Generation and characterization of the sea bass Dicentrarchus labrax brain and liver transcriptomes.
The sea bass Dicentrarchus labrax is the center of interest of an increasing number of basic or applied research investigations, even though few genomic or transcriptomic data is available. Current public data only represent a very partial view of its transcriptome. To fill this need, we characterized brain and liver transcriptomes in a generalist manner that would benefit the entire scientific community. We also tackled some bioinformatics questions, related to the effect of RNA fragment size on the assembly quality. Using Illumina RNA-seq, we sequenced organ pools from both wild and farmed Atlantic and Mediterranean fishes. We built two distinct cDNA libraries per organ that only differed by the length of the selected mRNA fragments. Efficiency of assemblies performed on either or both fragments size differed depending on the organ, but remained very close reflecting the quality of the technical replication. We generated more than 19,538Mbp of data. Over 193million reads were assembled into 35,073 contigs (average length=2374bp; N50=3257). 59% contigs were annotated with SwissProt, which corresponded to 12,517 unique genes. We compared the Gene Ontology (GO) contig distribution between the sea bass and the tilapia. We also looked for brain and liver GO specific signatures as well as KEGG pathway coverage. 23,050 putative micro-satellites and 134,890 putative SNPs were identified. Our sampling strategy and assembly pipeline provided a reliable and broad reference transcriptome for the sea bass. It constitutes an indisputable quantitative and qualitative improvement of the public data, as it provides 5 times more base pairs with fewer and longer contigs. Both organs present unique signatures consistent with their specific physiological functions. The discrepancy in fragment size effect on assembly quality between organs lies in their difference in complexity and thus does not allow prescribing any general strategy. This information on two key organs will facilitate further functional approaches.
Sorbonne Universités, UPMC Univ Paris 06, UMR 7232, BIOM, Observatoire Océanologique, F-66650, Banyuls/Mer, France; CNRS, UMR7232, BIOM, Avenue Fontaulé, 66650 Banyuls-sur-Mer, France.
Elodie
E
Magnanou
INRA, Plateforme bioinformatique Toulouse Midi-Pyrénées, UR875 Biométrie et Intelligence Artificielle, BP 52627, 31326 Castanet-Tolosan Cedex, France.
Christophe
C
Klopp
INRA, Plateforme bioinformatique Toulouse Midi-Pyrénées, UR875 Biométrie et Intelligence Artificielle, BP 52627, 31326 Castanet-Tolosan Cedex, France.
Celine
C
Noirot
Sorbonne Universités, UPMC Univ Paris 06, UMR 7232, BIOM, Observatoire Océanologique, F-66650, Banyuls/Mer, France; CNRS, UMR7232, BIOM, Avenue Fontaulé, 66650 Banyuls-sur-Mer, France.
Laurence
L
Besseau
Sorbonne Universités, UPMC Univ Paris 06, UMR 7232, BIOM, Observatoire Océanologique, F-66650, Banyuls/Mer, France; CNRS, UMR7232, BIOM, Avenue Fontaulé, 66650 Banyuls-sur-Mer, France.
Jack
J
Falcón
D000818:Animals; D001492:Bass / Q000235:genetics*; D001921:Brain / Q000378:metabolism*; D015723:Gene Library; D063990:Gene Ontology; D008099:Liver / Q000378:metabolism*; D017422:Sequence Analysis, DNA; D059467:Transcriptome
Brain; Fish; Liver; Pineal gland; Pituitary; Reference transcriptome