In the last fifty years, the application of the chemical nitrogen (N) fertilizer has given rise to a reasonable growth in crop yields along with significant adverse effects on our surroundings. Advanced techniques are consequently required to concurrently maintain both high yields and use of less N fertilizer to accelerate the N use efficiency (NUE) of several crops. This review summarizes the key steps associated with nitrogen metabolism in plants; different genes and transcription factors that are involved in the regulation of N response through integrated omic approaches ( proteomic, metabolomic and transcriptomic); the critical role of non-coding RNAs including miRNAs, ta-siRNAs, long non-coding(lnc)RNAs, also several epigenetic regulators, that act significantly behind N-response. This review has also highlighted the use of genome editing technologies (CRISPR/Cas9) and transgenic approaches for improving NUE in plants. Further it provides the critical analysis of recent findings indicate the research gaps and also highlighted the future scope in the relevant area.
Together, guard cells balance two conflicting pressures: water retention during drought and pathogen defence by means of pattern-triggered immunity, achieved through common molecular components: OST1 kinase, SLAC1 anion channels and WRKY transcription factors. In this review, the perception of signals at the membrane level, to the reprogramming of transcription at the nucleus, in guard cells is summarized and discussed, particularly in light of the fact that these cells are faced with multiple signals coming from different parts of the plant during simultaneous biotic and abiotic stress. We discuss antagonism and synergy between ABA-, jasmonic acid and ethylene-dependent regulation of stomatal closure, the PYR/PYL–PP2C–SnRK2 module involved in ABA-dependent regulation of stomatal closure and the PRR–MAPK cascade involved in immune-triggered stomatal closure. ROS and calcium function as convergence nodes and their amplitude, kinetics and subcellular localization define the identity of stress. Only ~40% of guard cells contain ABA-responsive programmes in individual cells, highlighting the presence of heterogeneity, which was not detected by population-based measurements. Pathogens exploit structural weaknesses like the targeting of OST1 by HopM1 for degradation and the stabilization of JAZ by coronatine, and guard cells metabolic constraints affect the metabolic cost of multiple responses to stress to measurable degree. We then examine translational approaches – genome editing specific to guard cells, tuning of hormone-sensitivity, and stress priming – as methods to produce climate-resilient crops with yield stability. Literature was collected from PubMed, Web of Science and Scopus by combining the keywords stomatal guard cells, ABA signaling, stomatal immunity, PAMP-triggered immunity, hormonal crosstalk and drought–disease trade-offs and prioritizing post-2015 publications and single-cell, genome-scale and quantitative studies. We finish with a list of three priority areas: crop-specific signaling architecture, translation of mechanistic insight into field performance, and quantification of metabolic flux trade-offs; each specifying potential concrete directions for future research.
Groundnut (Arachis hypogaea L.) is a major legume and oilseed crop, yet its productivity is constrained by biotic stresses, including fungal, bacterial, and viral pathogens and insect pests, which reduce yield and seed quality. These constraints are difficult to address through conventional breeding, because stress tolerance is polygenic and is further complicated by the allotetraploid genome and strong genotype × environment interactions. To overcome these limitations, multi-omics approaches are now used to dissect stress responses at the mechanistic level; in particular, the integration of transcriptomic and metabolomic data has revealed coordinated regulatory networks involving resistance genes, transcription factors, hormone-mediated signalling pathways, and secondary metabolite biosynthesis. Building on these insights, genome editing, particularly CRISPR/Cas together with base and prime editing, provides precise tools to study and modify these pathways, although in groundnut it has so far been applied mainly to seed oil quality and herbicide resistance. In parallel, machine-learning approaches are beginning to support candidate-gene prioritisation and trait prediction, though their use in groundnut remains limited and largely unvalidated. Realising the potential of these approaches will therefore depend less on the tools themselves than on resolving gene redundancy in the polyploid genome, achieving efficient transformation, and validating candidate genes under field conditions. By integrating multi-omics analysis, precision genome editing, and predictive modelling, this review outlines a framework to improve biotic stress resistance and seed quality in groundnut.
