Frontiers in Plant Science

Tillering plasticity is a key adaptive trait in sorghum influencing resource use efficiency via a plants ability to adjust branching to neighbour density. Neighbour detection through red:far-red (R:FR) light sensing regulates this plasticity. While molecular pathways regulating tiller outgrowth are partly known, the genetic architecture underlying density-responsive tillering has not been resolved in any grass species. A sorghum diversity panel (n = 895) was evaluated over two growing seasons (2023 and 2024) with plant spacing ranging from 5 to 60 cm. A linear mixed model incorporating neighbour distance and tiller counts estimated genotype-specific response. GWAS was conducted on isolated plants (no neighbours within 60 cm) and on estimated responsiveness to neighbours. GWAS identified 52 baseline tillering QTLs and 50 for spacing responsiveness, with 10 overlapping, suggesting shared genetic control. Comparison with 41 R:FR pathway candidate genes revealed enrichment in responsiveness QTLs (5/50, 10%) versus baseline (0/52, 0%) (Fishers exact test, P = 0.025). Our model identified 40 unique density-responsive tillering QTL regions. Reducing genotype response to neighbour absence could be a selection target to develop water-efficient sorghum varieties where controlled architecture may be more valuable than natural plasticity.

Tomato production, yield and fruit quality face major challenges due to several factors, including the complex polygenic inheritance of agronomically relevant traits, biotic and abiotic stresses, and increasingly stringent regulations limiting the use of phytosanitary products. In this context, bioinoculants have emerged as a sustainable strategy capable of enhancing yield without compromising fruit quality, conferring protection against different stresses and exerting a minimal or no impact on environment and human health. In this study, we evaluated the effects and the underlying mechanisms by which Streptomyces sp. N2A, an actinobacteria isolated from soybean rhizosphere, promotes seed germination, vegetative growth and yield in tomato, without modifying fruit quality. The obtained results demonstrated that the bacterial treatment significantly improved seedlin[g]s emergence and growth and development in vegetative stage. At harvest, yield was also significantly enhanced, mainly driven by increased individual fruit weight, which was positively correlated with a thicker pericarp in fruits from N2A-treated plants. Transcriptional analysis during fruit development revealed a coordinated induction of auxin and cytokinin signaling pathways before and after anthesis, providing a hormonal framework that underlies the promotion of pericarp growth. This study provides evidence of the beneficial effect of inoculation with Streptomyces sp. N2A on tomato yield and constitutes the first report describing the modification of fruit morphology and expression of genes involved in phytohormonal modulation during early growth and development, induced by a plant growth-promoting Streptomyces.

The ability of seeds to survive until dormancy recedes and the germination requirements are met is an adaptive strategy. Proteomics improves our understanding of the mechanisms that control the adaptation to environmental heterogeneity. In this study, we investigated two European beech populations from different habitats that differed in dormancy and germination traits. We found that the populations exhibited different germination strategies, which were reflected in coordinated but quantitatively different proteomic reprogramming. The Miekinia population exhibited stronger accumulation of proteins involved in nucleotide sugar biosynthesis, S-adenosylmethionine metabolism, and flavonoid biosynthesis. Enhanced nucleotide sugar biosynthesis indicates more intensive cell wall remodelling and carbohydrate metabolism, which support embryo growth and faster germination. Increased S-adenosylmethionine metabolism suggests the epigenetic and hormonal regulation of germination differences between populations. Higher flavonoid biosynthesis indicates an enhanced antioxidant capacity associated with environmental protection. In contrast, the Wisa population showed stronger accumulation of proteins involved in RNA processing, suggesting tighter post-transcriptional regulation and proteome reorganization during germination. Consistent with its deeper dormancy and later germination, the Wisa population appears to rely more on RNA-level regulation, whereas the Miekinia population prioritizes metabolic activation. These contrasting proteomic profiles likely reflect population-specific physiological strategies associated with dormancy depth and adaptation to different climatic conditions. HighlightProteomic reprogramming reveals population-specific germination strategies in European beech, linking dormancy depth with contrasting metabolic activation and RNA-level regulation during the transition from dormancy to germination.

Background and aims Plant volatile organic compounds (VOCs) change dynamically with plant development and in response to environmental conditions. However, their potential as non-invasive indicators of phenological progression remains poorly explored. In this study, we developed a framework integrating automated VOC sampling, time-resolved VOC profiling, and machine-learning analysis for the non-invasive assessment of plant phenology. Using soybean (Glycine max (L.) Merr.), we investigated whether development-associated temporal variation in VOC emissions could delineate and predict developmental phases. Methods We collected VOCs daily under controlled environmental conditions from 16 to 43 days after sowing, spanning the transition from vegetative to reproductive stages, using an automated sampling system coupled with thermal desorption-gas chromatograph-mass spectrometer (TD-GC-MS). To characterise temporal changes in VOC profiles associated with phenological progression, we analysed the daily VOC data using a multi-step pipeline combining statistical filtering and similarity-based network analysis. We defined VOC-derived developmental phases from similarity patterns in the VOC profiles, then developed and evaluated machine-learning models to predict these phases. Key results Seven VOCs exhibited distinct phase-dependent dynamics, including green leaf volatiles and monoterpenes showing characteristic temporal changes during phenological progression. Network-based clustering of VOC profiles resolved five developmental phases closely aligned with conventional developmental stages. A machine-learning model predicted these phases from the VOC profiles with high predictive accuracy on independent test data, demonstrating that phenological progression could be quantitatively inferred from VOC emission patterns. Conclusions Our findings support VOC profiling as a reliable and non-invasive approach for assessing phenological progression in soybean. By extracting temporally structured VOC signals, this framework captures developmental information that may be difficult to obtain through visual observation alone, particularly after canopy closure. VOC profiling offers a practical tool for monitoring crop developmental dynamics and has broader potential for plant phenotyping and precision crop management.

