Plasma membrane-localized receptors operate as dynamic signaling complexes and integrative networks, yet the spatial and temporal regulation of these interactions remain largely unknown. Here, by analyzing the components of a minimal Arabidopsis leucine-rich repeat receptor kinase network, we describe the differential diffusion and organization of receptor complex components and unveil the nanoscale spatial and temporal logic underlying the formation of receptor kinase complexes. The ligand-binding receptors FLS2 and BRI1, and the accessory receptor BIR3, are organized in plasma membrane nanodomains, within which the co-receptor BAK1 diffuses and is spatially arrested upon ligand perception. BAK1 spatial arrest relies on extracellular domain (ECD)-ECD interactions but does not require receptor complex activation. Mathematical modelling, single molecule imaging and bio-assays infer that accessory receptors maintain a dynamic pool of co-receptors in the vicinity of ligand-binding receptors to promote ligand-induced complex formation and signaling. We propose that ligand-induced receptor kinase complex formation is a deterministic process defined by the relative nanoscale spatial positioning of individual signaling and regulatory components.

Trans-species RNA interference (tsRNAi), in which plants produce small RNAs (sRNAs) to silence target genes in pathogens, has emerged as a promising strategy for disease control. However, whether tsRNAi constitutes an endogenous, regulated immune response remains unclear. Here, we show that ARGONAUTE10 (AGO10) plays a critical role in pathogen-induced tsRNAi. Loss of AGO10 in Arabidopsis abolished pathogen gene silencing during infection, leading to hypersusceptibility to oomycete and fungal pathogens. Importantly, AGO10 rapidly responds to pathogen infection through increased protein accumulation and re-location into discrete cytoplasmic condensates, thus promoting the production of trans-species sRNAs at the pathogen infection sites. This immune responsiveness relies on the N terminal intrinsically disordered region (IDR) of AGO10, which is responsible for sensing and responding to immune activation. Specific features in the IDR partitions AGO10 into two deeply diverged subgroups, AGO10a and AGO10b, with the immune responsiveness and defense function evolutionarily conserved in AGO10a but not AGO10b. Together, these findings establish tsRNAi as a bona fide, evolutionarily conserved immune response and position AGO10 as a signal-responsive hub linking pathogen perception to tsRNAi-based defense.

Genetically encoded pigments are powerful visual reporters and creative tools for biology, yet in plants the palette of pigment biosynthesis genes has remained largely limited to red betacyanins encoded by RUBY. Here we develop and characterize three new polycistronic constructs AMBER_v1, AMBER_v2, and GOLD that contain betalain biosynthesis enzymes to produce yellow, fluorescent betaxanthins in plant tissues. These tools expand the palette of publicly available pigmentation genes for use in plant research, education, and floral design.

Effectors are pathogen proteins that facilitate infection by manipulating plant immunity. Computational programs have been developed that identify effectors from sequence data. Many of these programs use internal models that have unavoidable biases due to their training processes and the diverse nature of effector sequence, function and phylogeny. Each programs ability to predict effectors across a broad range of plant pathogens is therefore limited. We hypothesised that a meta-predictor constructed using machine learning (ML) approaches could integrate predictions from multiple programs and improve our ability to predict effectors more accurately from bacteria, fungi, and oomycetes. We trained a range of classifiers using classical ML approaches and deep neural networks (DNNs), then selected eight: Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and five DNNs for evaluation. The training, test and validation data were carefully curated from effector and non-effector annotated sequence derived from the training and sample data of six programs: EffectorP 3.0, deepredeff, WideEffHunter, EffectorO, EffectiveT3, T3SEpp. The models were tested against existing programs on a test dataset, and we observed better performance from our models. The best-performing model was a DNN (Model_2) that balanced improved sensitivity with specificity across the three taxa. We observed using SHAP that all the features contributed to the output of Model_2, which might be the reason for its superior performance. The DNN was developed into a package, fimep, to allow easy use of our model.

Diploid potato breeding enables faster genetic improvement via selection against deleterious alleles in inbred lines, unlike breeding by intercrossing tetraploid varieties. Starch is the major source of calories in potato tubers, but the starch properties of diploid lines have rarely been reported. In this study, we provide a comprehensive characterisation of tuber and starch properties in two diploid lines that are early isolates from the Solynta breeding program, B26 and B100, and their F1 hybrids. B100 produced fewer, but larger tubers compared to B26, and both diploid lines produced tubers that are smaller than the tetraploid variety, Clearwater Russet. The low tuber yield of B100 correlates with its high self-compatibility and fruit production. Pruning of fruits in B100 significantly increased total tuber yield per plant by stimulating more tuber initiations, but had no effect on average tuber weight, starch content or starch structure. Among the diploid, hybrid and tetraploid lines examined, there were no differences in the total starch content of tubers. Although amylopectin structure and amylose content were similar between the two diploid lines and the tetraploid comparison, B26 had elevated levels of resistant starch and a striking elongated granule morphology. Our results showcase the variation in source-sink relations and starch structure in diploid potato breeding material, demonstrating their potential for research into the genetics underpinning metabolic and quality traits.

