Search Results (745)

The fig tree (Ficus carica L.) is one of the oldest cultivated fruit trees in the Mediterranean region and represents an important genetic resource for both traditional and emerging production systems. Despite its agronomic and economic relevance, modern fig breeding remains limited, and large-scale phenotypic evaluations across Mediterranean germplasms are still scarce. The objective of this study was to assess phenotypic diversity and identify key agronomic traits relevant for fig breeding. A total of 257 female fig genotypes conserved in germplasm banks located in Spain, Turkey, and Tunisia were used. Over two consecutive seasons (2021 and 2022), a total of 27 morphological, phenological, and pomological traits were assessed according to the International Union for the Protection of New Varieties of Plants (UPOV) descriptors for fig (TG265/1), with 23 phenotypic traits retained for statistical analyses. Linear mixed models were used to estimate marginal means and to partition genetic and environmental variance, while multivariate analyses and trait correlations were employed to explore the structure of phenotypic diversity. The germplasm exhibits remarkable variation in productive type, reproductive behaviour, harvesting date, and fruit quality traits. Harvesting date spans nearly three months. Fruit weight ranges from 11.7 to 134.5 g, total soluble solids from 9 to 39 °Brix, and maturation index values reached high levels, indicating pronounced sweetness during fruit ripening. Most genotypes showed high skin scratch resistance, absence of cracking at maturity, and medium or small ostiole size, highlighting the presence of ideotypes specifically suited for fresh market production. Heritability estimates indicate strong genetic control of key traits, such as fruit weight, fruit size, and total soluble solids, highlighting their suitability for selection in breeding programs. Stakeholder prioritisation further confirmed the relevance of fruit size, sweetness, firmness, and ostiole characteristics, helping to identify best genotypes for breeding and agronomic purposes. Overall, this study demonstrates the value of Mediterranean fig germplasm as a reservoir of valuable agronomic and commercial traits and provides a robust phenotypic framework to support future breeding, conservation, and cultivar selection strategies. Full article

This study aimed to investigate whether mixed heavy metal exposure (lead, cadmium, manganese, and arsenic) during pregnancy induces gestational diabetes mellitus (GDM)-like phenotypes and to explore the associated molecular alterations. We examined the effects of exposure on metabolic disturbances using a Sprague-Dawley rat model exposed to low- and high-dose mixed heavy metals, with doses selected based on biomonitoring data. The results showed that high-dose mixed heavy metal exposure significantly increased blood glucose levels in rats, elevated the area under the curve (AUC) during the oral glucose tolerance test (OGTT), and induced insulin resistance and dyslipidemia. Concurrently, pathological examinations revealed hepatocyte steatosis, inflammatory cell infiltration, and mitochondrial abnormalities in liver tissues. Transcriptomic and metabolomic analyses identified significant disruption of the glycerophospholipid metabolic pathway following heavy metal exposure, suggesting the involvement of this pathway in the observed metabolic disturbances. Lasso regression analysis identified Insig1 as a candidate gene associated with lipid metabolic alterations, a finding subsequently validated by qPCR. Overall, mixed heavy metal exposure during pregnancy was associated with GDM-like metabolic abnormalities in rats. Disruption of glycerophospholipid metabolism and altered Insig1 expression likely contribute to these effects, providing molecular evidence linking mixed heavy metal exposure to gestational metabolic dysfunction. Full article

