Plant Communications

Auxin is a key phytohormone that regulates all aspects of plant growth, development, and environmental responses, making the precise analysis of its distribution and signaling essential for understanding plant adaptation and physiological processes. However, despite the agricultural importance of oilseed rape (Brassica napus), the lack of robust, species-specific molecular tools limits detailed studies of hormone signaling in this crop. Here, we developed and characterized reporter systems for the sensitive visualization and quantification of auxin distribution and signaling in B. napus. The DR5cc auxin signaling reporter and a novel synthetic auxin-responsive reporter, BIP3, assembled from promoter fragments of three oilseed rape IAA genes, were generated to drive GUS expression. In hairy roots, both reporters showed auxin-responsive expression in the root apical meristem that became broader after auxin treatment. In transgenic seedlings, flowers at anthesis, and 12-day-old embryos, DR5cc exhibited a more defined expression pattern than BIP3. To monitor real-time auxin dynamics under abiotic stress, DR5cc fluorescent reporters were employed in hairy roots. Mannitol and NaCl treatments induced a time-dependent increase in fluorescence, peaking at 6-12 h before returning to basal levels after 24 h. Furthermore, dual-reporter assays enabled simultaneous monitoring of auxin and cytokinin signaling, revealing distinct hormone-specific spatial responses in hairy roots. Finally, we established a quantitative DII (qDII) reporter system using degron domains from B. napus Aux/IAA proteins, providing a high-resolution quantitative readout of auxin depletion. Together, these reporter systems enable spatial, temporal, and quantitative analyses of auxin dynamics during development and stress adaptation in oilseed rape.

Legumes include some of the worlds most significant crop species, such as cowpea (Vigna unguiculata), a subsistence crop widely grown in sub-Saharan Africa. Despite their importance, legume crop improvement is hindered by a lack of high-resolution expression data, particularly for reproductive tissues and cell types. Here, we report on VigExp, a tool for visualising cowpea gene expression datasets. We demonstrate its utility across a range of vegetative and reproductive cell types of varieties IT97K-499-35 and IT86D-1010, which exhibit 93.75% protein sequence conservation and are amenable to stable transformation. This includes previously published transcriptomes of vegetative, floral and seed tissues, combined with developmentally staged male and female reproductive tissues. Also integrated are novel transcriptomes of laser-captured cell types covering reproductive development from meiosis to early embryo formation post-fertilisation. Spatial expression patterns and transcript levels can be visualised through an electronic fluorescent pictograph (eFP) browser. Validated by RT-qPCR, in situ hybridisation, transgenic, and CRISPR gene editing analyses, the predictive accuracy of VigExp matches prior cowpea functional study observations. Critical genes for nodule development and regulation were also identified and their expression patterns established in cowpea. Novel reference genes, constitutively expressed gene promoters for visualization makers/gene-editing, and tissue and cell specific gene promoters for targeting these regions, are identified. The A-type cyclin, VuTAM2, was also identified, with a critical role in male meiosis established. Collectively, VigExp represents an adaptable and updatable resource to support crop improvement in cowpea and other legumes, which are often highly syntenic with respect to genome composition.

O_LIEngineering nitrogen fixing crops requires not only transferring the nitrogenase structural genes, but also the accessory genes to synthesize its iron-sulphur cofactors. Scaffold protein NifU is a critical element in this system as the starting point of nitrogenase cofactor assembly. NifU has been successfully produced in plants, however, its optimal production required high levels of iron in the medium. This is likely due to a faulty connection with the endogenous iron trafficking network C_LIO_LITo identify specific elements targeting iron to NifU, pull-down assays were performed to identify showing bacterioferritin A (BfrA) as a likely candidate. Co-immunopurification, mutant characterization, iron transfer assays, and co-expression in Nicotiana benthamiana assays were carried out. C_LIO_LIBfrA transfers iron to NifU through protein-protein interactions. When these two proteins were co-expressed in N. benthamiana leaves, there was an increase in NifU production. In turn, it led to doubling NifH synthesis, a nitrogenase structural protein that is also required for the synthesis of the more complex nitrogenase cofactors. C_LIO_LIOur results provide a new element towards engineering nitrogen-fixing crops. They also underscore the importance of transferring the metal delivery systems when expressing metalloproteins in heterologous systems. C_LI

