Nitrogen is a critical factor in plant growth, development, and crop yield. NODULE-INCEPTION-like proteins (NLPs), which are plant-specific transcription factors, function as nitrate sensors and play a vital role in the nitrogen response of plants. However, the genome-wide identification of the gene family, the elucidation of the underlying molecular mechanism governing nitrogen response, and haplotype mining remain elusive in millet. In this study, we identified seven members of the gene family in the millet genome and systematically analyzed their physicochemical properties. Evolutionary tree analysis indicated that members can be classified into three subgroups, with members from the same species preferentially grouped together within each subgroup. Analysis of gene structure characteristics revealed that all members contained 10 conserved motifs, as well as the RWP-RK and PB1 domains, indicating that these motifs and domains have been relatively conserved throughout evolution. Additionally, we identified a significant abundance of response elements related to hormones, stress, growth, and development within the promoter regions of members, suggesting that these members are involved in regulating diverse physiological processes in millet. Transcriptome data under low-nitrogen conditions showed significant differences in the expression profiles of and compared to the other members. RNA-seq and qRT-PCR results demonstrated that significantly responds to low-nitrogen stress. Notably, we found that is involved in nitrogen pathways by regulating the expression of the , , , and genes. More importantly, we identified an elite haplotype, Hap2, of , which is gradually being utilized in the breeding process. Our study established a foundation for a comprehensive understanding of the gene family and provided gene resources for variety improvement and marker-assisted selection breeding.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.3390/ijms252312938 | DOI Listing |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11641658 | PMC |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!