Background/Objectives: Essential oils (EOs) have multi-target antifungal activity, but their translation is limited by volatility and poor aqueous dispersibility. Randomly methylated β-cyclodextrin (RAMEB) inclusion may enhance effective exposure and thereby alter susceptibility, stress responses, and biofilm outcomes in a species-dependent manner. This study quantified species-specific planktonic and biofilm susceptibility to four EOs and their RAMEB complexes across clinically relevant Candida species. Methods: Lavender (L), lemon balm (B), peppermint (P), and thyme (T) oils and their RAMEB complexes (RL, RB, RP, and RT) were tested against C. albicans and non-albicans Candida. Susceptibility thresholds were used to derive phase plasticity metrics. Functional inhibition was assessed via planktonic metabolism/viability and established biofilm metabolism/viability/biomass. Mechanistic signatures were captured by ROS/RNS measurements and a qPCR analysis of antioxidant genes (CAT1, GPX1, and SOD1) was performed. Mixed-effects models and multivariate/unsupervised and interpretable classification approaches (k-means, PCA, and CRT) were used to integrate endpoints and stratify response phenotypes. Results: Susceptibility thresholds were strongly species-structured (lowest MIC₉₀/EC₁₀ for C. albicans; higher thresholds and broader sublethal windows in non-albicans species). RAMEB complexation produced formulation-dependent shifts in efficacy, with RT emerging as the most consistent broad-spectrum inhibitory condition across compartments. Biofilm biomass was comparatively insensitive even when viability was suppressed, indicating a decoupling of structural biomass from biocidal activity. Mechanistic signatures were broadly conserved across species and linked to antioxidant-program engagement, with CAT1-related rules contributing to responder/tolerant classification. Conclusions: Integrating MIC/EC plasticity with functional and mechanistic markers supports the rational selection of EO formulations; RAMEB complexation, particularly RT, prioritizes candidates for further pharmaceutical optimization while highlighting species-specific vulnerabilities. Full article

Background: Rome IV criteria promote a symptom-based (“positive”) diagnosis of pediatric disorders of gut–brain interaction (DGBIs). In clinical practice, however, organic gastrointestinal diseases may mimic DGBIs and lead to diagnostic revision after further evaluation. We aimed to quantify the diagnostic stability of an initial Rome IV-oriented functional diagnosis in a tertiary pediatric outpatient setting and to identify symptom phenotypes associated with a higher likelihood of later organic reclassification. Methods: We performed a single-center retrospective cohort study (2014–14 May 2021) based on outpatient chart review. Eligible patients were children and adolescents aged 0–18 years with an initial Rome IV-oriented functional diagnosis. Diagnostic reassessment was based on follow-up data, available laboratory and instrumental investigations, and/or response to exclusion therapies. Final diagnoses after reassessment were categorized as functional only, organic, or mixed. Groups were compared using Pearson’s chi-square test. Results: The cohort included 220 males (50.0%) and 220 females (50.0%), with a mean age of 8.86 ± 4.65 years. After reassessment, 343/440 (77.95%) remained functional, 73/440 (16.59%) were reclassified as organic, and 24/440 (5.45%) were classified as mixed. Final diagnosis differed by GI tract involvement (p = 0.001) and by symptom cluster (p = 0.001). Upper GI/dyspepsia-spectrum presentations showed the highest organic yield (27.03%), followed by lower abdominal pain/IBS-spectrum presentations (19.61%). Diarrhea and vomiting/cyclic vomiting each showed 16.67% organic diagnoses (mixed: 10.0% and 7.14%, respectively), whereas constipation showed the greatest diagnostic stability (98.89% functional; 1.11% organic). Functional confirmation rates were similar before and during the pandemic (77.71% vs. 78.70%; p = 0.756). Monthly case volume was higher in 2020–2021 (6.29 vs. 4.61 cases/month). Conclusions: In this tertiary cohort, about one in six children initially diagnosed with a functional disorder were later found to have an organic disease, and an additional 5% had mixed organic–functional presentations. Diagnostic revision was associated with presenting phenotype, with the highest organic yield observed in dyspepsia/upper GI presentations and the lowest in constipation. These findings support symptom-stratified evaluation and follow-up alongside Rome IV criteria. Full article

The common bean (Phaseolus vulgaris L.) is a major food legume and an important plant genetic resource for sustainable agriculture. Effective use of this diversity requires integrated evaluation of phenotypic variation and agronomic performance, with preliminary assessments of line performance across seasons. In this study, phenotypic diversity was evaluated in a subsample of the INCREASE R-core collection, a large and well-defined core set of common-bean SSD lines derived from heterogeneous germplasm lines. A total of 507 lines were characterized using 57 agro-morphological traits. Multivariate analyses revealed wide phenotypic diversity structured mainly by growth habit, phenology, and yield-related traits, with clear differentiation among lines. Mixed-data clustering identified cluster 4 as the main phenotypic group associated with higher seed- and yield-related performance and composed predominantly of indeterminate climbing landraces. Multi-trait selection indices generally ranked lines from this group highest, while early, small-seeded types tended to show lower overall performance. Evaluation of a selected subset of 19 lines across two growing seasons revealed marked year-to-year variation in yield performance, indicating contrasting responses among otherwise high-performing lines. The multi-trait genotype–ideotype distance index further distinguished lines with balanced performance across traits and years. Overall, this study shows that large-scale phenotypic characterization combined with multi-trait evaluation can provide a useful exploratory basis for identifying breeding-relevant ideotypes and promising lines for further validation for common-bean improvement. Full article