High temperature during grain filling increases rice grain chalkiness and deteriorates grain appearance under climate warming. Although several loci that reduce chalkiness have been identified, breeding strategies that integrate grain level heat tolerance with panicle level heat avoidance remain limited. Here we characterized SL2033, a chromosome segment substitution line carrying a long IR64 derived segment on chromosome 10, and evaluated the combination of the chromosome 10 segment with Appearance quality of brown rice 1 (Apq1), a quantitative trait locus associated with reduced heat induced chalkiness that acts at the grain level. Compared with its recurrent parent Koshihikari, SL2033 had longer flag leaves, altered vertical plant architecture, and lower panicle temperature. Total starch and protein contents were comparable between the two genotypes, whereas RNAseq analysis of the developing endosperm identified specific differences in heat, stress, and cell wall related transcripts. In a two year field trial, a pyramided line combining the SL2033 derived segment with Apq1 had the highest proportion of perfect grains and lowest frequencies of multiple chalky kernel types during the year with hotter grain filling conditions, with no detectable yield penalty. The pyramided line combined longer flag leaves, as in SL2033, with shorter panicle exsertion, as in an Apq1 near isogenic line, and had the lowest panicle temperature among the tested genotypes. Time series unmanned aerial vehicle imaging also detected genotype dependent differences in plant height during early grain filling, supporting distinct temporal patterns of plant development among the lines. These findings demonstrate that pyramiding genetic loci that confer panicle level and grain level heat tolerance is a promising strategy for improving rice grain appearance under high temperature field conditions, which are becoming increasingly prevalent.

