The Plant Journal

Biolistic transformation is a versatile tool in plant science, yet high equipment costs and tissue damage from high-pressure gas remain significant barriers. Building on our previously developed "TSGMAC", a low-cost, helium-free biolistic system, we report three major advancements to enhance its throughput, delivery quality, and quantitative capability. First, a "guide barrel" assembled from commercial DIY fittings was developed; it effectively eliminates physical tissue damage and ensures uniform particle distribution, even in soft tissues like bok choy (Brassica rapa subsp. chinensis). Second, a rapid gene expression platform using PCR products was characterized. Results demonstrate that linear DNA constructs are efficiently circularized via non-homologous end joining (NHEJ) in plant cells, and protein expression is robust regardless of the relative positions of the promoter, coding sequence, and terminator. This system bypasses time-consuming cloning. Third, a cost-effective, highly sensitive dual-luciferase assay system utilizing teal Luc (teLuc) and inexpensive firefly luciferase (FLuc) inhibitors was established. This integrated workflow enables rapid, quantitative molecular biology using supermarket-obtained materials and standard PCR reagents. Our findings provide a practical foundation for plant scientists, synergistically accelerating gene functional analysis and genetic tool development.

Pangenome-level gene family identification often applies sequence similarity clustering without phylogenetic or synteny information, which risks biologically misleading evolutionary inferences. Using five transcription factor families (bHLH, MYB, NAC, WRKY, MADS-box) across 401 rice pangenome accessions, we compared clustering strategies: OrthoFinder alone, cd-hit alone, MMseqs2 alone, and OrthoFinder-informed refinement by cd-hit or MMseqs2. Methods solely based on sequence similarity merged distinct orthogroups and generated fewer orthogroups than approaches incorporating graph-based orthology. Conflicting cluster assignments, measured against OrthoFinder, varied strongly among families, from approximately 14% in MADS-box to approximately 57% in MYB, and were associated with protein length differences. Core, shell, and cloud gene classifications shifted substantially depending on the method, especially in MYB, NAC, and WRKY families. Critically, Ka/Ks distributions for core genes were highly method-sensitive, with orthology-aware methods yielding more convergent and less variable estimates of selective pressure, whereas noncore gene estimates remained robust. These findings demonstrate that neglecting graph-based orthogroup inference inflates methodological artifacts. We recommend a two-step strategy: initial graph-based orthogroup delineation followed by sequence similarity refinement to balance evolutionary accuracy and resolution in pangenome-scale gene family studies.

In nature, plants are subjected to multiple environmental stress factors simultaneously or sequentially. Recent studies revealed that when three or more stress factors impact a plant simultaneously (termed multifactorial stress combination; MFSC), plant survival declines, even if the intensity of each individual stress involved in the MFSC is low. We previously identified RAP2.3 as a key transcription factor (TF) required for Arabidopsis thaliana survival, specifically under a MFSC of salt+excess light+heat stress (i.e., S+EL+HS). Here we report that RAP2.3 is required for the expression of SIGMA3, a nuclear-encoded factor that directs plastid RNA polymerase to specific plastid promoters, and MYB51, a key stress response TF involved in glucosinolate metabolism and oxidative stress responses, specifically during a MFSC of S+EL+HS. Like rap2.3 mutants, myb51 and sig3 mutants display significantly low survival rate specifically under the MFSC of S+EL+HS. Based on MYB51 gene regulatory network analysis and characterization of jasmonic acid (JA) mutants, we further reveal that suppression of JA signaling could play an important role in promoting plant survival under conditions of S+EL+HS. Our findings uncover an additional layer of the response of plants to MFSC, as well as identify potential targets for breeding crops with enhanced tolerance to climate change.

