Genetic variations and gene expression profiles of Rice Black-streaked dwarf virus (RBSDV) in different host plants and insect vectors: insights from RNA-Seq analysis

Abstract

Abstract Rice black-streaked dwarf virus (RBSDV) is an etiological agent of a destructive disease infecting some economically important crops from the Gramineae family in Asia. While RBSDV causes high yield losses, genetic characteristics of replicative viral populations have not been investigated within different host plants and insect vectors. Herein, eleven publicly available RNA-Seq datasets from Chinese RBSDV-infected rice, maize, and viruliferous planthopper (Laodelphax striatellus) were obtained from the NCBI database. The patterns of SNP and RNA expression profiles of expected RBSDV populations were analyzed by CLC Workbench 20 and Geneious Prime software. These analyses discovered 2,646 mutations with codon changes in RBSDV whole transcriptome and forty-seven co-mutated hotspots with high variant frequency within the crucial regions of S5-1, S5-2, S6, S7-1, S7-2, S9, and S10 open reading frames (ORFs) which are responsible for some virulence and host range functions. Moreover, three joint mutations are located on the three-dimensional protein of P9-1. The infected RBSDV-susceptible rice cultivar KTWYJ3 and indigenous planthopper datasets showed more co-mutated hotspot numbers than others. Our analyses showed the expression patterns of viral genomic fragments varied depending on the host type. Unlike planthopper, S5-1, S2, S6, and S9-1 ORFs, respectively had the greatest read numbers in host plants; and S5-2, S9-2, and S7-2 were expressed in the lowest level. These findings underscore virus/host complexes are effective in the genetic variations and gene expression profiles of plant viruses. Our analysis revealed no evidence of recombination events. Interestingly, the negative selection was observed at 12 RBSDV ORFs, except for position 1015 in the P1 protein, where a positive selection was detected. The research highlights the potential of SRA datasets for analysis of the virus cycle and enhances our understanding of RBSDV’s genetic diversity and host specificity.

Keywords

• RBSDV
• RNA-Seq datasets
• Genetic diversity
• Host specificity