Soybean, a widely cultivated leguminous crop valued for its protein, amino acids, and oil, faces the challenge of maintaining protein levels, which have an inverse correlation with yield. Reducing leaf chlorophyll levels could increase seed protein levels without compromising yield; however, this is yet to be tested. Therefore, to understand the impacts of low chlorophyll mutations on soybean yield and seed composition, we screened and compared 25 low chlorophyll soybean mutants to their 11 dark green parents. PI548210 (Lincoln mutant) demonstrates a higher concentration of protein without affecting yield compared to its dark green parent PI548362 (Lincoln), suggesting it as a good candidate for further large-scale field trials. PI547555 (Y11/y11, Clark mutant) demonstrates a lower concentration of oil without impacting yield, alongside lower gross photosynthesis, but with chlorophyll levels in the pod and seed tissues that are comparable to its dark green parent PI548533 (Clark). These findings are consistent with the oil concentration of the soybean being influenced by pod and seed photosynthesis, which is correlated with pod height and row spacing. Chlorophyll levels in the leaf do not necessarily correlate with those in the pod and seed of low chlorophyll mutants, possibly due to substantially lower expression of chlorophyll synthesis genes in the pod and seed. SIGNIFICANCEO_LIPI548210 (Lincoln mutant), one of twenty-five low chlorophyll soybean mutants, demonstrates a higher concentration of soybean protein without affecting yield compared to its dark green parent (Figure 1 and Table 1). C_LIO_LIPI547555 (Y11/y11, Clark mutant), a low chlorophyll soybean mutant, demonstrates a reduced concentration of soybean oil without impacting yield, alongside lower gross photosynthesis in pod and seed tissues compared to its dark green parent (Figures 3 and Table 2). These findings suggest that the oil concentration of the soybean is influenced by pod and seed photosynthesis, which is in turn influenced by pod height and row spacing (Figure 2). C_LIO_LIChlorophyll levels in the leaf do not necessarily correlate with those in the pod and seed of low chlorophyll mutants, possibly due to substantially lower expression of chlorophyll synthesis genes in the pod and seed (Figure 5-6). C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/744892v1_fig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@4282dcorg.highwire.dtl.DTLVardef@9d565forg.highwire.dtl.DTLVardef@1918292org.highwire.dtl.DTLVardef@1359b1_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Two low chlorophyll mutants are as healthy as their dark green parents. Lincoln and its low chlorophyll mutant, left; Clark and its low chlorophyll mutant, known as Y11/y11, right. It can be seen by eye that the plants have low chlorophyll (light green/yellow leaves) but a similar growth habit to their dark green parents. See Supplemental Figures 1-4 for contrast, where low chlorophyll mutants are stunted in growth compared to their dark green parents. C_FIG O_TBL View this table: org.highwire.dtl.DTLVardef@657ec9org.highwire.dtl.DTLVardef@166e75borg.highwire.dtl.DTLVardef@df23c7org.highwire.dtl.DTLVardef@1a60124org.highwire.dtl.DTLVardef@194ed96_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONComparison of seed yield, weight, seed composition between low chlorophyll mutants and their dark green parents. ANOVA is used with linear mixed model (random effect = block, fixed effect = variety). Least squares mean is used to compare. For yield and seed composition, N=4 blocks. For leaf chlorophyll (SPAD), N=40. Yield is average yield per plant (g). n.s. = not significant. C_TABLECAPTION C_TBL O_FIG O_LINKSMALLFIG WIDTH=179 HEIGHT=200 SRC="FIGDIR/small/744892v1_fig3.gif" ALT="Figure 3"> View larger version (26K): org.highwire.dtl.DTLVardef@7a368aorg.highwire.dtl.DTLVardef@192b8f0org.highwire.dtl.DTLVardef@1abb738org.highwire.dtl.DTLVardef@89e978_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 3.C_FLOATNO Light response curve of low chlorophyll mutant (Y11/y11, PI547555) and its parent (Clark, PI548533). Rates of net and gross photosynthesis of low chlorophyll (white) and dark green parents (black) pods under field conditions. Each dot represents a value (n=4) {+/-}SE. We assumed that the seeds greatly inhibited the transmittance of light through the pod and used photosynthetic photon flux density for a single-side. C_FIG O_TBL View this table: org.highwire.dtl.DTLVardef@3f0528org.highwire.dtl.DTLVardef@16ba712org.highwire.dtl.DTLVardef@a5ab2aorg.highwire.dtl.DTLVardef@889254org.highwire.dtl.DTLVardef@3efa4f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 2.C_FLOATNO O_TABLECAPTIONPod photosynthetic parameters for low chlorophyll mutant (Y11/y11, PI547555) and its parent (Clark, PI548533). Photosynthesis was measured 1 September through 15 September 2021 at the University of Illinois Energy Farm in Urbana, IL, USA. The statistical analysis was done using ANOVA with linear mixed model (alpha=0.05). N=4 {+/-} SEM for Clark and N=3 {+/-} SEM for Y11. C_TABLECAPTION C_TBL O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/744892v1_fig2.gif" ALT="Figure 2"> View larger version (23K): org.highwire.dtl.DTLVardef@a36c26org.highwire.dtl.DTLVardef@1116c8forg.highwire.dtl.DTLVardef@ee5e61org.highwire.dtl.DTLVardef@1766712_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO Low chlorophyll mutant (Y11/y11, PI547555) and its parent (Clark, PI548533) differ in concentration of seed oil, which interacts with height of pod and row spacing. The box plots show the median (central line), the lower and upper quartiles (box) and the minimum and maximum values (whiskers). The statistical analysis was done using ANOVA with linear mixed model (n=3 blocks, alpha=0.05). Least squares mean is used to compare. N.s., non- significant in the analysis. A. Concentration of oil in low chlorophyll mutant seeds from the upper canopy decreased by 4% compared to the dark green parent (18.2% vs 19%) while there was no difference between them in the seeds from the lower canopy (20.2% vs 20.6%). B. Schematic layout of 2013 field setting showing two different row spacings. C. Concentration of oil in low chlorophyll mutant decreased by 2% in 38cm spacing (21.4% vs 22%) while there was no difference in 19cm spacing (21.3% vs 21.7%) in 2013 field. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC="FIGDIR/small/744892v1_fig5.gif" ALT="Figure 5"> View larger version (22K): org.highwire.dtl.DTLVardef@68e508org.highwire.dtl.DTLVardef@94a6ccorg.highwire.dtl.DTLVardef@152a187org.highwire.dtl.DTLVardef@1eae137_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 5C_FLOATNO (greenhouse). Correlation between the level of leaf chlorophyll (x-axis: SPAD reading) and the level of immature pod or seed chlorophyll (y-axis, mg/g DW). Line represents the linear regression model. R-squared is a coefficient of determination, the percentage of the response variable variation that is explained by the linear model. Pod is labeled by the fresh weight of seeds it contained. A. Level of chlorophyll of 25-100mg pod (n=18). B. Level of chlorophyll of 100-200mg pod (n=17) . C. Level of chlorophyll of 25-100mg seed (n=17). D. Level of chlorophyll of 100-200mg seed (n=20). C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/744892v1_fig6.gif" ALT="Figure 6"> View larger version (28K): org.highwire.dtl.DTLVardef@167fd88org.highwire.dtl.DTLVardef@361472org.highwire.dtl.DTLVardef@786325org.highwire.dtl.DTLVardef@1b53855_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 6.C_FLOATNO Levels of gene expression in chlorophyll synthesis pathway. A. CHL common pathway genes; Glutamyl-tRNA reductase (GluTR). Glutamate 1- semialdehyde aminotransferase (GSA-AT). ALA dehydratase (ALAD). Uroporphyrinogen III synthase (UROS). Uroporphyrinogen III decarboxylase (UROD). Protoporphyrinogen IX oxidase (PPO). B. Mg branch; Mg-chelatase (Mgch). Magnesium-protoporphyrin IX monomethyl ester cyclase (MPEC). Protochlorophyllide reductase (POR). 3,8-divinyl protochlorophyllide a 8-vinyl-reductase (4VCR). Heme pathway; Ferrochelatase (FECH). Heme oxygenase (HO). Phytochromobilin synthase (HY). Data come from Severin et al (2010). RPKM, reads per kilobase per million mapped reads. DAF, days after flowering. The source seed is experimental line A81-356022 which was generated by introgressing G. soja (PI468916) into G. max (A81-356022). C_FIG