Grain legumes such as pea (Pisum sativum L.) accumulate large amounts of seed storage proteins without nitrogen fertilization due to their symbiosis with nitrogen-fixing bacteria, making them a key source of plant-based proteins. Seed growth and the accumulation of seed storage proteins are tightly regulated by complex gene networks; however, the mechanisms governing these processes in pea remain poorly understood. In this study, we generated a comprehensive seed expression atlas covering six developmental stages in pea (cv Cameor), including the key transition stage from embryogenesis to early seed filling, providing a detailed temporal resolution of transcriptional dynamics throughout seed development in this species. Co-expression network analysis highlighted several candidate transcription factors potentially involved in the transition towards seed filling. Among them, we characterized the seed-specific NF-YB transcription factor PsLEC1-like (PsL1L), the major LEC1-type factor expressed during early pea seed development. Functional analyses using TILLING mutants demonstrated that loss of PsL1L function reduces seed size and seed nitrogen content and impairs early embryo growth from the end of embryogenesis. Finally, we show that the expression of the B3-domain transcription factor PsFUS3, but not that of PsLEC2 or PsABI3, is reduced in the loss-of-function l1l mutant, suggesting that PsL1L acts upstream of PsFUS3 to control seed size.

Understanding plant growth dynamics requires imaging across day-and-night cycles to quantify growth, movement and development in the aerial plant body and to capture the rhythmic nature of these processes. This requires imaging in light during the day and in darkness at night without perturbing plant physiology. Nighttime imaging has typically depended on infrared (IR) illumination, producing monochrome datasets that require specialised hardware and separate analysis pipelines when combined with daytime RGB imaging. Here, we evaluated very low-intensity green (dimG) illumination from standard LEDs as a practical alternative for colour-consistent nighttime imaging and assessed its physiological impact in Arabidopsis thaliana and Lactuca sativa (lettuce). We show that high resolution colour images can be obtained under dimG using low- cost cameras, with sufficient consistency between full-spectrum and dimG images to allow direct comparison and unified image analysis. We show that very low-fluence green light (<0.5 mol m-2 s-1) does not sustain circadian oscillations of gene activity under continuous exposure and does not perturb rhythms when applied during the dark phase of diel cycles. DimG imaging enabled accurate detection of diel leaf movement profiles in Arabidopsis circadian mutants, revealing genotype-specific phase differences under varying photoperiods. In lettuce, dimG pulses and continuous dimG enabled accurate quantification of diel leaf movement without affecting growth, stomatal opening, electron transport rate or chlorophyll content. Motion profiles under continuous dimG mirrored those under darkness. Our findings establish dim green illumination as a cost-effective solution for night-time imaging, simplifying phenotyping workflows with minimal impact on physiology.

Chilling stress induces photosystem I (PSI) photoinhibition in chilling-sensitive cucumber, in which insufficient activity of the chloroplast NADH dehydrogenase-like complex (NDH) leads to PSI over-reduction and damage. However, it is not yet clear whether these findings can be generalized to other species or what the molecular mechanism underlying impaired NDH function is. In this study, we first examined whether NDH is essential for PSI protection under chilling stress using an NDH-deficient rice mutant. Compared with wild-type plants, the NDH-deficient mutant exhibited enhanced PSI over-reduction and pronounced PSI photoinhibition under chilling stress. In contrast, rice plants expressing flavodiiron protein (FLV), which functions as an alternative electron acceptor downstream of PSI, did not exhibit PSI photoinhibition under chilling stress, demonstrating that electron sink capacity of NDH is important for PSI protection under chilling stress. Furthermore, analysis of the factors responsible for NDH dysfunction under chilling stress in cucumber revealed that chilling stress destabilizes the PSI-NDH supercomplex, leading to NDH monomerization and a consequent loss of NDH activity. This NDH monomerization is likely attributable to chilling-induced damage to the light-harvesting complex Lhca, which mediates the association between PSI and NDH. Together, these results indicate that NDH is essential for protecting PSI from photoinhibition under chilling stress in both rice and cucumber, and that chilling-induced destabilization of the PSI-NDH supercomplex represents a key molecular mechanism underlying PSI over-reduction and photoinhibition.