Predicting the distribution of invasive species in urban mountain ecosystems is important for biodiversity conservation and effective management. We developed a sequential two-stage species distribution modelling framework to characterize habitat suitability for the invasive vine Thunbergia alata in the Metropolitan District of Quito and to evaluate the contribution of citizen science records, systematic field surveys, and multi-source environmental data. In the first stage, 637 iNaturalist occurrence records retained after quality control were combined with 12 bioclimatic variables from WorldClim to develop a preliminary MaxEnt model. The resulting habitat suitability map was classified into five categories and used to design a stratified field survey across the predicted suitability gradient. We sampled 1,009 locations, obtaining 450 confirmed presences and 559 independent absence records. In the second stage, the field-derived occurrence data were used to develop a refined MaxEnt model incorporating the bioclimatic variables together with elevation, slope, land cover, VIIRS nighttime lights, NDVI, and the red spectral band. Environmental predictors were standardized to a common 5m. spatial resolution and screened for multicollinearity. Both models were evaluated using receiver-operating characteristic analyses and AUC, with 10 replicate runs and 25% of occurrence records withheld for testing. Mean AUC values were 0.851 ± 0.012 and 0.902 ± 0.008 for the preliminary and refined models, respectively. In the preliminary model, habitat suitability was primarily associated with broad-scale climatic variables, particularly precipitation seasonality and temperature-related variables. In the refined model, nighttime light intensity and elevation showed the highest contributions and permutation importance, while NDVI and climatic variables also contributed to model predictions. Independent field validation showed that 47.2% of absence observations occurred in the two lowest suitability classes, whereas 33.5% occurred in areas classified as highly or very highly suitable. The refined model therefore captured substantial spatial variation in habitat suitability while also revealing areas of mismatch between predicted suitability and field observations. These results demonstrate the value of sequentially integrating citizen science, systematic field observations, and fine-resolution environmental predictors to improve invasive species mapping. This framework provides a practical approach for supporting targeted monitoring and management of invasive plants in complex urban mountain ecosystems.
Late-spring frost (LSF) is a phenology-dependent freezing hazard that occurs after spring growth has begun, affecting either deacclimated tissues in overwintering plants or newly emerged tissues with limited freezing tolerance in spring-sown crops. Unlike general cold stress, LSF disproportionately damages deacclimated young tissues and reproductive organs under rapidly fluctuating field temperatures. This review critically evaluates the phenological, physiological, and molecular determinants of LSF and distinguishes direct evidence from mechanisms inferred from conventional cold-stress studies. Rather than treating conserved cold-response pathways as established LSF mechanisms, we evaluate their relevance according to evidence strength, developmental stage, organ sensitivity, and deacclimation status. Across crops and woody perennials, injury severity is governed by the interaction among developmental stage, organ sensitivity, deacclimation status, minimum temperature, exposure duration, cooling rate, and post-frost recovery conditions. Major physiological constraints include membrane destabilization, osmotic imbalance, excessive ROS accumulation, and impaired photosynthesis and reproductive development. Conserved cold-response modules involving Ca²⁺ signaling, mitogen-activated protein kinase (MAPK) cascades, the inducer of CBF expression 1 (ICE1)-CBF/DREB pathway, antioxidant systems, lipid remodeling, and hormone crosstalk provide plausible mechanistic hypotheses for LSF resilience. However, direct evidence remains limited, and their relevance depends on tissue specificity, developmental timing, deacclimation status, and rapid reactivation after frost exposure. Hormonal regulation is further shaped by a growth-defence trade-off, because stress-protective responses can restrict spring growth and reproductive success, whereas growth-promoting programs accelerate the loss of cold hardiness. Future research should prioritize field-relevant frost simulations, organ- and stage-resolved phenotyping, validation of candidate genes in reproductive tissues under realistic LSF conditions, and integration of weather forecasting, phenology, cold-hardiness models, breeding, and practical frost protection. This review provides an evidence-constrained perspective on conserved cold-response mechanisms in the context of LSF and highlights priorities for future research.
