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At least 37 records · Page 2Linked to original sources
PubMed2026

Strigolactones constrain rice drought acclimation by suppressing ROS scavenging through the D53-OsWRKY31-ZFP36 module.

Strigolactones (SLs) are a class of plant hormones essential for tiller development and yield under diverse environmental conditions. Drought is a major limiting factor for rice yields. Although SLs contribute to drought resistance, mechanisms and practical applications of SL pathway in drought acclimation of rice remain poorly understood. Our study shows that short-term dehydration represses SL biosynthesis in rice roots. Genetic assays indicate that disruption of SL biosynthesis or signaling elevates rice drought resistance, whereas SL signaling activation or supplementation with the SL analog GR244DO impairs drought resistance. SLs negatively regulate drought acclimation by promoting degradation of the repressor protein DWARF53 (D53). D53 interacts with the transcription factor OsWRKY31 via its N-terminal domain and suppresses the protein level of OsWRKY31, which binds to and represses transcription of the ZFP36 promoter. ZFP36 encodes a zinc-finger transcription factor that promotes H2O2 scavenging to sustain reactive oxygen species (ROS) homeostasis during drought stress. Notably, the drought-resistant upland rice variety IRAT109 exhibits lower SL levels in root exudates than the lowland rice variety Nipponbare (NP). Genome editing of key components in SL pathway enhances drought resistance in NP, Huazhan (HZ), and IRAT109. The agronomic potential of tuning SL biosynthesis is further supported by the elite D17/HTD1 allele, which weakens SL biosynthesis and improves drought resistance and grain yield in Nekken 2 (NK2) under field conditions. These findings uncover a key mechanism underlying SL-repressed drought acclimation in rice and provide an effective strategy to improve drought resistance in diverse rice varieties amid ongoing climate change.

D53↗
PubMed2026

Wheat breeding during and after the "green revolution" contributed to the reduced use of elite nitrogen metabolism alleles linked to nitrogen use efficiency.

The wheat "Green Revolution (GR)" that occurred from the 1960s to the 1970s significantly enhanced the harvest index and resistance to lodging, thereby increasing grain production, but at the cost of reduced nitrogen (N) use efficiency (NUE) in wheat. The NUE of wheat is mainly regulated by N metabolism genes (NMGs). However, the evolutionary process of NMGs during GR and post-GR wheat breeding, as well as which of them affect NUE, remains unclear. Here, we collected 265 wheat varieties that were released before, during, and after the GR and investigated grain yield per plant and 24 other traits under different N supply conditions. Next, we identified the genotypes of these wheat varieties using a 100 K targeted sequencing array. Then, we systematically analyzed the signatures in the genomes of GR and post-GR released varieties compared with pre-GR released varieties through population divergence (Fst) and nucleotide diversity (π) ratio analyses, and found that 41 NMGs were located within the selective sweep regions during the GR and post-GR breeding. We further identified 118 quantitative trait loci (QTLs) involved in regulating NUE through genome-wide association studies (GWAS). Four NMGs-NRT1 AND PEPTIDE TRANSPORTER FAMILY 2.7-D (TaNPF2.7-D), TaNPF2.3-D, TaNPF2.7 L-D, and QUASIMODO2-B (TaQUA2-B)-were located within overlapping regions of selective sweeps and NUE-related QTLs. Notably, the elite haplotypes of these genes for NUE are less utilized in GR and post-GR released cultivars. Furthermore, we found that TaNPF2.7-D positively regulates nitrate exudation as well as the wheat development. Collectively, our findings uncover an important reason for the reduction in NUE in modern cultivars and provide a valuable resource for improving wheat NUE.

Triticum↗
PubMed2025

Comparing artificial and convolutional neural networks with traditional models for Genomic prediction in wheat.