Accurate quantification of leaf lesion severity is essential for plant disease research and phenotyping but is often limited by subjective visual scoring and time-intensive manual image analysis. We present LIME, a fully automated, open-source image analysis pipeline for high-throughput quantification of leaf lesions from disease assay images. LIME integrates zero-shot leaf segmentation using the Segment Anything Model with a convolutional neural network for lesion area estimation. Applied to Arabidopsis thaliana leaves infected with Sclerotinia sclerotiorum, the proposed approach achieved a mean absolute percentage error of 12.9%, comparable to observed intrarater variability in manual scoring. Stratified evaluation across lesion-size groups demonstrated consistent prediction accuracy for small, intermediate, and large lesions, and comparative analysis showed that the deep learning-based model substantially outperformed color-based baseline methods. Under GPU-accelerated execution, LIME processed complete assays containing approximately 200 leaves in 15 minutes, representing an approximate 13-fold reduction in processing time relative to manual annotation. Together, these results indicate that LIME enables objective, reproducible, and scalable quantification of leaf lesion severity in standardized plant pathology assays. The pipeline is released as an open-source tool to support quantitative phenotyping studies.

Functional validation of genetic components in plants often requires cloning them separately into both plant and bacterial expression vectors, a process that is both time-consuming and laborious. This study aimed to simplify this workflow by developing plant-bacteria dual-host promoter systems that drive high-level constitutive expression in both environments. To achieve this, two variants of the chloramphenicol acetyltransferase promoter (PCAT), a bacterial {sigma} factor-dependent promoter, were integrated into the cauliflower mosaic virus 35S promoter (P35S), and their performance was evaluated using a hygromycin phosphotransferase (HPT)-GFP fusion reporter. One of these variants, PCAT1, conferred hygromycin resistance to Escherichia coli (DH5 and BL21 (DE3)) and maintained high-level expression comparable to the original P35S in onion epidermal cells. A hybrid P35S enhancer-PNOS system also conferred hygromycin resistance to E. coli, but its activity in inducing GFP signals in onion cells remained lower than that of P35S. Due to its compact size (89 bp) and efficiency, PCAT1 can serve as a module for converting standard plant vectors into dual-host systems, accelerating gene characterization and the development of new gene-based tools.

Norway spruce (Picea abies) responds to attacks by the spruce bark beetle (Ips typographus) through the rapid activation of local defense mechanisms, but field studies can be difficult to standardize due to variable attack pressure and environmental heterogeneity. Here, we developed a phytotron-based assay that mimics early beetle-associated stress using insect-derived protein extracts, enabling reproducible molecular analyses under controlled conditions. Ten-week-old spruce seedlings were stem-treated with mock buffer or beetle protein extracts, followed by transcriptomic analyses of stem tissues and targeted metabolomic profiling of needles at 2 and 48 h post-inoculation. RT-qPCR analysis revealed rapid transcriptional activation of signaling and defense genes in Norway spruce, with NP-40-based protein extracts producing the most consistent early response. RNA-seq analysis revealed transcriptional dynamics, with 488 differentially expressed genes detected at 2 h and 84 at 48 h post-inoculation relative to mock-treated controls. Early responses at 2 h were characterized by activation of genes associated with immune perception and signal transduction. By 48 h, the response shifted toward accumulation of transcripts encoding defense proteins such as chitinases, defensins, proteinase inhibitors, and pathogenesis-related (PR) proteins. Importantly, a substantial proportion of differentially expressed genes overlapped with those previously identified in mature Norway spruce trees during pioneer bark beetle attack under field conditions, supporting the biological relevance of the assay. In contrast, targeted analyses of secondary metabolites performed in needle tissue revealed limited systemic changes across time points, suggesting that early induced defenses may remain largely localized to the stem. Together, these results demonstrate that beetle-derived proteins trigger a rapid and temporally structured defense response in Norway spruce seedlings and establish a reproducible elicitor-based platform for dissecting conifer immune responses and screening spruce genotypes for bark beetle resistance. HighlightBark beetle protein elicitors trigger temporally structured immune responses in Norway spruce seedlings that overlap with responses observed in mature trees, with rapid immune signaling at 2 h followed by defense protein accumulation at 48 h.

