Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived head kidney leukocytes transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: The leukocytes of tilapia were treated with PBS(A), heat-killed S.agalactiae(B), sodium nitrite(C) or heat-killed S.agalactiae and sodium nitrite co-treatment(D),respectively. Then the mRNA profiles were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level. qRT–PCR validation was performed using SYBR Green assays Results: Using an optimized data analysis workflow, we mapped about 40 million sequence reads per sample to the tilapia genome in the head kidney leukocytes of tilapia.10 candidate genes were randomly selected to quantify their mRNA expression levels of treatment and control groups by q-PCR. Results showed that the Pearson’s correlation coefficient between q-PCR and RNA-seq was 0.939. Total of 6173 transcripts were differently expressed, with a fold change =2 and p value <0.05. Conclusions: Our study represents the first detailed analysis of tilapia head kidney leukocytes transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a fish cell. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Overall design: The mRNA profiles of leukocytes treated by A) PBS, B) Streptococcus agalactiae, C) nitrite or D) Streptococcus agalactiae and nitrite co-treatment were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000.