Rice (Oryza sativa L.) is a major food crop for half the world’s population but is constantly endangered by a variety of pathogens. Nucleotide-Binding Site Leucine-Rich Repeat (NBS-LRR) genes are important genes in plant innate immunity through which plants respond to pathogen effectors directly. The objective of this study was to conduct an extensive next-generation genomic analysis of the rice NBS-LRR gene family to understand its involvement in plant–microbe interactions and for its potential use in crop protection.
We performed an integrative computational analysis with bioinformatics methodologies. Genes were predicted by a database search and the hidden Markov model and confirmed by the conserved domain database. This analysis consisted of gene structure visualization, motif identification with the MEME suite, phylogenetic reconstruction with MEGA, GO term enrichment analysis, protein structure prediction with αFold2, and cis-regulatory element analysis from upstream of the gene.
An analysis showed that there were 10 conserved motifs in whole NBS-LRR: motifs 1, 4, and 5 were important in recognizing pathogens. Phylogenetic analysis revealed eight evolutionary lineages, and gene duplication events were found in Groups 4 and 7. In GO enrichment, similar functions, including the identification of roles in defense responses, ATP binding, and plasma membrane, were verified. Seven OSDRP protein structure predictions were of high confidence (98.2-100%) and were homologous to one LRR receptor-like kinase and six Toll-like receptors. The cis-regulatory study showed wide distribution of MYB and G-box motifs, and the first gene was identified as a transcriptional hotspot.
This detailed study contributes to our understanding of the molecular composition and evolution of rice NBS-LRR genes. The recognition of eight phylogenetic clades and the clustering of regulatory elements provide excellent candidates for the breeding of disease-resistant crops, laying the groundwork for the development of next-generation crop protection strategies.