Poplar (Populus spp.) is a model system for tree biology. Specifically, P. tremula x P. alba INRA 717-1B4 (hereafter "poplar 717") has become an important platform for functional genomics and synthetic biology due to its rapid growth and ease of transgenesis. Here, we present a single-cell RNA-seq atlas of the poplar 717 shoot, including apical meristem, primary and secondary stems, and three stages of leaf development. Analysis of ca. 159,000 cells resolved 40 transcriptionally distinct clusters representing 7 major cell types, providing a high-resolution view of shoot development and tissue organization. We focused on the epidermis which constituted >15% of cells in the shoot atlas for in-depth characterization of epidermal heterogeneity. By integrating known marker genes with transcriptomic signatures consistent with established poplar leaf phytochemistry, we annotated epidermal cell subclusters corresponding to developmental stages, spatial location, and specialized cell types, including a distinct population of non-glandular trichomes. Coupling the single-cell RNA-seq atlas with bulk transcriptome data from glabrous mutants enabled the identification of novel trichome markers. Experimental validation of a representative trichome-specific promoter established a tool with potential to support cell type-targeted-metabolic engineering. We provide the poplar 717 atlas to the community through the BioPoplar Atlas Viewer (http://bio-poplar-atlas.com), providing a platform to explore the poplar transcriptome at single-cell resolution and a foundation for data-driven cell type-aware genetic engineering strategies in poplar.

Plant genetic transformation technologies are essential for functional genomics and genome engineering in plants. While transient expression systems offer a rapid alternative to stable transformation, existing platforms are often constrained by low efficiency, technical complexity, and limited scalability. Here, we developed AgroGem, an efficient Agrobacterium-mediated transient transformation system utilizing a geminiviral replicon-based T-DNA vector for Arabidopsis and Brassicaceae species. AgroGem significantly outperformed existing transient approaches, including AGROBEST and protoplast-based assays, in CRISPR-mediated editing efficiency. Moreover, AgroGem recapitulated the mutation spectra and chromatin accessibility-dependent editing patterns observed in stable transformation across both Cas9 and Cas12a systems, indicating that it captures genome editing outcomes in native chromatin contexts. Leveraging this capability, we performed high-resolution profiling of CRISPR-induced mutation outcomes across a panel of DNA repair mutants and identified distinct repair signatures, including unexpected roles for KU80 and XRCC4 in regulating non-homologous end joining (NHEJ). AgroGem also supported bimolecular fluorescence complementation assays for protein-protein interaction studies in Arabidopsis and was readily adapted to plate-based formats for high-throughput applications. Together, these results establish AgroGem as a robust, scalable, and versatile platform for genome editing, DNA repair analysis, and functional genetics in plants.

Plant diseases remain a major challenge to global food production, and timely, accurate, and scalable detection of plant stress is critical to reducing these losses. Recent advances in digital imaging and artificial intelligence offer unprecedented opportunities for precision crop disease detection and management. Yet, existing plant disease datasets remain often fragmented across crop and disease systems, and are largely dominated by controlled-environment imagery. The lack of standardized, interoperable, and representative datasets limits reproducibility, transferability, and scalability of AI systems, thereby constraining their deployment in operational agricultural applications. Here we present LeafMD, an integrated multimodal plant disease dataset and benchmark resource that includes LeafNet 2.0, a large-scale multimodal digital image dataset comprising 255,855 image-text pairs across 37 crop species, 197 crop-disease classes, and 9 geographic regions spanning tropical, subtropical, and temperate agricultural systems. Unlike conventional datasets, LeafNet 2.0 integrates biologically grounded symptom descriptions with image-level annotations of early and late disease stages, enabling symptom-aware analysis of disease progression under realistic field conditions. We further introduce LeafBench 2.0 as part of LeafMD, a visual-question answering benchmark covering nine fine-grained plant pathology tasks, including pathogen classification, lesion characterization, symptom interpretation, and disease severity assessment. Evaluation across 16 vision-language models revealed substantial performance gaps between coarse disease recognition and fine-grained pathological reasoning, while agriculture-adapted models consistently outperformed several larger general-domain architectures on symptom-oriented tasks. Together, LeafNet 2.0 and LeafBench 2.0 establish LeafMD as a multimodal resource for developing disease-aware agricultural foundation models and studying fine-grained pathological reasoning in real-world environments.

