- Open Access
Generation and analysis of a 29,745 unique Expressed Sequence Tags from the Pacific oyster (Crassostrea gigas) assembled into a publicly accessible database: the GigasDatabase
- Elodie Fleury1,
- Arnaud Huvet1,
- Christophe Lelong1,
- Julien de Lorgeril2,
- Viviane Boulo2,
- Yannick Gueguen2,
- Evelyne Bachère2,
- Arnaud Tanguy3,
- Dario Moraga4,
- Caroline Fabioux4,
- Penelope Lindeque5,
- Jenny Shaw5,
- Richard Reinhardt6,
- Patrick Prunet7,
- Grace Davey8,
- Sylvie Lapègue9,
- Christopher Sauvage9,
- Charlotte Corporeau1,
- Jeanne Moal1,
- Frederick Gavory10,
- Patrick Wincker10,
- François Moreews11,
- Christophe Klopp11,
- Michel Mathieu1,
- Pierre Boudry1 and
- Pascal Favrel1Email author
© Fleury et al; licensee BioMed Central Ltd. 2009
Received: 28 November 2008
Accepted: 29 July 2009
Published: 29 July 2009
Although bivalves are among the most-studied marine organisms because of their ecological role and economic importance, very little information is available on the genome sequences of oyster species. This report documents three large-scale cDNA sequencing projects for the Pacific oyster Crassostrea gigas initiated to provide a large number of expressed sequence tags that were subsequently compiled in a publicly accessible database. This resource allowed for the identification of a large number of transcripts and provides valuable information for ongoing investigations of tissue-specific and stimulus-dependant gene expression patterns. These data are crucial for constructing comprehensive DNA microarrays, identifying single nucleotide polymorphisms and microsatellites in coding regions, and for identifying genes when the entire genome sequence of C. gigas becomes available.
In the present paper, we report the production of 40,845 high-quality ESTs that identify 29,745 unique transcribed sequences consisting of 7,940 contigs and 21,805 singletons. All of these new sequences, together with existing public sequence data, have been compiled into a publicly-available Website http://public-contigbrowser.sigenae.org:9090/Crassostrea_gigas/index.html. Approximately 43% of the unique ESTs had significant matches against the SwissProt database and 27% were annotated using Gene Ontology terms. In addition, we identified a total of 208 in silico microsatellites from the ESTs, with 173 having sufficient flanking sequence for primer design. We also identified a total of 7,530 putative in silico, single-nucleotide polymorphisms using existing and newly-generated EST resources for the Pacific oyster.
A publicly-available database has been populated with 29,745 unique sequences for the Pacific oyster Crassostrea gigas. The database provides many tools to search cleaned and assembled ESTs. The user may input and submit several filters, such as protein or nucleotide hits, to select and download relevant elements. This database constitutes one of the most developed genomic resources accessible among Lophotrochozoans, an orphan clade of bilateral animals. These data will accelerate the development of both genomics and genetics in a commercially-important species with the highest annual, commercial production of any aquatic organism.
Genome research on the Pacific oyster, Crassostrea gigas, has been facilitated by the recent development of species-specific tools such as linkage maps [1, 2], large-insert libraries , a public clearing-house , and gene expression profiles [5–7]. Several factors motivate further development of genomic resources for C. gigas: (I) Because this species has the highest annual production of any aquatic organism, C. gigas has been the subject of a great deal of research to elucidate the molecular basis underlying the physiological and genetic mechanisms of economically-relevant traits. (II) The Pacific oyster's phylogenic position in the Lophotrochozoa, an understudied clade of bilaterian animals, makes molecular data on C. gigas highly relevant for studies of genome evolution. (III) Oysters play an important role as sentinels in estuarine and coastal marine habitats where increasing human activities exacerbate the impacts of disease and stress in exploited populations. (IV) C. gigas can be an invasive species when introduced into new habitats . As a result, the Pacific oyster is becoming an attractive model species for genome-related research activities focusing on comparative immunology [e.g. [9–11]], disease ecology [e.g. [12–14]], stress response to pollutants and parasites [e.g. ], developmental and reproductive physiology [e.g. [16, 17]] and evolutionary genetics [e.g. [18–20]].
