A cDNA Microarray for Crassostrea virginica and C. gigas

Abstract

The eastern oyster, Crassostrea virginica, and the Pacific oyster, C. gigas, are species of global economic significance as well as important components of estuarine ecosystems and models for genetic and environmental studies. To enhance the molecular tools available for oyster research, an international group of collaborators has constructed a 27,496-feature cDNA microarray containing 4460 sequences derived from C. virginica, 2320 from C. gigas, and 16 non-oyster DNAs serving as positive and negative controls. The performance of the array was assessed by gene expression profiling using gill and digestive gland RNA derived from both C. gigas and C. virginica, and digestive gland RNA from C. ariakensis. The utility of the microarray for detection of homologous genes by cross-hybridization between species was also assessed and the correlation between hybridization intensity and sequence homology for selected genes determined. The oyster cDNA microarray is publicly available to the research community on a cost-recovery basis.

Gene Expression Patterns During the Larval Development of European Sea Bass (Dicentrarchus Labrax) by Microarray Analysis

“…Finally, our study demonstrates that valuable results can be obtained through a large scale heterologous microarray approach when homologous chips are not available. Possibility of cross species cDNA hybridization at subdivision or closer levels could be a beneficial tool for revealing gene expression in various marine organisms of other taxa starting from the chips already available in molluscs (Jenny et al, 2007), algae (Jamers et al, 2006) and crustaceans (Wang et al, 2006). Table 1 The 15 most abundant gene ontology categories associated with the 1,278 analyzed genes Table 2 The four most highly represented biological processes (GO) associated with the differentially regulated gene.…”

Genomic Approaches in Aquaculture and Fisheries

“…Until now, Suppression Subtractive Hybridization (SSH) has been the method the most frequently used to identify genes differentially expressed between contrasting individuals. However, novel high-throughput transcriptome analysis methods such as microarrays (Jenny et al 2007), MPSS , or SAGE are likely to increasingly contribute to the identification of genes of interest in the near future. In salmonids, a microarray has been used to study gene expression in fish exposed or not to Pisciricketsia salmonis (Rise et al 2004).…”

“…For two oyster species, C. virginica and C. gigas, an international group of collaborators has constructed a cDNA microarray (4,460 sequences from C. virginica and 2,320 from C. gigas) (Jenny et al 2007). This array is notably used to estimate the response of C. gigas families to heat stress challenge (Lang et al 2008).…”

Transferability of Cupped Oyster EST (Expressed Sequence Tag)-Derived SNP (Single Nucleotide Polymorphism) Markers to Related Crassostrea and Ostrea Species

“…While they provide models for genetic and environmental studies (Jenny et al, 2007), more importantly oyster species have shown the highest production rates of any farmed aquatic animal since the mid 90's, and provided approximately one-tenth of global aquaculture production in 2011 (FAO, 2013). Growth in demand for cultured edible oysters has seen genetic improvement programs for some species initiated in several countries (Langdon et al, 2003) but most stock improvement programs are still in the early stage of development and lack the large numbers of genetic markers required.…”

“…In non-model organisms, however, where availability of nucleotide sequence is often limited or absent, SNPs have to be identified via laboratory screening (Sauvage et al, 2007;Kim et al, 2011). Given the growth in public EST databases for a diverse array of taxa including oysters (Jenny et al, 2007;Fleury et al, 2009), SNP marker development has become a subject of great interest as these markers provide considerable advantages over microsatellite markers (Kim et al, 2011). This is because they are distributed abundantly across the genome, are often functionally relevant, are less mutable than SSRs, and in general are more robust in the laboratory and for data interpretation (Morin and McCarthy, 2007;Kim et al, 2011).…”