The red/far-red sensing photoreceptor phytochrome B (phyB) governs multifaceted plant development and responses to light and temperature stimuli. PhyB photoconversion between red-absorbing, inactive Pr and far red-absorbing, active Pfr states, imparted by its covalently bound bilin chromophore, enables rapid switching and plasticity of phyB signaling activities. The phyBY276H variant (YHB) is photochemically inert but adopts a constitutively active Pfr-like structure regardless of light conditions, which becomes a versatile model to dissect phyB signaling mechanisms. Here, we conducted a large-scale EMS mutagenesis screen on YHB-expressing transgenic lines, mining intragenic suppressor mutations that would unveil critical residues for phyB structure-function relationships. Comparative analyses of 26 nonsense variants suggested modular organization of phyB overall structure and dispensability of the C-terminal HKRD domain for phyB signaling. Amongst fourteen novel and nine known loss-of-function missense variants identified herein, G284E was of particular interest for its fully suppressed constitutive activity in darkness and its restored photochemistry and light responsiveness. The G284E mutation was further tested to also nullify another constitutively active phyBY303V allele by eliminating chromophore attachment. P309L was the sole variant identified which fully suppressed YHB in both dark and light conditions. C402Y profoundly elicited YHB protein instability. Three variants G118R, C402Y and G538D markedly reduced chromophorylation levels of YHB. Although the chromophore binding site variant C357Y was a strong loss-of-function allele, it retained residual signaling activity with respect to PIF3 protein turnover in dark-grown seedlings, presumably due to its ability to noncovalently bind chromophore. Two tandem prolines (P799, P800) proved critical to YHB structural integrity/stability as well as signaling activity. In summary, these diverse variants shed new insights into multiple levels by which the YHB (and thereby phyB) signaling is initiated, tuned, and disseminated.

Salicylic acid (SA), a central hormone in plant immunity, is biosynthesized via a recently elucidated phenylalanine-derived pathway in most seed plants. This pathway requires benzyl alcohol as a key substrate for the formation of the SA precursor benzyl benzoate. However, how benzyl alcohol is produced in plants was unclear. Here, we identify a two-step conversion of benzoyl-CoA to benzyl alcohol via benzaldehyde in Nicotiana (N.) benthamiana. From a forward genetic screen for SA-deficient mutants, the and {beta} subunits of heterodimeric benzaldehyde synthase (BalS) involved in the conversion of benzoyl-CoA to benzaldehyde were found to be required for SA biosynthesis in N. benthamiana. Further reverse genetic analysis revealed that the NADPH-dependent benzaldehyde reductase (BalR1) acts downstream of BalS to convert benzaldehyde to benzyl alcohol. Interestingly, OsBalR1, but not OsBalS or OsBalS{beta}, is required for maintaining high basal SA levels in rice, suggesting the presence of redundant benzoyl-CoA-reducing activities or alternative biosynthesis routes for benzyl alcohol production. Together, this work defines the missing enzymatic steps in phenylalanine-derived SA pathway and provides insights into the evolutionary diversification of SA production strategies in plants.

Cytokinin (CK) N-glucosides are the most abundant CK metabolites in Arabidopsis and most angiosperms, yet their role in cytokinin activity and response is unclear. Here, we examined metabolomic, transcriptomic, and proteomic profiles of seven CK N-glucoside conjugates in detached Arabidopsis leaves across a 144-hour dark-induced senescence (DIS) timecourse. All tested N-glucosides were found to undergo a slow conversion to their corresponding base forms at position-dependent rates, with N9-glucosides releasing base faster than their corresponding N7-glucosides. Conversion during DIS was strictly isoform-specific and not accompanied by coordinated induction of CK biosynthesis genes, arguing against de novo synthesis as the source of accumulated base. Despite progressive base accumulation, N-glucoside-treated leaves produced substantially fewer Differentially Expressed Genes than direct base application at comparable base concentrations, revealing a disconnect between hormone presence and transcriptional output. Unbiased model comparison identified the base:glucoside ratio as a stronger predictor of CK-Two Component Signaling (TCS) gene expression than absolute base concentration, though modulated by base-type-specific receptor affinities. Early proteomic profiling further revealed a coordinated response shared across N-glucosides but largely absent from base treatments. Together, these findings support that CK N-glucosides as kinetically slow, position-dependent reservoirs whose presence in abundance modulate activation of CK-TCS elicited by bioactive forms. HighlightsPhysiology, metabolomic, transcriptomic, and proteomic findings here support CK N-glucosides as kinetically slow, position-dependent reservoirs whose presence in abundance modulate activation of CK-TCS elicited by bioactive forms.