With the rapid development of sequencing technology, the application of genomic prediction has become more and more common in breeding schemes of livestocks and crops. Selecting an appropriate statistical model is of central importance to achieve high prediction accuracy. Recently, machine learning models have been expected to upgrade genomic prediction into a new era. However, the perspective still suffers from lack of evidence that machine learning models can generally outperform the traditional ones on empirical data sets. In this study, we compared two machine learning models based on artificial neural network (ANN) and convolutional neural network (CNN) with four traditional models, including genomic best linear unbiased prediction (GBLUP), Bayesian ridge regression (BRR), BayesA and BayesB, using three published data sets for grain yield in wheat. For each model, we considered two variants: modeling and ignoring the genotype-by-environment ([Formula: see text]) interaction. In the comparison, we considered two strategies of cross-validation: predicting genotypes that have not been evaluated in any environment (CV1) and predicting genotypes that have been tested in other environments (CV2). Our results showed that traditional Bayesian models (BayesA, BayesB, and BRR) outperformed GBLUP, ANN and CNN when considering [Formula: see text] interaction. The accuracies of ANN and CNN were higher than traditional models only in CV1 and when [Formula: see text] interaction was ignored. It was also found that the performance of the two machine learning models was significantly affected by the interaction between the CV strategy and the way of treating the [Formula: see text] interaction, while that of the four traditional models was only influenced by whether the [Formula: see text] interaction was considered or not. Thus, machine learning models can be a powerful complementary to the traditional ones and their superiority may depend on the prediction scenario. Among the two machine learning models, we observed that the accuracy of ANN was higher than CNN in most cases, indicating that it is still challenging to adapt complex machine learning models such as CNN to genomic prediction.

ANN↗
PubMed2026

Watershed-scale risk assessment of cadmium contamination in Chinese cropland soils: Dual pathways of irrigation input and flood-driven transport.

Irrigation and flood events serve as critical pathways for the transport of cadmium (Cd) from industrial sources into cropland soils at the watershed scale, constituting a major driver of widespread Cd contamination in China's cropland soil. This study evaluated the risk of Cd contamination in cropland soils across China's nine major river basins at the watershed scale, focusing on the contributions of irrigation and flood events, and conducted a sensitivity analysis of key risk factors. The assessment was conducted within a framework that considered factors including hazard, exposure, and vulnerability. The results revealed that numerous watersheds in southeastern China are exposed to dual pressures of Cd contamination risks in cropland soils, driven by both irrigation practices and flood events. Watersheds categorized as High-High, High-Moderate, or Moderate-High risk, reflecting combined Cd contamination risks from irrigation and flood, are vital to China's grain production, contributing 67.1 % of the national cropland area and 66.4 % of the grain yield. The study suggests localized strategies for managing cropland soils Cd contamination risks from irrigation and flood at the watershed scale in China, alongside strengthened cross-regional collaboration in southeastern China.

Cadmium↗
PubMed2026

Natural variation in Miniature5 determines mitochondrial nad1 splicing and seed development in maize.

Seed size is a key determinant of cereal grain yield, but natural variations in defective-kernel genes have rarely been applied in maize breeding. Here, we report the positional cloning of maize Miniature5 (Mn5), which encodes a mitochondrial-targeted P-class pentatricopeptide repeat (PPR) protein. Further analysis shows that a missense mutation of Mn5, Mn5Val109, presents in maize populations and correlates with reduced seed size. The Mn5Val109 variant exhibits compromised function in the miniature5 (mn5-ref) mutant, failing to trans-splice mitochondrial nad1 intron1, drastically reducing the abundance and activity of respiratory complex I, accompanied by disorganized mitochondrial cristae. Mn5 directly binds to domain IV of the pre-nad1.1 transcript. Notably, this binding site is located downstream of the previously presumed 3'-terminus bound by MITOCHONDRIA STABILITY/PROCESSING PPR FACTOR1 (MSP1), thus redefining the 3'-end of the nad1.1 pre-RNA. Furthermore, Mn5 physically interacts with the maturases ZmnMAT1 and ZmnMAT3, as well as the PPR proteins PPR-SMR1 and SPR2, which are broadly involved in organellar group II intron splicing. Together, our results suggest that Mn5 recruits maturases and PPR proteins to form spliceosomal complexes responsible for the trans-splicing of nad1 intron1. Importantly, natural variations in Mn5 confer differences in seed size control, offering potential for breeding high-yield maize varieties.

Zea mays↗
PubMed2026

The domestication-associated WHP10 tandem cluster of amino acid transporter genes enhances whole-plant protein accumulation in maize.