Sitka spruce (Picea sitchensis (Bong.) Carr.) is among the most commercially important tree species in European and North American forestry, and genetic improvement programmes are therefore essential for promoting its productivity and sustainability. This research emphasises the significance of the breeding programmes. The primary objective of this study was to provide more reliable information on family selection for the improvement programme of Sitka spruce by accounting for competition and environmental heterogeneity effects. Analyses in the present study were carried out on historical inventory data of height (HT) and diameter at breast height (DBH) from a half-sib progeny trial of Sitka spruce in Ireland. Tree measurement data were collected at ages 6, 12, 15 and 20 years. A mixed linear model incorporating spatial and competition terms was applied to estimate genetic parameters of the Sitka spruce population. The direct genetic effects of each family on its own phenotypes and the competition effect on its neighbour’s phenotype were examined over time. The study demonstrated an analytical approach for assessing both genetic as well as environmental aspects of competition in a Sitka spruce progeny trial. The combined model integrating competition and spatial terms (model CS) improved model fit compared with the basic model, which only included the random effects of genetic and experimental design factors (model B), with an AIC difference of up to 3609 between them. Residual error obtained from model CS was usually smaller than from model B, with the greatest reduction of 85%. Furthermore, model CS generally improved the estimation of heritability for growth traits, by up to 241, when compared with model B. In addition, genetic differences in competitive ability among families were also observed. Families with favourable combinations of direct genetic and competitive breeding values were suggested for selection in subsequent cycles of the breeding programme, i.e., families with relatively high direct genetic breeding value but low and consistent competitive breeding value over time. This work develops a practical framework to inform future family selection for Sitka spruce improvement programmes. Full article

Background/Objectives: To identify major dietary patterns among adults aged ≥45 years and examine their associations with metabolic health–obesity phenotypes. Materials and Methods: We analyzed 32,091 adults aged ≥45 years from the 2015 China Adults National Chronic Disease and Nutrition Surveillance. Diet was assessed using three consecutive 24 h dietary recalls, with household condiment weighing used to improve estimation of cooking oil and salt intake. Dietary patterns were derived using principal component analysis and categorized into quartiles. Multinomial logistic regression adjusted for energy intake and key sociodemographic/lifestyle factors to estimate odds of metabolically unhealthy non-obesity (MUNO), metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) versus metabolically healthy non-obesity (MHNO). Results: Four patterns with geographic variation were identified: (1) the Rice–Vegetable–Pork pattern; (2) the Fruit–Egg–Dairy pattern; (3) the Red Meat–Offal–Snack pattern; and (4) the Soybeans–Tubers–Grains pattern. Compared with Q1, Q4 of Pattern 1 was associated with lower odds of MHO (OR = 0.42, 95% CI: 0.38–0.46) and MUO (OR = 0.40, 95% CI: 0.36–0.44). Pattern 2 and Pattern 3 were associated with higher odds of MHO (Q4 vs. Q1: OR = 1.42 and 1.21) and MUO (OR = 1.36 and 1.14, all p < 0.001). Pattern 4 was inversely associated with MHO (OR = 0.85, 95% CI: 0.79–0.92) but positively associated with MUNO (OR = 1.16, 95% CI: 1.08–1.24). Conclusions: The Rice–Vegetable–Pork pattern was associated with more favorable obesity-related metabolic phenotypes, whereas energy-dense, animal-derived patterns were associated with higher odds of obesity phenotypes; the Soybeans–Tubers–Grains pattern showed mixed associations. Full article

