Search Results (278)

The genetic architecture of wheat yield-related traits is complex due to their polygenic control, relatively low heritability, and strong genotype–environment interactions. Commonly used characteristics of wheat productivity include thousand-grain weight (TGW), grain weight per ear (GWE), and grain number per ear (GNE). To identify stable loci associated with productivity-related traits in common wheat, we performed QTL analysis using two mapping populations derived from crosses between contrasting cultivars. The populations were phenotyped for GNE, GWE, and TGW over two years. In addition, GWAS was conducted using a cultivar panel phenotyped for yield and GWE over ten years, and for GNE, GWE, and TGW over two years. The most reproducible loci were located on chromosomes 2D, 4A, 5A, 5B, 6A, 6B, and 7A. From these regions, 16 SNPs were selected for KASP marker development. Validation in an independent panel of 296 spring common wheat varieties phenotyped over three years identified three most informative markers: wsnp_Ex_c16175_24619793 (4A), wsnp_Ex_c2171_4072995 (5A), and BS00034554_51 (6B), all consistently associated with TGW and additionally associated with GWE, GNE, or yield in individual years. These markers may be useful for marker-assisted selection of wheat productivity-related traits. Full article

The corpus luteum number in sows is a key reproductive indicator for measuring ovulation rate and reproductive efficiency. Its formation is precisely regulated by a complex gene regulatory network composed of multi-level molecular interactions. To systematically elucidate the molecular basis of this trait, this study comprehensively analyzed genes located within QTL for corpus luteum number. This approach identified a series of key regulatory molecules specifically expressed in the ovary, including transcription factors (TFs), long non-coding RNAs (lncRNAs), and microRNAs (miRNAs). Using bioinformatics methods to predict the target genes of candidate miRNAs, combined with functional enrichment analysis, revealed that these target genes were significantly enriched in multiple core reproductive pathways closely related to cell proliferation, differentiation, and hormone regulation, including the ErbB signaling pathway, PI3K-Akt signaling pathway, and TGF-beta signaling pathway. Based on the above findings, this study ultimately constructed a TF-lncRNA-miRNA-mRNA network, which is associated with QTL for corpus luteum number. Furthermore, key genes were validated via quantitative real-time PCR (qRT-PCR). Significant positive correlations were identified between the transcription factor NEUROG2 and lncRNA LOC102167554, along with its potential target gene ESRP1, as well as between transcription factor SNAI2 and lncRNAs (LOC102167554, LOC102167796) and their potential target genes (FXR, ERBB4). In addition, the functional validation results showed that the interference of LOC102167554 significantly reduced the proliferation ability of sGCs. These key genes represent potential targets for genetic improvement of sow reproduction. Full article

Chronic obstructive pulmonary disease (COPD) is characterized by persistent airflow limitation, chronic airway inflammation, and immune dysregulation, and currently available therapies remain insufficient to effectively halt disease progression. In this study, we used an integrative, hypothesis-generating strategy to investigate the potential mechanisms of baicalein against COPD by combining multi-dataset transcriptomic analysis, single-cell transcriptomics, machine learning-based feature selection, Mendelian randomization (MR), molecular simulation, virtual knockout analysis, and in vitro validation. Putative targets of baicalein were predicted using CTD, SEA, and SwissTargetPrediction, and were intersected with COPD-related genes collected from GeneCards and OMIM. Four GEO datasets (GSE20257, GSE42057, GSE76925, and GSE130928) were integrated after batch-effect correction, yielding a combined cohort of 260 control samples and 250 COPD samples. Candidate genes were prioritized by intersecting the results of LASSO regression, random forest, and support vector machine. Immune-cell infiltration was estimated using CIBERSORT, and single-cell transcriptomic data were used to define the cellular localization of prioritized genes. Formal protein-level MR analysis was conducted for CD163 using deCODE plasma protein pQTL/GWAS summary statistics as the exposure dataset and the IEU OpenGWAS COPD dataset (ebi-a-GCST90018807) as the outcome dataset. Molecular docking, molecular dynamics simulation, and virtual knockout analysis were further used to provide structural and network-level supportive evidence. Finally, LPS-stimulated BEAS-2B cells were used as an epithelial inflammatory model to evaluate the effects of baicalein by CCK-8 assay, wound-healing assay, ELISA, and RT-qPCR. Five core genes were prioritized, namely ABCC1, CD163, CYP1B1, IKBKB, and PIK3CA. Immune infiltration and single-cell analyses suggested that macrophage-associated immune regulation may represent an important mechanistic direction. MR analysis provided supportive genetic evidence for prioritizing CD163 in COPD. Molecular simulation offered preliminary structural support for several target-compound interactions. In LPS-stimulated BEAS-2B cells, baicalein reduced inflammatory cytokine release and modulated the expression of IKBKB, PIK3CA, IL1B, IL6, and IL10, thereby providing epithelial-level support for the predicted network. Taken together, these findings suggest that baicalein may exert anti-inflammatory effects in COPD through a multi-target, immune-associated mechanism, with macrophage-related regulation and CD163 emerging as noteworthy candidate directions for further investigation. This study provides an integrative framework for target prioritization and mechanistic exploration, while the predicted macrophage-centered mechanisms still require dedicated validation in immune-cell and in vivo models. Full article