Viroids are plant infectious agents that threaten agricultural production. Current viroid detection methods rely on RT-PCR-based assays, which require specialized laboratory equipment and can sometimes produce false-negative results or non-specific amplification due to the high sequence conservation among closely related viroid species. CRISPR-based diagnostics, particularly Cas12-based systems for DNA detection (DETECTR) and Cas13a-based systems (SHERLOCK) for RNA detection, have emerged as powerful tools for nucleic acid diagnostics. However, most existing workflows still rely on target amplification and, in the case of Cas13a systems, require additional in vitro transcription steps, limiting their simplicity and direct applicability for plant diagnostics. Here, we developed a direct amplification-free Cas13a-based detection platform for viroids using potato spindle tuber viroid (PSTVd) as a model. We optimized CRISPR RNA (crRNA) design, identified inhibitory effects of plant total RNA on readout signal, and employed simplified viroid RNA enrichment workflows enabling robust detection in plant samples. The system further supported both PSTVd-specific and broad-spectrum pospiviroid (genus Pospiviroid) detection and was successfully extended to avocado sunblotch viroid (family Avsunviroidae), demonstrating its adaptability across distinct viroid families. Together, these results establish a practical and modular Cas13a-based platform, not only for viroid diagnostics, but also for broader applications in RNA-derived plant pathogen detection. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/736049v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1d04170org.highwire.dtl.DTLVardef@1783aa3org.highwire.dtl.DTLVardef@51baa7org.highwire.dtl.DTLVardef@1b542b9_HPS_FORMAT_FIGEXP M_FIG C_FIG Significance statementA simplified RNA enrichment workflow combined with CRISPR-Cas13a enables direct, amplification-free detection of plant viroids. The assay supports early and reliable diagnosis across different tomato varieties and provides a practical strategy for improving molecular detection of plant pathogens.

In Asteraceae species, the capitulum is a compact inflorescence, featuring a characteristic reproductive structure. Despite the identification of a few key regulatory factors, the transcriptome-level information on the developing capitulum remains limited. Here, we applied single-cell and spatial transcriptome sequencing to investigate the developing Gerbera hybridas capitulum during floret differentiation. We obtained a transcriptomics atlas encompassing different stages of the Gerbera capitulum and analyzed the cellular and spatial dynamics of gene expression. Using marker gene expression and GO enrichment of cluster-specific DEGs, we annotated putative cell types and described changes in gene expression across sampled stages, potentially associated with ongoing developmental processes. We detected activity of previously undescribed MADS-box genes and defined their spatial expression patterns. Notably, the MADS-box gene GAGL12 was found to be enriched in the putative capitulum phloem cells. The GAGL12 protein was shown in yeast two-hybrid assays to interact with several other MADS-domain proteins with hypothesized functions in vasculature development, and further detailed in silico analyses supported a candidate role in the development of capitulum vasculature. Altogether, we provide integrative and dynamic transcriptomic insight into capitulum and floret development and lay a basis for future functional studies of the control and development of this intriguing reproductive structure.

Accurate segmentation of plant disease symptoms is essential for crop monitoring and phenotyping, yet it typically requires costly pixel-level annotations. Weakly supervised semantic segmentation (WSSS) alleviates this burden using image-level labels, but its performance depends on the quality of spatial priors such as class activation maps (CAMs). We investigate whether text-guided segmentation with the Segment Anything Model 3 (SAM3) can serve as an alternative weak supervision signal. Three pseudo-mask generation strategies are compared: (i) CAMs refined with SAM or SAM3, (ii) zero-shot text-guided SAM3, and (iii) a hybrid approach combining weak spatial cues with text prompts. The resulting pseudo-masks are used to train a DeepLabV3 model. Text guidance alone matches or outperforms conventional WSSS, achieving up to 0.46 IoU without spatial supervision and 0.61 IoU on a public dataset, although performance is sensitive to text prompt formulation. The hybrid strategy improves robustness, reaching 0.50 IoU on the primary dataset and 0.58 IoU on the additional dataset while reducing prompt sensitivity. Overall, text guidance is a promising alternative to conventional weak supervision, while hybrid approaches provide a more robust solution for plant disease segmentation.