Chronic kidney disease is rising worldwide, and kidney transplantation remains the preferred modality of kidney replacement therapy. However, long-term graft survival continues to be limited by chronic alloimmune injury, particularly antibody-mediated rejection (ABMR) and its chronic active form. This narrative review synthesizes contemporary evidence on the immunopathogenesis, epidemiology, diagnosis, and management of kidney allograft rejection, with a deliberate focus on studies from the last five years and on United States and European cohorts. We summarize current concepts of T cell–mediated rejection (TCMR), ABMR, mixed and donor-specific antibody (DSA)–negative phenotypes, and the evolution of the Banff classification, highlighting how chronic active ABMR has emerged as a leading cause of death-censored graft loss. We then critically appraise the conventional diagnostic triad of creatinine/eGFR, DSA, and biopsy and review emerging tools, including donor-derived cell-free DNA, urinary chemokines such as CXCL9 and CXCL10, additional blood- and urine-based biomarkers, and biopsy transcriptomics. We also examine how artificial intelligence and machine learning may support digital pathology, multimodal risk prediction, and data integration, while recognizing the current challenges of biological interpretability, external validation, and clinical implementation. Finally, we propose a rejection-focused precision-medicine framework and outline key research gaps, including multicenter validation, trial-ready endpoints, and governance for AI-enabled pathways. Overall, the field is moving from isolated diagnostic signals toward integrated, biologically informed, and clinically actionable approaches to rejection detection and risk stratification. Full article

Bloodstream infection (BSI) is a major cause of morbidity and mortality in patients with chronic kidney disease (CKD), particularly those receiving hemodialysis. Delayed identification of pathogens and their resistance profiles can lead to inappropriate therapy and adverse outcomes. This review evaluates rapid molecular diagnostic approaches for detecting pathogens and resistance markers in BSI, with emphasis on their application in CKD. These technologies provide faster microbiological information by enabling direct or accelerated detection of pathogens and selected resistance determinants. Clinical studies indicate that their use supports prompt adjustment of antimicrobial therapy, especially when combined with antimicrobial stewardship and applied after blood culture positivity. In CKD, identification of the causative organism facilitates treatment selection aligned with renal function and helps reduce unnecessary exposure to nephrotoxic agents. However, diagnostic accuracy differs among platforms, and detection of resistance genes does not consistently reflect phenotypic susceptibility. Furthermore, most evidence is derived from mixed hospital populations rather than CKD-specific cohorts. These factors require careful interpretation within the clinical context. Rapid molecular diagnostics can enhance antimicrobial decision-making in BSI, but their effectiveness depends on integration with conventional microbiology and structured care pathways. Further research in CKD populations is required to clarify their impact on clinical outcomes and to support implementation in nephrology practice. Full article

Objective: The objective of this study was to characterize real-world distributions of C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) across major rheumatic diagnoses and to quantify concordance/discordance patterns and combined CRP-ESR inflammatory phenotypes. Methods: We retrospectively extracted all CRP and ESR tests performed in a tertiary university rheumatology hospital (January 2018–December 2023), including ICD-10-coded diagnoses. Analyses were conducted at the measurement level and patient level (medians across repeated tests). CRP and ESR were expressed as raw values and multiples of ULN and categorized into severity strata. CRP and ESR datasets were merged by patient identifier and calendar date to define same-day pairs; paired analyses used Spearman correlations and ULN-based phenotype classes. Sensitivity analyses tested alternative pairing windows, first-pair-only analyses, phenotype persistence rules, and tertile/quartile discordance definitions. Results: Among 16,921 patients with ≥1 CRP and 17,126 with ≥1 ESR, CRP was more disease-discriminative and only negligibly age-related, whereas ESR increased modestly with age and showed marked sex shifts across severity categories. Inflammatory burden was highest in gout and rheumatoid arthritis, intermediate in psoriatic arthritis and ankylosing spondylitis, and lower in connective tissue diseases (systemic lupus erythematosus, mixed connective tissue disease, Sjogren’s disease, systemic sclerosis, and dermato/polymyositis) and osteoarthritis; CRP distributions were more strongly right-tailed than ESR. Merging yielded 44,427 same-day CRP-ESR pairs from 16,824 patients (99.1% match). CRP and ESR were moderately correlated at measurement and patient levels, yet discordance was common: 27.3% of pairs showed isolated elevation of a single marker. Conclusions: In routine rheumatology care, CRP and ESR provide complementary information. CRP-ESR dissociation is frequent, persists at the patient level, and follows diagnosis-dependent phenotype patterns. Full article