Background/Objectives: Glomerular diseases (GD) possess strong polygenic susceptibility, yet exact causal genes remain unclear because most variants identified by genome-wide association studies (GWAS) reside in non-coding regions. While transcriptome-wide association studies (TWAS) effectively decode complex traits, cross-tissue profiling for GD remains largely unexplored. Therefore, this study employs an integrative cross-tissue TWAS and Mendelian randomization framework to systematically identify and validate novel GD susceptibility genes. Methods: We conducted a systematic cross-tissue TWAS integrating Genotype-Tissue Expression (GTEx) v8 eQTL data across 49 tissues. Candidate genes were nominated using five complementary frameworks (sparse canonical correlation analysis (sCCA), functional summary-based imputation (FUSION), fine-mapping of causal gene sets (FOCUS), summary-data-based Mendelian randomization (SMR), and multi-marker analysis of genomic annotation (MAGMA)). Findings were refined via Mendelian randomization (MR), pathway enrichment, protein interaction networks, and druggability profiling. Results: We identified 21 candidate susceptibility genes for GD, with 10 genes (AGER, C6orf48, CSNK2B, CYP21A2, HLA-DRB1, HSD17B8, LST1, MICB, PRRT1, TCF19) strongly supported by MR analysis. Notably, five of these MR-prioritized genes (C6orf48, CSNK2B, HSD17B8, LST1, and PRRT1) were previously unreported. Functionally, these prioritized genes are primarily involved in immune modulation, inflammation, and steroid metabolism. Furthermore, five genes (AGER, CSNK2B, CYP21A2, HLA-DRB1 and MICB) were identified as potentially druggable targets. Conclusions: This first systematic cross-tissue TWAS of GD prioritizes a set of genetically supported susceptibility genes. By uncovering novel drivers and druggable proteins, this study advances the mechanistic understanding of GD and provides a foundation for future therapeutic development and precision nephrology. Full article

Cucurbit crops—including cucumber (Cucumis sativus), watermelon (Citrullus lanatus), and melon (Cucumis melo)—are of major economic and nutritional importance worldwide. Yet their productivity and quality are severely compromised by foliar fungal diseases, particularly powdery mildew (PM), downy mildew (DM), and target leaf spot (TLS). While PM and DM have been extensively studied, TLS has emerged as an increasingly prevalent and damaging disease in key production regions, yet it remains comparatively understudied—especially with respect to its molecular basis and comparative pathobiology relative to PM and DM. Current reliance on chemical fungicides is hampered by escalating pathogen resistance and concerns over residual toxicity, whereas conventional breeding approaches face inherent limitations in pyramiding durable, broad-spectrum resistance against multiple pathogens. In this context, cucumber has emerged as a pivotal model species for dissecting foliar disease resistance mechanisms in cucurbits, supported by a high-quality reference genome, extensive resequencing datasets, diverse germplasm collections, and an efficient Agrobacterium-mediated transformation system. Despite these advantages, existing reviews predominantly address PM or DM resistance in isolation; comprehensive syntheses integrating TLS resistance advances—and critically, cross-disease comparisons of genetic architecture, transcriptional reprogramming, and defense signaling—are notably scarce. Furthermore, the translational pipeline—from gene discovery and functional validation to deployment in marker-assisted or genome-edited breeding—lacks systematic evaluation. Here, we provide a focused, cucumber-centered review that (i) synthesizes recent progress in mapping QTLs and GWAS loci, and characterizing key resistance-associated gene families (such as NLRs, RLKs, PR genes) conferring resistance to PM, DM, and TLS; (ii) integrates transcriptomic, epigenomic, and proteomic evidence to delineate conserved versus pathogen-specific host responses; (iii) highlights breakthroughs and unresolved questions in TLS resistance research, including the roles of novel susceptibility factors and non-canonical immune regulators; and (iv) critically assesses bottlenecks in translating resistance genes into practical breeding outcomes—such as linkage drag, functional redundancy, and genotype-by-environment interactions—and proposes empirically grounded strategies for accelerating molecular design of multi-disease-resistant cultivars. Collectively, this review aims to bridge fundamental insights with applied breeding goals, offering a conceptual and strategic framework for integrated management of foliar fungal diseases and the development of durable, broad-spectrum resistance in cucurbits. Full article