The genomic strategies currently employed for the identification of novel and previously-characterized genes affecting phenotypes of interest in the Pacific oyster include the identification of quantitative trait loci (QTL), and high-throughput studies of gene expression . QTL mapping of genetic variation affecting, for example, resistance to summer mortality  or hybrid vigor  requires a large number of mapped molecular markers and testing for associations between marker genotypes and phenotypes to identify chromosomal regions harbouring genes that directly affect the trait of interest. Recently developed BAC libraries and fingerprinting  (P. Gaffney, Pers. Com.), have facilitated fine mapping of such regions, and ultimately specification of marker position on the genetic linkage map, allowing gene-assisted selection. Functional genomic approaches are also required for gene-expression profiling experiments such as macroarrays , microarrays , SAGE (Serial Analysis of Gene Expression), MPSS (Massively Parallel Signature Sequencing) , or technologies addressing single genes, such RT-qPCR (real-time quantitative PCR). These techniques have potential applications in ecological monitoring , evaluating oyster broodstock for selective breeding and understanding of gene regulation involved, for example, in the molecular pathways associated with responses to stress or pathogens.
Summary statistics of the Pacific oyster cDNA libraries.
No. of sequences retrieved
No. of valid sequences
Average length insert (bp)
cDNA gonad *
cDNA embryos and larvae and central nervous system (GENOSCOPE)
embryos, larvae, CNS
cDNA hemocytes (GENOSCOPE)
cDNA digestive gland subtracted library (AQUAFIRST)
cDNA mantle-edge subtracted library (AQUAFIRST)
cDNA hemocyte subtracted library (AQUAFIRST)
cDNA gonad subtracted library (AQUAFIRST)
cDNA muscle subtracted library (AQUAFIRST)
cDNA gills subtracted library (AQUAFIRST)
This resource is highly valuable for identifying important gene networks controlling physiological processes, it facilitates the development of molecular markers for the construction of a reference genetic map, and it allows large-scale, expression-profiling experiments using microarrays. These tools will be useful to advance our knowledge of the genetic and physiological bases of development, reproduction, immunology, and associated processes that are important for oyster aquaculture. Finally, this work will be very useful for the annotation phase of the entire oyster genome, the principal objective of an international community of oyster biologists  that will provide a critical point of comparison for understanding the early diversification of animals and their genome, as has been recently proposed for the gastropod snail Lottia gigantea http://genome.jgi-psf.org/Lotgi1/Lotgi1.home.html.
Construction and content
1. Biological samples
1.1. Resistant and Sensitive oysters for the subtractive libraries
Resistant (R) and Susceptible (S) oyster families were produced, through divergent selection for high or low survival of summer mortality, as fully described previously . After completing rearing of oysters through larval development in the IFREMER hatchery in La Tremblade (France, July 2004), we transferred juvenile oysters to the nursery of Bouin (Vendée, France) until March 2005, when the oysters were deployed in the field at Fort Espagnol (South Brittany, France). We collected samples of gonad, muscle, digestive gland, hemocytes, mantle-edge, and gills from 12 R and 12 S oysters on two dates (May 25 and June 6, 2005) and individual tissues from each line were pooled at each sampling date.
1.2. Biological material for the "all developmental stages and central nervous system" cDNA library
Mature, wild oysters, collected on the Atlantic coast of Brittany (France), were spawned and reared in captivity as described in . From this pool, we sampled various developmental stages, which we identified microscopically: oocytes before fertilization, 4-cell and 8-cell embryos (1 and 2 hours post-fertilization [hpf], respectively), morula (3 hpf), blastula (5 hpf), gastrula (7 hpf), trochophore larvae (16 hpf) and D-larvae (2 days post-fertilization [dpf]), early veliger larvae (7 dpf), later veliger larvae (14 dpf), pediveliger larvae (18 dpf), and spat after metamorphosis (27 dpf). We extracted total mRNA from one million oysters from each developmental stage from oocyte to trochophore, and 250,000 from later stages, and from the visceral ganglia microscopically dissected from 10 wild, adult oysters
1.3. Biological material for "hemocytes" cDNA library
We sampled hemocytes from six adult oysters exposed to each of 24 experimental conditions (total n = 144), all combinations of four kinds of bacterial challenge, two times post-challenge, and oysters collected from three geographic origins: Atlantic coast (La Tremblade), Normandie (Bay des Veys) and Mediterranean Sea (Thau lagoon). We performed the bacterial challenges by immersing oysters in seawater containing (I) live, non-virulent Micrococcus luteus and Vibrio tasmaniensis (2.5 × 108 bacteria/L for each strain), (II) live, virulent Vibrio splendidus (5 × 108 bacteria/L), (III) a mix of heat-killed, virulent Vibrio splendidu s and Vibrio aesturianaus (2.5 × 108 bacteria/L for each strain) and (IV) unchallenged oysters. For each condition, we collected hemolymph at 22 and 24 h post challenge from the pericardial cavity through the adductor muscle. We isolated hemocytes separately from these samples (24 experimental conditions) by centrifugation at 700 g for 10 min (4 C) and discarded the plasma. Hemocytes were further subjected to several experimental procedures (see below).
