Horticulture Research

Nitrogen-use efficiency (NUE) is a pivotal breeding target in tomato (Solanum lycopersicum L.) to sustain production under reduced N inputs. Here, we leveraged a recently developed tomato multi-parent advanced generation inter-cross (ToMAGIC) population to identify lines with superior performance under reduced N availability. The eight founders and a core subset of 118 ToMAGIC lines were characterized with 10,684 SNP markers and evaluated under optimal (opN, 15 mM) and suboptimal (subN, 8 mM) N supply in an experiment totalling 1,576 plants, generating 48,068 data points across 61 phenotypic variables. Under both N treatments, ToMAGIC lines exhibited transgressive segregation for most traits, confirming the value of this population as a reservoir of untapped variation. Notably, under subN conditions, harvest index (Hi) increased by 29-44%, suggesting adaptive resource redistribution toward reproductive sinks. Variance partitioning revealed that agronomic and NUE-related traits were largely under genetic control, with heritability estimates frequently above 0.80 and broadly conserved across N treatments. Multivariate trait analysis identified fruit yield N concentration (NUE component, CN,y), shoot biomass N content (NAb), and shoot growth-related traits as the main drivers of treatment differentiation. Finally, proxy traits were prioritized by integrating response magnitude, heritability, trait correlations, and treatment-discriminatory power into multi-trait selection indices. This strategy generated favorable predicted genetic gains, reaching 158% for high-performance lines and 170% for subN-adapted lines, and consistently identified lines 402, 428, 518, 800, and 816 as promising pre-breeding materials. Overall, this study supports ToMAGIC as a powerful resource for developing N-efficient cultivars suited for sustainable agriculture.

In plant breeding and genetics, recent advances in high-throughput phenotyping are beginning to meet the growing demand for large-scale, high-quality phenotypic data that emerged after the development of next-generation sequencing technologies. Recent developments in phenomics have been incorporated into almond breeding programs, facilitating the large-scale acquisition of quantitative phenotypes and the dissection of the genetic architecture underlying morphological and quality-related traits. The implementation of a high-throughput phenotyping platform integrating RGB and hyperspectral imaging with genotyping using the 60K almond SNP array enabled the large-scale characterization of almond populations and the identification of 567 robust marker-trait associations across 66 traits. These analyses revealed two major genomic hotspots on chromosomes 2 and 5 associated with morphological and quality-related traits. These regions harbored biologically relevant candidate genes, including genes associated with OVATE family proteins, brassinosteroid signaling, protein ubiquitination, and acyl-CoA metabolism, as well as other regulators of organ growth, cell proliferation, hormone signaling, and seed development. Furthermore, a novel candidate gene encoding a COMT-like O-methyltransferase involved in lignin biosynthesis was identified and proposed to contribute to shell hardness, a major genetically controlled trait in almond. Together, these findings demonstrate the potential of integrating high-throughput phenomics and genomics to dissect complex traits, identify candidate genes, and accelerate genomics-informed breeding in almond.

As extreme heat events increase in frequency and intensity worldwide, understanding how woody perennial crops respond to higher maximum temperatures is critical. Perennials face distinct challenges, persisting across many seasons under increasingly variable and extreme conditions, and heat waves threaten the viability of wine grape cultivars through impacts on yield, wine quality, and long-term vine health. To test whether irrigation practices before and during heat waves affect grapevine carbon (C) storage and health, we experimentally manipulated irrigation regimes surrounding heat waves from 2019-2021 in a commercial Cabernet Sauvignon vineyard in the Lodi AVA of Californias Central Valley. Vine physiological traits and yield were measured throughout, and whole-vine nonstructural carbohydrate (NSC) concentrations were quantified after three growing seasons. Although lower supplemental irrigation reduced photosynthesis, stomatal conductance, and fruit yield, whole-vine NSCs did not differ significantly in any perennial organ by the experiments end, indicating that reproductive output and final NSC status responded to irrigation on different timescales. These results suggest that moderate supplemental irrigation during heat events is sufficient to mitigate negative impacts on yield and quality while supporting recovery of NSC reserves, though longer-term monitoring is needed to confirm that this short-term resilience persists.

