Transcriptome Analysis Based on RNA-Seq in Understanding Pathogenic Mechanisms of Diseases and the Immune System of Fish: A Comprehensive Review

Abstract

In recent years, with the advent of next-generation sequencing along with the development of various bioinformatics tools, RNA sequencing (RNA-Seq)-based transcriptome analysis has become much more affordable in the field of biological research. This technique has even opened up avenues to explore the transcriptome of non-model organisms for which a reference genome is not available. This has made fish health researchers march towards this technology to understand pathogenic processes and immune reactions in fish during the event of infection. Recent studies using this technology have altered and updated the previous understanding of many diseases in fish. RNA-Seq has been employed in the understanding of fish pathogens like bacteria, virus, parasites, and oomycetes. Also, it has been helpful in unraveling the immune mechanisms in fish. Additionally, RNA-Seq technology has made its way for future works, such as genetic linkage mapping, quantitative trait analysis, disease-resistant strain or broodstock selection, and the development of effective vaccines and therapies. Until now, there are no reviews that comprehensively summarize the studies which made use of RNA-Seq to explore the mechanisms of infection of pathogens and the defense strategies of fish hosts. This review aims to summarize the contemporary understanding and findings with regard to infectious pathogens and the immune system of fish that have been achieved through RNA-Seq technology.

Keywords: fish disease; immune system; next-generation sequencing; transcriptome.

Figure 1

Illustration demonstrating the stepwise workflow of a conventional RNA-Seq-based transcriptome analysis. Four major steps are involved: (i) Experimental design; (ii) Sample preparation and library generation; (iii) Next-generation sequencing of the library; (iv) Bioinformatic analysis.

Figure 2

Schematic representation of the processing of data obtained from next-generation sequencing (NGS), by means of bioinformatics. Briefly, the raw reads obtained from NGS are subjected to quality assessment, and high-quality clean reads are further processed for transcriptome assembly. The assembled normalized transcriptome could be further explored for biological insights.