2. RNA preparation
Total RNA was isolated using Trizol reagent (Gibco BRL) at a concentration of 1 ml/30 mg of tissue. For SSH experiments and hemocyte samples, we isolated polyadenylated RNA using the Quickprep micro mRNA purification kit (Amersham). We measured RNA concentration with a spectrophotometer at 260 nm using the conversion factor 1 OD = 40 μg/ml RNA, and RNA quality was determined using a Bioanalyser 2100 (Agilent).
3. cDNA library construction and sequencing of the clones
3.1. Construction of subtractive libraries
The mRNA from each pool of tissue RNA (6 tissues in total) was used as the template for SSH following the PCR-select cDNA subtraction kit procedure (Clontech). Hybridization and subtraction steps were carried out in both directions, i.e. for forward subtraction the Resistant (R) sample (tester) was subtracted from the Susceptible (S) sample (driver) and vice versa for reverse subtraction. The PCR products from both subtractions were cloned into pCR 2.1® TOPO plasmid using TOP10 One Shot ® competent cells for transformation (Invitrogen).
3.2. Construction of "all Developmental stages and central nervous system" cDNA library
Total RNA (0.3 μg) from a pool of various developmental stages and visceral ganglia was used for ds cDNA synthesis and amplification using the SMART approach. Recovered cDNA was equalized using the Duplex-Specific nuclease (DSN)-based normalization method . Efficiency of normalization was measured by real-time PCR. A severe decrease (shift of 11 amplification cycles) in actin relative copy number was measured in the normalized cDNA sample, when compared to the non normalized sample. Resulting, normalized cDNA was then amplified, directionally cloned into pAL17.3 plasmid (Evrogen, Moscow), and was used to transform the XL1-Blue E. coli strain (Stratagene) to generate a cDNA library of 5 × 105 independent clones.
3.3 Construction of oyster "hemocytes" cDNA library
The cDNA library was built by GATC Biotech AG (Germany). Briefly, 1 μg of total RNA, composed of equimolar concentrations from oyster hemocytes from each of the 24 experimental conditions, was used for ds cDNA synthesis. The normalization method consisted of denaturation and controlled, incomplete reassociation of double-stranded cDNA, followed by selective cloning of the cDNA corresponding to the single-stranded, normalized fraction. Efficiency of normalization was measured by non-radioactive, Reverse Northern blot analysis of normalized and non-normalized cDNA. Briefly, an array containing 96 randomly-selected clones derived from the non-normalized cDNA library was hybridized with normalized and non-normalized cDNA. Comparison of homogenization of hybridization signals from the normalized probe to the non-normalized probe indicated the efficiency of normalization (data not shown). Normalized cDNA was then amplified, directionally cloned into pBluescriptIISK(+) plasmid (Stratagene), and was used to transform E. coli XL1-BlueMRF' (Stratagene) to generate a normalized cDNA library of 8.3 × 104 independent clones.
For subtracted libraries and the normalized cDNA gonad library , the clones were sequenced at the Max Planck Institute platform (Berlin, Germany) using an ABI 3730 automatic capillary sequencer, the ABI Big Dye Terminator sequencing kit and universal primer. For the two other normalized cDNA libraries, sequencing was performed at the Genoscope facility (CEA Evry, France) as described above.