Grain number per spike (GNS) is a key component of wheat yield, yet its genetic architecture remains incompletely understood. This study phenotyped 610 wheat accessions for GNS in four environments and genotyped them using 429,721 single nucleotide polymorphisms (SNPs). The phenotypes were associated with the SNPs using a three-variance multi-locus random-SNP-effect mixed linear model (3VmrMLM) to identify quantitative trait nucleotides (QTNs), as well as QTN-by-environment (QEI) and QTN-by-QTN (QQI) interactions. These genetic components and residual error explained approximately 18%, 31%, 28%, and 23% of the phenotypic variance, respectively. Two and one previously reported genes were found around QTNs and QEIs, respectively. Bioinformatics and haplotype analyses subsequently yielded 25 candidate genes, 22 gene-by-environment interactions (GEIs), and 24 gene-by-gene interactions (GGIs) around the QTNs, QEIs, and QQIs, respectively. Notably, TraesCS1D01G280000, the wheat homolog of OsRopGEF10, was located near a major QTN explaining over 10% of the total phenotypic variation. A gene interaction network constructed from all identified genes highlighted the central role of GGIs in GNS regulation. Environmental variation may reshape the regulatory network through GEIs. Furthermore, superior haplotypes of 12 candidate genes were identified, providing valuable targets for improving wheat yield. Overall, this study dissects the genetic architecture of GNS and offers practical resources for wheat molecular breeding. Full article

Mixed hepatocellular carcinoma (HCC)–neuroendocrine carcinoma (NEC) is a major type of liver mixed neuroendocrine–non-neuroendocrine neoplasm (MiNEN). Primary liver NEC, which is very rare, is mostly associated with HCC rather than pure NEC. To characterize the cancer cell heterogeneity of the HCC and NEC components, we comprehensively analyzed the protein expression of three cancer cell biological markers (TERT, Ki-67, and p53) and five differentiation markers (one hepatocyte marker and four neuroendocrine markers) via immunohistochemistry and immunofluorescence using curative resection tissues from three patients with liver MiNEN. TERT/Ki-67/p53 proteins, which are related to cell proliferation and malignancy, were independently expressed in the HCC and NEC components; Ki-67 was highly expressed among the three proteins in both cancer components, and the expression of all three markers was higher in the NEC component than in the HCC component. Despite the intracomponent and intercomponent heterogeneity, the expression signatures of the three markers were similar between the two components, potentially suggesting a common origin of mixed HCC-NEC. An in-depth exploration of intracomponent heterogeneity using differentiation markers revealed multiple intermediate phenotypes of cancer cells, i.e., HCC-like and NEC-like cells, mainly in the HCC component. Histologically NEC-like cells rather than HCC-like cells tended to have an intermediate percentage of Ki-67-positive cells, compared with NEC cells. The spatial distribution of various intermediate cancer cell phenotypes suggests that mixed HCC-NEC may involve the transdifferentiation from HCC cells to NEC cells through the dedifferentiation of HCC. Full article

Background: In clinical practice, LDL-dominant familial hypercholesterolemia (FH) may overlap phenotypically with triglyceride-dominant or mixed familial dyslipidemia. Rule-based diagnostic approaches like the Dutch Lipid Clinic Network (DLCN) and Simon Broome (SB) criteria are frequently used in countries with limited genetic testing, but their concordance with molecular confirmation is inconsistent. In a large Turkish tertiary-care cohort, we studied phenotype-related discordance between clinical criteria and molecular data and tested whether machine learning (ML) models could improve the prediction of reportable pathogenic/likely pathogenic variant positivity among patients with a clinical FH phenotype. Methods: Patients referred for suspected familial hyperlipidemia underwent targeted next-generation sequencing with a 9-gene panel. For the ML analysis, we focused on FH cases with a definitive molecular status (pathogenic/likely pathogenic vs. no reportable variant; variants of uncertain significance were excluded) and applied an 80/20 stratified split (n = 200; 82 molecular-positive cases). Elastic-net logistic regression, random forest, and XGBoost models trained on routinely available clinical variables were compared with dichotomized SB and DLCN classifications. Results: SB positivity was significantly more frequent in triglyceride-dominant phenotypes than in FH (68.4% vs. 52.3%, p = 0.041), despite the substantially lower molecular positivity (14.0% vs. 36.9%, p = 0.002), indicating FH-like false-positive clinical classification in mixed dyslipidemia. In the FH test set, the ML models showed higher discrimination for reportable pathogenic/likely pathogenic variant positivity than dichotomized rule-based criteria (AUC: XGBoost 0.808; random forest 0.769; elastic-net 0.747 vs. SB 0.639; and DLCN 0.598). Thirteen novel variants absent from gnomAD were identified, predominantly in LDLR. Conclusions: In this real-world Turkish cohort, within clinically defined FH cases, ML models performed better at predicting LP/P variant positivity than dichotomized DLCN and Simon Broome criteria. ML-based risk stratification may support prioritization for genetic testing; however, external validation is warranted. Full article

