by 12% over JGRA and 3% over EADW+GW. Incorporating functional gene priors further improved hybrid prioritization: hybrids selected by TOPlus showed 5.90-19.64% higher yield than those selected by the original TOP method while maintaining comparable performance for other traits. The TOPlus algorithm internally clustered the functional genes into environmentally stable and plastic gene groups, with stable genes associated with core plant developmental processes and plastic genes enriched in stress-response and environmental-adaptation pathways. Independent validation in commercial hybrid panels demonstrated that TOPlus supports region-level suitability assessment and extrapolative deployment across diverse agroecological zones for specific candidate maize hybrid varieties. Overall, by integrating enviromic data and functional gene priors within an interpretable framework, TOPlus provides a biologically grounded and data-driven approach for cross-environment prediction and multi-trait synergic selection of hybrids for specific regions in maize breeding.
Engineering enzymes with enhanced activity and stability is a central goal of biotechnology, yet the inherent trade-off between optimizing global protein fitness and specific substrate binding affinity poses a significant challenge. Here, we present ESM-FEP, a computational framework that synergistically integrates a fine-tuned protein language model with alchemical free energy perturbation (FEP) to overcome this limitation. Our workflow employs a parameter-efficient fine-tuned ESM-2 model to perform high-throughput saturation mutagenesis, rapidly identifying mutations that preserve protein fitness. Top-ranking candidates are then subjected to rigorous FEP simulations to precisely quantify changes in substrate binding affinity. When applied to engineer the Zea mays dioxygenase ZmHSL1B for improved detoxification of the herbicide mesotrione, ESM-FEP efficiently navigated the mutational landscape and identified a quadruple mutant M5 (Q140H/Y205F/L332R/K336F). This variant demonstrated a catalytic efficiency approximately 7-fold higher than that of the wild-type enzyme, which was corroborated by in vitro assays and a detailed kinetic analysis. Furthermore, transgenic Arabidopsis thaliana expressing the engineered mutant M5 exhibited significantly enhanced herbicide tolerance, validating its functional efficacy in a biological context. The ESM-FEP framework establishes a generalizable and efficient strategy for the rational design of gain-of-function enzymes, with broad applications in biocatalysis, bioremediation, and precision agriculture.
Plasma membrane (PM) acts as the primary interface between a plant cell and its fluctuating environment. Classically defined as conduits for substrates movement across the PM, membrane transporters function as dynamic signal integrators, actively negotiating the trade-off between vegetative growth and stress adaptation. In this review, we synthesize emerging paradigms across the NPF/NRT, PIN, and ABC transporter families to illustrate how these proteins orchestrate cellular decision-making through three interconnected principles. First, we highlight multisubstrate specificity as a regulatory strategy, illustrating how structural flexibility enables individual transporters (e.g., NRT1.1, ABCG16) to serve as molecular junctions where nutrient, hormonal, and defense signaling pathways intersect. Second, we examine spatiotemporal compartmentalization as a determinant of response speed and specificity. By contrasting PIN polarity in developmental patterning with the stress-responsive intracellular partitioning of ABCG transporters, we outline an “intracellular reservoir” mechanism for buffering cytosolic signaling. Based on this, we propose a “gear-shift” model wherein the dynamic redistribution of existing transporter pools among the endoplasmic reticulum (ER), vacuole, and PM allows rapid cellular transitions between growth and defense states. Third, we explore the phosphorylation-controlled state of transporters, detailing how convergence by Ca2+-responsive and kinase-mediated networks rapidly tunes transporter activity, oligomeric complex assembly (e.g., homo/heterodimerization), and protein stability. By framing transporters as flexible integration nodes rather than simple pumps, we aim to provide a conceptual unifying framework for understanding plant resilience and highlight novel regulatory targets, such as phosphosite editing and trafficking signals, for next-generation crop engineering.
Plants undergo metabolic reprogramming, including senescence, in response to pathogen attack. While senescence-associated genes (SAGs) are critical to this process, the genes that integrate plant defense and senescence processes remain largely unknown. Here, we identified and characterized SENESCENCE ASSOCIATED GENE 1 (SEN1) as a central regulator that coordinates these processes in Arabidopsis. SEN1 is transcriptionally activated by abscisic acid (ABA) via its key component, ABA INSENSITIVE 4 (ABI4). SEN1 interacts with TRXm1, and the interaction modulates sulfotransferase activity of SEN1. Disruption of sen1 and trxm1 mutants reduces reactive oxygen species (ROS), alters the glutathione redox balance (GSH/GSSG), increases susceptibility to pathogens, and delays senescence. Hydrogen sulfide (H2S), a product of SEN1-mediated sulfur transfer, amplifies the module by inducing ABI4 expression. Notably, H2S enhances ABI4 transcriptional activity via persulfuration at Cys250, establishing a self-reinforcing loop. Overall, we propose a regulatory triad in which the ABI4-SEN1-TRXm1 module integrates ABA and H2S signaling to dynamically balance redox homeostasis. This study reveals a molecular switch that fine-tunes plant responses to biotic stress.
The maintenance of iron homeostasis is fundamental to plant survival, preventing both iron deficiency and toxicity. This equilibrium is orchestrated by transcription factors (TFs), including those from the basic helix-loop-helix (bHLH) family. Numerous bHLH TFs have been identified as positive regulators of plant iron uptake, but negative regulators remain largely unknown. In this study, we demonstrated that bHLH106 can bypass the FIT-centered transcriptional regulatory network and directly bind to the promoter of IRT1 (Iron Regulated Transporter 1), inhibiting its expression. The FIT-IRT1-mediated iron-uptake pathway is activated under iron deficiency, promoting the accumulation of intracellular iron. As intracellular iron levels rise, CARK3 (Cytosolic ABA Receptor Kinase 3) phosphorylates bHLH106 to promote its recruitment to the IRT1 promoter, enhancing the transcriptional repression of IRT1 by bHLH106 and thus limiting iron uptake. Under iron-deficient conditions, bHLH106 expression is suppressed, and bHLH106 protein levels are reduced. The transcriptional repression of IRT1 by bHLH106 is alleviated, facilitating FIT-mediated upregulation of IRT1 expression and promoting iron uptake. In summary, the CARK3-bHLH106-IRT1 module enables plants to adapt rapidly to fluctuations in iron levels.
Seed size is a key agronomic trait in watermelon: large seeds are favorable for sowing, whereas small-seeded watermelons are preferred for consumption. However, the causal genetic variations and underlying mechanisms that govern seed size in watermelon remain poorly understood. Here, we identified a copy-number variation (CNV) tightly linked to seed size; a single copy is present in large-seeded watermelons, whereas four copies are present in small-seeded lines. Compared with the single-copy CNV, the four-copy CNV contains two additional TATA boxes and activates the transcription of a downstream long-noncoding RNA (C. lanatus lncRNA seed size 1 [ClLNC-SS1]) on the antisense strand. Knockout of ClLNC-SS1 in the small-seeded line resulted in larger seeds and repressed the expression of ClBige1b, which is located downstream of the CNV on the sense strand. ClBige1b encodes a multidrug and toxic compound extrusion transporter, and its overexpression in a large-seeded line resulted in smaller seeds. By contrast, knockout of ClBige1b increased seed size in a small-seeded line, markedly increasing cell expansion in the exocarp, endocarp, and endosperm by reducing auxin contents in the developing seeds. Our findings demonstrate that the newly identified CNV regulates seed size via the ClLNC-SS1-ClBige1b module in watermelon, providing novel insight into the regulation of seed size and laying a foundation for its genetic improvement in watermelon and other crops.
Engineering disease resistance in plants has traditionally relied on modifying pathogen perception, host susceptibility or immune signaling. Here, we explore a complementary strategy that couples pathogen-effector recognition to host proteostasis, aiming to reduce the intracellular accumulation of delivered virulence factors. We identified a minimal α-helical peptide from soybean GmRNF181, designated RXLR Effector Bait Tag (REBT). REBT bound PsAvh5 and a subset of WY1-type RXLR effectors, whereas recognition was constrained by the accessibility of the WY1 motif within full-length effectors. By fusing REBT to an ATG8-interacting motif (AIM), we generated AIM-REBT, a genetically encoded chimeric protein degrader (GE-CPDs) designed to recruit plant autophagy. In planta, AIM-REBT reduced the accumulation of REBT-bound effectors in a manner requiring both the AIM module and effector binding, and the observed effects were consistent with ATG8a-associated, autophagy-vacuole-related clearance. Transient and stable expression assays demonstrate robust resistance against multiple Phytophthora spp. in tobacco, soybean, and potato. Resistance was attenuated in NbATG8a-silenced leaves and was not observed against the unrelated fungal pathogen Alternaria alternata, supporting target-dependent activity. Under the tested conditions, stable AIM-REBT expression caused no obvious growth-related defects in tobacco or potato. These findings provide proof of concept that pathogen-effector recognition can be coupled to host degradation pathways to directly reduce intracellular virulence factors and complement existing disease-resistance engineering strategies.