4. Database, sequence processing and contig assembly
The sequences were first cleaned up from vector and adaptator sequences. Repeats and contaminants were removed by comparison with several sequence databases such as Univec, Yeast and E. coli genomes. The PolyA site was identified by its relative position to the vector multiple-cloning site. In the 30 bases preceding the polyA site, we searched for putative polyadenylation signals (AATAAA and ATTAAA) . Valid sequences, that had a PHRED score over 20 on at least 100 bp, were submitted to the EMBL-EBI Nucleotide Sequence database http://www.ebi.ac.uk/embl/. Because of the large number of sequences, we used a two-step process to assemble these sequences into contigs. The first step built clusters of sequences sharing at least 75 bp with an identity rate of 96% using MegaBlast . The second step constructed coherent contigs from the previous clusters using CAP3 , at the recommended stringency of 40 bp overlap with 90% sequence identity. Once the contigs were built and their annotation completed, all data were loaded in a locally-adapted Ensembl database.
To obtain as much information as possible concerning the contigs, we performed similarity searches with BlastX http://blast.ncbi.nlm.nih.gov/Blast.cgi using a variety of databases: UniProt/SwissProt, UniProt/TrEMBL, ProDom (protein domains), UniGene Human Clusters, UniGene taxon specific Clusters, TIGR Taxon Specific Clusters, Ensembl specific transcripts (cDNA), and other Sigenae Contigs. We then loaded the annotations into the GigasDatabase. We identified putative open-reading frames (ORFs) by choosing the longest possible translation into amino acid sequence, using Emboss sixpack http://bioweb2.pasteur.fr/docs/EMBOSS/sixpack.html. Sequences with ORFs smaller than 100 codons (300 bp) were removed from the dataset.
5. Gene ontology annotation
To link ESTs with BlastX hits with putative function, we annotated all of them according to gene ontology (GO) terms by using the program KAAS (KEGG Automatic Annotation Server: http://www.genome.jp/tools/kaas/), which provides functional annotation of genes by Blast comparisons (single best hit) against the manually curated KEGG Genes database . The top level consists of the following categories: metabolism, genetic information processing, environmental information processing, and cellular processes. The second level divides these functional categories into finer sub-categories . The distribution of genes in each of the main ontology categories was examined, and the percentages of unique sequence in each of the assigned GO terms were computed.
6. in silico mining of microsatellites and SNPs
We searched a set of 56,327 unique sequences for microsatellite markers using SRR finder (http://www.maizemap.org/bioinformatics/SSRFINDER/SSR_Finder_Download.html; ) with a minimum repeat of 4. This provided a table of raw data which was then exported to MS Excel® to calculate the number of di-, tri-, and tetra-nucleotide repeats, their respective lengths, and starting positions. Putative SNPs were detected using the Pupasuite v1.0 (http://pupasuite.bioinfo.cipf.es/, ). The 56,327 ESTs were assembled in 7,940 contigs wherein putative SNPs were identified and characterized to calculate the percentage of each type of mutation (ts/tv, synonymous/non-synonymous).
Utility and discussion
1. Generation of ESTs
To augment the 1894 recently-published sequences from the normalized cDNA libraries produced by the "Marine Genomic Europe" program , we sequenced a novel part of the gonad library. In addition, we also constructed two new, directionally-cloned, normalized oyster cDNA libraries: one including all developmental stages from embryos to larvae and visceral ganglia, and one from bacteria-challenged and unchallenged hemocytes. Single-pass sequencing produced sequences from the 5' regions of mRNA from each library, resulting in 12,162 sequences, 13,191 sequences, and 14,472 sequences, respectively (Table 1).
Finally, to increase the number of genes characterized that are related to summer mortality [13, 14, 17], we constructed libraries from six different tissues (digestive gland, mantle-edge, hemocytes, gonad, muscle, and gills) using Suppression Subtractive Hybridization (SSH) between selectively-bred Resistant (R) and Sensitive (S) oyster lines , by subtracting in both directions (R-S and S-R). These SSH libraries produced of a total of 8,064 sequences, with approximately 1,000 sequences per library (Table 1). All 47,889 sequences were subjected to pre-processing to eliminate poor-quality sequences and remove cloning-vector sequences. After removing clones with very short inserts or no inserts, and those with poor sequence quality, we obtained a total of 40,845 (85.3%) high-quality ESTs with an average length of 413 bp (Table 1). All EST sequences have been deposited in GenBank with the accession numbers [AM857416-AM869575] for gonad library, [CU998430–CU999999; FP000001–FP012228] for hemocyte library, [CU983906–CU998429] for developmental stages and visceral ganglia library, and [CU681473–CU681818; CU682012–CU682338; CU683068–CU683823; CU683828–CU683864; CU684729–CU686587; FP89705–FP89949] for the SSH libraries.