Serum gamma-glutamyltransferase (GGT) is a biomarker for cardiovascular disease, but the role of its encoding gene family in ischemic stroke (IS) is unknown. This pilot study of 1288 individuals (600 cases and 688 controls) investigated GGT1, GGT5, GGT6, and GGT7 polymorphisms using the MassARRAY-4 system. Conventional single-variant, haplotype, and diplotype analyses were complemented by Model-Based Multifactor Dimensionality Reduction (MB-MDR) with stability assessment and model prioritization. Conventional analysis identified female-specific associations for three GGT5 variants (rs8140505, rs2275984, and rs2267073; P_perm < 0.05). A common GGT5 haplotype was protective in females (P_perm = 0.02). Diplotype analysis revealed joint effects of GGT genotypes on IS risk in females (FDR < 0.05). MB-MDR uncovered complex higher-order interactions (P_perm < 0.0001): in women, 12 models represented second-order interactions between smoking and individual GGT variants. In men, 8 models centered on GGT1 rs5751909 spanning second- to fourth-order interactions with alcohol, smoking, and other GGT family members. All prioritized models passed FDR correction (q < 0.05) and achieved higher weighted composite scores. eQTL data linked these variants to regulatory networks controlling glutathione metabolism, oxidative stress, and inflammation. This study supports a novel hypothesis on the combined involvement of GGT gene family polymorphisms and pro-oxidant environmental factors in ischemic stroke predisposition, demonstrating that disease risk is shaped by sex-specific gene–environment interactions. The pronounced sexual dimorphism highlights the need for sex-specific personalized approaches: smoking cessation may be particularly impactful in women carrying GGT5 risk variants, while alcohol moderation could be prioritized in men with GGT1 risk variants. Full article

Diabetic kidney disease (DKD) affects approximately 40% of patients with diabetes mellitus and remains a leading cause of end-stage renal disease worldwide. Early diagnosis and identification of therapeutic targets are critical for improving patient outcomes, yet reliable biomarkers are lacking. This study integrated transcriptomic data from the Gene Expression Omnibus (GEO) database (GSE96804, GSE30528, and GSE142025) with machine learning algorithms and Mendelian randomization (MR) to identify diagnostic biomarkers for DKD. Differentially expressed genes (DEGs) were identified and intersected with key modules from weighted gene co-expression network analysis (WGCNA). Four machine learning methods—least absolute shrinkage and selection operator (LASSO), random forest (RF), support vector machine-recursive feature elimination (SVM-RFE), and extreme gradient boosting (XGBoost)—were applied for feature selection. Five hub genes (SPP1, CD44, VCAM1, C3, and TIMP1) were identified at the intersection of these approaches. Two-sample MR analysis using eQTL data from the eQTLGen Consortium and kidney function GWAS from the CKDGen Consortium provided evidence supporting potential causal associations between SPP1, C3, and TIMP1 expression and estimated glomerular filtration rate decline. Immune infiltration analysis via CIBERSORT estimated elevated proportions of M1 macrophages and activated CD4⁺ memory T cells in DKD samples, with all five hub genes showing correlations with macrophage infiltration. A diagnostic model based on these five genes achieved a cross-validated area under the receiver operating characteristic curve (CV-AUC) of 0.938 in the discovery dataset and AUC values of 0.917 and 0.889 in two independent external validation cohorts. Drug–gene interaction analysis identified 10 candidate compounds targeting the hub genes. These findings provide a computational framework for identifying candidate diagnostic biomarkers and generating hypotheses regarding potential therapeutic targets for DKD; however, all results are derived from in silico analyses and require experimental validation—including qPCR, immunohistochemistry, and prospective clinical cohort studies—before clinical applicability can be established. Full article

Grain quality in bread wheat is a complex trait determined by multiple genetic factors and their interaction with environmental conditions. This study investigated the genetic architecture of key grain quality traits in the Avalon × Cadenza double haploid (DH) population under contrasting climatic conditions in Kazakhstan. A set of 101 spring-type DH lines was evaluated over three years in three major wheat-growing regions of Kazakhstan, representing northern, central, and southern environments. Grain yield and nine grain quality traits were assessed, including amylose content (Amc, %), test weight per liter (TWL, g/L), grain protein content (GPC, %), gliadin content (Gli, %), glutenin content (Glu, %), grain hardness (GH, %), grain vitreousness (GV, %), falling number (FN, s), and sedimentation value determined in a 2% acetic acid solution (SV, mL). The objectives were to characterize phenotypic variation, examine trait relationships, and identify major and environmentally stable quantitative trait loci (QTLs) controlling grain quality. QTL mapping identified 89 QTLs associated with the nine studied traits, including 82 major QTLs explaining more than 10% of phenotypic variation and 16 stable QTLs detected in two or more environments. The largest numbers of QTLs were found for GPC, SV, and TWL. Stable QTLs were distributed across all three wheat genomes, with important regions detected on chromosomes 1A, 1B, 2D, 4A, 4D, 5A, 6A, and 7D. Several stable QTLs co-localized with genomic regions previously associated with grain quality and developmental regulation, including loci near Wx-B1, Rht-D1, and Ppd-D1, suggesting biologically meaningful links among gluten composition, starch biosynthesis, plant development, and grain physical properties. These results improve understanding of the genetic control of wheat grain quality across diverse environments in Kazakhstan and provide promising targets for marker-assisted selection to combine improved end-use quality with wide environmental adaptation. Full article

Alternaria brown spot, caused by the tangerine pathotype of Alternaria alternata, is a destructive fungal disease affecting citrus production worldwide. Nucleotide-binding site-leucine-rich repeat (NBS-LRR) genes constitute a major class of plant immune receptors; however, their genome-wide characteristics and potential association with Alternaria brown spot resistance loci in citrus remain poorly understood. In this study, we performed a comprehensive genome-wide identification and comparative analysis of NBS-LRR genes across representative citrus species. A total of 417 and 326 NBS-LRR genes were identified in Citrus reticulata and Citrus clementina, respectively, and were classified into NL, CNL, TNL, and RNL subfamilies based on domain architecture. Phylogenetic reconstruction, gene structure analysis, conserved motif composition, chromosomal distribution, synteny relationships, and promoter cis-element profiling collectively revealed considerable structural variation and lineage-specific expansion of the NBS-LRR gene family in citrus genomes. By integrating previously reported quantitative trait locus (QTL) data for Alternaria brown spot, we identified several NBS-LRR genes located within a resistance-associated genomic interval on chromosome 3. Among these, a candidate gene, designated LRR2, exhibited differential transcriptional responses upon pathogen inoculation and displayed distinct sequence variations between citrus genotypes. Structural modeling and molecular docking analyses suggested potential binding interfaces between LRR2 and multiple host-selective toxins, although the biological relevance of these interactions requires further experimental validation. Subcellular localization assays in Nicotiana benthamiana showed that LRR2 is distributed in both the nucleus and cytoplasm. Notably, transient overexpression of LRR2 triggered hypersensitive response-like cell death and H₂O₂ accumulation. Collectively, this study provides a comprehensive overview of the citrus NBS-LRR gene family and presents a multifaceted characterization of a QTL-anchored candidate gene. These findings establish a genomic and molecular framework for further functional investigations of citrus–Alternaria interactions. Full article

