Whole transcriptome analysis and critical gene regulatory network analysis during Schistosoma japonicum infection and praziquantel treatment in mice / 中国血吸虫病防治杂志

ABSTRACT

Objective To investigate long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) interactions and identify the critical gene regulatory network during Schistosoma japonicum infections and praziquantel treatment using whole transcriptome sequencing. Methods A total of 110 male C57BL/6 mice were randomly divided into the control group, the infection group and the treatment group. Mice in the infection treatment and the control group were infected with S. japonicum cercariae via the abdomen, and liver specimens were sampled from 10 mice 3, 6, 8 weeks post-infection. Praziquantel treatment was given to mice in the treatment group 8 weeks post-infection, and liver specimens were sampled from 10 mice 2, 4, 6, 8, 10 weeks post-treatment. Total RNA was isolated from mouse liver specimens, and the transcriptome library was constructed for highthroughput whole transcriptome sequencing. The significant differentially expressed genes were subjected to functional annotations, Gene Ontology (GO) terms enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Correlation analysis of liver specimens was performed using R Corrplot and Himsc functions, and the lncRNAmiRNA-mRNA interaction network analysis was performed using R MixOmics and Himsc functions. Results There were 1 176 differentially expressed miRNAs, 5 270 differentially expressed mRNAs, and 2 682 differentially expressed lncRNAs between the infection group and the control group, 1 289 differentially expressed miRNAs, 7 differentially expressed mRNAs, and 69 differentially expressed lncRNAs between the treatment group and the infection group, and 1 210 differentially expressed miRNAs, 4 456 differentially expressed mRNAs, and 2 016 differentially expressed lncRNAs between the treatment group and the control group. Correlation analysis showed a higher correlation of gene expression between the treatment group and the control group. Principal component analysis showed obvious separate clustering between the infection group and the treatment group. The differentially expressed genes with significant relevance were significantly enriched in 24 GO terms, including arachidonic acid metabolic process, xenobiotic catabolic process, unsaturated fatty acid metabolic process, xenobiotic metabolic process, long-chain fatty acid metabolic process, and 8 KEGG metabolic pathways, including cholesterol metabolism, tyrosine metabolism, linoleic acid metabolism, retinol metabolism, and steroid hormone biometabolism. Conclusions There were 23 mRNAs including Cyp2b9 and 14 lncRNAs including Rmrpr in the core position of the gene regulatory network, which may play a critical role in S. japonicum infections and praziquantel treatment, and 9 miRNAs including miR-8105 may serve as potential molecular markers for diagnosis of S. japonicum infections.