2. Contig assembly of the ESTs
Summary statistics of the ESTs generated from the Pacific oyster Crassostrea gigas available in the GigasDatabase.
Number of high quality ESTs (new ESTs + public)
56327 (40845 + 15482)
Average length of high quality ESTs (bp)
Number of contigs
Number of ESTs in contigs
Number of singletons
Number of unique sequences
BlastX searches and contig analysis for the complete collection of oyster contigs, based on GigasDatabase EST clustering.
Number of unique sequences
Number of unique sequences with BlastX hits
Percentage of unique sequences with BlastX hits
Number of contigs containing:
> 6 ESTs
3. Putative identities of ESTs
4. Gene ontology annotation
Gene ontology annotation using the KEGG Automatic Annotation Server for the unique Crassostrea gigas sequences from the GigasDatabase.
Amino Acid Metabolism
Metabolism of Other Amino Acids
Glycan Biosynthesis and Metabolism
Biosynthesis of Polyketides and Nonribosomal Peptides
Metabolism of Cofactors and Vitamins
Biosynthesis of Secondary Metabolites
Xenobiotics Biodegradation and Metabolism
Genetic Information Processing
Folding, Sorting and Degradation
Replication and Repair
Environmental Information Processing
Signaling Molecules and Interaction
Cell Growth and Death
Selection of some candidate Crassostrea gigas ESTs similar to genes potentially involved in some physiological regulatory networks.
Best hit description
Endo- paracrine controls
inhibin bA like
CU994284, CU991852, CU987529, CU984099, CU991056
CU998185, CU991852, CU983909, CU993729, CU987283, CU993729, CU988008
cysteine rich bmp regulator 2
Energy metabolis m/reproduct ion
FP001644, FP008029, FP008849, FP002487, CU984370, CU989738, CU997056
c1q-like adipose specific protein
leptin receptor overlapping transcript-like 1
FP010154, FP001573, CU993420, CU991531
ovary-specific c1q-like factor
phosphatidylinositol 3-kinase p110 beta
acetyl-coenzyme a carboxylase alpha
adiponectin receptor 1
camp-dependent protein kinase
CU983945, FP005412, CU994912
sterol regulatory element binding factor 1
FP006535, FP010171, CU984422, FP005108, CU998652
CU999108, CU988309, CU993827
myeloid differentiation primary response gene
FP004666, FP011576, FP002604, CU995719
CU989449, FP009504, CU998458, CU988135
gigasin 2 protein
FP000856, FP003629, FP006010, FP006279, CU994639
FP005503, CU999465, FP006037, FP011761
lipopolysaccharide binding protein
CU983947, CU996720, FP002226
lps-induced tn factor
Concerning the allocation of energy to reproduction, which may play a crucial role in the ability of oysters to survive summer mortality [13, 17], relevant genes potentially involved in the signaling pathway linking reproduction to energy balance have been retrieved, such as ESTs encoding PI3-kinase catalytic subunit beta enzyme (phosphatidylinositol 3-kinase beta, Table 5), leptin receptor, adiponectin-like (ovary-specific c1q-like factor, c1q-like adipose specific protein, Table 5) and a neuropeptide Y ligand (Table 5). Such signaling molecules were recently identified in vertebrates and have important regulatory effects on reproduction [39, 40]. For example, leptin and adiponectin were reported to promote fecundity and the growth of germinal cells by increasing the utilization of oxidizable sources. At the opposite, neuropeptide Y inhibits reproduction when energy storage is deficient [41, 42].