Rising winter temperatures threaten deciduous fruit tree productivity by depleting carbohydrate reserves during dormancy. This study investigated Stem Photosynthetic Capacity (SPC), a rare adaptive trait from wild Prunus arabica, as a mechanism to enhance almond carbon economy. Using extreme segregating groups from the F1 population (P. dulcis X P. arabica), we evaluated physiological performance through high-resolution lysimetric and multi-year orchard monitoring. High-SPC [SPC(+)] genotypes maintained significantly greater stem CO2 assimilation and transpiration during leafless periods compared to low-SPC [SPC(-)] progenies. Over five successive seasons, SPC(+) trees exhibited a 33.3% increase in trunk secondary growth and reached 10% bloom approximately 8 days earlier. Most importantly, the SPC(+) group achieved a 4.6-fold increase in mean kernel yield when compared to SPC(-) group. These findings demonstrate that SPC provides a flexible, supplementary winter carbon source that directly supports both vegetative and reproductive development. Integrating SPC into commercial almond breeding programs may offer a valuable strategy to improve climate resilience and help sustain yields under warming conditions. HighlightIntegrating stem photosynthesis into commercial almond hybrids provides a winter carbon source that advances blooming, expands trunk growth by [~]33%, and increases kernel yields by more than 4.5-fold.

Flax (Linum usitatissimum L.) has been domesticated for dual end uses as linseed and fiber flax, yet the genomic basis of morphotype divergence remains unclear. Here, we constructed a morphotype-resolved pangenome by integrating three newly generated near telomere-to-telomere genome assemblies with 14 previously published ones. Despite substantial variation in assembly size, driven primarily by DNA transposons, gene content was highly conserved, with little evidence for significant morphotype-specific gene presence-absence variation. Population genomic analyses of 407 accessions revealed that fiber flax had reduced nucleotide diversity, extended linkage disequilibrium, and a more compact population structure relative to linseed, consistent with stronger selection and a narrower genetic base. Genome-wide differentiation was heterogeneous and concentrated in discrete regions. Integration of FST, nucleotide diversity ratios, Tajimas D, and genome-wide association signals identified morphotype-enriched genomic blocks distributed across the genome. Many candidate regions are primarily supported by directional shifts in nucleotide diversity rather than extreme differentiation, indicating selection on standing genetic variation. Genome-wide association analyses identified 1,712 unique quantitative trait nucleotides (QTNs), with predominantly small effect sizes and strong enrichment in gene-proximal regions, consistent with a polygenic architecture. Overall, fiber flax traits tend to be controlled by fewer loci with moderate-to-large effects, whereas linseed traits exhibit a more diffuse genetic architecture. Patterns of Tajimas D further support non-classical selection dynamics, with predominantly positive values in linseed and localized negative values in fiber flax, consistent with selection on standing genetic variation. Together, our results suggest that flax morphotype divergence is driven primarily by selection on pre-existing allelic variation within a conserved gene repertoire. This study provides a comprehensive framework linking genome structure, population genomics, and trait architecture, and highlights the importance of standing genetic variation as a key resource for flax breeding and improvement.

In vitro regeneration of Citrus plants is a widely used method, however, induction of adventitious roots from regenerated shoots remains a major bottleneck, limiting the recovery of healthy plants for commercial production and genomic research for crop improvement. We established an in vitro regeneration system producing profuse, healthy roots for sweet orange (Citrus sinensis cv. Benyenda) by optimising combinations and concentrations of auxins. Prior to optimising the rooting media (RTMs), we obtained a shoot regeneration rate of 90.6% from sweet orange epicotyl explants using a cytokinin, 6-benzylaminopurine (BAP). Across twelve auxin-supplemented RTMs containing different concentrations of indole-3-butyric acid (IBA) and/or 1-naphthaleneacetic acid (NAA), rooting percentages ranged from 8 - 87.5%. The combination of IBA 1.0 mg L-1 and NAA 0.1 mg L-1 promoted the best overall performance, 75 {+/-} 7.2% rooting percentage with healthy, callus-free roots ([≥]5 cm in length), whereas other RTMs with other auxin combinations induced callus and limited root elongation. The best-performing SRM and RTM were subsequently used for selection and recovery of transgenic sweet orange lines carrying an empty CRISPR/Cas9 construct, resulting in an 4.8% transformation efficiency. Both transgenic and non-transgenic rooted plantlets were successfully acclimatised under glasshouse conditions with a survival rate of 90%. This enhanced regeneration system overcomes rooting bottleneck and improves plant survival,enabling faster recovery of transgenic citrus lines within four months. It supports accelerated development for commercial applications and advances in citrus genetic improvement.

