Generation and analysis of ESTs from the eastern oyster, Crassostrea virginica Gmelin and identification of microsatellite and SNP markers

Abstract Background The eastern oyster, Crassostrea virginica (Gmelin 1791), is an economically important species cultured in many areas in North America. It is also ecologically important because of the impact of its filter feeding behaviour on water quality. Populations of C. virginica have been threatened by overfishing, habitat degradation, and diseases. Through genome research, strategies are being developed to reverse its population decline. However, large-scale expressed sequence tag (EST) resources have been lacking for this species. Efficient generation of EST resources from this species has been hindered by a high redundancy of transcripts. The objectives of this study were to construct a normalized cDNA library for efficient EST analysis, to generate thousands of ESTs, and to analyze the ESTs for microsatellites and potential single nucleotide polymorphisms (SNPs). Results A normalized and subtracted C. virginica cDNA library was constructed from pooled RNA isolated from hemocytes, mantle, gill, gonad and digestive tract, muscle, and a whole juvenile oyster. A total of 6,528 clones were sequenced from this library generating 5,542 high-quality EST sequences. Cluster analysis indicated the presence of 635 contigs and 4,053 singletons, generating a total of 4,688 unique sequences. About 46% (2,174) of the unique ESTs had significant hits (E-value ≤ 1e-05) to the non-redundant protein database; 1,104 of which were annotated using Gene Ontology (GO) terms. A total of 35 microsatellites were identified from the ESTs, with 18 having sufficient flanking sequences for primer design. A total of 6,533 putative SNPs were also identified using all existing and the newly generated EST resources of the eastern oysters. Conclusion A high quality normalized cDNA library was constructed. A total of 5,542 ESTs were generated representing 4,688 unique sequences. Putative microsatellite and SNP markers were identified. These genome resources provide the material basis for future microarray development, marker validation, and genetic linkage and QTL analysis.