Finally, concerning the innate immunity of C. gigas, new immune-system components have been identified, including signal-transduction elements, LPS binding proteins, antimicrobial peptides, and various protease inhibitors. In particular, a new component of the NF-κB pathway , a Toll receptor-like protein, has been sequenced. The most significant feature of the NF-κB pathway is the central role of the NF-κB family in transcriptional activator proteins, ubiquitously expressed and involved in wide variety of biological processes, including inflammation, cell proliferation and differentiation in mammals, as well as development in insects .
Further functional studies will be necessary, however, to demonstrate the involvement of these annotated ESTs in the different physiological processes of C. gigas. Indeed, this work encourages the use of functional studies, such as RNA interference , to ascertain the functions of these genes.
5. in silico markers
in silico microsatellite (Msat) mining of the GigasDatabase.
Number of Msat
Putative Single Nucleotide Polymorphism (SNP) identification from the GigasDatabase.
Putative SNP distribution in contigs with various number of ESTs.
Number of contigs
Putative SNP sites
with > 50 sequences
with 11–50 sequences
with 6–10 sequences
with 5 sequences
with 4 sequences
with 3 sequences
with 2 sequences
In the present paper, we report the production and the sequencing of clones from 9 cDNA libraries derived from different C. gigas tissues, and from oysters sampled under different conditions, obtaining 40,845 high-quality ESTs that identify 29,745 unique transcribed sequences. Putative annotation was assigned to 43% of the sequences showing similarity to known genes, mostly from other species, in one or more of the databases used for automatic annotation. The high percentage of C. gigas ESTs (57%) with no hits in the protein database implies that there is an enormous potential for discovery of new genes in this species, and possibly new gene networks and metabolic pathways. All data on ESTs, clustering, and annotation can be accessed from the dedicated database, GigasDatabase, available at http://public-contigbrowser.sigenae.org:9090/Crassostrea_gigas/index.html. There is a variety of data-access options, such as database searches on annotation including gene assignments and GO terms, as well as access to self-explanatory, web-based detail annotation archive. This large set of well-characterized clones represents a significant addition to the existing genomic resources for oysters. Indeed, Crassostrea gigas, which belongs to the Lophotrochozoans, a large but understudied clade of bilaterian animals, represents a rare non-model species for which the genomic resources available will be very important. Several research teams are now using this important sequence information to examine oyster gene-expression profiles under various experimental and environmental conditions.
Availability and requirements
Project name: the GigasDatabase.
The Oyster EST contig browser aimed to produce and maintain an automatic annotation of Oyster EST libraries established in three consecutive projects, the Marine Genomics Network of Excellence, the European AquaFirst project and the Crassostrea gigas Genoscope project.
The Project home page is: http://public-contigbrowser.sigenae.org:9090/Crassostrea_gigas/index.html
Operating system: LINUX.
Programming language: Perl 5.8.
Other requirements: MySQL 5 or higher, Apache 2.
Licence: Apache like License (free software license with no copyleft).
Any restrictions to use by non-academics: no.
The research presented in this paper was performed within the framework of several research projects funded by: Genoscope (11/AP2006-2007), Marine Genomics Network of Excellence (GOCE-CT-2004-505403), the European project "Aquafirst" (513692) in the Sixth Framework Program, ANR "CgPhysiogène" (ANR-06-GANI-009) and "Gametogenes" (ANR-08-GENM-041).
All sequence analyses were conducted in collaboration with the SIGENAE bioinformatics team. Specific requests for EST sequence chromatograms should be addressed at firstname.lastname@example.org.
We thank G. Wikfors for his help for editing the English language. We also thank three anonymous reviewers for their comments and suggestions on the manuscript.