Globe artichoke (Cynara cardunculus var. scolymus L.) comprises a broad range of local ecotypes and varietal groups whose genetic diversity has been investigated through different molecular markers. However, recent advances in next-generation sequencing and pangenomics approaches provide new opportunities to capture genome-wide variation at higher resolution and to develop practical tools for varietal discrimination, traceability, and germplasm conservation. In this study, we developed the first pangenomic framework for cultivated artichoke and evaluated pangenome-informed SNP markers for varietal fingerprinting. Whole-genome resequencing data from the Italian local ecotype Asti Sori were integrated with publicly available genomic data from representative globe artichoke and cultivated cardoon accessions to construct and annotate a pangenome. Genome-wide SNP and presence/absence variation (PAV) analyses were combined with pangenome-anchored genotyping-by-sequencing (GBS) data from 45 accessions representing the main cultivated varietal groups. The pangenome revealed a largely conserved core gene repertoire alongside a smaller accessory component, with gene accumulation curves suggesting a tendency toward saturation within the sampled cultivated germplasm. SNP- and PAV-based analyses provided complementary views of accession relationships and consistently resolved the principal cultivated groups. Across the broader germplasm panel, pangenome-anchored GBS-derived SNPs identified well-supported phylogenetic clusters corresponding to recognized varietal types. A reduced panel of 50 SNPs, selected through iterative random subsampling, retained at least 90% of the genetic diversity captured by the full dataset and reproduced its main population structure. This compact pangenome-anchored marker set provides a practical foundation for varietal fingerprinting, DUS-oriented applications, traceability, and conservation of traditional globe artichoke germplasm. Validation across independent collections will be required before routine deployment.

Background: Germplasm collections contain wide genetic diversity that is valuable for plant breeding, but conducting phenotypic evaluation for all genotypes in field trials is rarely feasible. Bayesian optimization offers a way to decide, season by season, which genotypes to cultivate in order to identify superior genotypes with fewer evaluations. However, standard Bayesian optimization commonly starts from randomly selected genotypes and mainly relies on surrogate models built from marker genotype information, while the text-based passport information that accompanies germplasm is not fully used. We examined whether pre-trained large language models can provide prior knowledge that improves these decisions in germplasm evaluation. Results: We constructed a large-language-model-guided Bayesian optimization framework that introduces large language models into two parts of the Bayesian optimization workflow. In zero-shot warmstarting, a large language model proposes initial genotypes using passport information such as cultivar name, country of origin, and subpopulation, optionally together with principal component scores derived from genome-wide single-nucleotide-polymorphism markers. In addition, we evaluated a large-language-model-based surrogate model that predicts phenotypic values for untested genotypes using in-context learning from previously evaluated genotypes. Using a rice germplasm panel and two target traits (seed number per panicle for maximization and protein content for minimization), we compared strategies. For seed number per panicle, zero-shot warmstarting with a general-purpose instruction-following model reduced the number of evaluated genotypes needed to reach the best genotype, whereas improvements were small for protein content. When genomic information was available, Gaussian-process-based Bayesian optimization was the strongest overall approach, while the large-language-model-based surrogate model outperformed random baselines and was competitive in some settings. When genomic information was not available, predictions based on passport information improved efficiency compared with fully random strategies. Conclusions: Pre-trained large language models can inject useful agronomic knowledge into Bayesian optimization for germplasm evaluation, particularly by improving early-stage genotype selection, and can also support optimization when genomic information is unavailable. As models better handle long genomic sequences together with passport information, large-language-model-guided Bayesian optimization may become a practical and explainable decision-support approach for agricultural optimization.

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.

Celiac disease (CeD) is an immune-mediated condition triggered by wheat gluten in genetically predisposed individuals. The immune reaction in people with CeD is driven by particular gluten amino acid sequences, or immunogenic epitopes. Some of these epitopes elicit strong immune responses in the majority of CeD patients and are designated as immunodominant epitopes. Previous research has shown correlations between the amount of immunogenic wheat epitopes consumed and the onset of CeD, suggesting that reducing wheat immunogenic epitopes may reduce CeD incidence at the population level. Gluten consists of gliadins and glutenins, with gliadins having the majority of the immunodominant epitopes and glutenins playing a major role in dough strength and breadmaking quality (BMQ). This study used radiation-induced deletions, chemical mutagenesis, and natural variation in wheat (Triticum aestivum) to generate genetic stocks with reduced immunogenic epitope content. Most lines were developed in the wheat cultivar Summit, for which we produced a full genome assembly and annotation. We used exome capture to characterize these deletions and identify prolamins located within and outside the deletions. We combined different deletions and developed molecular markers to facilitate their deployment. For chromosome arms 1BS and 1DS, we generated two alternative lines: one lacking immunogenic epitopes for the development of CeD-safe genetic stocks for research purposes, and another retaining selected glutenins for breeding commercial lines with reduced immunogenicity and adequate BMQ. By making these non-transgenic genetic stocks publicly available, we aim to accelerate the development of wheat varieties with reduced immunogenicity and, eventually, a fully CeD-safe wheat.