Background: Resistance to protoporphyrinogen oxidase (PPO) inhibiting herbicides is mainly driven by diverse target-site mutations, reducing the effectiveness of this site of action in row crop systems. Fendioxypyracil is a newly developed PPO inhibitor with high intrinsic grass and broadleaf activity, but its performance against resistant populations and target-site enzyme variants remains insufficiently characterized. Results: Enzyme assays using PPO2 from Amaranthus palmeri and Setaria viridis demonstrated that fendioxypyracil maintained low IC50 values across a broad range of resistance associated mutations, including dG210 deletion and G210, R128, and G399 substitutions, whereas oxadiazon, tiafenacil, and saflufenacil showed substantial loss of potency. Greenhouse dose response experiments confirmed strong fendioxypyracil efficacy, with susceptible and G399A populations controlled at <3 g ai/ha, while dG210 and R128G populations showed only moderate shifts in sensitivity but remained effectively controlled at the recommended rate. Transgenic Arabidopsis thaliana expressing resistant PPX2 alleles exhibited faster and more severe injury with fendioxypyracil compared to saflufenacil. Field trials conducted in a PPO resistant Amaranthus palmeri population demonstrated that fendioxypyracil provided consistent weed control and density reduction, matching the performance of trifludimoxazin and saflufenacil while exceeding that of fomesafen. Conclusion: Fendioxypyracil provides robust and broad-spectrum activity against PPO resistant Amaranthus populations and target mutant enzymes, maintaining efficacy across diverse mutation backgrounds. These results demonstrate its potential as an effective tool for managing PPO inhibitor resistance and sustaining weed control in row-crop production systems.

Plant root cellular architecture and cell wall composition influence plant productivity, stress resilience, biotic interactions, and potentially soil carbon accumulation. This study establishes comprehensive compositional parameters for roots of a lowland switchgrass genotype, DVR3. Root traits were analyzed in 12.5 cm depth segments, from Zone 1 near the surface to Zone 4 down to 50 cm. Mean abundance ({micro}g/mg) for major cell wall components included cellulose 470 {+/-} 20, xylose 250 {+/-} 20, lignin 170 {+/-} 15, and total suberin 35 {+/-} 5. Composition and cellular anatomy varied with depth, in a partially coordinated manner. Cross sections showed extensive aerenchyma in mature root regions despite greater root mass density, corresponding to abundant lignin and cellulose. Deep roots were enriched for pectin-associated traits, including arabinogalactan II, homogalacturonan, and arabinose-associated linkages. Suberin content did not vary significantly, though Casparian strip formation, endoderm and exoderm thickening, and suberin surface staining progressed with development. Similar trends in root lignin and specific root length were observed for another lowland switchgrass genotype, AP13. These results suggest that it may be possible to genetically enhance native switchgrass root chemistry to promote soil penetration and below-ground carbon accumulation by reducing variability with development, potentially via cell-type specific adjustments. HighlightOlder, shallower switchgrass crown roots are enriched in lignin and cellulose, and deeper, younger roots are pectin-rich with juvenile cellular anatomy. A more uniform compositional distribution might enhance below-ground traits. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/744798v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@159de98org.highwire.dtl.DTLVardef@124d714org.highwire.dtl.DTLVardef@1a49c14org.highwire.dtl.DTLVardef@2fa67_HPS_FORMAT_FIGEXP M_FIG C_FIG Schematic summary of switchgrass root anatomy and composition across four 12.5-cm depth zones of a 50-cm root system. Zone 1 represents older, shallow roots and Zone 4 includes younger roots and root tips. Representative cross-sections show greater aerenchyma development in older roots than in young root tips. The compositional heatmap shows higher cellulose, lignin, and xylose in Zone 1, higher pectin and nitrogen in Zone 4, and relatively little variation in suberin across zones.

Concurrent exposure to heat and drought stress compromises legume productivity, yet their combined effects are rarely quantified systematically. We compiled a database of 18 studies covering seven legume species. From these, we extracted 929 physiological, biochemical, and yield-related traits and calculated actual-to-additive ratios to classify heat-drought interactions as antagonistic (ratio < 1), additive (ratio = 1), or synergistic (ratio > 1). Additive heat-drought relationships accounted for 59 % of all classifiable observations, 37% relationships were antagonistic, and 4% synergistic. The relationship varied with species, genotype, trait, and experimental conditions highlighting the complexity of combined abiotic stress effects. The results challenge the common assumption that concurrent stresses invariably exacerbate damage and underscore the need for more realistic, quantitatively defined stress treatments as well as frameworks that integrate trait-level responses into predictive models of crop growth and development. Our synthesis provides a quantitative foundation to understand legume phenotypes under the increasingly frequent co-occurrence of heat and drought stress and identifies research areas where further work is needed to improve insight into combined stress responses. HighlightsO_LICombined heat and drought responses were mainly additive or antagonistic. C_LIO_LIEvidence is biased toward few legumes and controlled environments. C_LIO_LIField-based, multi-species studies are needed to identify adaptive traits. C_LI

