Background: Turbot Scophthalmus maximus is an economically important species extensively aquacultured in China. The genetic selection program is necessary and urgent for the sustainable development of this industry, requiring more and more genome background knowledge. Transcriptome sequencing is an excellent alternative way to identify transcripts involved in specific biological processes and exploit a considerable quantity of molecular makers when no genome sequences are available. In this study, a comprehensive transcript dataset for major tissues of S. maximus was produced on basis of an Illumina platform.
Results: Total RNA was isolated from liver, spleen, kidney, cerebrum, gonad (testis and ovary) and muscle. Equal quantities of RNA from each type of tissues were pooled to construct two cDNA libraries (male and female). Using the Illumina paired-end sequencing technology, nearly 44.22 million clean reads in length of 100 bp were generated and then assembled into 106,643 contigs, of which 71,107 were named unigenes with an average length of 892 bp after the elimination of redundancies. Of these, 24,052 unigenes (33.83% of the total) were successfully annotated. GO, KEGG pathway mapping and COG analysis were performed to predict potential genes and their functions. Based on our sequence analysis and published documents, many candidate genes with fundamental roles in sex determination and gonad differentiation (dmrt1), growth (ghrh, myf5, prl/prlr) and immune response (TLR1/TLR21/TLR22, IL-15/IL-34), were identified for the first time in this species. In addition, a large number of credible genetic markers, including 21,192 SSRs and 8,642 SNPs, were identified in the present dataset.
Conclusion: This informative transcriptome provides valuable new data to increase genomic resources of Scophthalmus maximus. The future studies of corresponding gene functions will be very useful for the management of reproduction, growth and disease control in turbot aquaculture breeding programs. The molecular markers identified in this database will aid in genetic linkage analyses, mapping of quantitative trait loci, and acceleration of marker assisted selection programs.