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.

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.

AbstractTomato production faces a persistent challenge from the tomato leaf miner, Phthorimaea absoluta, a pest that severely limits yields while effective resistance in cultivated varieties remains scarce. To address this gap, wild tomato relatives represent a promising reservoir of resistance traits. In this study, 24 tomato accessions, including both cultivated types and wild species, were evaluated under greenhouse (no-choice) and tunnel (choice) conditions. Resistance mechanisms were characterized through measures of antibiosis such as leaflet lesion type, proportion of attacked leaflets, and mine density. The results revealed substantial variation between and within species, allowing classification of accessions into resistant, intermediate, and susceptible groups through multivariate analysis. Notably, the wild accession Solanum habrochaites PI248707 exhibited strong resistance, in contrast to susceptible cultivated varieties such as Rose de Berne. Under choice conditions, PI248707 sustained limited damage and disrupted larval development, with early instar larvae present but few reaching advanced stages, indicating an inhibitory defense response. Untargeted metabolomic profiling further highlighted pronounced constitutive differences between wild and cultivated accessions, with S. pennellii and S. habrochaites displaying higher metabolic diversity. By integrating phenotypic and metabolic data, specific metabolite classes associated with resistance were identified. These findings underscore the potential of wild tomato germplasm in breeding programs, with PI248707 standing out as a strong candidate for resistance introgression.

Scalesia gordilloi is a critically endangered species endemic to San Cristobal Island in the Galapagos archipelago and represents one of the most unique and vulnerable lineages within the adaptive radiation of the genus Scalesia. Despite its evolutionary distinctiveness and conservation importance, no genomic resources have been available for this species. Here, we present the first high-quality reference genome of S. gordilloi, generated using Oxford Nanopore long-read sequencing. Across three PromethION R10.4.1 flow cells, we obtained 80.5 Gb of long reads (~25X coverage), which enabled a highly contiguous 3.61 Gb assembly composed of only 549 contigs and an N50 of 106.6 Mb. BUSCO completeness reached 98.6%, with assembly metrics comparable to other high-quality Asteraceae genomes. Repeat annotation revealed that 76.2% of the genome is composed of interspersed elements, dominated by LTR retrotransposons. Structural annotation resulted in 47,913 high-confidence protein-coding genes, consistent with expectations for large, repetitive Asteraceae genomes. This genome provides a critical foundation for conservation genomics, enabling assessments of genetic diversity, inbreeding, and adaptive potential in the species. It further establishes a framework for comparative genomics across the Scalesia radiation and supports future efforts to protect and restore one of the most threatened plant lineages of the Galapagos Islands.

Flowering time strongly influences crop adaptation, plant architecture, generation turnover, and breeding efficiency, but the functional organization of florigen genes remains poorly resolved in many polyploid orphan crops. Quinoa (Chenopodium quinoa) is a climate-resilient allotetraploid crop with extensive variation in flowering behavior, and genome analyses have identified multiple FLOWERING LOCUS T (FT)-like homologs. However, genome sequence and expression information alone cannot determine which homologs provide effective florigenic output in planta. Here, we combined apple latent spherical virus-mediated overexpression (VOX) and virus-induced gene silencing (VIGS) in quinoa with heterologous expression in Arabidopsis thaliana, domain-swapping analyses, and cross-germplasm validation to functionally dissect quinoa FT activity. Although several CqFT homologs were transcriptionally induced during the floral transition, their functional outputs were markedly unequal. CqFT1A and CqFT1B-1 acted as the major florigenic activators: overexpression of either gene induced rapid and synchronized flowering, whereas CqFT1-VIGS delayed flowering. In contrast, CqFT2A and CqFT2B retained only weak flowering-promoting activity, whereas CqFT1B-2 showed no detectable promotive effect under the conditions tested, revealing a clear functional hierarchy among transcriptionally induced CqFT homologs. Domain-swapping analyses showed that C-terminal variation contributes to, but does not fully explain, functional divergence among CqFT homologs. In late-flowering highland lines, elevated FT input accelerated flowering, induced coordinated floral transition, and shortened the time to viable seed production. These findings identify CqFT1A and CqFT1B-1 as the major florigenic activators in quinoa and establish a functional genomics framework for resolving and modulating flowering-time control in polyploid orphan crops.