Potato (Solanum tuberosum L.), the worlds fourth most cultivated crop, suffers yield losses of up to 40-50% from early blight caused by the necrotrophic fungal pathogen Alternaria solani. In this study we performed gas chromatography-mass spectrometry (GC-MS)-based untargeted metabolomics to characterize temporal alterations in metabolite composition, metabolic pathway regulation, and discriminatory biomarker metabolites in the susceptible Indian potato variety Kufri Jyoti, analyzing infected leaves, non-infected leaves, and lesion-associated necrotic tissues across four days post-inoculation (DPI).Metabolite annotation identified 58 compounds, including sugars, organic acids, amino acids, and secondary metabolites.. Multivariate analyses resolved distinct, largely non-overlapping metabolic clusters for control, infected leaves (1-4 DPI), and lesion tissue (Bs1-Bs3). A biphasic metabolic response was observed: early infection (1-2 DPI) was characterized by general suppression of primary metabolism, while late infection (3-4 DPI) showed pronounced upregulation of glycolysis, the TCA cycle, GS/GOGAT, and the shikimate pathway. Key discriminatory metabolites included asparagine, oxoproline, GABA, phenylalanine, and aromatic amino acids. Lesion tissues exhibited distinct metabolic fingerprints, with early disruption of amino acid recycling followed by a late rebound of defense-associated metabolites. Notably, defence-associated phenolics were detected exclusively within lesion tissue and were absent from whole-leaf profiles, demonstrating that spatially resolved lesion sampling captures defence chemistry that whole-leaf analysis alone would miss. The identified biomarker metabolites, particularly those linked to the shikimate and GS/GOGAT pathways, represent promising candidates for metabolite-assisted breeding and targeted crop protection strategies against early blight in potato. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/745268v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@18131edorg.highwire.dtl.DTLVardef@f4fbe6org.highwire.dtl.DTLVardef@1c5db61org.highwire.dtl.DTLVardef@c5ef6d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Heavy-metal accumulation in cereal grains is becoming critical for European food safety, regulation and plant breeding. In the EU, Cd maximum levels in certain foodstuffs have been revised, including lowering or establishing limits for relevant food categories, while new maximum levels for nickel (Ni) have recently been introduced for several foodstuffs, including cereal categories, with limits for oats and selected cereals applying from 2026. Together, these developments create an urgent need to identify genetic and physiological mechanisms that reduce Cd and Ni accumulation in cereal grains while maintaining crop quality and productivity. Against this regulatory and food-safety background, our broader RNA-seq experiment investigates early transcriptional responses to Cd and Ni in oat F2 segregants contrasting for metal accumulation. The full dataset includes low- and high-accumulating segregants, roots and developing caryopses sampled at 3 h and 7 h after treatment. In the present pilot analysis, we focus on the Cd response in developing caryopses of the low-Cd accumulating segregant AS131 to identify candidate processes associated with reduced grain Cd accumulation. The strongest transcriptional responses were not dominated by canonical Cd-detoxification pathways. At 3 h after Cd exposure, differentially expressed transcripts were mainly associated with cell-wall functions, endosperm transfer-cell-specific PR60 proteins, DUF239-containing proteins and cysteine proteinase inhibitors, whereas several dehydration-, pathogen-, defence-, cell-wall-loosening- and ROS- related genes were repressed. By 7 h, the response suggested a shift towards homeostatic acclimation, with induction of TIP2 aquaporins, thiamine thiazole synthases, EF-Tu proteins, coatomer-related genes and carbohydrate metabolism-associated genes, together with repression of LEA/SMP/dehydrin genes, FRO7-like genes, EF-hand calcium-binding proteins and stress-regulatory transcription factors. Pathway-level analyses were broadly consistent with these transcript-level patterns, highlighting structural, nucleosome-associated, translation-related, metabolic and developmental processes. Several Cd-responsive transcripts were also associated with broader abiotic-stress responses, suggesting recruitment of shared stress-regulatory modules rather than Cd-specific detoxification pathways alone. Overall, these results support a working hypothesis in which low Cd accumulation in developing oat grain may involve regulation of solute-transfer interfaces, cellular protection, intracellular homeostasis, trafficking pathways and caryopsis developmental programmes. These findings provide candidate processes for future comparison with high-Cd accumulating segregants, root tissues and Ni responses in the broader dataset.