Glucose-6-phosphate dehydrogenase (G6PDH) catalyzes the first step of the oxidative pentose phosphate pathway, generating NADPH to sustain redox metabolism and signaling. However, whether individual G6PDH isoforms directly regulate oxidative stress signaling remains unclear. To determine the contribution of the different Arabidopsis G6PDH isoforms to oxidative stress signaling, we introduced single T-DNA mutants into the catalase-deficient cat2 background, a genetic system in which intracellular H2O2 production activates salicylic acid (SA)-dependent cell death and defense pathways. Interestingly, impairment of cytosolic, but not chloroplastic G6PDH activity suppressed cat2-triggered phenotypes, with loss of G6PD5 function fully abolishing lesion formation. The cat2 g6pd5 double mutant phenocopied the SA biosynthesis-deficient mutant cat2 sid2 and showed reversion of defense responses as well as metabolomic and transcriptomic profiles to the wild-type state. Strikingly, despite the suppression of SA-dependent lesions, loss of G6PD5 activity does not appear to reduce stress intensity. On the contrary, cat2 g6pd5 plants exhibit increased glutathione synthesis and oxidation, elevated expression of oxidative stress marker genes, and enhanced accumulation of reactive nitrogen species relative to cat2. Protein-protein interaction analyses revealed that G6PD5 associates with several redox and defense-related proteins. In particular, we confirmed a physical interaction between G6PD5 and thioredoxin h5, a key component of redox-dependent SA signaling. However, analysis of cat2 trxh5 and cat2 npr1 lines indicated that this interaction alone cannot explain the G6PD5-dependent control of SA responses. Our work reveals that cytosolic G6PD5 integrates redox metabolism with immune signaling to control plant responses to oxidative stress.

Accurate and reproducible assessment of foliar disease severity is essential for evaluating the performance of heterogeneous plant communities and understanding host-pathogen interactions. However, traditional visual scoring methods remain subjective, with limited precision, and difficult to scale in large phenotyping experiments. Here, we present a semi-automated image analysis workflow designed to quantify multiple foliar disease symptoms simultaneously on wheat flag leaves sampled from varietal mixtures. The workflow combines three methodological components: (i) a standardized protocol for leaf sampling and imaging, (ii) supervised machine learning segmentation using Random Forest implemented in Ilastik to classify multiple symptoms (powdery mildew and yellow rust), and (iii) a graphical user interface facilitating pipeline deployment by non-specialist operators. To evaluate the influence of image representation on classification performance, four color spaces (RGB, HSV, HLS, LAB) were systematically compared. The approach was validated using images of durum wheat flag leaves collected from a field experiment assessing eight-way varietal mixtures under natural fungal pressure. Cross-validation against manually annotated images demonstrated high segmentation accuracy across all symptom. Comparison among color spaces revealed only minor differences in performance. Overall, this workflow offers a cost-effective, annotation-efficient and reproducible alternative to deep learning approaches, leveraging open-source and actively maintained tools while requiring limited training data and enabling objective, reproducible and scalable disease phenotyping.

Potato crop is highly vulnerable to abiotic stresses like salinity and low nutrient availability. Rapid identification of stress-resilient genotypes is therefore essential for breeding, yet conventional phenotyping is often slow, space-demanding and expensive. We present LOCOPOTS -- a LOw-COst high-throughput screening platform for in vitro POTatoes under abiotic Stress -- which combines individual in vitro plant culture, low-cost RGB imaging and machine-learning-based automatic segmentation using a trained model of a convolutional neural network, based on U-Net architecture. LOCOPOTS enabled the automated extraction of growth, colour, and vegetation-index traits and demonstrated robust performance across independent phenotyping rounds. We screened 30 potato varieties under control, low-nutrient and saltinity conditions, identifying contrasting growth and physiological responses. Integrated traits such as final area and height, Area_AUC and height_AUC, together with GLI, Chol, cive and chlorophyll fluorescence parameters, discriminated genotype performance under stress. Metabolic profiling further revealed genotype-specific reprogramming in carbon and nitrogen metabolism under low nutrition and salt stress, including changes in fructose, myo-inositol, {beta}-aminobutyric acid, {gamma}-aminobutyric acid, proline, and certain polyamines, identifying them as specific chemical biomarkers of plant stress responses. LOCOPOTS provides a scalable, affordable and space-efficient platform for early screening of potato genetic diversity and identification of candidate traits associated with stress resilience.