Improving protein accumulation in maize is essential for sustainable agriculture, yet the regulatory mechanisms governing the intermediate "flow" of organic nitrogen remain elusive. Here, we show that the maize stem acts as a regulatory node for nitrogen allocation. By integrating spatial transcriptomics and metabolomics with quantitative genetics, we demonstrate that a transport-oriented stem program orchestrates the high-protein phenotype of the wild maize accession Ames21814. We identified a major locus, Whole-plant High Protein 10 (WHP10), that encodes a tandemly duplicated cluster of amino acid transporter genes. WHP10 exhibits strong vascular-biased expression, driven by promoter divergence that enhances the wild allele's activity. Functional assays and genetic validation support a model in which the WHP10 cluster facilitates the transport of multiple nitrogen-rich amino acids, thereby contributing to vascular-associated amino acid transport and post-uptake organic-nitrogen partitioning. Our findings establish stem flow as a regulatory layer for protein accumulation and identify WHP10 as a high-value target for precision breeding to enhance whole-plant protein accumulation without compromising grain yield.

Zea mays↗
PubMed2025

Integrative omics of the genetic basis for wheat WUE and drought resilience reveal the function of TaMYB7-A1.

Improving wheat drought resilience and water use efficiency (WUE) is critical for sustaining productivity under increasing water scarcity. Here, we integrate genome-wide association study (GWAS), expression quantitative trait locus (eQTL) mapping, population-transcriptome analysis, and summary-data-based mendelian randomization (SMR), followed by functional validation using indexed EMS mutants and transgenic lines, to systematically identify key WUE regulators. GWAS across water conditions in 228 accessions identifies 73 quantitative trait loci (QTLs) for WUE-traits. Transcriptome profiling of 110 diverse accessions reveals 28 drought-responsive modules. eQTL mapping uncovers 146,966 regulatory variants, including condition-specific hotspots associated with key drought-related pathways. Integrative analysis underscores 85 high-confidence candidate genes, notably TaMYB7-A1. Overexpression of TaMYB7-A1 enhances photosynthesis, WUE, root development, and grain yield under drought condition by activating TaPIP2;2-B1 (water transport), TaRD20-D1 (stomatal regulation), and TaABCB4-B1 (root growth), reflecting reduced water loss and improved physiological resilience. Our study presents a comprehensive regulatory map and robust targets for wheat drought adaptation and resilient cultivar breeding.

Triticum↗
PubMed2026

Dissecting genetic variance structure and evaluating genomic prediction models for single-cross hybrids derived from Stiff Stalk and Non-Stiff Stalk maize heterotic groups.

The early 20th-century discovery of heterosis and the establishment of heterotic groups transformed maize (Zea mays L.) into a keystone of global agriculture. However, maize breeding faces two significant challenges: the gradual decline of general combining ability (GCA) variance within heterotic groups and the impracticality of testing all possible single crosses in the early stages of a breeding program. Here, we developed genomic best linear unbiased prediction (GBLUP)-based multikernel models, using additive and two alternative nonadditive genomic relationship matrices, to estimate the variance components associated with the general combining ability of Stiff Stalk (SS) and Non-Stiff Stalk (NSS) heterotic groups and the specific combining ability arising from their crosses. We further applied these models to predict the performance of untested single-cross combinations under varying levels of parental information. We showed that the SS and NSS groups retained significant GCA variance across traits in both early- and late-maturity groups. The SS group, in contrast, exhibited no detectable GCA variance in grain yield for the intermediate-flowering subset of hybrids, highlighting a limitation for future genetic improvement. Furthermore, our results showed that GBLUP-based multikernel models effectively identified superior hybrids when parental information was available. In the absence of this information, however, these models underperformed compared to covariance-based approaches. Both nonadditive matrices yielded similar results, indicating that they capture comparable genetic relationship patterns despite their distinct formulations. Overall, this study sheds light on the future use of US maize commercial germplasm and demonstrates how GBLUP-based multikernel models can improve the efficiency of hybrid breeding programs.

Zea mays↗
PubMed2026

OsMYB8-OsARF12/25 module fine-tunes tiller angle via auxin signaling pathway in rice.