Rising temperatures increasingly threaten plant survival, particularly for long-lived forest trees that face repeated exposure to extreme climatic events. However, the specific mechanisms underlying transient transcriptomic and epigenetic responses to thermal stress, and how these relate to evolutionary selection, remain poorly understood. Here, we present a near telomere-to-telomere genome assembly of Populus wilsonii, a montane tree species endemic to the eastern Hengduan Mountains. To investigate the multi-omic responses related to thermotolerance, we integrated transcriptomic, methylomic, and small RNAome profiling under control, heat-stress, and recovery conditions, alongside population-scale genome resequencing. In addition to an extensive transcriptomic response to heat stress, our findings uncover immediate regulatory mechanisms-including transposable element (TE) activation and repression, CHH methylation reprogramming, and small RNA-mediated pathways-that collectively modulate heat-responsive gene expression. Furthermore, population genomic analyses revealed that these heat-induced genes are under stronger purifying selection and exhibit epigenetic priming that may be maintained over evolutionary timescales. We infer that the epigenetic plasticity provided by dynamic CHH methylation and TEs likely acts as a crucial short-term buffer for plant survival, modulating vital stress-response genes that are further maintained by strict evolutionary constraints over long timescales. This study offers novel insights into how forest trees balance transient epigenetic flexibility with enduring genetic stability to survive accelerating climate change.
Plant receptor kinases perceive diverse peptide signals to coordinate stress responses and developmental programs. The HAESA-LIKE 3 (HSL3/NUT) receptor recognizes CTNIP/SCREW phytocytokines-disulfide-constrained peptides that regulate immune signaling and stress adaptation. However, how HSL3 distinguishes these structurally constrained peptides from linear signaling molecules remains unknown. Here we report near-atomic resolution cryo-EM structures of HSL3 in apo and CTNIP448-70-bound states at ∼2.6 Å, using Arabidopsis CTNIP4 as a representative family member, revealing the mechanism of disulfide-constrained peptide recognition. The conserved CTNIP motif occupies a negatively charged pocket in the C-terminal region of HSL3 through a combination of polar contacts, hydrogen bonds, salt bridges, and van der Waals interactions. The receptor employs a two-step recognition mechanism-electrostatic steering followed by motif anchoring-that enables rapid ligand capture, consistent with the dynamic nature of stress signaling. Notably, an N-glycan at Asn449 directly contacts the CTNIP4 peptide, establishing glycosylation as an active participant in ligand recognition. Structure-guided mutagenesis combined with reactive oxygen species (ROS) burst assays confirmed the functional importance of key binding interfaces. N-terminal truncation experiments revealed a minimal active fragment: CTNIP451-70 supported both rapid ROS production and sustained seedling growth inhibition, whereas the shorter CTNIP454-70 variant retained ROS activity but failed to trigger long-term seedling growth inhibition. Structure-guided coevolutionary analysis across plant lineages reveals patterns of both conserved and variable receptor-ligand interfaces, highlighting evolutionary flexibility while preserving core features of recognition. These conserved recognition principles, mediated by receptor glycosylation and evolutionary plasticity, enable specificity in peptide signaling, with implications for engineering stress-resilient crops.
BIGS is an integrated genomic selection platform for Brassica napus that combines standardized genomic and phenotypic resources with DeepVAE-based phenotype prediction and model interpretation. The platform supports genomic prediction and candidate locus prioritization, providing a practical resource for rapeseed genetics and breeding.
Spatial transcriptomics has transformed plant biology by restoring the spatial context lost in bulk and dissociation-based transcriptomic approaches. This review synthesizes recent progress across diverse plant species and tissues, showing that gene expression is not only cell-type specific but also tightly organized by position within organs and developmental niches. Studies of meristems, vascular tissues, and floral organs reveal spatially segregated developmental programs underlying growth and differentiation; seed and grain analyses uncover compartmentalized programs controlling nutrient transport, dormancy, and embryogenesis; plant-microbe and emerging plant-parasite studies show that symbiosis, immunity, and feeding-site development depend on sharply localized host responses; and work on photosynthesis, drought adaptation, and regeneration demonstrates that metabolic and stress-related processes are likewise spatially patterned. Together, these findings establish spatial gene expression as a fundamental organizing principle of plant development and physiology. At the same time, the plant spatial transcriptomics community faces important limitations, including restricted spatial resolution in standard array-based platforms, reliance on computational deconvolution, uneven taxonomic coverage, limited temporal resolution, and a persistent gap between correlation and causal validation. The next stage of plant spatial transcriptomics will require true single-cell spatial resolution, standardized computational pipelines, spatial multi-omics integration, improved benchmarking across platforms, and functional perturbation of spatially defined regulators. By connecting transcriptomic position to biological function, spatial transcriptomics is poised to move plant science from descriptive atlas-building toward mechanistic and predictive understanding with major implications for crop improvement and resilience.