Plant receptor-like kinases (RLKs) are involved in diverse processes, ranging from growth and reproduction to interactions with microbes. Variation in the extracellular domains delineates several RLKs subfamilies, including the malectin-like domain leucine-rich repeat receptor-like kinases (MLD-LRR-RLKs). Symbiosis Receptor-like Kinase (SymRK) is the prototypical member of MLD-LRR-RLKs and is required for microbial accommodation in host roots during root endosymbiosis. Yet, comparative phylogenetic analysis of SymRK orthologs in the broader context of MLD-LRR-RLK subfamily evolution remains limited. In this study, we examined the inventory, phylogeny and clade-specific evolutionary and transcriptional characteristics of this receptor group. SymRK and its closest homologs are present in most land plant lineages and group into four major clades and six additional species-specific clades. These clades can be distinguished by their evolutionary characteristics as either conserved with reduced gene copy number changes (including SymRK) or expanded and diversified, as observed in clade IV. Clade IV dynamics are largely driven by tandem gene duplications, which often arise within gene clusters. We further analysed the evolutionary characteristics of MLD-LRR-RLKs at the population level in Arabidopsis thaliana accessions. We found that some genes are conserved across accessions and are therefore likely to be functionally important, whereas a subset of genes, often located within tandem clusters, are highly diverse and likely contribute to accession-specific adaptations. Finally, most MLD-LRR-RLKs in the A. thaliana Col-0 accession are expressed in roots and respond broadly to biotic stimuli at the transcriptional level. Notably, clustered genes frequently exhibited divergent expression profiles, suggesting transcriptional diversification. Together, we revealed two contrasting evolutionary characteristics among members of the MLD-LRR-RLK subfamily, potentially associated with their functions in plants.

Prenylated isoflavonoids are widely distributed specialized metabolites within the Fabaceae and contribute to various characteristic biological activities for both plants and humans. Several aromatic prenyltransferases (PTs) have been identified in Glycyrrhiza species, which are the most widely consumed crude drugs in traditional Chinese medicine. However, these enzymes do not sufficiently explain the structural diversity of prenylated flavonoids produced in the Glycyrrhiza genus. To identify additional novel PTs, we used elicited cultured Glycyrrhiza glabra roots as source material, in which elicitor treatment of cultured roots increased the accumulation of multiple prenylated flavonoids. To identify the responsible enzyme, PT candidates were screened using G. uralensis transcriptomes, currently the sole publicly available transcriptomic resource within the genus, and a homolog designated GgBSPT1 (BSPT; a broad-substrate prenyltransferase) was subsequently isolated from elicited cultured G. glabra roots. GgBSPT1 differed from previously identified Glycyrrhiza PTs in both amino acid sequence and enzymatic properties. GgBSPT1 catalyzed 3'-prenylation of isoliquiritigenin and 6-prenylation of five flavonoids, i.e., this PT displayed broad substrate acceptance across 20 distinct flavonoid structures. Overall, elicited cultured G. glabra roots enabled the identification of a previously unrecognized PT that is functionally distinct from earlier reported Glycyrrhiza PTs. This study provides a new insight into the metabolic plasticity of Glycyrrhiza species and expands the enzymatic toolkit for future metabolic engineering of prenylated phytochemicals by the unusually broad substrate specificity of GgBSPT1. Main conclusionUsing cultured Glycyrrhiza glabra roots, we identified a new prenyltransferase involved in the formation of a variety of flavonoids, thereby revealing novel prenylated isoflavonoid pathways in licorice.

