Wei Ren

Summary: How carbon (sucrose) and nitrogen (amino acid) accumulation is coordinatively controlled in cereal grains remains largely enigmatic. We found that overexpression of the strigolactone (SL) biosynthesis gene CAROTENOID CLEAVAGE DIOXYGENASE 8 (CCD8) resulted in greater ear diameter and enhanced sucrose and amino acid accumulation in maize kernels. Loss of ZmCCD8 function reduced kernel growth with lower sugar and amino acid concentrations. Transcriptomic analysis showed down‐regulation of the transcription factors ZmMYB42 and ZmMYB63 in ZmCCD8 overexpression alleles and up‐regulation in zmccd8 null alleles. Importantly, ZmMYB42 and ZmMYB63 were negatively regulated by the SL signalling component UNBRANCHED 3, and repressed expression of the sucrose transporters ZmSWEET10 and ZmSWEET13c and the lysine/histidine transporter ZmLHT14. Consequently, null alleles of ZmMYB42 or ZmMYB63 promoted accumulation of soluble sugars and free amino acids in maize kernels, whereas ZmLHT14 overexpression enhanced amino acid accumulation in kernels. Moreover, overexpression of the SL receptor DWARF 14B resulted in more sucrose and amino acid accumulation in kernels, down‐regulation of ZmMYB42 and ZmMYB63 expression, and up‐regulation of ZmSWEETs and ZmLHT14 transcription. Together, we uncover a distinct SL signalling pathway that regulates sucrose and amino acid accumulation in kernels. Significant association of two SNPs in the 5′ upstream region of ZmCCD8 with ear and cob diameter implicates its potential in breeding toward higher yield and nitrogen efficiency.

Nitrogen and genotype play vital roles in modulating plant disease resistance. Maize (Zea mays L.) rough dwarf disease (MRDD) is a global viral disease that has caused serious yield losses. However, it is not clear how nitrogen and genotype interact to affect MRDD. We conducted field experiments in 2011 and 2013 to investigate the MRDD incidence, yield, and yield loss rate of 59 maize hybrids under high nitrogen (HN) and low nitrogen (LN). Compared with HN, the MRDD incidence and yield loss rate of S‐sensitive hybrids (nitrogen significantly influenced MRDD incidence in susceptible genotypes) could be significantly reduced by 50.6% and 35.5%, respectively, in LN without compromising maize yield. In contrast, R‐insensitive types (resistant hybrids in which MRDD incidence was unresponsive to nitrogen treatment) could maintain high MRDD resistance and yield at HN. US hybrid 78599 and inbred line Dan340 were the main parental resources of the resistant genotypes, and inbred lines Huangzao4 and Ye478 were the main parental resources of the susceptible genotypes. The physiological mechanism leading to increased MRDD incidence was thought to be higher nitrogen concentrations in the stalks. This study provided theoretical support for using reasonable nitrogen management to control MRDD and breeding MRDD‐resistant maize hybrids.

Plant–microbe interactions are key to nutrient-use efficiency. Root microbes are influenced by rhizosphere soil and plant cultivars. The impact of cultivar-by-nitrogen (N) interactions on the maize-root microbiome remains unclear, yet it is crucial for understanding N use efficiency in maize. This study evaluated the effects of maize cultivars and N forms, along with their interactions, on the diversity and composition of root bacteria and fungi. Additionally, we examined correlations between soil microbes and root metabolites. The maize cultivar Zhengdan 958 (ZD958) showed a positive response to the mixture of nitrate and ammonium N, resulting in increased in biomass, grain yield, shoot N content, grain N content, and root area. In contrast, the cultivar Denghai605 (DH605) did not exhibit a similar response. The diversity and composition of root bacteria and fungi differed between ZD958 and DH605. The N form primarily affected the community structure of rhizospheric fungi in ZD958 and rhizospheric bacteria in DH605, rather than endophytic microbes. A mixed N supply increased the relative abundance of Basidiomycota, which was positively correlated with ZD958 yield. For DH605, a mixed N treatment enhanced nitrification functions involving Bacteroidetes and Proteobacteria, while it reduced the effects of ammonium N supply. The dominant rhizospheric microbes in DH605 showed a stronger response to changes in root metabolites compared to those in ZD958. A mixed N supply increased the content of palmitoleic acid in ZD958 root exudates, facilitating the recruitment of beneficial rhizospheric microbes, which promotes maize growth. In DH605, a mixed N supply decreased the concentration of sphinganine, which is significantly correlated with Acidobacteria (negatively), Proteobacteria (negatively), Bacteroidetes (positively), and TM7 (positively). Our findings suggest that different maize cultivars respond differently to N forms, causing distinct rhizospheric microbial effects, and that root metabolites send metabolic signals to regulate and recruit key bacterial and fungal communities.