Copy number variants (CNVs) are large-scale genomic alterations that contribute substantially to genetic diversity and may influence phenotypic variation in livestock. This study investigated the genome-wide CNV landscape of three Vietnamese indigenous chicken breeds. Whole-genome sequencing on the Illumina platform (3–5× coverage) was performed on 24 individuals from Dong Tao (DT), Cay Cum (CC), and Ri (RI) breeds. A total of 1743 CNVs were detected, clustering into 315 copy number variation regions (CNVRs). Most CNVRs were rare, with 31.7% present in only one animal among breeds. Across the genome, 122 unique CNVRs were distributed over 28 chromosomes, predominantly the first five. Losses were the most frequent type (45.9%), followed by gains (39.3%), and mixed events (14.8%). Within these CNVRs, 3633 genes were identified. In DT and RI, CNVR-embedded genes included several candidates, potentially related to adaptability, development, and phenotypic diversification. Notably, DT harbored genes such as EGLN1, OASL, GPX1, DUOX1/DUOXA2 (adaptation, stress/immune response) and LRP4, ZIC1, ZIC4, JARID2, KMT2C, OGN, OMD, and PLOD2 (developmental and skeletal traits), whereas in RI they included genes such as CACNA1S, CALCR, CAPN3, and MAPK13/MAPK14, which may contribute to muscle, bone, and physiological regulation. Functional enrichment analysis revealed numerous genes and Quantitative Trait Loci (QTLs) associated with metabolic, developmental, and immune-related pathways. This study provides the first comprehensive genome-wide CNV profile of Vietnamese indigenous chickens and offers a valuable genomic resource for investigating the genetic basis of breed-specific and adaptive phenotypes. Full article

Background/Objectives: Plant architecture is a critical determinant of high-density tolerance and yield potential in maize (Zea mays L.), yet the genetic networks orchestrating these complex traits require deeper elucidation. Methods: In this study, we utilized a Multi-parent Advanced Generation Inter-cross (MAGIC) population comprising 935 recombinant inbred lines (RILs) derived from 16 diverse elite founders. A comprehensive phenotypic characterization of six pivotal architectural traits—plant height (PH), ear height (EH), ear leaf length (LL), ear leaf width (LW), tassel main axis length (TL), and tassel branch number (TBN)—was conducted across three distinct agro-ecological environments. Results: Phenotypic analysis revealed substantial natural variation and high broad-sense heritability (H² ranging from 60% to 86%), with TBN exhibiting the most pronounced variability. Correlation architecture demonstrated a strong coupling between vertical growth traits (PH and EH, r = 0.73), while lateral leaf expansion (LW) and tassel complexity (TBN) showed significant genetic independence. Using a mixed linear model (MLM) for genome-wide association studies (GWAS), we identified 21 significant SNP–trait associations, including distinct chromosomal clusters on chromosome 8 for EH and chromosome 7 for TBN. By integrating genomic intervals with tissue-specific expression profiling, 23 core candidate genes were prioritized. Notably, Zm00001d042528 (FAS1), involved in chromatin assembly, was implicated in modulating meristematic cell division for plant stature. Other key regulators included Zm00001d020537 (O5) and Zm00001d025360 (F-box protein), which were associated with reproductive organ development and leaf elongation, respectively. Conclusions: These results indicate that maize plant architecture is regulated by a modular genetic framework, with specific loci independently regulating canopy structure and source–sink components. It should be noted that the findings of this study are based solely on statistical models identifying significant associations between genetic loci and phenotypes; the biological regulatory functions of the candidate genes have not yet been experimentally validated. Nevertheless, this study provides new insights into the molecular mechanisms underlying maize morphogenesis and lays a solid theoretical foundation for molecular design breeding aimed at developing high-yielding varieties tolerant of high planting densities. Full article