Polycomb Repressive Complex 2 (PRC2) is a histone H3K27 methyltransferase that represses gene expression. Arabidopsis thaliana (A. thaliana) has several different PRC2 isoforms that are functionally distinct during the life cycle of the plants. However, their biochemical and structural characteristics have not been investigated. Here, we biochemically characterized PRC2 isoforms having different catalytic subunits: SWNINGER (SWN; PRC2 SWN ) and CURLY LEAF (CLF; PRC2 CLF ). Interestingly, PRC2 SWN showed much lower activity than PRC2 CLF . In addition, PRC2 SWN methylates histone H3K27 in mono and di-methylation, while PRC2 CLF shows robust tri-methylase activity. We also determined the cryo-electron microscopy (cryo-EM) structures of PRC2 SWN and PRC2 CLF , revealing that the substrate binding pocket of the SWN SET domain is blocked by a loop in the pre-SET domain, functioning as an auto-inhibitory loop, while that of the CLF SET domain is freely accessible. Introduction of CLF-like mutations in the auto-inhibitory loop in SWN enhances PRC2 SWN activity. Furthermore, structure-guided in planta analysis shows that a CLF-mimetic SWN mutant rescues the CLF knockout phenotype. Our work provides structural and molecular insights into the isoform-specific regulatory mechanism of plant PRC2.

Progressive climate change is driving increasingly devastating crop losses through droughts, heatwaves and other adverse weather. Combined with shrinking arable land and spreading plant diseases, this makes it crucial to enable crops to grow efficiently in unfavorable, dynamic environments. Because stressors demand prompt, highly coordinated responses, plant stress adaptations rely heavily on epigenetic regulation. Histone deacetylases (HDAs), particularly class I, were recently shown to repress these responses. As constitutive defense is energetically costly, tools enabling temporal modulation of such mechanisms are highly sought after in crop biotechnology. This study evaluated whether valeric acid (VA), a five-carbon carboxylic acid, can inhibit HDA and activate plant defense responses. Here we show that VA is a potent HDA inhibitor that confers resistance to multiple abiotic and biotic stresses in Arabidopsis, and further validate the abiotic component in maize and tomato. Despite its simple chemical structure, structural and transcriptomic evidence shows that VA acts by selectively inhibiting two major stress-repressing deacetylases, HDA19 and HDA6. By targeting these epigenetic switches, VA activates natural defense and acclimation responses. Time-course transcriptomic analyses further revealed that priming with VA induces transcriptional memory, which, together with VA-induced metabolic rewiring, enables rapid and efficient responses to future stressors. Most importantly, despite activating energetically demanding defenses, VA promotes vegetative growth and increases yield under normal conditions, thereby breaking the growth-defense trade-off. These findings establish VA as the first epigenetic biostimulant of its kind, capable of improving plant performance under both abiotic and biotic stress while simultaneously increasing crop yield. As the epigenetic mechanisms underlying its action are evolutionarily conserved, VA priming emerges as a promising universal strategy to mitigate the climate-driven global crisis of crop losses.

Polyacetylene glycosides exhibit notable pharmacological activities, yet the glycosyltransferases acting on their polyacetylene scaffolds remain unknown. Here we report a telomere-to-telomere genome assembly of Codonopsis pilosula and, guided by spatial metabolomics, characterize three UDP-glycosyltransferases: CpUGT76BG1 and CpUGT76BG2 catalyze the direct glycosylation of lobetyol to lobetyolin, while CpUGT94BY2 performs subsequent sugar-sugar coupling to produce lobetyolinin, with each activity confirmed by in planta overexpression. Structural modeling reveals that CpUGT76BG1 and CpUGT76BG2 employ a deep hydrophobic tunnel to fully encase the linear polyacetylene chain, a binding architecture distinct from the shallow pockets used by canonical plant UGTs for planar aromatic substrates. Ancestral sequence reconstruction across eleven nodes partitions the UGT76 lineage into three functionally distinct evolutionary stages, tracing the trajectory from an ancestral shallow pocket to this specialized deep architecture. These findings establish the key glycosylation steps of polyacetylene glycoside biosynthesis, define a tunnel-based paradigm for non-planar substrate recognition, and reveal how tandem duplication-driven active site remodeling generates metabolic novelty.