Plants generally enhance their root growth in the form of greater biomass and/or root length to boost nutrient uptake in response to short-term low nitrogen (LN). However, the underlying mechanisms of short-term LN-mediated root growth remain largely elusive. Our genome-wide association study, haplotype analysis, and phenotyping of transgenic plants showed that the crucial nitrate signaling component NIN-LIKE PROTEIN3.2 (ZmNLP3.2), a positive regulator of root biomass, is associated with natural variations in root biomass of maize (Zea mays L.) seedlings under LN. The monocot-specific gene AUXIN/INDOLE-3-ACETIC ACID14 (ZmAux/IAA14) exhibited opposite expression patterns to ZmNLP3.2 in ZmNLP3.2 knockout and overexpression lines, suggesting that ZmNLP3.2 hampers ZmAux/IAA14 transcription. Importantly, ZmAux/IAA14 knockout seedlings showed a greater root dry weight (RDW), whereas ZmAux/IAA14 overexpression reduced RDW under LN compared with wild-type plants, indicating that ZmAux/IAA14 negatively regulates the RDW of LN-grown seedlings. Moreover, in vitro and vivo assays indicated that AUXIN RESPONSE FACTOR19 (ZmARF19) binds to and transcriptionally activates ZmAux/IAA14, which was weakened by the ZmNLP3.2–ZmARF19 interaction. The zmnlp3.2 ZmAux/IAA14-OE seedlings exhibited further reduced RDW compared to ZmAux/IAA14 overexpression lines when subjected to LN treatment, corroborating the ZmNLP3.2–ZmAux/IAA14 interaction. Thus, our study reveals a ZmNLP3.2–ZmARF19–ZmAux/IAA14 module regulating root biomass in response to nitrogen limitation in maize.

Key Message The genetic architecture of RSA traits was dissected by GWAS and coexpression networks analysis in a maize association population. Abstract Root system architecture (RSA) is a crucial determinant of water and nutrient uptake efficiency in crops. However, the maize genetic architecture of RSA is still poorly understood due to the challenges in quantifying root traits and the lack of dense molecular markers. Here, an association mapping panel including 356 inbred lines were crossed with a common tester, Zheng58, and the test crosses were phenotyped for 12 RSA traits in three locations. We observed a 1.3 ~ sixfold phenotypic variation for measured RSA in the association panel. The association panel consisted of four subpopulations, non-stiff stalk (NSS) lines, stiff stalk (SS), tropical/subtropical (TST), and mixed. Zheng58 × TST has a 2.1% higher crown root number (CRN) and 8.6% less brace root number (BRN) than Zheng58 × NSS and Zheng58 × SS, respectively. Using a genome-wide association study (GWAS) with 1.25 million SNPs and correction for population structure, 191 significant SNPs were identified for root traits. Ninety (47%) of the significant SNPs showed positive allelic effects, and 101 (53%) showed negative effects. Each locus could explain 0.39% to 11.8% of phenotypic variation. By integrating GWAS results and comparing coexpression networks, 26 high-priority candidate genes were identified. Gene GRMZM2G377215, which belongs to the COBRA-like gene family, affected root growth and development. Gene GRMZM2G468657 encodes the aspartic proteinase nepenthesin-1, related to root development and N-deficient response. Collectively, our research provides progress in the genetic dissection of root system architecture. These findings present the further possibility for the genetic improvement of root traits in maize.

Effective in-season crop nitrogen (N) status diagnosis is important for precision crop N management, and remote sensing using an unmanned aerial vehicle (UAV) is one efficient means of conducting crop N nutrient diagnosis. Here, field experiments were conducted with six N levels and six maize hybrids to determine the nitrogen nutrition index (NNI) and yield, and to diagnose the N status of the hybrids combined with multi-spectral data. The NNI threshold values varied with hybrids and years, ranging from 0.99 to 1.17 in 2018 and 0.60 to 0.71 in 2019. A proper agronomic optimal N rate (AONR) was constructed and confirmed based on the measured NNI and yield. The NNI (R² = 0.64–0.79) and grain yield (R² = 0.70–0.73) were predicted well across hybrids using a random forest model with spectral, structural, and textural data (UAV). The AONRs calculated using the predicted NNI and yield were significantly correlated with the measured NNI (R² = 0.70 and 0.71 in 2018 and 2019, respectively) and yield (R² = 0.68 and 0.54 in 2018 and 2019, respectively). It is concluded that data fusion can improve in-season N status diagnosis for different maize hybrids compared to using only spectral data.

Key message A new strategy that integrated multiple public data resources was established to construct root gene co-expression network and mine genes regulating root system architecture in maize. A root gene co-expression network, containing 13,874 genes, was constructed. A total of 53 root hub genes and 16 priority root candidate genes were identified. One priority root candidate was further functionally verified using overexpression transgenic maize lines. Abstract Root system architecture (RSA) is crucial for crops productivity and stress tolerance. In maize, few RSA genes are functionally cloned, and effective discovery of RSA genes remains a great of challenge. In this work, we established a strategy to mine maize RSA genes by integrating functionally characterized root genes, root transcriptome, weighted gene co-expression network analysis (WGCNA) and genome-wide association analysis (GWAS) of RSA traits based on public data resources. A total of 589 maize root genes were collected by searching well-characterized root genes in maize or homologous genes of other species. We performed WGCNA to construct a maize root gene co-expression network containing 13874 genes based on public available root transcriptome data, and further discovered the 53 hub genes related to root traits. In addition, by the prediction function of obtained root gene co-expression network, a total of 1082 new root candidate genes were explored. By further overlapping the obtained new root candidate gene with the root-related GWAS of RSA candidate genes, 16 priority root candidate genes were identified. Finally, a priority root candidate gene, Zm00001d023379 (encodes pyruvate kinase 2), was validated to modulate root open angle and shoot-borne roots number using its overexpression transgenic lines. Our results develop an integration analysis method for effectively exploring regulatory genes of RSA in maize and open a new avenue to mine the candidate genes underlying complex traits.