Agarwood is a high-value resin formed in the heartwood of certain trees, mainly species of Aquilaria and Gyrinops. It is valued for its complex fragrance and strong cultural and spiritual significance. Among these trees, Gyrinops spp. are important in Indonesia, but their biosynthetic pathways remain less understood than those of Aquilaria. At the same time, rising global demand, slow, unpredictable resin formation, and overexploitation have raised serious concerns about the long-term sustainability of agarwood resources. As a result, the international trade of all agarwood-producing species is strictly regulated. In this review, the potential of synthetic biology and metabolic engineering to support more sustainable agarwood production is examined, with a particular focus on Gyrinops. The chemical and biological basis of agarwood formation is discussed, especially on the production of oxygenated sesquiterpenes and 2-(2-phenylethyl)chromones (PECs). In vitro systems, together with fungal or chemical elicitation, are also evaluated as tools for metabolite production and biosynthetic gene discovery. In addition, the potential of heterologous hosts, including Saccharomyces cerevisiae, Yarrowia lipolytica, Chlamydomonas reinhardtii, and Nicotiana spp., is considered to produce agarwood high-value metabolites. In silico and AI-driven approaches are further highlighted as tools to accelerate the identification and optimization of key Gyrinops biosynthetic genes. Overall, the metabolic engineering approach in Gyrinops agarwood is positioned not as a replacement for natural agarwood production but as a complementary strategy to support conservation, sustainable cultivation, and responsible use of agarwood resources.
R-loops, three-stranded nucleic acid structures composed of an RNA: DNA hybrid and a displaced single-stranded DNA, have emerged as central regulators of transcription, chromatin organization, genome stability, and stress responses in plants. Over the past decade, R-loops detection technologies have undergone a paradigm shift from antibody-dependent approaches such as DRIP-seq to high-resolution, low-input methods including CUT&Tag, MapR, and R-ChIP, and culminating in nanopore sequencing, which enables direct, strand-specific, and long-read detection of RNA: DNA hybrids. This review provides the first comprehensive synthesis of R-loops mapping technologies specifically tailored to plant systems, with a distinctive focus on their translational applications in agriculture and food chemistry. We critically evaluate the strengths and limitations of each platform, tracing the technological trajectory from bulk, antibody-based profiling to single-cell-compatible, modification-aware, and real-time detection. We further propose that R-loops dynamics constitute a previously underappreciated nexus linking transcriptional regulation to food quality traits, including the biosynthesis of flavonoids, phenolic compounds, amino acids, and other bioactive metabolites that determine nutritional value, flavor, and post-harvest stability. By bridging plant molecular biology with food chemistry, this review demonstrates how R-loops mapping can inform precision breeding and CRISPR-based genome editing to enhance crop productivity, stress resilience, and food quality. We conclude by identifying critical gaps and outlining actionable future directions, positioning R-loops biology as an emerging pillar for sustainable agriculture and global food security.
Meeting the increasing demand for safe, nutritious, and climate-resilient food requires innovative strategies to enhance vegetable productivity and quality while overcoming the limitations of conventional breeding. Vegetables are vital sources of essential nutrients, vitamins, minerals, and bioactive compounds; however, their genetic improvement remains constrained by long generation cycles, complex reproductive biology, and labor-intensive selection processes. Therefore, modern breeding practices are needed on an urgent basis to speed up the generation time of vegetable cultivars. The emerging genome editing techniques complement conventional breeding approaches by enabling the rapid development of improved cultivars with targeted agronomic, nutritional and stress resilience traits. Among genome editing tools, the clustered regularly interspaced short palindromic repeats (CRISPR) /CRISPR-associated protein-9 (Cas9) genome editing technique has received extensive attention in recent years due to its precise and highly efficient editing in genomes. This review provides a critical assessment of recent advances in CRISPR/Cas9-mediated vegetable improvement, with emphasis on applications in yield enhancement, nutritional quality improvement, abiotic and biotic stress tolerance, and de novo domestication. Furthermore, we highlight the emerging integration of CRISPR/Cas9 with speed breeding and artificial intelligence (AI)-guided target selection as a next-generation breeding strategy to accelerate gene discovery, improve editing precision, shorten generation cycles, and facilitate the development of transgene-free (T-DNA-free) elite vegetable cultivars. We also critically evaluate the current bottlenecks in vegetable genome editing and discuss future opportunities for integrating advanced genome editing technologies, AI-enabled approaches, and accelerated breeding pipelines to overcome these challenges and facilitate the development of sustainable, climate-resilient vegetable crops.
