Comparison of grouper infection with two different iridoviruses using transcriptome sequencing and multiple reference species selection.

Abstract

Due to high-density aquafarming in Taiwan, groupers are commonly infected with two different iridoviruses: Megalocytivirus (grouper iridovirus of Taiwan, TGIV) and Ranavirus (grouper iridovirus, GIV). Iridoviral diseases cause mass mortality, and surviving fish retain these pathogens, which can then be horizontally transferred. These viruses have therefore become a major challenge for grouper aquaculture. In this study, comparisons of the biological responses of groupers to infection with these two different iridoviruses were performed. A novel approach for transcriptomic analysis was proposed to enhance the discovery of differentially expressed genes and associated biological pathways. In this method, suitable and available reference species are selected from the NCBI taxonomy tree and the Ensembl and KEGG databases instead of either choosing only one model species or adopting the NCBI non-redundant dataset as references. Our results show that selection of multiple appropriate model species as references increases the efficiency and performance of analyses compared to those of traditional approaches. Using this method, 17 shared pathways and 5 specific pathways were found to be significantly differentially expressed following infection with the two iridoviruses, among which 11 pathways were additionally identified based on the proposed method of multiple reference species selection. Among the pathways responsive to infection with a specific iridovirus, the spliceosomal pathway (ko03040; p-value = 0.0011) was exclusively associated with TGIV infection, while the glycolysis/gluconeogenesis pathway (ko00010; p-value = 0.0032) was associated with GIV infection. These findings and designed corresponding biological experiments may facilitate a deeper understanding of the mechanisms by which both TGIV and GIV cause fatal infections, as well as the ways in which they induce different pathologies and symptoms. We believe that the proposed novel mechanism for de novo transcriptomic analysis provides superior and comprehensive functional annotations and that the resulting shared and specific pathways identified may help immunologists develop specific vaccines against various types of iridovirus in the near future.