Expressed sequence tags from normalized cDNA libraries prepared from gill and hypodermal tissues of the blue crab, Callinectes sapidus

Biomineralizations: insights and prospects from crustaceans

For growing, crustaceans have to molt cyclically because of the presence of a rigid exoskeleton. Most of the crustaceans harden their cuticle not only by sclerotization, like all the arthropods, but also by calcification. All the physiology of crustaceans, including the calcification process, is then linked to molting cycles. This means for these animals to find regularly a source of calcium ions quickly available just after ecdysis. The sources of calcium used are diverse, ranging from the environment where the animals live to endogenous calcium deposits cyclically elaborated by some of them. As a result, crustaceans are submitted to an important and energetically demanding calcium turnover throughout their life. The mineralization process occurs by precipitation of calcium carbonate within an organic matrix network of chitin-proteins fibers. Both crystalline and stabilized amorphous polymorphs of calcium carbonate are found in crustacean biominerals. Furthermore, Crustacea is the only phylum of animals able to elaborate and resorb periodically calcified structures. Notably for these two previous reasons, crustaceans are more and more extensively studied and considered as models of choice in the biomineralization research area.

EST analysis on the gonad development related organs and microarray screen for differentially expressed genes in mature ovary and testis of Scylla paramamosain

A total of 5160 high quality ESTs (expressed sequence tags) averaging 357 bp were collected from normalized cDNA libraries created from testis, ovary and mixed organs of mud crab Scylla paramamosain. Clustering and assembly of these ESTs resulted in a total of 3837 unique sequences with 576 overlapping contigs and 3261 singletons. Comparisons with the GenBank non-redundant (Nr) protein database (BLASTx, e-values <10(-5)) revealed putative functions or matched homologs from other organisms for 847 (22%) of the ESTs. Several gonad development related genes such as cathepsin C, thioredoxin peroxidase, vitellogenin receptor precursor, 50S ribosomal protein L24 and ubiquitin-conjugating enzyme E2 isoform 2 were identified from this EST project and demonstrated as gonad differential expression genes by rqRT-PCR. Sixty five different types of SSRs (simple sequence repeats) were identified from the total 411 EST-SSR motifs. A home-made cDNA microarray containing 5664 spots was developed and the hybridization results indicated that 39 unique transcripts were differentially expressed in testis and ovaries (P<0.05). The expression levels of eleven unique transcripts examined by rqRT-PCR were matched with microarray fairly. These results will provide a useful resource for functional genomic studies on the biology of reproduction of mud crab.

Shared probe design and existing microarray reanalysis using PICKY

BACKGROUND

Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations.

RESULTS

PICKY 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. PICKY 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, PICKY does not sacrifice the quality of shared probes when choosing them. The latest PICKY 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making PICKY 2.1 more versatile to microarray users.

CONCLUSIONS

Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.

Salinity-stimulated changes in expression and activity of two carbonic anhydrase isoforms in the blue crabCallinectes sapidus

Two isoforms of the enzyme carbonic anhydrase (CA) in the blue crab gill,CasCAg and CasCAc, were identified, sequenced, and found to match the membrane-associated and cytoplasmic isoforms, respectively. The membrane-associated isoform is present in much higher levels of mRNA expression in both anterior and posterior gills in crabs acclimated to high salinity (35 p.p.t.), but expression of the cytoplasmic isoform in the posterior gill undergoes a significantly greater degree of up-regulation after exposure to low salinity (15 p.p.t.). CasCAc has the largest scope of induction (100-fold) reported for any transport-related protein in the gill,and this may be necessary to overcome diffusion limitations between gill cytoplasm and the apical boundary layer. Furthermore, the timing of the changes in expression of CasCAc corresponds to the timing of the induction of protein-specific CA activity and CA protein concentration. No changes in CA mRNA expression or activity occur in the anterior gills. The pattern of up-regulation of expression of mRNA of the α-subunit of the Na+/K+-ATPase is similar to that for CasCAc, and both precede the establishment of the new acclimated physiological state of the crab in low salinity. A putative `housekeeping' gene, arginine kinase, also showed about a threefold increase in expression in response to low salinity,but only in the posterior gills. These results suggest that for studies of expression in crustacean gill tissue, a control tissue, such as the anterior gill, be used until an adequate control gene is identified.

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

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

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.

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MESH Headings

• Animals
• Computational Biology
• Contig Mapping
• DNA, Complementary/metabolism
• Expressed Sequence Tags
• Gene Expression Profiling
• Gene Library
• Genomics/methods
• Microsatellite Repeats
• Models, Genetic
• Molecular Sequence Data
• Ostreidae
• Polymorphism, Single Nucleotide
• Tissue Distribution

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Affiliation(s)

Jonas Quilang The Fish Molecular Genetics and Biotechnology Laboratory, Department of Fisheries and Allied Aquacultures and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, 203 Swingle Hall, Auburn University, Auburn, AL 36849, USA Institute of Biology, College of Science, University of the Philippines, 1101 Diliman, Quezon City, Philippines
Shaolin Wang The Fish Molecular Genetics and Biotechnology Laboratory, Department of Fisheries and Allied Aquacultures and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, 203 Swingle Hall, Auburn University, Auburn, AL 36849, USA
Ping Li The Fish Molecular Genetics and Biotechnology Laboratory, Department of Fisheries and Allied Aquacultures and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, 203 Swingle Hall, Auburn University, Auburn, AL 36849, USA
Jason Abernathy The Fish Molecular Genetics and Biotechnology Laboratory, Department of Fisheries and Allied Aquacultures and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, 203 Swingle Hall, Auburn University, Auburn, AL 36849, USA
Eric Peatman The Fish Molecular Genetics and Biotechnology Laboratory, Department of Fisheries and Allied Aquacultures and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, 203 Swingle Hall, Auburn University, Auburn, AL 36849, USA
Yongping Wang Haskin Shellfish Research Laboratory, Institute of Marine and Coastal Sciences, Rutgers University, 6959 Miller Ave., Port Norris, NJ 08349, USA
Lingling Wang Haskin Shellfish Research Laboratory, Institute of Marine and Coastal Sciences, Rutgers University, 6959 Miller Ave., Port Norris, NJ 08349, USA
Yaohua Shi Haskin Shellfish Research Laboratory, Institute of Marine and Coastal Sciences, Rutgers University, 6959 Miller Ave., Port Norris, NJ 08349, USA
Richard Wallace The Fish Molecular Genetics and Biotechnology Laboratory, Department of Fisheries and Allied Aquacultures and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, 203 Swingle Hall, Auburn University, Auburn, AL 36849, USA
Ximing Guo Haskin Shellfish Research Laboratory, Institute of Marine and Coastal Sciences, Rutgers University, 6959 Miller Ave., Port Norris, NJ 08349, USA
Zhanjiang Liu The Fish Molecular Genetics and Biotechnology Laboratory, Department of Fisheries and Allied Aquacultures and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, 203 Swingle Hall, Auburn University, Auburn, AL 36849, USA

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