Multi-trait genomic prediction offers a practical route to improve selection for costly, complex traits in clonally propagated crops such as cassava. In a Brazilian breeding panel of 1,078 cassava clones genotyped with 25,923 SNPs and phenotyped for six agronomic traits, we compared single-trait (ST) and multi-trait (MT) GBLUP models. Stage-wise mixed models produced BLUEs that fed into ST and MT-GBLUP. We tested five cross-validation schemes that mimic breeder realities: ST baseline (CV1); naive all-traits MT prediction for unphenotyped candidates (CV2); MT prediction using auxiliary trait phenotypes in the test set (CV3); and two sparse-phenotyping regimes with missingness by trait (CV4) or by clone (CV5) at 25%, 50%, and 75% levels. The main results were that, under the ST baseline (CV1), predictive ability ranged from 0.50 for DMC and 0.45 for FRY down to 0.13 for Le.Dis. A naive full MT model (CV2) performed approximately on par with ST-GBLUP. In contrast, MT designs (CV3) that included informative auxiliary traits, such as shoot yield and combinations with plant vigor and leaf disease severity, yielded small gains for DMC with predictive ability of approximately 0.51 (+2%), while FRY predictive ability increased to approximately 0.65 (+44%), accompanied by RMSE reductions for FRY up to approximately 13.5% (e.g. RMSE approximately 6.2). Sparse-phenotyping simulations (CV4/CV5) demonstrated that MT models sustain or even improve predictive ability under realistic missing-data regimes (PA {approx} 0.62 - 0.65). Selection concordance between MT and ST top-10% sets was generally high (>0.80), and MT configurations produced measurable improvements in expected selection response and genetic gain per cycle for several target traits. These results indicate that strategically implemented MT-GBLUP, using a small set of biologically and operationally informative auxiliary traits and optimized sparse phenotyping, can materially increase predictive accuracy and selection efciency for economically critical cassava traits while reducing phenotyping burden.

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.

Drought is a major abiotic stress threatening plant productivity and agricultural sustainability, yet the molecular mechanisms underlying adaptive root responses to water deficit in the water use strategies continuum remain insufficiently understood, particularly in perennial crops. In this study, we explored drought responses in nine accessions belonging to three wild Vitis species (V. acerifolia, V. candicans, and V. doaniana) displaying varying drought-response strategies. Plants were subjected to moderate drought stress (40% soil water content) for three weeks under greenhouse conditions. By integrating physiological, metabolic, and transcriptomic analyses, we aimed to identify both conserved and species-specific mechanisms associated with drought adaptation. Differential expression analyses revealed a conserved core set of drought-responsive genes shared among species, including genes involved in abscisic acid signaling, reactive oxygen species detoxification, solute transport, and plant defense. In parallel, each species exhibited distinct transcriptional and metabolic signatures reflecting alternative adaptive strategies related to osmoregulation, and oxidative stress mitigation. Weighted gene co-expression network analysis (WGCNA) further revealed significant associations between constitutive, non-plastic gene expression and root phenotypic traits. Overall, our findings demonstrate that wild Vitis species rely on both conserved stress-responsive pathways and species-specific constitutive regulation to cope with drought stress. These results highlight the importance of root-associated traits and intrinsic regulatory networks in shaping drought adaptation and provide new targets for the development of drought-resilient grapevine rootstocks.

Applications of tissue culture are critical for Cannabis sativa L. (cannabis), supporting clonal propagation, germplasm preservation, pathogen elimination, among other biotechnological applications. However, extensive genetic diversity associated with cannabis results in highly variable responses to in vitro conditioning, and no consensus basal media formulation exists to support reproducible micropropagation across genotypes. To address these limitations, a hybridized ensemble-NSGA-II approach was employed for concurrent optimization of individual media components to create a species specific, cultivar inclusive basal salt formulation for cannabis micropropagation. The resulting PHJ media represents a unique formulation that overcomes recalcitrance across a wide array of cannabis cultivars, facilitating improved growth and uniformity for the nine cultivars used in its development and validation. These results remain consistent from explant initiation through multiple rounds of subculture. The ability of PHJ to overcome genotypic recalcitrance is telling of its potential applicability with an array of plant species beyond cannabis. Additionally, robust performance both with and without plant growth regulators underscores the plausible use of PHJ for diverse applications beyond standard micropropagation. Ultimately, this cultivar-inclusive basal medium demonstrates utility for both scientific research and industrial-scale operations.

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.