Stay-green trait is an important agronomic characteristic closely related to high yield, good quality, and stress resistance of maize. This study explored the differences in nitrogen uptake and translocation of different stay-green maize hybrids, aiming to provide a theoretical basis for the physiological mechanism of high nitrogen efficiency in maize.

The tested materials were the stay-green hybrid Shandan 650 and the non-stay-green hybrid Zhengdan 958. In 2023, 6 N treatments were applied: N1 (0 kg·hm^-2), N2 (60 kg·hm^-2), N3 (120 kg·hm^-2), N4 (180 kg·hm^-2), N5 (240 kg·hm^-2), and N6 (300 kg·hm^-2). In 2024, a nitrogen×density interaction experiment was conducted with three N levels—low N (LN, 0 kg·hm^-2), medium N (MN, 180 kg·hm^-2), and high N (HN, 240 kg·hm^-2)—and two planting densities—low density (LD, 60000 plants·hm^-2) and high density (HD, 75000 plants·hm^-2). After the silking stage of maize, indicators were determined for each treatment, such as SPAD value of ear leaves, total number of green leaves per plant, dry matter, and nitrogen accumulation in vegetative organs and grains. Meanwhile, nitrogen absorption and translocation rates as well as nitrogen use efficiency-related indicators were analyzed.

Grain yield of both hybrids initially increased and then stabilized with rising N rates, with Shandan 650 consistently outperforming Zhengdan 958 across all N and density treatments. Post-silking, Shandan 650 exhibited faster chlorophyll degradation (SPAD decline: 65.1% vs. 49.9%) and greater green leaf loss than Zhengdan 958, particularly under low N. Shandan 650 demonstrated superior N remobilization efficiency, especially under low N and high density, with significantly higher N translocation from leaves to grains. Overall, Shandan 650 achieved significantly higher N remobilization efficiency, nitrogen use efficiency, nitrogen agronomic efficiency, and nitrogen harvest index than Zhengdan 958. Furthermore, under high-density planting conditions, reasonable nitrogen reduction further enhanced its nitrogen efficiency performance.

The functional stay-green maize variety Shandan 650 maintains consistent greenness and photosynthetic capacity until a certain period before physiological maturity, at which point a rapid decline occurs along with nitrogen remobilization. Its strong nitrogen translocation capacity in vegetative organs enhances nitrogen translocation rate and nitrogen use efficiency, and higher nitrogen efficiency could be achieved under reasonable nitrogen reduction and density increase.

Ear traits are important components of grain yield in maize. Dissecting their genetic basis and mining significant SNPs using genome-wide association study (GWAS) can provide references for cloning functional genes and breeding high-yield maize varieties.

A total of 115 superior inbred lines from Shaan A group and Shaan B group, as well as four domestic backbone lines were selected as parents. Based on NCⅡ genetic design, an association population consisting of 442 hybrids was constructed, which was planted in two different environments to collect phenotype data of ear traits. Meanwhile, all parental lines were sequenced by the tunable genotyping by sequencing (tGBS) protocols. According to the genotype of inbred lines, altogether 19 461 high-quality SNPs were inferred in the association population. Then, GWAS was performed using 19 461 SNPs and phenotype data by three models including additive, dominance and epistasis, respectively. Combining with the transcriptome data of maize ear related tissues in the public database and the annotation information of genes, candidate genes were predicted.

Phenotypic data analysis showed that eight ear traits followed a continuous distribution, and there were 3.78%-45.25% of phenotypic variation. Analysis of variance indicated that environment and genotype effects reached an extremely significant level (P<0.001), and the range of broad-sense heritability was from 54.15% to 68.89%. And there were significantly positive or negative correlations among ear traits of hybrids. In total, 16, 3, 79 significant SNPs/pairs were identified under additive, dominant, and epistatic models, respectively. The significant loci detected by the three models cumulatively explained 38.21%-60.69% of the phenotypic variation of each trait. The cumulative phenotypic variation of significant SNP detected by additive model and epistatic model was 0.00-41.26% and 15.18%-45.36%, respectively. Effect analysis of significant SNPs identified by additive and dominant models showed most SNPs with additive or partial dominance effects, and only two with over-dominance effects. Further, only seven single-SNPs and five interaction pairs explained more than 5% of the phenotypic variation, and 17 candidate genes were predicted based on the SNP locations and gene expression information.

Ear traits of maize hybrids were mainly affected by additive and epistasis effects, but less by dominance effects. Multiple SNPs identified by additive and dominant models showed additive and partially dominance effects, and aggregating favorable alleles of these SNPs could improve the target traits.

Genetic improvement for efficient utilization of maize nutrients represents a crucial method to ensure national food security. Exploring quantitative trait locus (QTL) and related candidate genes of nitrogen use efficiency can provide a theoretical basis for improving the efficiency of nitrogen fertilizer in maize and cultivating high-yield and high-efficiency maize varieties.

In this study, QTL mapping analysis in one recombinant inbred line (RIL) population constructed by KA105 and KB024 was performed for grain yield under two different nitrogen treatments, including the derived traits partial factor productivity from applied nitrogen (PFPN), low nitrogen tolerance coefficient (LNTC) and nitrogen agronomic efficiency (NAE). Concurrently, integrating the seedling transcriptome data of the parent KA105 under nitrogen treatment, differentially expressed genes were identified, and candidate genes associated with maize nitrogen use efficiency were mined through co-expression analysis. Subsequently, the selected candidate genes were validated using qRT-PCR.

Through mapping analysis, a total of 36 QTLs distributed across different chromosomes were detected, explaining 1.63% to 17.26% of the phenotypic variation. Among these, eight major QTLs with a phenotypic variation explanation rate exceeding 10% were identified, along with seven genetically stable QTLs commonly identified across different traits or environments. Notably, qNNGYP1 located on chromosome 1 has been repeatedly detected in previous studies, with a phenotypic explanation rate of up to 11.73%. Additionally, other QTLs (qNNGYP1, qPFPN1) co-located in this interval across different environments, suggesting it as a focal region for further investigation. Combining transcriptome data of seedlings under low nitrogen stress, 39 differentially expressed genes within these QTL intervals were identified, and 6 key genes were identified through co-expression network prediction. The result of qRT-PCR indicated that the expression trends of the candidate genes under both nitrogen treatments were consistent with the transcriptome data. Specifically, GRMZM2G366873 was involved in the regulation of auxin homeostasis and may participate in maize responses to low nitrogen stress, drought stress, and boron stress through auxin signal transduction, also regulating ear length. GRMZM2G414192 was involved in the response of the photosynthetic system to low nitrogen stress and was regulated by brassinosteroids. GRMZM2G414043 was associated with maize grain length and biomass, while GRMZM2G040642 may be involved in the long-distance signal transduction of nitrogen.

In summary, a total of 36 QTLs were identified, distributed across chromosomes 1, 4, 5, 7, 8, and 9, including eight major QTLs (PVE>10%). The candidate genes GRMZM2G366873, GRMZM2G414192, GRMZM2G414043, and GRMZM2G040642 were identified as potential genes for maize nitrogen efficiency.