Understanding plant traits that contribute to maintenance of physiological activities under drought is crucial for sustainable rice production. Leaf morphological characters together with UAV-based HTP measurements of canopy temperature (CT), NDVI, leaf water potential (ψLeaf), photosynthetic traits like A, gs E and Ci with drought response index (DRI) were collected from >600 indica genotypes in two field dry seasons. This dataset from the 3K rice sequenced genomes under well-watered (WW) and managed drought stress (MDS) revealed drought-induced leaf morpho-functional interactive changes related to grain yield under drought. Onset of drought caused ~14-20% reduction in Ci, 35 – 56% reduction in A causing serious loss in yield. Correlations analyses from two years field dry seasons dataset revealed that the combination of initially broader leaves capable of increasing leaf thickness in response to drought, as evidenced by changes in SLA, together with maintenance of ψLeaf, supporting a higher Anet can collectively drive towards a higher DRI. The SLA changes up to even ~50% in one of the best performing genotypes with high DRI values upon severe drought stress. GWAS identified seven QTLs for DRI which include known drought-responsive aquaporin, dehydrin, and heat shock protein genes, which coincide with the GWAS interval identified for CT on chromosome 7. This study identified a tentative pathway linking genomic loci to water balance, leaf development, and photosynthesis-related traits under drought. Our results provide opportunities to select the best-performing rice genotypes, enhance understanding about how to improve grain yield of rice under drought by mechanistic exploration whereas aid drought breeding efforts by selecting optimal haplotype combinations or gene edits.
REVEILLE (RVE) transcription factors, belonging to the CCA1/LHY-like MYB family, are conserved across the plant lineage and play central roles in regulating the plant circadian oscillator, with emerging functions extending beyond clock regulation to stress modulation. Here, we synthesize recent advances on the evolution, structural architecture, and functional characterization of RVE proteins across plant species. We highlight the functions of RVEs as essential transcriptional activators within the circadian oscillator, as rhythmic chromatin remodelers, and as components of feedback loops that orchestrate day-night gene expression. We discuss the non-circadian functions of RVE genes in plants, including plant growth regulation, metabolic coordination, hormone signaling, and their coordinated roles in responses to cold, salt, and heat stressors. Furthermore, we discuss the emerging functions of RVE genes in soybean and their potential regulation of legume symbiosis. We identify unresolved controversies that warrant further investigation and propose future research directions to address these knowledge gaps. Finally, we outline a research roadmap and discuss the potential of RVE-mediated strategies for soybean trait improvement.
Cold stress during the booting stage severely affects rice productivity by damaging reproductive organs, particularly disrupting tapetum function and pollen development, reducing seed-setting rates, and causing substantial yield losses. Key physiological and biochemical processes, including carbohydrate metabolism, reactive oxygen species (ROS) homeostasis, and hormone-mediated signaling pathways involving abscisic acid (ABA), gibberellins (GA), auxin (IAA), cytokinins (CKs), jasmonic acid (JA), and ethylene (ET), play critical roles in regulating reproductive-stage cold tolerance. This review systematically examines the effects of cold stress on anther development, with particular emphasis on tapetum–microspore interactions and the coordinated regulation of metabolic, redox, and hormonal pathways that determine pollen fertility under low-temperature conditions. We further summarize the genetic architecture underlying cold tolerance, including major quantitative trait loci (QTLs), cloned genes, and regulatory factors such as CTB4a, CTB2, CTF1, and qCTB7, which contribute to reproductive-stage cold tolerance through diverse molecular mechanisms. Moreover, we discuss genes conferring cross-stage tolerance and evaluate their potential applications in rice breeding programs. Finally, we highlight current knowledge gaps and future opportunities for integrating genetic, physiological, and multi-omics approaches to improve reproductive-stage cold tolerance. By synthesizing these advances, this review provides a theoretical framework for developing climate-resilient rice cultivars with stable fertility and productivity under low-temperature stress.
Helminthosporium leaf blight (HLB) of wheat is an increasingly important foliar disease complex prevalent in warm and humid production environments, caused by different combinations of multiple necrotrophic fungi, primarily Bipolaris sorokiniana, Pyrenophora tritici-repentis, and Alternaria triticina. Unlike classical single-pathogen systems, HLB represents a dynamic, multi-pathogen pathosystem characterized by frequent co-infection, overlapping symptoms and shared infection niches, complicating diagnosis and resistance breeding. This review synthesizes current knowledge on pathogen diversity, epidemiology, and host–pathogen interactions, with emphasis on necrotrophic effector–host sensitivity gene interactions operating under the inverse gene–for-gene model and their interplay with polygenic resistance mechanisms. Advances in QTL mapping, genome-wide association studies, and meta-QTL analyses are critically evaluated alongside emerging insights into effector diversity, virulence evolution, and genomic plasticity. Advances in molecular diagnostics, high-throughput phenotyping, and artificial intelligence-assisted disease detection are also discussed in the context of improving pathogen identification and trait resolution. Recent advances in pangenomics further provide a population-level perspective on pathogen and host diversity, highlighting the role of accessory genomes, effector variability and structural variation in shaping disease outcomes and resistance architecture. We propose a unified framework in which durable resistance is achieved by minimizing effector-triggered susceptibility while enhancing polygenic resistance. Future breeding strategies should integrate susceptibility gene management, pyramiding of stable resistance loci, and genomics-assisted selection to develop wheat cultivars with broad-spectrum, durable resistance against this multi-pathogen disease system.