White lupin (Lupinus albus L.) is a cool-season grain legume with seed crude protein of 33-47%, competitive with soybean (Glycine max L.) meal. It also fixes nitrogen and mobilizes soil phosphorus. Because soybean is a summer crop, white lupin can occupy Southeastern winter fields as a complementary protein source. Breeding for seed protein is limited by the cost and throughput of reference phenotyping. To determine how each is best deployed, we compared the utility of near-infrared spectroscopy (NIRS)-based phenomic selection with genomic selection based on 246,847 SNPs from low-pass, whole genome sequencing in a panel of Auburn University breeding lines and USDA National Plant Germplasm System germplasm. A handheld NIR calibration against Dumas reference protein reached screening-grade accuracy (R2 = 0.81). Under common cross-validation, phenomic predictive ability was 0.93 and genomic was 0.12. The low genomic value was consistent with moderate heritability (H2 = 0.33) and strong genotype-by-year interaction. Beyond predictive ability, NIRS recovered superior accessions the strictest selection intensity, and 40 to 60 reference assays sufficed to calibrate the model. Handheld NIRS is a low-cost tool for protein calibration and early-generation screening, while genomic prediction remains suited to parental selection, together supporting a complementary strategy for legume breeding Plain Language SummarySoybean meal is the main protein source for livestock and fish farms in the United States. Because soybean is a summer crop, many Southeastern fields sit idle or grow low-value cover crops in winter. White lupin, a cool-season legume whose seeds are as protein-rich as soybean meal, makes a good complementary winter crop: it yields high-protein grain while serving as a cover crop that fixes nitrogen and frees up soil phosphorus for later crops. In our early-stage lupin breeding program, measuring seed protein by standard lab methods is slow and costly. We built a calibration that lets a handheld scanner estimate protein from light, and compared it with predicting protein from the plants DNA. The scanner gave accurate, low-cost protein screening from only about 40-60 lab tests, while DNA-based prediction remains suited to guiding parent selection. Used together, these tools offer breeders a practical path to develop high-protein white lupin. Core ideasO_LIHandheld NIRS provides screening-grade prediction of white lupin seed crude protein. C_LIO_LISpectra carried more usable protein signal than markers by measuring seed chemistry directly. C_LIO_LINIRS and genomic prediction serve different stages of a white lupin breeding program. C_LIO_LIAbout 40 to 60 reference assays sufficed to calibrate NIRS to near-full accuracy. C_LI

BackgroundThe capitulum of Asteraceae is a highly specialized inflorescence whose formation requires the coordinated regulation of multiple developmental processes, including floral organ identity and floral meristem determinacy. The LEAFY (LFY)-UNUSUAL FLORAL ORGANS (UFO) regulatory module is known to play an important role in flower development; however, naturally occurring mutations affecting this pathway have not been genetically characterized in gerbera (Gerbera hybrida). ResultsIn this study, we characterized a novel gerbera mutant identified during a commercial crossing program and named it marimo based on its green, spherical capitulum. Morphological observations revealed the repeated formation of secondary and tertiary floret-like organs within primary floret-like organs. Scanning electron microscopy showed that the epidermal structure of the green organs in marimo was similar to that of wild-type involucral bracts. RNA sequencing identified numerous differentially expressed genes between marimo and the wild type, and network and Gene Ontology analyses highlighted gene groups associated with flower development, reproductive organ differentiation, and tissue structure formation. RNA-seq analysis showed increased expression of LFY and reduced expression of GGLO1, a PISTILLATA/GLOBOSA-like B-class MADS-box gene, in the marimo mutant. RT-qPCR analysis of a segregating population further confirmed reduced GGLO1 expression in marimo-type individuals. In addition, a single-nucleotide deletion was identified in the coding region of UFO. This deletion was predicted to cause a frameshift and a premature stop codon. In selfed progeny of No. 251, the UFO genotype was fully associated with capitulum phenotype, and only individuals homozygous for the mutant allele exhibited the marimo phenotype. ConclusionsThese results indicate that the naturally occurring frameshift mutation in UFO is the strongest candidate variant underlying the marimo phenotype. RNA-seq analysis showed increased LFY expression and markedly reduced GGLO1 expression in the marimo mutant. Reduced activity of the LFY-UFO regulatory module may therefore have altered the expression of GGLO1 and other floral organ development-related genes despite the continued expression of LFY. These changes may have affected both floral organ identity and floral meristem determinacy, resulting in the formation of green involucral bract-like organs and the repeated production of floret-like organs. The marimo mutant provides a useful genetic resource for investigating capitulum development in Asteraceae and may also serve as breeding material for introducing novel ornamental traits into gerbera.

Photosynthesis is among the most consequential yet genetically complex traits in crop plants, and translating its natural variation into actionable genomic targets remains a central challenge for breeding climate-resilient varieties. To start addressing this, researchers are generating increasingly large, multi-environment field photosynthesis datasets. Yet, these data have been structurally under-analysed since their inception. Here we report the outcomes of the first dedicated hackathon focused on computational mining of such field data held in Accra, Ghana, in March 2026. Bringing together data scientists, plant physiologists, geneticists, and breeders from Europe and Africa, these interdisciplinary teams used photosynthetic data collected with hand-held fluorometers to genome-wide marker data across four crop species: cowpea (Vigna unguiculata), barley (Hordeum vulgare), common bean (Phaseolus vulgaris), and potato (Solanum tuberosum). Despite using different species and methods, independent teams identified the same three key findings. First, mechanism-informed feature engineering and dynamic modelling recover genetic signals that are not detected or discarded in standard analysis pipelines, resulting in traits with improved heritability and meaningful associations with yield. Secondly, machine learning methods proved effective at uncovering genetic associations, with temporally resolved features substantially outperforming single time-point measurements. Third, raw chlorophyll fluorescence and absorbance traces consistently contained more information and predictive power than the extracted parameters currently used. A defining feature of this event was having experimentalists and data scientists working together, enabling AI approaches to be grounded in domain knowledge and biological mechanisms rather than relying on data alone.