Chalkiness is a complex quantitative trait regulated by both genetic and environmental factors. Reducing chalkiness has long been a research focus in rice genetics and breeding. A total of 108 markers on/closely linked to starch biosynthesizing genes, grain shape and chalkiness QTLs were used to detect interactions affecting chalkiness. A total of 30 and 39 marker pairs with significant bigenic epistasis were identified for percentage of grain with chalkiness (PGWC) and degree of endosperm chalkiness (DEC), respectively, of which 16 were commonly found in both traits. Using markers associated with chalkiness and marker pairs with significant epistatic effects as candidate predictors increased the coefficient of determination (R²) of the best multiple regression models for predicting both traits. GBSSI, SSIIa and the interaction between GBSSI and GBSSII were consistently identified in optimal models, indicating their critical roles in regulating rice chalkiness. R² for DEC and PGWC ranged from 36.5% to 42.7% and from 52.9% to 73.8% in two environments, respectively. PGWC decreased significantly from 38.9% to 15.10% after three cycles using marker-assisted recurrent selection (MARS). This study suggests that epistasis contributes substantially to the regulation of chalkiness, and demonstrates that MARS can effectively improve chalkiness without imposing obvious negative impacts on eating quality. Full article

Background: Improving grain yield in wheat remains a top priority, requiring integrated breeding and genetic strategies. This complexity poses a major challenge, driven by quantitative polygenic inheritance, environmental influence, and intricate genetic interactions. We investigated genetic factors and their interactions for agronomic and yield traits in two high-yielding winter wheat cultivars adapted to the US Southern Great Plains. Methods: A bi-parental mapping population consisting of 221 F₇ recombinant inbred lines (RIL) derived from ‘TAM 204’ and ‘Iba’ was evaluated for three years in 11 Texas environments. Both parents and RIL population were genotyped on Illumina NovaSeq 6000 and sequences were aligned to IWGSC RefSeq v1.0 using Bowtie2 for SNP calling. For QTL analyses, each trait was analyzed by individual environment, across multiple environments and mega-environments. Results: A total of 86 QTL were mapped for five traits and among them 32 were consistent in more than one environment or analysis. Among consistent QTL, four were pleiotropic to more than one agronomic or yield traits mapped on chromosomes 2B (57.18, 59.47 Mb) and 2D (29.34, 40.64 Mb). The consistent QTL on chromosome 2D (29.34 Mb) was pleiotropic to GYLD, DTH, TW, TKW and explained maximum phenotypic variation for all traits, representing photoperiod gene (Ppd-D1). Another QTL on chromosome 2D (40.64 Mb) was pleiotropic to GYLD and TW and based on the physical position comparisons it likely reflects a unique locus in Iba. The pleiotropic consistent QTL Qgyld.tamu.2B.59 from TAM 204 represents Ppd-B1 gene. Moreover, it is more likely that Qdth.tamu.5B.575 represents the Vrn-B1 gene in Iba. A total of 23 digenic epistatic interactions involved consistent QTL for all traits. Amongst these, epistatic interactions between the consistent QTL on 2B (57.18 Mb) and 2D (29.34 Mb) were observed for GYLD, DTH and TKW. Conclusions: Our findings revealed key allelic diversity and interaction effects in elite wheat cultivars, paving the way for marker development for identified pleiotropic loci and implementation in marker-assisted selection and recombination breeding. Full article

Rice (Oryza sativa L.) grain quality is a critical determinant of market value, consumer acceptance, and nutritional security. This multifaceted trait is governed by the dynamic interaction of genotype (G), environment (E), and management practices (M). In this review, we synthesize recent advances in understanding these multifaceted determinants. We first delineate the genetic architecture, emphasizing key genes and quantitative trait loci (QTLs) such as Wx, ALK, Chalk5, and the GS3/GW families, which control starch composition, gelatinization temperature, chalkiness, and grain dimensions, forming the foundational blueprint for quality potential. We examine how this genetic potential is influenced by environmental factors, focusing on the detrimental impacts of abiotic stresses, particularly high temperatures during grain filling and drought, which impair milling yield, increase chalkiness, and modify starch and protein profiles. Furthermore, we discuss how optimized agronomic strategies—including precision water management (e.g., alternate wetting and drying), balanced nitrogen fertilization, and targeted micronutrient (e.g., silicon) application—can mitigate these adverse effects and potentially improve specific quality parameters. Post-harvest handling is identified as the final determinant of product quality. We conclude that achieving high and stable rice quality under climate variability requires an integrated G × E × M approach. Prospects include next-generation breeding for climate-resilient quality, precision agronomy guided by real-time sensing, synergistic soil health management, and the integration of systems biology with digital agriculture to design sustainable, high-quality rice production systems. Full article