- Hubert S, Hedgecock D: Linkage maps of microsatellite DNA markers for the Pacific oyster Crassostrea gigas . Genetics. 2004, 168 (1): 351-362. 10.1534/genetics.104.027342.PubMed CentralView ArticlePubMedGoogle Scholar
- Li L, Guo X: AFLP-based genetic linkage maps of the pacific oyster Crassostrea gigas (Thunberg, 1793). Mar Biotechnol. 2004, 6 (1): 26-36. 10.1007/s10126-003-0001-0.View ArticlePubMedGoogle Scholar
- Cunningham C, Hikima J, Jenny MJ, Chapman RW, Fang GC, Saski C, Lundqvist ML, Wing RA, Cupit PM, Gross PS, et al: New resources for marine genomics: bacterial artificial chromosome libraries for the Eastern and Pacific oysters (Crassostrea virginica and C. gigas). Mar Biotechnol (NY). 2006, 8 (5): 521-533. 10.1007/s10126-006-6013-9.View ArticleGoogle Scholar
- McKillen DJ, Chen YA, Chen C, Jenny MJ, Trent HF, Robalino J, McLean DC, Gross PS, Chapman RW, Warr GW, et al: Marine genomics: a clearing-house for genomic and transcriptomic data of marine organisms. BMC Genomics. 2005, 6 (1): 34-10.1186/1471-2164-6-34.PubMed CentralView ArticlePubMedGoogle Scholar
- Saavedra C, Bachère E: Bivalve genomics. Aquaculture. 2006, 256 (1–4): 1-14. 10.1016/j.aquaculture.2006.02.023.View ArticleGoogle Scholar
- Hedgecock D, Lin JZ, DeCola S, Haudenschild CD, Meyer E, Manahan DT, Bowen B: Transcriptomic analysis of growth heterosis in larval Pacific oysters (Crassostrea gigas). Proc Natl Acad Sci USA. 2007, 104 (7): 2313-2318. 10.1073/pnas.0610880104.PubMed CentralView ArticlePubMedGoogle Scholar
- Jenny MJ, Chapman RW, Mancia A, Chen YA, McKillen DJ, Trent H, Lang P, Escoubas JM, Bachere E, Boulo V, et al: A cDNA microarray for Crassostrea virginica and C. gigas. Mar Biotechnol (NY). 2007, 9 (5): 577-591. 10.1007/s10126-007-9041-1.View ArticleGoogle Scholar
- Ruesink JL, Lenihan HS, Trimble AC, Heiman KW, Micheli F, Byers JE, Kay MC: Introduction of non-native oysters: Ecosystem effects and restoration implications. Annual Review of Ecology, Evolution, and Systematics. 2005, 36: 643-689. 10.1146/annurev.ecolsys.36.102003.152638.View ArticleGoogle Scholar
- Bachere E, Gueguen Y, Gonzalez M, de Lorgeril J, Garnier J, Romestand B: Insights into the anti-microbial defense of marine invertebrates: the penaeid shrimps and the oyster Crassostrea gigas . Immunol Rev. 2004, 198: 149-168. 10.1111/j.0105-2896.2004.00115.x.View ArticlePubMedGoogle Scholar
- Badariotti F, Lelong C, Dubos MP, Favrel P: Characterization of chitinase-like proteins (Cg-Clp1 and Cg-Clp2) involved in immune defence of the mollusc Crassostrea gigas . Febs J. 2007, 274 (14): 3646-3654. 10.1111/j.1742-4658.2007.05898.x.View ArticlePubMedGoogle Scholar
- Lelong C, Badariotti F, Le Quere H, Rodet F, Dubos MP, Favrel P: Cg-TGF-beta, a TGF-beta/activin homologue in the Pacific Oyster Crassostrea gigas, is involved in immunity against Gram-negative microbial infection. Dev Comp Immunol. 2007, 31 (1): 30-38. 10.1016/j.dci.2006.05.005.View ArticlePubMedGoogle Scholar
- Gaffney PM, Bushek D: Genetic aspects of disease resistance in oysters. Journal of Shellfish research. 1996, 15: 135-140.Google Scholar
- Samain JF, Dégremont L, Soletchnik P, Haure J, Bédier E, Ropert M, Moal J, Huvet A, Bacca H, Van Wormhoudt A, et al: Genetically based resistance to summer mortality in the Pacific oyster (Crassostrea gigas) and its relationship with physiological, immunological characteristics and infection process. Aquaculture. 2007, 268 (1–4): 227-243. 10.1016/j.aquaculture.2007.04.044.View ArticleGoogle Scholar