Understanding the genetic diversity and population structure of breeding materials is essential for developing stress-resilient cultivars. In tropical maize, where drought and low soil nitrogen (low N) severely limit productivity, continuous development of tolerant varieties remains a priority. This study assessed the genetic diversity and population structure of 250 doubled haploid lines (DHLs) derived from five drought- and low N-tolerant tropical populations. Genotyping was performed using mid-density DArTseq markers, yielding 3,305 high-quality SNPs for analysis. Results revealed a moderate level of diversity among the DHLs, with an average genetic distance of 0.39, a polymorphism information content (PIC) of 0.33, and a minor allele frequency (MAF) of 0.29. These values reflect substantial allelic variation, important for identifying complementary parental combinations in hybrid development. Discriminant analysis of principal components (DAPC) grouped the DHLs into five distinct clusters, largely corresponding to their source populations, although some admixture was observed. This indicates that while the genetic backgrounds of the source populations were mostly retained, recombination introduced useful variation. Overall, the clear population structure and high diversity observed among these DHLs provide a strong genetic foundation for future maize improvement. These lines represent valuable resources for heterotic group formation, hybrid development, and recurrent selection schemes aimed at enhancing drought and low nitrogen tolerance in tropical maize.

The rejection of self-incompatible (SI) Brassica pollen is mediated by three signaling branches that function in parallel in the stigma. The recognition of SI pollen by the stigma S-Receptor Kinase (SRK) results in activation of the ARM-Repeat-Containing 1 E3 ubiquitin ligase (ARC1) which mediates the degradation of compatibility factors, the FERONIA (FER) and ANJEA (ANJ) receptor kinases that induces ROS accumulation to inhibitory levels and the M Locus Protein Kinase (MLPK) which may also be connected to ROS production. Arabidopsis self-incompatibility is regulated by SRK as well, but the signaling events downstream of SRK following SI pollen perception are less well-understood. In this study, we evaluated the requirements of FER, ANJ and HERCULES RECEPTOR KINASE 1 (HERK1) for SI pollen rejection in the transgenic Arabidopsis thaliana SI-Col-0{psi} srka-1 line. The{psi} srka-1 T-DNA disrupting the expression of the endogenous{psi} SRKA gene was crossed into SI-Col-0 to prevent any potential SRK transgene silencing. T-DNA mutants for FER and ANJ/HERK1 were then crossed into the SI-Col-0{psi} srka-1 line. Using standard assays for pollen-stigma interactions, the SI phenotypes were assessed for the SI-Col-0 fer, SI-Col-0 anj-1 and SI-Col-0 anj-1 herk1-1 lines. Our results presented here indicated that FER and ANJ are not required in the stigma for Arabidopsis SI pollen rejection, further providing evidence for a divergence in the SI downstream signaling pathway in Arabidopsis.

Cassava (Manihot esculenta Crantz) is a major staple crop across tropical and subtropical regions. Despite advances in genomic selection, delayed, non-flowering, and asynchronous flowering remain key bottlenecks in breeding programs. To better understand the molecular basis of flowering-time variation, we performed RNA sequencing across three genotypes with contrasting flowering phenotypes (early, late, and non-flowering) sampled at three developmental stages under contrasting light regimes in field conditions (natural light and three-hour night-break with white light). Comparative transcriptomic analysis revealed distinct gene expression patterns associated with flowering responses. Genotype comparisons with no light supplementation revealed stage-specific enrichment of biological processes. Light supplementation was associated with changes in the expression of key components of photoperiodic and circadian regulation, as well as pathways involved in flowering-time integration and hormone and sugar-related signaling. These findings suggest that coordinated changes across multiple biological pathways regulate flowering behavior in cassava. The candidate genes and expression patterns reported provide a foundation for functional studies and advance our understanding of molecular mechanisms governing flowering-time regulation in cassava.

Volatile organic compounds (VOCs) define the distinctive aroma of cannabis and critically influence consumer preference, cultivar authentication, and breeding programs. However, systematic characterization of VOC diversity across commercial drug-type cultivars remains limited. This study presents a comprehensive volatilomics-based phenotypic characterization of 165 commercial drug-type cannabis accessions using gas chromatography with flame ionization detection and mass spectrometry (GC-FID/MS). We identified 61 high-confidence VOCs assigned to three biosynthetic classes: terpenoids (n = 45), fatty acid-derived volatiles (n = 12) and amino acid-derived volatiles (n = 4), resolved into 12 subclasses. Analysis of variance revealed highly significant among-accession differences for all compounds (p < 0.001; 2 = 0.67-0.97), with repeatability estimates averaging 0.81 (range 0.50-0.95). Unsupervised clustering partitioned accessions into three distinct chemotypes (n = 90, 53, and 22), supported by principal component and t-SNE analyses. Machine learning-based feature selection identified a consensus panel of 12 discriminative compounds (camphene, -fenchene, sabinene, -terpinene, ({+/-})-limonene, -humulene, linalool, endo-fenchol, {Delta}3-carene, -thujene, {gamma}-terpinene and -phellandrene) that recovered the chemotype assignment of 32 of 33 held-out accessions. Estimated odor-activity screening ranked prenylthiol, -pinene, ({+/-})-limonene, linalool and myrcene highest among the odor-active compounds. All three chemotypes shared a prenylthiol-dominated core (67-77% of summed OAV) and were distinguished by the extent and nature of terpenoid modulation of that core: minimally modulated (Cluster ZERO), citrus-floral modulated (Cluster ONE) and pine-terpenic modulated (Cluster TWO). These findings indicate that volatile diversity in this panel can be summarized by three reproducible chemotypes, providing a quantitative basis for accession characterization and a foundation for future breeding and quality-assessment studies.