O_LIThe control of amount of nuclear proteins is fundamental in regulating plant gene expression, but the mechanisms of quantitative dynamics of the nuclear proteome are largely unstudied during adaptive responses to pathogens. C_LIO_LIHighly specific labeling, enrichment and measurement of the nuclear proteome was performed using TurboID LC-MS of Arabidopsis thaliana leaves treated with the pathogen-associated molecular pattern (PAMP), flg22, and/or cycloheximide. The chosen experimental approach allowed discrimination of the effects of translation, nuclear protein import, trafficking of preexisting proteins, derepression, and nuclear protein turn-over upon elicitation of basal immunity. C_LIO_LIThe highly specific, deep coverage of proteins in the nucleus makes this study a resource for anyone interested in plant nuclear proteome dynamics and defense. C_LIO_LIAround 2,000 nuclear proteins were repeatedly quantified, including more than 300 transcription factors or other proteins related to transcription. Several proteins with documented activity in endosomes were newly synthesized and imported into nuclei upon PAMP challenge, suggesting alternative nuclear functions in PAMP-triggered immunity (PTI). Circadian clock components, including the transcription factor, CIRCADIAN CLOCK ASSOCIATED 1 (CCA1)-HIKING EXPEDITION (CHE), were depleted upon PAMP challenge, suggesting a safeguard against untimely induction of systemic acquired resistance (SAR). C_LIO_LIBased on proteomic patterns, proteins moonlighting in the nucleus as well as trafficking and turn-over regulation of the proteome are common elements during plant immunity. C_LI

Quantifying root traits such as root length (RL) and root surface area (RSA) from minirhizotron imagery is a valuable approach for overcoming the phenotyping bottleneck that limits understanding and improvement of crop productivity, resource use efficiency and resilience in field experiments. However, current approaches remain labor-intensive, and deep learning (DL) methods suffer from limited generalization ability. We present RootQuant, an end-to-end DL model that simultaneously predicts RL and RSA directly from minirhizotron images using only whole-image trait values as supervision, thereby eliminating the need for pixel-level annotations. The models generalization ability was evaluated across species and fine-tuning configurations. The practical applicability of the model was further assessed under field conditions by converting image-derived RL estimates into volumetric root length density (vRLD). Using 118,191 maize and soybean images collected between 2009 and 2020, RootQuant trained on both species achieved an R2 of 0.90 and an RMSE of 2.9 mm for RL, and an R2 of 0.88 and an RMSE of 4.2 mm2 for RSA. The same mixed-species model generalized strongly across species, yielding an 8% relative improvement in R2 and a 30% lower RMSE on maize compared with the same architecture trained on a single species and applied zero-shot. Image-derived RL predictions converted to vRLD showed the expected depth-dependent decline in vRLD, as was also found by coincident destructive quantification of roots washed out of soil cores. By providing a generalist backbone model trained on a large dataset from two major crop species, RootQuant enables high-throughput simultaneous estimation of two relevant root traits directly from raw imagery without task-specific fine-tuning, thereby accelerating in situ root system analysis and phenotyping applications.

