Maize grain yield depends mainly on the photosynthetic efficiency of functional leaves, which is controlled by an array of gene networks and other factors, including environmental conditions. MicroRNAs (miRNAs) are small RNA molecules that play important roles in plant developmental regulation. A few senescence-associated miRNAs (SA-miRNAs) have been identified as important participants in regulating leaf senescence by modulating the expression levels of their target genes. To elucidate miRNA roles in leaf senescence and their underlying molecular mechanisms in maize, a stay-green line, Yu87-1, and an early leaf senescence line, Early leaf senescence-1 (ELS-1), were selected as experimental materials for the differential expression of candidate miRNAs. Four small RNA libraries were constructed from ear leaves at 20 and 30 days after pollination and sequenced by Illumina deep sequencing technology. Altogether, 81 miRNAs were detected in both lines. Of these, 16 miRNAs of nine families were differentially expressed between ELS-1 andYu87-1. The phenotypic and chlorophyll content analyses of both lines identified these 16 differentially expressed miRNAs as candidate SA-miRNAs. In this study, 16 candidate SA-miRNAs of ELS-1 were identified through small RNA deep sequencing technology. Degradome sequencing results indicated that these candidate SA-miRNAs may regulate leaf senescence through their target genes, mainly transcription factors, and potentially control chlorophyll degradation pathways. The results highlight the regulatory roles of miRNAs during leaf senescence in maize.

The remediation of lead (Pb)-contaminated soils through eco-friendly strategies is critical for sustainable agriculture. This study investigated the role of arbuscular mycorrhizal fungi (AMF) in enhancing maize tolerance to Pb stress and modulating rhizosphere microbial communities. A pot experiment was conducted with maize (Baiyu833) under four Pb concentrations (0, 900, 1800, 2700 mg·kg⁻¹) and three AMF treatments: non-inoculation (Non), Funneliformis mosseae (Fm), or Rhizophagus intraradices (Ri). The results demonstrated that AMF inoculation significantly increased plant biomass, boosted antioxidant enzyme activities (SOD, POD), and reduced malondialdehyde (MDA) levels, mitigating Pb-induced oxidative stress. AMF restricted Pb translocation to aerial parts, with root Pb accumulation reaching 2110.76 mg·kg⁻¹ (Fm) and 2090.56 mg·kg⁻¹ (Ri) under Pb2700, enhancing phytostabilization. High-throughput sequencing revealed that AMF inoculation enriched α-diversity indices and restructured bacterial communities, favoring beneficial taxa like Promicromonospora, which are linked to heavy metal resistance and plant growth promotion. Principal coordinate analysis highlighted distinct clustering of microbial communities driven by AMF, emphasizing their role in alleviating Pb toxicity. These findings underscore that AMF enhance maize resilience to Pb by regulating antioxidant defense, immobilizing Pb in roots, and recruiting stress-tolerant rhizosphere microbiomes. This study provides insights into AMF-assisted phytoremediation as a sustainable strategy for Pb-contaminated soils.

Cadmium (Cd) significantly influences the morphological, physiological traits, and transport capacity of plants, but the underlying mechanism of Cd stress still remains to be further studied. In this study, physiological, transcriptomic, and metabolomic analyses were conducted to examine the morphological and physiological traits of two elite maize inbred lines, Chang7_2 (C7_2, a Cd-resistant line) and Zheng58 (Z58, a Cd-sensitive line) under control and Cd stress conditions. The results of morphological traits indicated that C7_2 reduced by 9.50–29.60% under Cd stress, whereas Z58 displayed more pronounced morphological changes ranging from 10.12 to 41.72% under Cd stress. Physiological assessments revealed that C7_2 maintained relatively stable antioxidant enzyme activity, while Z58 demonstrated more rapid alterations in the antioxidant system under Cd stress. Transcriptomic analysis identified 3030 differentially expressed genes (DEGs) unique to C7_2 and 4298 DEGs unique to Z58, with 1746 common DEGs shared between the two lines. Functional annotation revealed that the unique DEGs in C7_2 were mainly enriched in plant hormone signal transduction, plant–pathogen interactions, and the MAPK signaling pathway, while the unique DEGs in Z58 were mainly enriched in ribosome-related functions, plant hormone signal transduction, and phenylpropanoid biosynthesis. Metabolomic analysis identified 12 superclasses encompassing 896 metabolites in C7_2 and Z58, primarily including lipids and lipid-like molecules, organic acids and derivatives, as well as organoheterocyclic compounds. Analysis of differentially accumulated metabolites (DAMs) revealed fewer DAMs were accumulated in C7_2 under Cd stress. Further analysis identified that the three pathways of GPI anchor biosynthesis, glycerophospholipid metabolism, and purine metabolism were among the top 10 metabolic pathways in C7_2 and Z58. The integrative analysis highlighted the crucial roles of phenylpropanoid biosynthesis and zeatin biosynthesis in C7_2 for resistance to Cd stress. This study provides novel insights into the molecular and metabolic pathways underlying Cd tolerance in maize by integrating transcriptomic and metabolomic analyses of two contrasting inbred lines, providing a theoretical foundation for the future breeding of Cd-tolerant varieties.

Maize breeding is greatly affected by hybrid vigor, a phenomenon that hybrids exhibit superior performance than parental lines. The immortalized F₂ population (IMF₂) is ideal for the genetic dissection and prediction of hybrid performance. Here, in this study, we conducted the QTL mapping and genomic prediction of six traits related to plant architecture using an IMF₂ population. Broad-sense heritability of these traits ranged from 0.85 to 0.94. Analysis of genetic effects showed that additive variance was the main contributor to phenotypic variations. The mapping of quantitative trait loci (QTLs) revealed 10 to 16 QTLs (including pleiotropic loci and epistatic QTLs) for the six traits. Additionally, we identified 15 fine-tuning QTLs for plant height (PH). For genomic prediction (GP), the model of additive and dominance (AD) exhibited higher prediction accuracy than those fitting general combining ability (GCA) and its combination with special combining ability (SCA) effects for all tested traits. And adding the epistasis (E) effect into the AD model did not significantly increase its prediction accuracy. Moreover, the identified 15 fine-tuning QTLs of PH, which exerted large genomic prediction effects, were verified by the marker effect of GP. Our results not only provide an approach for the fine-mapping of fine-tuning QTLs but also serve as references for GP breeding in crops.