Analysis of stress-responsive transcriptome in the intestine of Asian seabass (Lates calcarifer) using RNA-seq

Abstract

Identification of differentially expressed genes (DEGs) and regulated pathways in response to stressors using a whole-genome approach is critical to understanding the mechanisms underlying stress responses. We challenged Asian seabass with lipopolysaccharide (LPS), Vibrio harveyi, high salinity and fasting, and sequenced six cDNA libraries of intestine samples using Roche 454 RNA-seq. Over 1 million reads (average size: 516 bp) were obtained. The de novo assembly obtained 83 911 unisequences with an average length of 747 bp. In total, 62.3% of the unisequences were annotated. We observed overall similar expression profiles among different challenges, while a number of DEGs and regulated pathways were identified under specific challenges. More than 1000 DEGs and over 200 regulated pathways for each stressor were identified. Thirty-seven genes were differentially expressed in response to all challenges. Our data suggest that there is a global coordination and fine-tuning of gene regulation during different challenges. In addition, we detected dramatic immune responses in intestines under different stressors. This study is the first step towards the comprehensive understanding of the mechanisms underlying stress responses and supplies significant transcriptome resources for studying biological questions in non-model fish species.

Keywords: RNA-seq; disease; intestine; nutrition; stress.

Figure 1.

Volcano plots showing the gene expression differences among challenges and controls. The RPKM-normalized transcript count data sets were analysed by using the NOIseq program: the x-axis shows the probability for each gene of being differentially expressed and the y-axis shows the log-ratio (gene expression fold change after challenge). For each treatment, the total DEG number that identified by the program (probability 0.8 as a threshold) was shown.

Figure 2.

A Venn diagram describing overlaps among genes differentially expressed after treatments. All the DEGs (probability 0.8 as a threshold) under four treatments were compared with each other. The unique genes in each library and crosstalk genes among different libraries were illustrated.

Figure 3.

Venn diagrams describing overlaps among differentially regulated pathways after four treatments. The regulated pathways in response to four treatments were divided into two groups (up and down), and within each group, the regulated pathways were compared with each other. The overlapping pathway numbers among different libraries are illustrated.

Figure 4.

Alternative splicing variants of IFABP-a and -b genes and their expression in the intestines of the Asian seabass individuals with extreme growth traits. (A) The transcript sequences and their corresponding genomic sequences of the splice variants of IFABP-a and IFABP-b genes are presented. ‘e1’–‘e4’ show the exons and UTRs in variants, ‘M’ and ‘*’ denote the approximate location of the predicted translation start site and stop codon for each variant, respectively; (B) Gene expression of the splice variants in two groups of the Asian seabass with extreme body weight sizes. Significant level: ‘**’, t-test P value < 0.01 and ‘***’, t-test P value < 0.001.