Aegilops species are the closest wild relatives of wheat and an important reservoir of genetic diversity for its improvement. Despite their potential, many Aegilops genomes remain poorly characterized. Here we present high-quality assemblies of 18 diploid, tetraploid, and hexaploid Aegilops genomes, which, along with the previously published genomes, complete the production of reference assemblies for all 25 genomes in this genus. Assembly sizes ranged from 5.24 Gb in diploids to 12.65 Gb in hexaploids, with scaffold N50 values up to 749.2 Mb. Gene annotation identified 53,035-156,779 protein-coding genes, of which 21,865-60,490 were classified as high-confidence. Orthogroup-based pangenome analysis across the 25 Aegilops genomes identified 80,521 orthogroups, including 15,809 core, 61,735 dispensable, and 2,977 species-specific orthogroups, highlighting substantial gene content variation among genomes. Phylogenetic analysis of 63 Triticum and Aegilops genomes/subgenomes based on near single-copy orthologs defines the phylogenetic relationships within the Triticum/Aegilops complex and confirms diploid progenitors of polyploid lineages. Ae. mutica (T) and Ae. speltoides (S) belong to the B lineage while the remaining Sitopsis grouped within the D lineage. Structural variation analyses using diploid progenitors as references revealed extensive large-scale rearrangements following polyploidization, emphasizing the dynamics of their evolution. Transposable element (TE) annotation further highlighted subgenome-specific TE expansions and contractions, providing insights into the mechanisms shaping genome structure after polyploidization. Collectively, these genomic resources provide a comprehensive framework for exploring Aegilops diversity, understanding polyploid evolution, and accelerating wheat improvement.

Biuret, a nitrogen-rich by-product of urea and a common contaminant of urea-based fertilisers, has long been considered a passive phytotoxin, affecting plant performances. Yet its effects on root development and the existence of endogenous mechanisms of perception or tolerance remain largely uncharacterised. Here we combined physiological, developmental, genetic and transcriptomic approaches to investigate the response of Arabidopsis thaliana to biuret. Biuret inhibited primary root growth in a dose-dependent manner by reducing meristematic cell division rather than cell elongation, and concomitantly impaired shoot growth by limiting leaf expansion. This root inhibition was reversible upon biuret removal and was accompanied by increased auxin-responsive (DR5) and decreased cytokinin-responsive (TCS) outputs at the root apex, consistent with a regulated remodelling of meristem activity rather than purely cumulative damage. A forward genetic screen identified the biuret-resistant mutant bir29, which sustained root and inflorescence development under inhibitory concentrations. Using {superscript 1}N-labelled biuret, we showed that resistance occurred without any change in biuret influx or accumulation, uncoupling sensitivity from exposure. Whole-genome transcriptomics revealed that bir29 fails to execute the wild-type response, neither repressing the cell-cycle machinery nor deploying the stress-associated programme induced by biuret. Genetic characterisation linked resistance to multiple genomic loci required for full resistance. Together, the results indicate that biuret triggers an active, reversible and genetically tractable developmental response, suggesting that this xenobiotic compound is integrated into endogenous signalling networks. Significance StatementBiuret, a poorly metabolised contaminant of urea fertilisers, is generally regarded as a passive phytotoxin, yet we show that it inhibits Arabidopsis root growth through a reversible and genetically tractable developmental response, accompanied by reorganised auxin and cytokinin signalling, rather than through cumulative chemical injury. The isolation of the resistant mutant bir29 suggests that plants integrate this xenobiotic molecule into endogenous signalling networks, reframing biuret as an informative probe of root developmental regulation.

PremiseSeed size and morphology are critical traits in agriculture, ecology, and genetics, but high-throughput quantification of these traits is often limited by labor-intensive manual measurements or expensive, platform-specific imaging software. Methods and ResultsWe developed SeedMeasure, a lightweight, open-source, and cross-platform command-line tool written in Python that automates the measurement of seed area, length, and width from images. Using a simple imaging setup, the program processes images by correcting for perspective skew, filtering debris, and exports quantitative data alongside quality-check images. We validated SeedMeasure across nine diverse species, ranging from small Arabidopsis thaliana seeds to large Zea mays kernels. The tool quickly handles images using multithreading and demonstrates high reproducibility, yielding low coefficients of variation across repeated runs. ConclusionsCompared to existing software, SeedMeasure is free, offers faster processing through parallel computing, and provides standalone executables that require no programming dependencies. SeedMeasure offers an accessible, cost-effective, and high-throughput approach for rapid phenotypic profiling, making advanced seed morphological analysis available to researchers without specialized laboratory hardware.