Fusarium ear rot (FER), caused by Fusarium verticillioides, is a devastating disease that substantially reduces maize yield and compromises kernel quality. To investigate the genetic and molecular basis of resistance, an F₂ population derived from a cross between the resistant inbred line 3IBZ2 and the susceptible inbred line KW5G321 was analysed. By integrating bulked segregant analysis sequencing (BSA-Seq) with RNA sequencing (RNA-Seq), a major quantitative trait locus (QTL), designated qFER4, was identified on chromosome 4. Genetic analysis further demonstrated that qFER4 confers resistance through partial dominance. Transcriptome profiling of the resistant line revealed 7684 and 7906 differentially expressed genes (DEGs) at 36 and 72 h post inoculation (hpi), respectively. These DEGs were significantly enriched in defence-related biological processes and pathways, including phenylpropanoid biosynthesis, jasmonic acid signalling, MAPK cascades, and plant-pathogen interactions. By combining QTL mapping with transcriptome analyses, four candidate genes within the qFER4 interval were screened. Sequence analysis identified extensive structural variations in the promoter and coding regions of Zm00001d053393, including a premature stop codon predicted to lead to a gain-of-function mutation. In contrast, the other three genes exhibited only minor promoter polymorphisms with identical coding sequences between the parental lines. Overall, this study identifies a novel major-effect QTL and candidate gene associated with FER resistance, providing a foundation for gene function and a valuable genetic resource for breeding FER-resistant maize varieties. Full article

Rice yield is a complex quantitative trait. Although a lot of genes for yield have been cloned, their genetic basis remains unknown. In the present study, a set of chromosome segment substitution line population (CSSL) was developed, derived from the indica variety Huanghuazhan as the recipient parent and the Aus variety N22 as the donor parent, and a high-density bin map containing 609 bins was constructed by resequencing. The CSSL population comprised 155 families with an average background recovery rate of 93.02%. Nine yield-related traits, including plant height, panicle number, panicle length, primary branch number, spikelet number per panicle, grain number per panicle, seed setting rate, 1000-grain weight, and grain yield per plant, were evaluated across four environments. The results showed significant differences in yield-related traits between the two parents across four environments. All nine traits showed continuous distribution with transgressive segregation. Spikelet number per panicle, grain number per panicle and 1000-grain weight showed strong correlations with each other, whereas panicle number had weak correlations with them. A total of 80 main-effect quantitative trait loci (QTLs) affecting yield-related traits were identified, among which 13 QTLs were repeatedly detected in multiple environments, 45 QTLs were located in 8 pleiotropic QTL regions, and 47 QTLs showed significant interactions with environments. In addition, 260 pairs of epistatic QTLs underlying yield-related traits were identified, of which 2 pairs stably expressed across different environments, and 11 pairs controlled more than two traits. These findings provide a theoretical basis for clarifying the genetic differentiation between indica and Aus and cloning yield-related genes, and offer valuable gene resources for molecular breeding of high-yield rice varieties. Full article

Brachypodium distachyon has become a widely studied model plant due to its small genome, ease of cultivation under controlled conditions, and value for synteny and molecular studies. Regarding disease, Fusarium is one of the main fungal genera infecting cereal crops, F. cerealis, F. graminearum, F. poae, and F. pseudograminearum being isolated frequently from several agricultural regions. Therefore, the present study aimed to evaluate three pathosystems, combining three hosts (B. distachyon, barley, and wheat) with four Fusarium species to confirm the use of B. distachyon in Fusarium–crop system models. Three controlled experiments were performed to assess the impact on seeds, roots, and spikes. Variables such as germination inhibition, McKinney’s index, percentage of necrosis, area under the disease progress curve, disease incidence, disease severity, and grain weight were measured. Regarding Fusarium species, the results confirm that F. pseudograminearum could be more aggressive on roots, while F. graminearum affects spikes more severely. In contrast, F. cerealis and F. poae are generally moderate to weak pathogens with irregular behaviour depending on the plant species or genotype. No clear varietal resistance pattern emerged except for wheat genotypes with a known resistance/susceptibility QTL. The present study highlights the importance of using multiple experiments for accurate phenotype characterisation, as relying on a single technique is insufficient. In conclusion, the results presented in the manuscript provide valuable insights into Fusarium spp.–B. distachyon interactions and resistance selection based on seed, root, and spike assessments. Moreover, this work confirmed the use of Brachypodium as a model plant for Fusarium–plant interaction studies. Full article