Sequencing and characterization of striped venus transcriptome expand resources for clam fishery genetics

The striped venus Chamelea gallina clam fishery is among the oldest and the largest in the Mediterranean Sea, particularly in the inshore waters of northern Adriatic Sea. The high fishing pressure has lead to a strong stock abundance decline, enhanced by several irregular mortality events. The nearly complete lack of molecular characterization limits the available genetic resources for C. gallina. We achieved the first transcriptome of this species with the aim of identifying an informative set of expressed genes, potential markers to assess genetic structure of natural populations and molecular resources for pathogenic contamination detection.

The 454-pyrosequencing of a normalized cDNA library of a pool C. gallina adult individuals yielded 298,494 raw reads. Different steps of reads assembly and filtering produced 36,422 contigs of high quality, one half of which (18,196) were annotated by similarity. A total of 111 microsatellites and 20,377 putative SNPs were identified. A panel of 13 polymorphic transcript-linked microsatellites was developed and their variability assessed in 12 individuals. Remarkably, a scan to search for contamination sequences of infectious origin indicated the presence of several Vibrionales species reported to be among the most frequent clam pathogen's species. Results reported in this study were included in a dedicated database available at http://compgen.bio.unipd.it/chameleabase.

This study represents the first attempt to sequence and de novo annotate the transcriptome of the clam C. gallina. The availability of this transcriptome opens new perspectives in the study of biochemical and physiological role of gene products and their responses to large and small-scale environmental stress in C. gallina, with high throughput experiments such as custom microarray or targeted re-sequencing. Molecular markers, such as the already optimized EST-linked microsatellites and the discovered SNPs will be useful to estimate effects of demographic processes and to detect minute levels of population structuring.