Wheat (Triticum spp.), a globally important staple crop, has a complex polyploid genome (di-, tetra-, and hexaploid) shaped by domestication and adaptation to diverse agro-ecological zones. This genomic complexity poses significant challenges for trait characterization and breeding. Recent advances in functional genomics, including reference genome assemblies, genome-editing tools, high-throughput phenotyping, and speed-breeding platforms, have revolutionized wheat research, enabled deeper exploration of agronomic traits, and accelerated the development of high-yielding, stress-resilient, and nutritionally enhanced varieties. Among emerging molecular tools, non-coding RNAs (ncRNAs) have gained prominence for their regulatory roles in gene expression and plant development, particularly under (a/biotic) stress conditions. Major ncRNAs like microRNAs (miRNAs), small interfering RNAs (siRNAs), and long non-coding RNAs (lncRNAs) are increasingly recognized for their roles in wheat’s key traits, including grain quality, productivity, and resistance to a/biotic stresses. High-throughput sequencing and bioinformatics pipeline have enabled the identification and functional analysis of ncRNAs, supporting the construction of regulatory networks and their integration into genomics-assisted breeding program. Despite rapid progress of multi-omics integration in wheat, a major knowledge gap remains in understanding the crosstalk among ncRNA classes and their dynamic regulation in multi-stress environments, which limits their translational use in wheat and other allied cereal improvement. Addressing this gap through integrative omics and functional validation will enhance the precision of trait dissection and molecular breeding. Furthermore, ncRNAs hold promise as biomarkers and gene-editing targets, offering novel avenues for trait improvement and sustainable wheat production under climate change scenarios.
Gibberellins (GAs) are diterpenoid phytohormones that regulate seed germination, organ elongation, flowering, and reproductive development, but recent work shows that GA function depends on spatially controlled homeostasis rather than hormone abundance alone. Here, we synthesize advances in GA biosynthesis, transport, and signaling, focusing on the localized production of bioactive GAs, movement of precursors such as GA₁₂, feedback regulation of GA 20-oxidase (GA20ox), GA 3-oxidase (GA3ox), and GA 2-oxidase (GA2ox), and the GIBBERELLIN INSENSITIVE DWARF1 (GID1)-DELLA signaling module. We discuss how DELLA-centered signaling integrates GA responses with auxin, abscisic acid, brassinosteroid, cytokinin, jasmonate, ethylene, and strigolactone pathways to coordinate source–sink relations, thermomorphogenesis, salinity responses, and growth–stress trade-offs. We also examine how classical dwarfing alleles and CRISPR/Cas-based genome editing of GA metabolic and signaling components are used to improve crop architecture while minimizing pleiotropic effects. Finally, we highlight unresolved questions involving tissue-level GA dynamics, non-canonical signaling in cereals, and environment-specific tuning of GA responses. By linking molecular mechanisms with stress adaptation and crop design, we present GA biology as a practical framework for improving plant performance in changing environments.
Abiotic stresses trigger excessive production of reactive oxygen species (ROS), resulting in oxidative damage to the crops. Recent advances in genome editing and transgenic technologies have enabled targeted manipulation of genes and pathways controlling antioxidant metabolism and redox homeostasis. This review examined the genetic, molecular, and metabolic regulation of diverse antioxidant responses across crop species, organs, and developmental phases. It aimed on determining the functional consequences of differences among tissues and growth stages in redox homeostasis under climatic stress. We overviewed studies that focused on genome-scale profiling, biochemicals, and metabolite analysis of stress-related antioxidants across different crop species to identify regulatory elements suitable for genome editing. These studies consistently indicated that antioxidant activity is determined by tissue specificity, developmental stage, and metabolic demand, in addition to regulation by specific genes and enzymes. In this review, we further showed the developing role of algorithm-based analytics and automated model-training approaches in enabling the identification of antioxidant regulatory targets, integration of complex datasets, and improved prediction of plant stress tolerance. These technological processes allow for efficient genomic selection, CRISPR-mediated genome editing, and transgenic manipulation for enhancing breeding strategies that are aimed at improving antioxidant response efficiency. Our review indicates that molecular and genomic regulation of antioxidants is a major mechanism for developing stress-tolerant crops.