Adventitious root formation (ARF) is a critical trait for the cost-effective propagation of grapevines in commercial nurseries. Poor rooting ability can limit the use and adoption of new rootstocks derived from underutilized Vitis species, constraining breeding efforts largely to the traditional trio: Vitis riparia, V. rupestris, and V. berlandieri. Despite its agronomic relevance, the genetic basis of ARF remains poorly characterized across the broader Vitis genus. In this study, we evaluated 308 accessions representing 18 Vitis species over three growing seasons, quantifying rooting performance at two developmental stages, callus-stage and post-transplant, alongside root biomass, cutting weight, and a derived transplant-response index. We observed extensive phenotypic variation both within and across species, and species rankings depended on the trait considered. V. riparia, V. rupestris and V. californica ranked among the top five species for all four rooting traits, whereas V. cinerea and V. candicans ranked among the lowest for root weight and post-transplant rooting. V. arizonica and V. acerifolia rooted well at the callus stage but were intermediate after transplanting, and V. berlandieri was among the weakest at the callus stage yet intermediate for post-transplant rooting. Repeatability was moderate to high for root weight (0.74) and callus-stage rooting (0.66), and lower for post-transplant rooting (0.47), reflecting both genetic control and season-to-season variation. Between-species differences accounted for 68% of the genetic variance in callus-stage rooting but only 10% in cutting weight. Rooting was associated with the climate of each accession's wild site of origin: after removing differences among species, accessions originating from sites with lower dry-season precipitation rooted better and produced more root biomass. Genome-wide association analysis using 3.4 million SNPs identified 54 significant SNPs resolving into 18 independent loci across four traits, with root weight contributing 12 of them. Candidate genes in linkage with these loci include a mitogen-activated protein kinase, a SCARECROW-LIKE GRAS transcription factor, PASTICCINO1, expansin A1, an AP2/ERF-RAV1 transcription factor, a tandem array of caffeoyl-CoA O-methyltransferases, and several sugar, peptide and nitrate transporters, implicating auxin-linked cell proliferation, cell wall and lignin remodeling, and solute transport. Genomic and phenomic prediction models yielded moderate accuracies across traits and seasons; up to r = 0.67 for post-transplant rooting within a season and r = 0.65 for previously unevaluated accessions. Moreover, the integration of spectral and genotypic data further improved predictive performance. Prediction accuracy was essentially flat between 5,000 and 50,000 markers. This study establishes a foundational framework for the genetic improvement of grapevine rootstocks, promoting broader use of resilient, high-performing, and clonally-propagable germplasm in viticulture.

Although the biosynthetic pathways of benzylisoquinoline alkaloids (BIAs) have been extensively investigated in several plant species, their transcriptional regulatory mechanisms remain only partially understood. Jasmonate (JA)-responsive group IX APETALA2/Ethylene Responsive Factor (AP2/ERF) transcription factors (TFs) are well-known regulators of specialized plant metabolism, including the biosynthesis of various alkaloids. However, their specific roles in BIA biosynthesis remain largely elusive. Here, we isolated five novel group IX AP2/ERF TFs, designated Benzylisoquinoline alkaloid Jasmonate-responsive AP2/ERF (BJE1-5), from Coptis japonica. Phylogenetic analysis revealed that Benzylisoquinoline alkaloid Jasmonate-responsive AP2/ERF (BJE) proteins belong to subclades distinct from group IXa, which contains well-known AP2/ERF TFs involved in alkaloid biosynthesis. Transient expression analyses in C. japonica protoplasts demonstrated that certain BJEs, particularly CjBJE3 and CjBJE5, positively regulated BIA biosynthetic genes through a mutual regulatory network among BJE members. Moreover, CjBJE3 expression was regulated by CjbHLH1, a unique-type basic helix-loop-helix (bHLH) TF specific to BIA-producing plants. Furthermore, heterologous expression of CjBJE3 and CjBJE5 in cultured Eschscholzia californica cells significantly enhanced the overall BIA production, particularly by increasing end-product benzophenanthridine BIAs, highlighting several uncharacterized biosynthetic genes clustered in the genome. Our findings suggest that BIA-producing species have developed a specific regulatory network comprised of CjbHLH1 and BJE TFs, providing valuable clues for identifying novel biosynthetic enzymes.