Tiller angle is a critical determinant of rice plant architecture and significantly impacts grain yield by influencing planting density and photosynthetic efficiency. Although auxin signaling is known to affect tiller angle in rice, the detailed regulatory networks remain largely unknown. In this study, we identify OsMYB8, an R2R3-MYB transcription factor, as a positive regulator of rice tiller angle. Functional analyses revealed that loss-of-function mutants of OsMYB8 exhibited reduced tiller angles and a more compact architecture, while overexpression of OsMYB8 resulted in more expanded tiller angles. Further investigations found that OsMYB8 might negatively regulate the shoot gravitropic response by disrupting asymmetric auxin distribution. At the molecular level, OsMYB8 directly binds to the promoters of 2 auxin response factors, OsARF12 and OsARF25, and represses their transcription. Genetic analyses confirmed that OsMYB8 acts upstream of OsARF12 and OsARF25 in regulating rice tiller angle. Our finding elucidates a previously uncharacterized OsMYB8-OsARF12/25 transcriptional module that fine-tunes auxin signaling to regulate tiller angle in rice, and offers valuable genetic targets for the optimization of rice architecture and yield potential.

Oryza↗
PubMed2026

Powering Genome Editing in Rice by Harnessing Promising Gene Resources: A Comprehensive Roadmap.

The imprecise breeding methods including recombination breeding, physical/chemical mutagenesis, and marker-assisted breeding have been extensively utilized for trait improvement of rice crop. Despite tremendous progress made through these breeding methods, the critical issues, such as linkage drag, unintended phenotype, and longer duration of time required to breed a cultivar, have been the major limitations. Among the new breeding technologies, genome editing (GE) has become the most promising approach because of its specificity, precision, and speed. Despite its transformative potential, genome editing continues to face several limitations in crop improvement. These include well-recognized policy challenges, such as biosafety regulations and intellectual property constraints, alongside technical barriers like inefficient tissue culture and transformation systems. Additionally, researchers remain constrained by the limited availability of precise gene information necessary for accurate targeted editing and effective trait enhancement. This review presents an analysis of genes that regulate abiotic and biotic stresses, yield, grain quality and nutrition, plant architecture, nutrient absorption and use efficiency, and other agronomically important traits of rice. The trait-wise probable target genes for genome editing have been discussed in detail. This review will serve as a ready reckoner for rice researchers and funding agencies.

Oryza↗
PubMed2025

Rice ETHYLENE RESPONSE FACTOR 101 increases leaf angle by upregulating BRASSINOSTEROID UPREGULATED 1.

The leaf angle (LA) is a critical component of plant architecture that directly influences photosynthetic efficiency and grain yield. In the present study, we found that ETHYLENE RESPONSE FACTOR 101 (OsERF101), an APETALA2/ethylene response factor, plays a role in LA formation. A null mutation in OsERF101 resulted in reduced LA, whereas transgenic plants overexpressing OsERF101 (OsERF101-OEs) exhibited increased LA. OsERF101 increased the development of the adaxial lamina joint (LJ). Transactivation assays and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis indicated that OsERF101 activated BRASSINOSTEROID UPREGULATED 1 (OsBU1) transcription by directly binding to its promoter. However, OsERF101 expression was suppressed by exogenous brassinosteroid (BR) treatment and elevated endogenous brassinolide (BL) levels during LJ development. Additionally, OsERF101 downregulated the expression of BR biosynthesis genes, including Brassinosteroid-deficient dwarf2 (OsBRD2) and CYP90B2/OsDWARF4, leading to reduced levels of endogenous BL, the most active BR, in OsERF101-OEs. These findings suggested that OsERF101 mediates a negative feedback loop that balances endogenous BR levels and signaling. Collectively, rice plants have evolved diverse regulatory mechanisms involving OsERF101 to tune LA formation and optimize plant architecture finely.

Oryza↗
PubMed2025

ONAC005 enhances salt stress tolerance by promoting suberin deposition in root endodermis.