Brassica napus, a vital global oilseed and vegetable crop, suffers severe yield losses due to aphid infestation. Current reliance on chemical pesticides raises ecological and resistance concerns, making the elucidation of host resistance mechanisms a priority for sustainable agriculture. This study employed an integrated physiological, biochemical and metabolomic approach to compare a highly resistant line (CF101) and a susceptible line (CF138) under aphid stress. Comprehensive phenotyping and physiology revealed that CF101 possesses superior and stable vegetative growth, enhanced photosynthetic performance, stronger basal antioxidant capacity, and more potent induced defense responses. Metabolomic profiling identified a coordinated defense network, with CF101 showing upregulation of key metabolites from the shikimate-phenylpropanoid pathway (e.g., phenolic acids, lignin precursors, coumarins), benzoxazinoids, oxylipins, and glucosinolate synthesis precursors. Concurrently, metabolites serving as potential aphid nutrients or involved in certain signaling pathways were downregulated. This profile suggests a dual strategy of enhancing direct chemical defenses while limiting resources available to the pest. Functional validation confirmed that exogenous application of two identified metabolites, L-Malic acid and 3-Aminosalicylic acid, significantly enhanced aphid resistance through antibiosis and repellency, though at a cost to vegetative growth. Our findings provide novel, systemic insights into the physiological and biochemical foundations of aphid resistance in B. napus, revealing specific metabolic pathways and candidate compounds that can inform future breeding programs and integrated pest management strategies.
Pan-transcriptomics represents a transformative advance in plant systems biology, extending the pangenome concept to encompass transcriptional, isoform, and regulatory diversity across populations. This review integrates structural genomics, transcriptomics, and quantitative genetics to elucidate how genotype-dependent expression, alternative splicing, and transcript presence–absence variation (tPAV) collectively shape phenotypic plasticity and environmental adaptation in crops. We present a unified methodological framework that combines short- and long-read sequencing, genotype-specific reference transcript dataset (RTD) construction, and pan-RTD integration within linear and graph-based coordinate systems. Comparative analyses across cereals, legumes, and polyploid crops reveal pervasive isoform turnover, stress-inducible dispensable transcripts, and structural variants that drive regulatory diversity. Coupling isoform-resolved expression matrices with eQTL and sQTL mapping uncovers the cis- and trans-regulatory polymorphisms underlying complex traits, while network-level analyses demonstrate how core and variable isoforms remodel co-expression and signalling architecture under stress. Finally, we highlight translational applications in marker development, predictive modelling, and AI-assisted molecular breeding. Together, these advances establish crop pan-transcriptomics as a central systems framework linking genome architecture to transcriptional regulation, phenotypic diversity, and next-generation breeding innovation. Statement of significance This review establishes a unified conceptual and methodological framework for crop pan-transcriptomics, integrating structural genomics, isoform diversity, and systems genetics to bridge genome architecture with transcriptional regulation and phenotypic diversity. Highlighting advances in genotype-specific reference transcript datasets, long-read sequencing, and isoform-resolved eQTL/sQTL mapping, it defines the analytical foundation for next-generation breeding and demonstrates how pan-transcriptomic approaches reveal dispensable and stress-responsive isoforms that enable predictive, AI-assisted crop improvement.
