Kaijian Huang

Background: Maize (Zea mays L.) serves as a crucial dietary source of folate for humans. However, the genetic regulatory mechanisms underlying the natural variation of folate in maize remain poorly understood. Here, we integrated multi-omics approaches to elucidate the molecular mechanisms governing folate accumulation in maize.Methods: A total of 380 maize kernels representing 190 maize inbred lines from China, Thailand, Mexico, and Peru were collected. RNA-seq was conducted on 380 maize kernel samples, and folate content was quantified using high-performance liquid chromatography (HPLC). The samples were stratified into high and low folate groups based on median folate values. Differentially expressed genes (DEGs) were identified between the two groups identified. Candidate genes associated with folate accumulation were further located by integrating transcriptome-wide association studies (TWAS) and genome-wide association studies (GWAS) analyses. Finally, quantitative real-time PCR (qRT-PCR) was employed to validate the expression patterns of these candidate genes.Results: A total of 137 DEGs that exhibited significant differences between the high-folate and low-folate groups were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that these genes were significantly enriched in pathways related to phenylpropanoid biosynthesis, oxidoreductase activity, and stress response. GWAS identified 2,153 candidate genes associated with folate traits (P ≤ 1.00E-05). Through the integration of DEGs and the intersection of genes identified by GWAS, seven candidate genes were further identified. In addition, TWAS analysis further identified 13 causal genes associated with the candidate genes, which are involved in folate biosynthesis. In addition, the expression levels of these candidate genes were validated by qRT-PCR experiments, suggesting significantly higher expressions in the high folate group compared to the low-folate group.Conclusion: This study identifies key regulatory genes potentially influencing folate accumulation in maize and provides critical insights for the development of biofortified maize varieties with enhanced nutritional value.

Increasing planting density is one of the most important strategies for generating higher maize yields. Moderate leaf rolling decreases mutual shading of leaves and increases the photosynthesis of the population and hence increases the tolerance for high-density planting. Few genes that control leaf rolling in maize have been identified, however, and their applicability for breeding programs remains unclear. Here we identified a maize abaxially rolled leaf1 (arl1) mutant with extreme abaxially rolled leaves and found that the size of the bulliform cells within the adaxial leaf blade surface increased in the arl1 mutant. Bulk segregation analysis mapping in an F₂ population derived from a single cross between arl1 and inbred line Gui18421 with normal leaves identified the arl1 locus on chromosome 2. Sequential fine-mapping delimited the arl1 locus to a 233.56-kb genomic interval containing three candidate genes. Sequence alignment between arl1 and Gui18421 identified an 8-bp insertion in the coding region of Zm00001eb082500, which led to a frame shift causing premature transcription termination in arl1 mutant. Meanwhile, both deep sequencing and Sanger sequencing showed that Zm00001eb082520 was present in Gui18421 but was absent in arl1. A pair of near isogenic lines (NILs) carrying the Gui18421 allele (NIL^Gui18421) and the arl1 allele (NIL^arl1) were developed, and the leaves of NIL^arl1 plants had greater light transmission and photosynthetic rate in the middle and lower canopy than did those of NIL^Gui18421 plants under high-density planting. Furthermore, NIL^arl1 had a higher seed setting rate, more kernels per ear, and an increased kernel weight per ear than NIL^Gui18421, and the grain yield of NIL^arl1 was not affected as the planting density increased, suggesting that the arl1 locus can be used for genetic improvement of high-density planting tolerance. Taken together, the identification of arl1 and evaluation of yield-related traits for NIL^Gui18421 and NIL^arl1 provide an excellent target for future maize improvement.

Water deficit is a key limiting factor for limiting yield in maize (Zea mays L.). It is crucial to elucidate the molecular regulatory networks of stress tolerance for genetic enhancement of drought tolerance. The mechanism of drought tolerance of maize was explored by comparing physiological and transcriptomic data under normal conditions and drought treatment at polyethylene glycol- (PEG-) induced drought stress (5, 10, 15, and 20) in the root during the seedling stage. The content of saccharide, SOD, CAT, and MDA showed an upward trend, proteins showed a downward trend, and the levels of POD first showed an upward trend and then decreased. Compared with the control group, a total of 597, 2748, 6588, and 5410 differentially expressed genes were found at 5, 10, 15, and 20 PEG, respectively, and 354 common DEGs were identified in these comparisons. Some differentially expressed genes were remarkably enriched in the MAPK signaling pathway and plant hormone signal transduction. The 50 transcription factors (TFs) divided into 15 categories were screened from the 354 common DEGs during drought stress. Auxin response factor 10 (ARF10), auxin-responsive protein IAA9 (IAA9), auxin response factor 14 (ARF14), auxin-responsive protein IAA1 (IAA1), auxin-responsive protein IAA27 (IAA27), and 1 ethylene response sensor 2 (ERS2) were upregulated. The two TFs, including bHLH 35 and bHLH 96, involved in the MAPK signal pathway and plant hormones pathway, are significantly upregulated in 5, 10, 15, and 20 PEG stress groups. The present study provides greater insight into the fundamental transcriptome reprogramming of grain crops under drought.

Maize (Zea mays L.) is the most important food security crop worldwide. Northern corn leaf blight (NCLB), caused by Exserohilum turcicum, severely reduces production causing millions of dollars in losses worldwide. Therefore, this study aimed to identify significant QTLs associated with NCLB by utilizing next-generation sequencing-based bulked-segregant analysis (BSA). Parental lines GML71 (resistant) and Gui A10341 (susceptible) were used to develop segregating population F₂. Two bulks with 30 plants each were further selected from the segregating population for sequencing along with the parental lines. High throughput sequencing data was used for BSA. We identified 10 QTLs on Chr 1, Chr 2, Chr 3, and Chr 5 with 265 non-synonymous SNPs. Moreover, based on annotation information, we identified 27 candidate genes in the QTL regions. The candidate genes associated with disease resistance include AATP1, At4g24790, STICHEL-like 2, BI O 3-BIO1, ZAR1, SECA2, ABCG25, LECRK54, MKK7, MKK9, RLK902, and DEAD-box ATP-dependent RNA helicase. The annotation information suggested their involvement in disease resistance-related pathways, including protein phosphorylation, cytoplasmic vesicle, protein serine/threonine kinase activity, and ATP binding pathways. Our study provides a substantial addition to the available information regarding QTLs associated with NCLB, and further functional verification of identified candidate genes can broaden the scope of understanding the NCLB resistance mechanism in maize.