Screening of differentially expressed microRNAs and target genes in two potato varieties under nitrogen stress.

BACKGROUND: A reasonable supply of nitrogen (N) fertilizer is essential for obtaining high-quality, high-level, and stable potato yields, and an improvement in the N utilization efficiency can effectively reduce N fertilizer use. It is important to use accurate, straightforward, and efficient transgenic breeding techniques for the identification of genes that can improve nitrogen use efficiency, thus enabling us to achieve the ultimate goal of breeding N-efficient potato varieties. In recent years, some of the mechanisms of miRNAs have been elucidated via the analysis of the correlation between the expression levels of potato miRNA target genes and regulated genes under conditions of stress, but the role of miRNAs in the inhibition/expression of key genes regulating N metabolism under N stress is still unclear. Our study aimed to identify the role played by specific enzymes and miRNAs in the responses of plants to N stress. RESULTS: The roots and leaves of the N-efficient potato variety, Yanshu4 ("Y"), and N-inefficient potato variety, Atlantic ("D"), were collected at the seedling and budding stages after they were exposed to different N fertilizer treatments. The miRNAs expressed differentially under the two types of N stress and their corresponding target genes were first predicted using miRNA and degradome analysis. Then, quantitative polymerase chain reaction (qRT-PCR) was performed to verify the expression of differential miRNAs that were closely related to N metabolism. Finally, the shearing relationship between stu-miR396-5p and its target gene StNiR was determined by analyzing luciferase activity levels. The results showed that NiR activity increased significantly with an increase in the applied N levels from the seedling stage to the budding stage, and NiR responded significantly to different N treatments. miRNA sequencing enabled us to predict 48 families with conserved miRNAs that were mainly involved in N metabolism, carbon metabolism, and amino acid biosynthesis. The differences in the expression of the following miRNAs were identified via screening (high expression levels and P < 0.05): stu-miR396-5p, stu-miR408b-3p_R-1, stu-miR3627-3p, stu-miR482a-3p, stu-miR8036-3p, stu-miR482a-5p, stu-miR827-5p, stu-miR156a_L-1, stu-miR827-3p, stu-miR172b-5p, stu-miR6022-p3_7, stu-miR398a-5p, and stu-miR166c-5p_L-3. Degradome analysis showed that most miRNAs had many-to-many relationships with target genes. The main target genes involved in N metabolism were NiR, NiR1, NRT2.5, and NRT2.7. qRT-PCR analysis showed that there were significant differences in the expression levels of stu-miR396-5p, stu-miR8036-3p, and stu-miR482a-3p in the leaves and roots of the Yanshu4 and Atlantic varieties at the seedling and budding stages under conditions that involved no N and excessive N application; the expression of these miRNAs was induced in response to N stress. The correlation between the differential expression of stu-miR396-5p and its corresponding target gene NiR was further verified by determining the luciferase activity level and was found to be strongly negative. CONCLUSION: The activity of NiR was significantly positively correlated with N application from the seedling to the budding stage. Differential miRNAs and target genes showed a many-to-many relationship with each other. The expression of stu-miR396-5p, stu-miR482a-3p, and stu-miR8036-3p in the roots and leaves of the Yanshu4 and Atlantic varieties at the seedling and budding stages was notably different under two types of N stress. Under two types of N stress, stu-miR396-5p was down-regulated in Yanshu4 in the seedling-stage and shoot-stage roots, and up-regulated in seedling-stage roots and shoot-stage leaves; stu-miR482a-3p was up-regulated in the seedling and shoot stages. The expression of stu-miR8036-3p was up-regulated in the leaves and roots at the seedling and budding stages, and down-regulated in roots under both types of N stress. The gene expressing the key enzyme involved in N metabolism, StNiR, and the stu-miR396-5p luciferase assay reporter gene had a strong regulatory relationship with each other. This study provides candidate miRNAs related to nitrogen metabolism and highlights that differential miRNAs play a key role in nitrogen stress in potato, providing insights for future research on miRNAs and their target genes in nitrogen metabolic pathways and breeding nitrogen-efficient potatoes.

Genome-wide identification, characterization, evolution and expression analysis of the DIR gene family in potato (Solanum tuberosum).

The dirigent (DIR) gene is a key player in environmental stress response and has been identified in many multidimensional tube plant species. However, there are few studies on the StDIR gene in potato. In this study, we used genome-wide identification to identify 31 StDIR genes in potato. Among the 12 potato chromosomes, the StDIR gene was distributed on 11 chromosomes, among which the third chromosome did not have a family member, while the tenth chromosome had the most members with 11 members. 22 of the 31 StDIRs had a classical DIR gene structure, with one exon and no intron. The conserved DIR domain accounts for most of the proteins in the 27 StDIRs. The structure of the StDIR gene was analyzed and ten different motifs were detected. The StDIR gene was divided into three groups according to its phylogenetic relationship, and 22 duplicate genes were identified. In addition, four kinds of cis-acting elements were detected in all 31 StDIR promoter regions, most of which were associated with biotic and abiotic stress. The findings demonstrated that the StDIR gene exhibited specific responses to cold stress, salt stress, ABA, and drought stress. This study provides new candidate genes for improving potato's resistance to stress.

Multi-dimensional variables and feature parameter selection for aboveground biomass estimation of potato based on UAV multispectral imagery.

Aboveground biomass (AGB) is an essential assessment of plant development and guiding agricultural production management in the field. Therefore, efficient and accurate access to crop AGB information can provide a timely and precise yield estimation, which is strong evidence for securing food supply and trade. In this study, the spectral, texture, geometric, and frequency-domain variables were extracted through multispectral imagery of drones, and each variable importance for different dimensional parameter combinations was computed by three feature parameter selection methods. The selected variables from the different combinations were used to perform potato AGB estimation. The results showed that compared with no feature parameter selection, the accuracy and robustness of the AGB prediction models were significantly improved after parameter selection. The random forest based on out-of-bag (RF-OOB) method was proved to be the most effective feature selection method, and in combination with RF regression, the coefficient of determination (R2) of the AGB validation model could reach 0.90, with root mean square error (RMSE), mean absolute error (MAE), and normalized RMSE (nRMSE) of 71.68 g/m2, 51.27 g/m2, and 11.56%, respectively. Meanwhile, the regression models of the RF-OOB method provided a good solution to the problem that high AGB values were underestimated with the variables of four dimensions. Moreover, the precision of AGB estimates was improved as the dimensionality of parameters increased. This present work can contribute to a rapid, efficient, and non-destructive means of obtaining AGB information for crops as well as provide technical support for high-throughput plant phenotypes screening.