Transcriptome Analysis Of Tobacco Root Response To Different Concentrations Of Nitrate
AGRONOMY JOURNAL(2020)
Abstract
We aimed to explore genes and transcription factors (TFs) in tobacco (Nicotiana tabacum L.) that were closely related to responses to different concentrations of nitrate (NO3-) in tobacco root. Cultivar K326 was used in this study. The RNA sequence data generated from K326 treated with high or low concentration of NO3- supplied at different time points (0, 6, 12, and 24 h) were analyzed to determine the transcriptome response of tobacco root to NO3- supply. The expression of numerous genes was altered after high and low NO3- treatment. Further analysis revealed 1981 and 3573 differentially expressed genes (DEGs) from low and high NO3- treatment groups, respectively. Comparative analysis identified 567 low-NO3--specific, 2159 high-NO3--specific, and 1414 commonly expressed genes. Combining short time-series expression miner (STEM) and weighed gene co-expression network analysis (WGCNA) results, 136 and 416 DEGs were identified from low and high NO3- groups, respectively, among which, 12 were TFs. In the constructed protein-protein interaction (PPI) network, three DEGs in high NO3- group (LOC107807186, LOC107792457, and LOC107786314) exhibited highest degrees. Within low NO3- group, LOC107798206, LOC107815159, and LOC107779796 had highest degrees. Among the 12 TFs, LOC107778750, LOC107810552, and LOC107804260 had the highest degrees. Our data provides valuable information about genes, especially the 12 TFs, which were induced by different concentrations of NO3- in tobacco root. These findings may be useful for identification of high or low NO3- treatment-induced genes and TFs, as well as for understanding potential gene regulation mechanisms in response to NO3- supply in tobacco.
MoreTranslated text
Key words
tobacco root response,transcriptome,nitrate
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined