Liver transcriptome analysis of the Sparus macrocephlus in response to Vibrio parahaemolyticus infection.

The black seabream (Sparus macrocephlus) is an economically pivotal aquaculture species cultured in China and Southeast Asian countries. To understand the molecular immune mechanisms underlying the response to Vibrio parahaemolyticus, a comparative gene transcription analysis were performed with utilized fresh livers of V. parahaemolyticus-immunized Sparus macrocephlus with a control group through RNA-Seq technology. A total of 256663 contigs were obtained after excluded the low-quality sequences and assembly. The average length of contigs collected from this research is 1066.93 bp. Furthermore, blast analysis indicates 30747 contigs were annotated based on homology with matches in the NT, NR, gene, and string databases. A gene ontology analysis was employed to classify 21598 genes according to three major functional categories: molecular function, cellular component, and biological process. A total of 14470 genes were discovered in 303 KEGG pathways. RSEM and EdgeR were introduced to estimate 3841 genes significantly different expressed (False Discovery Rate<0.001) which includes 4072 up-regulated genes and 3771 down-regulated genes. A significant enrichment analysis of these differentially expressed genes and isogenes were conducted to reveal the major immune-related pathways which refer to the toll-like receptor, complement, coagulation cascades, and chemokine signaling pathways. In addition, 92175 potential simple sequence repeats (SSRs) and 121912 candidate single nucleotide polymorphisms (SNPs) were detected and identified sequencely in the Sparus macrocephlus liver transcriptome. This research characterized a gene expression pattern for normal and the V. parahaemolyticus -immunized Sparus macrocephlus for the first time and not only sheds new light on the molecular mechanisms underlying the host-V. parahaemolyticus interaction but contribute to facilitate future studies on Sparus macrocephlus gene expression and functional genomics.