Salt stress impairs photosynthetic efficiency and consequently reduces the growth, development, and grain yield of crop plants. The formation of hydrophobic barriers in the root endodermis, including the suberin lamellae and Casparian strips, is a key adaptive strategy for salt stress tolerance. In this study, we identified the role of the rice NAC transcription factor, ONAC005, in salt stress tolerance. ONAC005 expression was induced by NaCl and abscisic acid (ABA). Expression analysis using the β-glucuronidase reporter gene driven by the ONAC005 promoter revealed that ONAC005 is predominantly expressed in the stele and endodermis of rice roots. The null mutation of ONAC005 increased sodium ion levels in the shoots and roots, indicating susceptibility to salt stress, whereas ONAC005 overexpression enhanced tolerance to salt stress by reducing sodium ion accumulation. Yeast one-hybrid, chromatin immunoprecipitation, and dual-luciferase assays demonstrated that ONAC005 upregulates the expression of trehalose-6-phosphate synthase 8 (OsTPS8) by directly binding to its promoter region, leading to increased trehalose accumulation. ONAC005 enhances the formation of the root hydrophobic barrier by upregulating OsTPS8 expression under salt stress. Furthermore, considering the altered expression of ABA signaling and responsive genes, ONAC005 regulates the expression of genes in specific stress-responsive pathways that are independent of OsTPS8-mediated signaling. These results indicate that ONAC005 positively regulates hydrophobic barrier formation in the roots, thereby enhancing salt stress tolerance in rice.

Oryza↗
PubMed2025

Multi-omics analysis of ubiquitin E2 genes in Setaria: evidence for the roles of E2 genes in various aspects of plant development, stress tolerance, and domestication.

Ubiquitin E2 enzymes (E2s) are critical mediators in the ubiquitination cascade, a post-translational modification process that regulates protein stability, activity, localization, and degradation. Here, we analyzed the E2 gene family in foxtail millet (Setaria italica), integrating comparative genomics, transcriptomics, and functional studies. A total of 52 E2 genes were identified and classified into four subfamilies (UBC, UEV, SCE, and RCE) based on phylogenetic analysis across 49 species. Notably, foxtail millet exhibited significant gene expansion. Tissue-specific expression profiling revealed distinct roles of E2 genes in growth and development. Haplotype and quantitative trait loci analyses demonstrated that several E2 genes, including SiUBC39, are associated with key agronomic traits, such as plant height, flowering time, and stress tolerance. Using CRISPR/Cas9, we validated the functional role of SiUBC39, finding that its disruption led to phenotypes resembling wild species (Setaria viridis), such as early flowering and reduced plant height and grain yield. IP-MS and transcriptome analysis revealed SiUBC39's involvement in growth and development regulation, drought stress response, and immune response. SiPIP2;1 and SiEhd2 were identified as interactors of SiUBC39, explaining its roles in blast resistance and flowering time control. Furthermore, domestication analysis identified an A/G mutation in the SiUBC39 promoter TATA box, distinguishing domesticated and wild haplotypes and highlighting its role in domestication selection. This study underscores the essential roles of E2 genes in regulating crop agronomic traits and stress responses, providing valuable insights for genetic improvement in foxtail millet and other cereals.

Setaria Plant↗
PubMed1979

High resolution scintiautoradiography.

An electron microscopic scintiautoradiographic method for studying histological sections is reported. An increase in the silver grain yield is attained by using a scintillator in embedding medium. The amplification effect for 3H-labeling reaches 3-fold and for 14C reaches a 15-fold. No lessening of autoradiographic resolution was observed. On the basis of these preliminary results only qualitative evaluation of data is discussed.

Animals↗
PubMed2024

QTL mapping for seed vigor-related traits under artificial aging in common wheat in two introgression line (IL) populations.

BACKGROUND: Seed vigor recognized as a quantitative trait is of particular importance for agricultural production. However, limited knowledge is available for understanding genetic basis of wheat seed vigor. METHODS: The aim of this study was to identify quantitative trait loci (QTL) responsible for 10 seed vigor-related traits representing multiple aspects of seed-vigor dynamics during artificial aging with 6 different treatment times (0, 24, 36, 48, 60, and 72 h) under controlled conditions (48 °C, 95% humidity, and dark). The mapping populations were two wheat introgression lines (IL-1 and IL-2) derived from recipient parent (Lumai 14) and donor parent (Shaanhan 8675 or Jing 411). RESULTS: A total of 26 additive QTLs and 72 pairs of epistatic QTLs were detected for wheat seed-vigor traits. Importantly, chromosomes 1B and 7B contained several co-located QTLs, and chromosome 2A had a QTL-rich region near the marker Xwmc667, indicating that these QTLs may affect wheat seed vigor with pleiotropic effects. Furthermore, several possible consistent QTLs (hot-spot regions) were examined by comparison analysis of QTLs detected in this study and reported previously. Finally, a set of candidate genes for wheat seed vigor were predicted to be involved in transcription regulation, carbohydrate and lipid metabolism. CONCLUSION: The present findings lay new insights into the mechanism underlying wheat seed vigor, providing valuable information for wheat genetic improvement especially marker-assisted breeding to increase seed vigor and consequently achieve high grain yield despite of further investigation required.

