MEME (Multiple Em for Motif Elicitation) is the most commonly used tool to identify motifs within deoxyribonucleic acid (DNA) or protein sequences. However, the results generated by the MEMEare saved using file formats .xml and .txt, which are difficult to read, visualize, or integrate with other widely used phylogenetic tree packages, such as ggtree. To overcome this problem, we developed the ggmotif R package, which provides two easy-to-use functions that can facilitate the extraction and visualization of motifs from the results files generated by the MEME. ggmotif can extract the information of the location of motif(s) on the corresponding sequence(s) from the .xml format file and visualize it. Additionally, the data extracted by ggmotif can be easily integrated with the phylogenetic data. On the other hand, ggmotif can obtain the sequence of each motif from the .txt format file and draw the sequence logo with the function ggseqlogo from the ggseqlogo R package. The ggmotif R package is freely available (including examples and vignettes) from GitHub at https://github.com/lixiang117423/ggmotif or from CRAN at https://CRAN.R-project.org/package=ggmotif.

Plants have evolved two layers of protection against biotic stress: PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI). The primary mechanism of ETI involves nucleotide-binding leucine-rich repeat immune receptors (NLRs). Although NLR genes have been studied in several plant species, a comprehensive database of NLRs across a diverse array of species is still lacking. Here, we present a thorough analysis of NLR genes across 100 high-quality plant genomes (PlantNLRatlas). The PlantNLRatlas includes a total of 68,452 NLRs, of which 3,689 are full-length and 64,763 are partial-length NLRs. The majority of NLR groups were phyletically clustered. In addition, the domain sequences were found to be highly conserved within each NLR group. Our PlantNLRatlas dataset is complementary to RefPlantNLR, a collection of NLR genes which have been experimentally confirmed. The PlantNLRatlas should prove helpful for comparative investigations of NLRs across a range of plant groups, including understudied taxa. Finally, the PlantNLRatlas resource is intended to help the field move past a monolithic understanding of NLR structure and function.

Weighted gene co-expression network analysis (WGCNA) is often used to analyze multi-sample (>15) data, identify co-expressed gene modules, and explore the relationship between co-expression modules and target traits in systematic biology. In order to explore the gene co-expression network in response to Magnaporthe oryzae infection in rice near iso-genic lines (NIL) carrying different broad-spectrum resistance genes. We analyzed the expression pattern of genes by WGCNA based on the data of GSE117030 form the GEO database and identified 23 co-expression modules. Combining expression patterns with phenotypes, we chose tan module and midnightblue module as target modules. GO enrichment analysis showed that most of the genes in the target module were related to cell components. A co-expression network was constructed for the genes in the target module, and some hub genes were screened out. These results provide new insights into further understanding the mechanism of broad-spectrum resistance genes and breeding rice varieties with disease resistance.