The ability to insert, delete, or modify genetic information is crucial for mechanistic studies and biotechnological applications. However, efficient genetic transformation remains a major bottleneck for research in maize and many other crops. Here, we report an optimized Agrobacterium-mediated transformation platform based on systematic reconstruction of tissue culture handling in the maize inbred line A188. Refinement of callus induction, selection, and regeneration substantially improved recovery of transgenic plantlets. To distinguish independent T-DNA insertion events, we developed TAFLP (T-DNA Amplified Fragment Length Polymorphism), a simple and inexpensive assay that amplifies T-DNA flanking sequences and can be performed using standard laboratory equipment. Our enhanced transformation pipeline was also applicable to the inbred line B104 as well as to hygromycin and G418 selection systems, demonstrating broad utility of our method. We validated the platform for CRISPR/Cas9 mutagenesis and reporter line generation. Using this approach, we isolated new loss-of-function alleles of MAC1 and ACOZ1 and generated reporter lines for analysis of meiotic protein dynamics. Together, these results provide a broadly applicable framework for improving maize transformation efficiency and recovering independent transgenic and genome-edited events.

RNA-seq datasets from medicinal yews are crucial for studying paclitaxel biosynthesis. However, cross-study data analyses are hindered by pronounced batch effects. Here, we compiled 45 RNA-seq samples from three studies across four tissues (bark, leaf, root, stem) and assessed 35 preprocessing pipelines combining six normalization strategies with five batch-effect correction approaches. Unsupervised clustering (HCA, k-means, Grade-of-Membership), evaluated using Jaccard and Adjusted Rand indices, revealed significant variability in batch effect removal. Supervised classification of tissue and project labels (Random Forest and linear/radial SVM) demonstrated improved accuracy in tissue type prediction, highlighting the effectiveness of correction methods. The processed data facilitated the identification of 189 putative ABC transporters across samples, six of which showing a strong correlation to the gene encoding 10-deacetylbaccatin-III-10{beta}-O-acetyltransferase, a key biosynthetic enzyme in the taxol pathway. High expression levels in leaf and bark further support their role in taxane intermediates trafficking in taxol biosynthesis. Structural analysis and molecular docking further supported the selection of these candidates, and the agreement between transcriptomic ranking and docking-based prioritization suggests that these transporters may participate in taxane intermediate recognition, trafficking, or export. These findings demonstrate the importance of normalization and batch effect correction in RNA-seq analysis to advance gene discovery in Taxus species and, more broadly, in plant research. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/723993v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1469162org.highwire.dtl.DTLVardef@1f2c4deorg.highwire.dtl.DTLVardef@15ad821org.highwire.dtl.DTLVardef@123676d_HPS_FORMAT_FIGEXP M_FIG C_FIG

In sunflower (Helianthus annuus L.), the composition of fatty acids in the seeds, primarily oleic, linoleic, stearic and palmitic acid, is of utmost importance for oil quality. Despite this, the genetic basis of this trait and its interaction with the environment is poorly understood. Understanding this interaction is critical to improvement of sunflower within the context of climate change. In this work, we incorporated fatty acid composition measurements from the sunflower SAM population and eight environments across an extensive geographic cline into GWAS. The SAM panel consists of 287 varieties representing approximately 90% of sunflower diversity, for which 2.2 million high-quality SNPs with a MAF > 5% are available. For increased power, multivariate GWAS was performed with four different inputs: (i) mean fatty acid composition within each environment, (ii) mean fatty acid composition within each environment omitting high oleic varieties, (iii) trait stability within environments quantified by standard errors among replicate samples ( stability) and (iv) Eberhart and Russells {beta} which quantifies trait stabilities across environments ({beta} stability). All four analyses yielded highly significantly associated SNPs. We found that high oleic varieties exhibited high {beta} trait stability, resulting in substantial overlap in markers between analyses (i) and (iv), with signals being fairly consistent between environments in analysis (i). For analyses (ii) and (iii), significant markers tended to vary between trials. For significant SNPs across all analyses, 147 candidate genes were identified, including promising candidates such as 15 fatty acid metabolism genes, 6 heat shock proteins and 22 transcription factors. Lastly, a large introgression consisting of two flanking inverted sequences on Chromosome 5 was found to coincide with stability in the Georgia trial, suggesting a role in FA composition stability under high heat conditions.