中华人民共和国农业农村部

Oocyte developmental competence relies on the coordinated progression of nuclear and cytoplasmic maturation, driven by the precise translational regulation of stored maternal mRNAs. Using an integrative transcriptomic and translatomic approach, we characterized the dynamic translational landscape of porcine oocytes during maturation. Through cross-species analysis with human and mouse data, we discovered conserved and species-specific translational programs, highlighting a greater translational resemblance between porcine and human oocytes. Comparative profiling further revealed aberrant maternal mRNA translational activation and degradation during in vitro maturation (IVM) vs. in vivo conditions, including defective translational activation of GPLD1 and HNRNPK, which were pinpointed as mechanisms compromising oocyte quality and embryonic development. To further dissect how translational regulation coordinates oocyte nuclear and cytoplasmic maturation, we employed a dbcAMP-induced cell cycle-synchronized model to identify gene sets with cell cycle-dependent and -independent translational activation. Characterization of these groups identified cytoplasmic polyadenylation element binding protein 1 (CPEB1) as a key orchestrator within the translational regulatory network, where it specifically activates the translation of cell cycle-dependent maternal factors through the cytoplasmic polyadenylation elements (CPEs) within 3’UTRs. Collectively, these findings elucidate key translational mechanisms during porcine oocyte maturation and offer a molecular basis for improving in vitro maturation and reproductive efficiency in livestock.

In facilitative plant-plant interactions, symbiosis play a crucial role in ecosystem functioning through resource sharing. The common mycorrhizal networks (CMNs) are known to play role in nutrient acquisition. Based on our previous observations of CMN integrity fostering tomato biomass and nutrients transfer in tomato-potato onion intercropping system. This experiment investigates how disrupting CMNs modulates transcript abundance of nutrient and hormone transporter genes and phytohormones in tomato within a tomato-potato onion intercropping system. We used Root Exclusion Chambers (RECs) to disrupt the indigenous CMNs and subsequently allowed these symbiotic networks to re-establish. Gene expression related to nutrients and hormones in response to CMN integrity in tomato was analyzed via RT-qPCR, and hormone levels were measured using HPLC. Intercropping with potato onion increased IAA and GA3 in tomato roots and showed higher abundance of nutrient transporter genes related to phosphorus (LePT3, 4, and 5), potassium (LeHAK5), sulphur (Sultr1;1 and 1;2), iron (IRT1 and LeNAS) and zinc (ZIPL and ZIP3L) when CMNs were intact. Disruption of CMNs reduced phytohormone levels and downregulated nutrient transporter genes in tomato, with partial restoration upon re-establishment of CMNs. CMN integrity is associated with modulated expression of nutrient transporter genes and phytohormones levels in tomato grown with potato onion, highlighting the potential role of CMNs in influencing nutrient acquisition and hormonal balance in intercropping system, providing a foundation for further mechanistic studies.

Phosphorus (P) availability is a critical constraint for tea (Camellia sinensis L.) production in acidic red soils of China, primarily due to strong fixation by iron (Fe) and aluminum (Al) oxides. Although intercropping with legumes such as white clover (Trifolium repens L.) has been shown to improve soil fertility, the temporal dynamics by which this practice influences P availability remain poorly understood. This study evaluated the hypothesis that intercropping tea with white clover enhances soil P mobilization over time through microbial and enzymatic processes. A field experiment was conducted in a subtropical tea growing region in China, comparing 1-year (short-term) and 20-year (long-term) tea-white clover intercropping systems, compared to tea monoculture controls. Soil samples were collected to assess chemical properties, microbial biomass carbon (MBC), nitrogen (MBN), phosphorus (MBP), phosphatase enzyme activities, and P fractions. Intercropping significantly increased soil organic matter, total nitrogen, available P, and microbial biomass, with more pronounced improvements under the long-term system. Available P increased by 85

Ammonia (NH3) and nitrous oxide (N2O) are the predominant constituents of reactive N (Nr) emissions from fertilized cropland, with their emission dynamics being characterized by a complex interrelationship. Soil amendment and Nr loss mitigation typically rely on the use or soil organic (e.g., biochar and organic fertilizer (OF)) and inorganic mineral (e.g., phosphogypsum (Pg) and phosphate tailings (Pt)) additives. However, the efficacy of the combined application of organic and inorganic amendments regarding the simultaneous mitigation of soil NH3 and N2O losses remains unclear. To address this knowledge gap, this study employed a static microcosm incubation experiment to analyze the impacts of combinations of biochars, OF, Pt, and Pg on soil NH3 and N2O emissions and regulative mechanisms. Results indicated that the combination of pristine biochar (B1) and Pg significantly reduced both NH3 volatilization and N2O emissions from soil compared with those after application of urea alone or urea with B1. Additionally, the combination of B1 and Pt decreased only N2O emissions. The application of acid-modified biochar (B2) significantly reduced both NH3 and N2O emissions from urea-added soil, while further Pg or Pt supplementation did not yield significantly higher mitigation efficiency of gaseous N losses. Substituting 50

Invasive aquatic plants such as water hyacinth (Eichhornia crassipes [Mart.] Solms) pose significant threats to freshwater ecosystems through obstruction of waterways, alteration of hydrodynamics, and impacts on biodiversity. Effective monitoring is critical for ecosystem protection and sustainable water management. However, learning-based approaches, such as machine learning and deep learning, require extensive annotated training data and substantial computational resources, limiting their suitability for large-scale operational monitoring. To address this, we developed a multitemporal image differencing (MID) approach that leverages the highly dynamic nature of water hyacinth in flowing waters. By analyzing a sequence of multitemporal satellite images, MID directly captures spatial and temporal changes, enabling timely and reliable detection of both established and newly forming patches. MID achieved an overall accuracy of 90.7%, comparable to the random forest classifier at 91.0%, while providing better discrimination of dynamic water hyacinth from stable nontarget vegetation, reflecting its ability to exploit temporal dynamics that single-date classifiers cannot capture. With high computational efficiency, simplicity, and scalability, MID is highly suitable for large-scale operational monitoring of invasive aquatic plants. These results demonstrate that MID is a robust and scalable framework for supporting ecological management and timely decision-making in dynamic freshwater systems.