Search

Maize is one of the most successful crops with regard to the utilization of heterosis. The haploid induction technique is one of the fastest methods to obtain pure maize material at the present stage. However, the molecular mechanism of haploid doubling is rarely reported. In this study, we treated B73 and ZNC442 haploid young shoots with colchicine for 0 h, 6.2 h, and 10 h, and analyzed the differentially expressed genes (DEGs). We found that colchicine treatment for 6.2 h and 10 h compared to 0 h resulted in a total of 4868 co-DEGs. GO enrichment analysis and KEGG metabolic pathway analysis found significantly enriched 282 GO terms and 31 significantly pathways, respectively. Additionally, The GO term and KEGG pathway genes of spindle, cytoskeleton, microtubules and nuclear division were selected for analysis, and three candidate genes were screened by taking intersections. Zm00001d033112, Zm00001d010525, and Zm00001d043386 were annotated as kinesin-associated protein 13, kinesin-like protein KIN-10C, and kinesin light-chain LC6, respectively. The real-time fluorescence quantification (RT-PCR) results revealed that Zm00001d033112, Zm00001d010525, and Zm00001d043386 had the same trends as RNA-seq. Interestingly, Zm00001d033112 is homologous gene AT3G20150 in Arabidopsis, which was involved in the regulation of chromosome movement and mitotic spindle assembly. Our study suggests that kinesin genes may play an important role in doubling chromosomes, thus providing valuable information for future studies on the molecular mechanisms of chromosome doubling in maize. [ABSTRACT FROM AUTHOR]

The pollution of heavy metals is extremely serious in China, including zinc (Zn), copper (Cu), lead (Pb), and cadmium (Cd). Heavy-metal-transporting ATPase (HMA) belongs to a subfamily of the P-ATPase family, which absorbs and transports Zn, Cu, Pb, and Cd in plants. Here, we describe a ZmHMA-encoding HMA family protein that positively regulates Cd and Zn tolerance. The real-time fluorescence quantification (RT-PCR) results revealed that ZmHMA3 had a high expression in B73, and the expression of ZmHMA3 was sensitive to Cd in yeast cells, which was related to Cd accumulation in yeast. Additionally, the Arabidopsis thaliana homologous mutants of AtHMA2 showed Cd sensitivity compared with WT. The overexpressing ZmHMA3 plants showed higher tolerance under Cd and Zn stresses than the wild type. The overexpression of ZmHMA3 led to higher Cd and Zn accumulation in tissues based on the subcellular distribution analysis. We propose that ZmHMA3 improves maize tolerance to Cd and Zn stresses by absorbing and transporting Cd and Zn ions. This study elucidates the gene function of the ZmHMA3 response to Cd and Zn stress and provides a reference for improving the characteristics of heavy metals enrichment in existing maize varieties and the plant remediation technology of heavy-metal-contaminated soil. [ABSTRACT FROM AUTHOR]

Here, four normalized difference water index (NDWI) variants, i.e., NDWI(860,970), NDWI(860,1240), NDWI(860,1640), and NDWI(1240,1640) are generated from the corn-oriented PROSAIL radiative transfer model. It is found that, instead of the linear relationship derived in previous studies, corn canopy water content (CWC) is best approximated as an exponential function of NDWI. Following the analysis of the PROSAIL-generated results, a newly optimized NDWI-based scheme is proposed for estimating corn CWC according to variations in the performance of the four NDWI variants under different CWC conditions. Validation results based on independent field data from the SMEX02, HiWATER2012, and Baoding2018 field experiments verify that this optimized NDWI-based corn CWC estimating scheme has a higher accuracy ($R = 0.87\,\,\pm \,\,0.03$ , RMSE = 0.2068 ± 0.0145 kg/m2) than existing NDWI-based strategies for corn CWC retrieval. The feasibility of retrieving corn vegetation water content (VWC) based on the optimized NDWI-based scheme is also investigated, and the superiority of the optimized NDWI-based scheme for retrieving corn VWC is assessed. By comparing with four other NDWI-based corn VWC estimating methods, as well as the corn VWC parameterization scheme applied in the SMAP soil moisture algorithm, it is shown that our optimized NDWI-based scheme has the best VWC estimation accuracy, with the highest $R$ of 0.89 ± 0.02 and the lowest RMSE of 0.7179 ± 0.0555 kg/m2. [ABSTRACT FROM AUTHOR]