The rapid evolution of plant pathogens poses a persistent threat to global agricultural sustainability, often outpacing the discovery and deployment of natural disease resistance genes. While bioengineering of plant intracellular immune receptors (NLRs) offers a potential solution, developing bespoke immune recognition remains constrained by the laborious characterisation of natural receptors and plant-pathogen interactions. Here, we describe a programmable framework that leverages generative AI protein design tools, RFdiffusion and ProteinMPNN, to design de novo integrated domains (IDs) against diverse pathogen effectors. By integrating these bespoke binders into the modular rice blast Pik-1/Pik-2 NLR receptor chassis, we successfully engineer recognition of a non-cognate virulence factor (effector) from the Panama disease pathogen, Fusarium oxysporum f. sp. cubense Tropical Race 4. Functional assays in Nicotiana benthamiana demonstrate that these de novo domains facilitate specific effector perception and initiate immune signalling, while structural and biophysical analyses confirm that de novo integrated domains maintain high structural fidelity to the initial designs and associate with their targets via the predicted interaction interfaces. Additionally, our findings provide orthogonal evidence for the role of integrated domains in regulation of NLR signalling, demonstrating integration of de novo IDs can either trigger autoactivity or, in some cases, lead to effector-mediated repression of cell death. By decoupling immune perception from natural evolutionary history through deploying AI-designed sensory domains, this work establishes a design-lead framework for generation of programmable plant immune receptors, providing a new avenue for bioengineering crops against emerging pathogens.

Phenotyping stomatal traits and their developmental plasticity is time-consuming but holds potential to improve water use efficiency and photosynthesis for designing stress-tolerant crops under climate change. Here, we develop a robust, high-throughput pipeline for phenotyping 14 stomatal traits in winter wheat related to size, variation, maximum conductance, and spatial patterning. We (1) analyze over 25,000 images from 60 wheat cultivars grown in growth chamber, greenhouse, and field conditions; (2) investigate the impact of light, temperature, and reduced water and nitrogen supply on stomatal traits and their developmental plasticity across adaxial and abaxial surfaces; and (3) evaluate genetic diversity and breeding progress of stomatal traits. Stomatal traits were highly broad-sense heritable, were largely plastic in response to environmental conditions, and showed genotype-specific responses. Stomatal traits of third leaves under controlled environments with stable light and temperature conditions reliably captured the genetic variance of flag leaves under field conditions. Our data suggests that the upper leaf surface contributed more to transpiration and cooling through consistently higher stomatal density, area, and maximum conductance, while the lower surface facilitated CO2 diffusion via systematic proper patterning and spacing. Breeding maintains the genetic diversity of stomatal traits, and our pipeline facilitates breeders to target them to enhance water use efficiency in high-yielding modern cultivars.

Plant regeneration is a major determinant of transformation and genome-editing efficiency, yet the endogenous regulatory networks controlling regenerative competence in horticultural crops remain incompletely understood. The miR319-TCP module regulates multiple developmental processes in plants, but its function in lettuce regeneration has not been defined. Here, we performed a genome-wide analysis of the TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) gene family in lettuce (Lactuca sativa). Thirty-three LsTCP genes were identified and classified into Class I/PCF, Class II/CIN, and Class II/CYC/TB1 groups. Five CIN-class genes, LsTCP2, LsTCP3, LsTCP4, LsTCP10, and LsTCP24, were predicted as high-confidence miR319 targets and supported by degradome-based cleavage evidence. MIR319-overexpression (OX319) explants showed enhanced de novo shoot regeneration, with 94.5% regeneration efficiency and 1.92 shoots per explant, whereas STTM-miR319 suppression (S319) explants showed reduced regeneration, with 28.5% regeneration efficiency and 0.36 shoots per explant. These phenotypes were associated with altered expression of several miR319-targeted CIN-TCP genes, particularly LsTCP4, LsTCP10, and LsTCP24. Disruption of LsTCP4 increased regeneration efficiency to 91.4% and shoot production to 2.05 shoots per explant, resembling the regeneration-enhancing effect of miR319 overexpression. In contrast, disruption of the non-target CIN gene LsTCP17 did not significantly affect regeneration under the tested conditions. Together, these results identify LsTCP4 as a key miR319-responsive negative regulator of de novo shoot regeneration and highlight miR319-mediated repression of LsTCP4 as a potential endogenous strategy for improving lettuce regeneration.