Angiosperm seed formation requires the coordinated development of the products of double fertilization, the embryo and the endosperm. The endosperm mediates efficient nutrient transfer from surrounding maternal tissues to the developing embryo. This function requires a polarized tissue organization, which manifests as early polar gene expression and polar cellularization dynamics. We show that the receptor kinase HAIKU2 acts in coordination with the transcription factor WRKY10/MINISEED3 to ensure robust endosperm polarity establishment through the activity of the homeodomain transcription factors WUSCHEL-RELATED HOMEOBOX 8 and 9. This process depends on egg cell fertilization and is mediated through the peptide PATHOGEN-INDUCED PEPTIDE-LIKE 7, which acts as a HAIKU2 ligand. Our results reveal how a molecular paracrine dialogue between the embryo and endosperm ensures optimal seed developmental coordination.

Plant cell wall (CW) integrity signaling enables early detection of microbial invasion, yet the receptors involved and their spatial and temporal dynamics during infection remain largely unknown. We identify ATHENA (ATHE)/MEE39, a previously uncharacterized malectin‑like leucin-rich repeat receptor kinase (Mal-LRR-RK) that contributes to defense against the root vascular pathogen Fusarium oxysporum (Fo), particularly in outer root layers where colonization begins. ATHE abundance, localization, and endocytic trafficking are rapidly remodeled during infection, and loss of ATHE compromises basal immunity and early pathogen‑induced transcriptional reprogramming. ATHE responds to altered cellulose synthesis, cellulose‑derived oligosaccharides, mechanically induced CW perturbations, and the fungal secreted peptide Fo‑RALF. In most of these contexts, ATHE acts together with the LRR-RK MIK2, forming a pathogen‑strengthened RK complex that fine‑tunes root responses to Fo. This represents the first example of a receptor complex visualized subcellularly in vivo during a plant-microbe interaction. Although Brassicaceae‑specific, heterologous expression of ATHE enhanced tomato resistance to Fo, highlighting its functional relevance across plant lineages and its potential use for crop engineering. Our work reveals a previously unrecognized strategy by which plants decode microbial threats through dynamic CW‑integrity surveillance.

Plant nucleotide-binding leucine-rich repeat (NLR) immune receptors typically confer resistance through recognition of specific pathogen effectors. The Arabidopsis NLR WRR4A defies this paradigm by recognizing multiple sequence-divergent effectors from Albugo candida, conferring resistance to multiple pathogen races. Despite minimal sequence similarity, these effectors share a conserved N-terminal ferredoxin-like fold. Through cryo-EM structure determination of two WRR4A resistosomes bound to sequence-distinct effectors, combined with AlphaFold modelling, we reveal a shape-based recognition mechanism: WRR4A engages structurally conserved backbone features of the effectors in a mostly side chain-independent manner, enabling recognition of diverse effectors with similar three-dimensional architectures. These insights guided successful engineering of WRR4A to acquire novel recognition specificity. In addition, analysis of the monomeric WRR4A resting state reveals a distinct domain architecture characteristic of C-JID–containing TIR-NLRs and informs their activation mechanism. This work provides insights into NLR-mediated broad-spectrum recognition and the potential for structure-informed engineering of improved crop resistance.

Pathogen pressure threatens legume crop productivity worldwide. Nucleotide-binding leucine-rich repeat (NLR) immune receptors serve as crucial plant resistance genes, recognizing pathogens and triggering immunity. However, the extent and patterns of NLR expression in different tissues and organs, notably across evolutionary time, remain largely uncharacterized. To investigate tissue-specificity of NLR expression in the Fabaceae (legumes), we conducted comparative analyses integrating phylogenomics and transcriptomics in root and shoot tissues across different legume species. The NLR repertoires of 28 legumes were grouped into five monophyletic clades: coiled-coil NLR (CC-NLR), Toll/interleukin-1 receptor NLR (TIR-NLR), G10-subclade CC NLR (CCG10-NLR), RESISTANCE TO POWDERY MILDEW 8-like CC NLR (CCR-NLR), and TIR-NB-ARC-like β-propeller WD40/tetratricopeptide repeats (TNPs). Most legume NLRs belonged to CC-NLR and TIR-NLR clades, followed by CCG10-NLR, CCR-NLR, and TNP clades. In seven of these species, comparative analysis of NLR expression in leaves versus roots revealed that over half (~57%) of expressed NLR genes showed predominant expression in one tissue: 34% in roots (451/1336), and 23% in leaves (311/1336). We identified 324 root-specific NLRs, 171 leaf-specific NLRs, and 841 non-specific NLRs, with an average tissue specificity per species of 32%. The closely related species grass pea (Lathyrus sativus) and pea (Pisum sativum) were an exception, showing higher levels of leaf-specific rather than root-specific NLR expression. We also identified conserved tissue expression patterns across legume species, resulting in a comprehensive resource describing tissue expression bias, enrichment, and specificity for 113 phylogenetic NLR subclasses. These legume NLR repertoires will support comparative studies between species and inform precision-breeding programs considering tissue expression patterns.