Triticum↗
PubMed2026

Heat stress impact on rice reproductive processes: challenges and new approaches.

Heat stress represents one of the most severe abiotic constraints to rice (Oryza sativa L.) productivity and is expected to intensify under ongoing climate change, particularly affecting the reproductive phase and leading to substantial yield and grain quality losses. This review synthesizes current knowledge on the impacts of heat stress on rice reproduction, with a focus on both male and female reproductive structures and their interactions. Evidence from anatomical, physiological, transcriptomic, and metabolomic studies to describe how elevated temperatures disrupt key reproductive processes, including microsporogenesis, anther dehiscence, pollen viability, pollen-pistil interactions, fertilisation, and embryo sac development were integrated in this review. It further discusses the genotype-dependent differences in reproductive thermotolerance; and key genes, metabolites, and pathways associated with heat stress perception, signalling, and tolerance are highlighted. Finally, it is briefly discussed how recent advances in breeding strategies, functional genomics and genome-editing technologies, particularly CRISPR-based approaches, are providing new opportunities to enhance reproductive resilience to heat stress and how it is essential to close the existing molecular knowledge gaps in the development of heat-tolerant rice varieties capable of sustaining productivity in a warming climate.

Oryza sativa (L.)↗
PubMed1979

Characterization of endotoxin from the rumen bacterium Megasphaera elsdenii.

Phenol-water extraction of Megasphaera elsdenii, a predominant gram-negative coccus in rumens of cattle fed high-grain diets, yielded material that exhibited typical characteristics of endotoxin. The extract was lethal to mice and to chicken embryos, caused biphasic fever in rabbits, leukopenia in mice, and local and generalized Shwartzman reactions; and induced tolerance to the lethal effect of the endotoxin in mice. The material contained carbohydrate, protein, lipid, phosphorus, and 2-keto-3-deoxyoctonate, but no nucleic acid. The beta-hydroxymyristic acid was absent. Results imply that M elsdenii endotoxin has many biological and chemical characteristics common to enterobacterial endotoxin. However, the median lethal doses in mice and in chicken embryos, and minimal dose required to elicit a local Shwartzman reaction, indicate that M elsdenii endotoxin's potency is low, which may explain why the large gram-negative bacterial population in the rumen of cattle is generally innocuous.

Animals↗
PubMed2026

Assessment of genomic prediction and genetic gain in multi‑population half-sib families in the perennial grass crop intermediate wheatgrass.

The University of Minnesota has been domesticating the perennial forage intermediate wheatgrass (IWG) since 2011 using a combination of conventional methods and modern breeding tools such as genomic selection. Globally, most IWG selection nurseries are spaced-planted individuals of several hundred genotypes whereas commercial fields established for grain production are row-planted panmictic populations. This study evaluated genomic prediction models and estimated genetic gain in yield and agronomic performance of row-planted IWG half-sib families assessed over 3 years and 2 locations, Lamberton and St. Paul, MN, USA. The strongest trait correlation was negative (r = -0.49) between 2023 St. Paul height and 2022 St. Paul seed size. The three St. Paul environments were more similar for plant height and seed size and so were the Lamberton environments yet no specific trend was observed for grain yield. Evaluation of different univariate and multivariate genomic prediction models showed that multivariate models outperformed the best univariate models by 23 percentage points, yet no single multivariate model was the best predictor of all traits. Cross-environment predictions were the best among St. Paul environments and no single environment was the best predictor of the remaining environments. Genetic gain estimates indicated a 20 kg ha-1 increase in grain yield and 3 cm reduction in plant height per breeding cycle. While no single model predicted all traits with high accuracy, results obtained in this study suggest that evaluating IWG sibs in row plots followed by genomic trait predictions could lead to desired breeding progress for desired traits.

Poaceae↗