The escalating global concerns over chemical pesticide usage and increasing pest pressures under climate change underscore the urgent need for sustainable biocontrol strategies. Fungal endophytes have emerged as promising agents for managing fungal plant pathogens. However, a comprehensive synthesis specifically focused on fungal endophyte-mediated biocontrol of fungal diseases has been lacking. Here, we analyze 115 studies documenting fungal endophyte-mediated biocontrol across diverse crop diseases. Our analysis identifies Trichoderma, Aspergillus, Fusarium, Penicillium, Colletotrichum, and Alternaria as the most frequently investigated endophyte genera, with wheat, tomato, and grapevine as the most common sources. Herbaceous plants dominate as endophyte sources, while cultivated plants are sampled nearly twice as often as wild plants, revealing significant sampling biases. Root-derived endophytes are most frequently studied, whereas reproductive tissues remain underexplored despite their potential for vertical transmission. We provide a comprehensive overview of seven key biocontrol mechanisms: antibiosis, competition, induced systemic resistance, mycoparasitism, defense signaling modulation, volatile organic compound production, and growth-defense tradeoffs. Notably, 74% of studies report multifactorial mechanisms operating concurrently, underscoring the synergistic nature of endophyte-mediated protection. Critical translational gaps are identified: only 17% of studies have progressed to field validation, and single-strain applications dominate (64% of studies) while mixed consortia remain underoptimized. We also examine factors influencing biocontrol efficacy, including endophyte-host compatibility, environmental conditions, and plant genotype, alongside challenges in evaluation methods, field-scale assessments, long-term monitoring, and economic considerations. This review advances our understanding of fungal endophyte-mediated disease control and provides insights for developing sustainable agricultural technologies.
Lipoxygenase 2 converts polyunsaturated fatty acids into volatile compounds, imparting an undesirable beany flavor to processed mungbean products. This experiment aims to assess the suitability of CRISPR/Cas9-based genetic modification of mungbean using protoplasts and agroinfiltration transient transformation assays. Robust and viable protoplasts were isolated using the tape sandwich method. Protoplast transfection was carried out using 40% PEG. A binary CRISPR/Cas9 construct targeting the Lipoxygenase 2 gene was agroinfiltrated into the abaxial leaf surface of two-week-old seedlings. Higher protoplast yield was obtained from fully grown, unifoliate leaves from 7-day-old seedlings compared to 12-day-old seedlings. The CaMV 35S promoter and CmYLCV are the best fits for transgene expression in mungbean and were selected for Cas9 and gRNA expression, respectively. Protoplast transformation with 5 min of PEG incubation achieved the highest transformation efficiency (similar to 55%), compared to 15 and 30 min of PEG incubation. Mutations were detected by linear amplicon sequencing of the PCR-amplified target region. Transformed protoplasts showed a combination of mutation types, primarily insertion/deletions, with some substitutions on all gRNA target sites. Additionally, robust RUBY pigmentation and GUS expression were obtained, indicating successful transient expression of T-DNA. In the agroinfiltration assay, mutations were detected at target sites guided by gRNA1 and gRNA2. Hence, an efficient method for assessing CRISPR/Cas9 activity in mungbean using protoplast transformation and agroinfiltration was established. This study provides a practical foundation for future efforts towards CRISPR/Cas9-mediated targeted modification of the Lipoxygenase 2 gene via stable transformation to potentially reduce undesirable beany flavor in mungbean.
Liriodendron tulipifera is a rich source of structurally diverse aporphine benzylisoquinoline alkaloids (BIAs), which exhibit various pharmacological activities including antioxidant, antitumor, and anti-rheumatic effects, indicating significant medicinal potential. Nevertheless, the clinical development of these compounds is limited by their low natural abundance in planta and poor synthetic biology yields, with enzyme resources and catalytic efficiency being the primary limiting factors for the latter. Methyltransferases (MTs) are critical for determining aporphine alkaloid diversity and bioactivity but remain largely uncharacterized in L. tulipifera. Here, we integrated genomic and evolutionary analyses to reveal a whole-genome duplication event in L. tulipifera, with expanded gene families significantly enriched in secondary metabolic pathways. Phylogenetic analysis of key BIA pathway genes revealed that they share a common ancestry between Magnoliids and Ranunculales, but evolved independently in Sapindales. Based on genomic data, a total of 65 methyltransferase genes (including 58 OMTs and 7 NMTs) were identified. Through phylogenetic analysis and expression pattern profiling, eight OMT and two NMT genes were selected as candidates. Enzyme activity assays demonstrated that LtOMT37 and LtOMT44 catalyze C7 O-methylation, while LtNMT4 and LtNMT6 catalyze N-methylation of multiple BIA pathway substrates. This study reports the first characterization of 7-O-methyltransferases in the Liriodendron, laying a foundation for deciphering the aporphine BIA pathway in magnoliids and providing new genetic resources for the sustainable production of BIAs.
