Bioinformatics analysis and function prediction of NBS-LRR gene family in Broussonetia papyrifera

Biotechnol Lett. 2023 Jan;45(1):13-31. doi: 10.1007/s10529-022-03318-y. Epub 2022 Nov 10.

Abstract

Most of the currently available disease resistance (R) genes have NBS (nucleotide-binding site) and LRR (leucine-rich-repeat) domain which belongs to the NBS-LRR gene family. The whole genome sequencing of Broussonetia papyrifera provides an important bioinformatics database for the study of the NBS-LRR gene family. In this study, 328 NBS-LRR family genes were identified and classified in B. papyrifera according to different classification schemes, where there are 92 N types, 47 CN type, 54 CNL type, 29 NL types, 55 TN type, and 51 TNL type. Subsequently, we conducted bioinformatics analysis of the NBS-LRR gene family. Classification, motif analysis of protein sequences, and phylogenetic tree studies of the NBS-LRR genes in B. papyrifera provide important basis for the functional study of NBS-LRR family genes. Additionally, we performed structural analysis of the chromosomal location, physicochemical properties, and sequences identified by genetic characterization. In addition, through the analysis of GO enrichment, it was found that NBS-LRR genes were involved in defense responses and were significantly enriched in biological stimulation, immune response, and abiotic stress. In addition, we found that Bp06g0955 was the most sensitive to low temperature and encoded the RPM1 protein by analyzing the low temperature transcriptome data of B. papyrifera. Quantitative results of gene expression after 48 h of Fusarium infection showed that Bp01g3293 increased 14 times after infection, which encodes RPM1 protein. The potential of NBS-LRR gene responsive to biotic and abiotic stresses can be exploited to improve the resistance of B. papyrifera.

Keywords: Abiotic stress; Broussonetia papyrifera; Cis-acting elements; DEGs; NBS-LRR genes.

Publication types

  • Review

MeSH terms

  • Binding Sites / genetics
  • Broussonetia*
  • Computational Biology
  • Phylogeny
  • Proteins / genetics

Substances

  • Proteins