- Huvet A, Herpin A, Degremont L, Labreuche Y, Samain JF, Cunningham C: The identification of genes from the oyster Crassostrea gigas that are differentially expressed in progeny exhibiting opposed susceptibility to summer mortality. Gene. 2004, 343 (1): 211-220. 10.1016/j.gene.2004.09.008.View ArticlePubMedGoogle Scholar
- Tanguy A, Boutet I, Laroche J, Moraga D: Molecular identification and expression study of differentially regulated genes in the Pacific oyster Crassostrea gigas in response to pesticide exposure. Febs J. 2005, 272 (2): 390-403. 10.1111/j.1742-4658.2004.04479.x.View ArticlePubMedGoogle Scholar
- Badariotti F, Kypriotou M, Lelong C, Dubos MP, Renard E, Galera P, Favrel P: The phylogenetically conserved molluscan chitinase-like protein 1 (Cg-Clp1), homologue of human HC-gp39, stimulates proliferation and regulates synthesis of extracellular matrix components of mammalian chondrocytes. J Biol Chem. 2006, 281 (40): 29583-29596. 10.1074/jbc.M605687200.View ArticlePubMedGoogle Scholar
- Fleury E, Fabioux C, Lelong C, Favrel P, Huvet A: Characterization of a gonad-specific transforming growth factor-beta superfamily member differentially expressed during the reproductive cycle of the oyster Crassostrea gigas . Gene. 2008, 410 (1): 187-196. 10.1016/j.gene.2007.12.017.View ArticlePubMedGoogle Scholar
- Wang Y, Xu Z, Guo X: Differences in the rDNA-bearing chromosome divide the Asian-Pacific and Atlantic species of Crassostrea (Bivalvia, Mollusca). Biol Bull. 2004, 206 (1): 46-54. 10.2307/1543197.View ArticlePubMedGoogle Scholar
- Sauvage C, Bierne N, Lapegue S, Boudry P: Single Nucleotide polymorphisms and their relationship to codon usage bias in the Pacific oyster Crassostrea gigas . Gene. 2007, 406 (1–2): 13-22.View ArticlePubMedGoogle Scholar
- Lopez-Flores I, de la Herran R, Garrido-Ramos MA, Boudry P, Ruiz-Rejon C, Ruiz-Rejon M: The molecular phylogeny of oysters based on a satellite DNA related to transposons. Gene. 2004, 339: 181-188. 10.1016/j.gene.2004.06.049.View ArticlePubMedGoogle Scholar
- Lang RP, Bayne CJ, Camara MD, Cunningham C, Jenny MJ, Langdon CJ: Transcriptome profiling of selectively bred Pacific Oyster Crassostrea gigas families that differ in tolerance of heat shock. Mar Biotechnol (NY). 2009,Google Scholar
- Sauvage C, Boudry P, Lapegue S: Identification and characterization of 18 novel polymorphic microsatellite makers derived from expressed sequence tags in the Pacific oyster Crassostrea gigas. Molecular Ecology Resources. 2009, 9: 853-855. 10.1111/j.1755-0998.2009.02525.x.View ArticlePubMedGoogle Scholar
- Dupont S, Obst M, Wilson K, Sköld H, Nakano H, Thorndyke MC: Marine Ecological Genomics – When Genomics meet Marine Ecology. Marine Ecology Progress Series. 2007, 332: 257-273. 10.3354/meps332257.View ArticleGoogle Scholar
- Tanguy A, Bierne N, Saavedra C, Pina B, Bachere E, Kube M, Bazin E, Bonhomme F, Boudry P, Boulo V, et al: Increasing genomic information in bivalves through new EST collections in four species: development of new genetic markers for environmental studies and genome evolution. Gene. 2008, 408 (1–2): 27-36. 10.1016/j.gene.2007.10.021.View ArticlePubMedGoogle Scholar
- Samain JF, McCombie H: Summer mortality of Pacific oyster Crassostrea gigas. The Morest Project. Versailles: Ed Quae. 2008, 379-Google Scholar
- Gueguen Y, Cadoret JP, Flament D, Barreau-Roumiguiere C, Girardot AL, Garnier J, Hoareau A, Bachere E, Escoubas JM: Immune gene discovery by expressed sequence tags generated from hemocytes of the bacteria-challenged oyster, Crassostrea gigas . Gene. 2003, 303: 139-145. 10.1016/S0378-1119(02)01149-6.View ArticlePubMedGoogle Scholar
- Hedgecock D, Gaffney PM, Goulletquer P, Guo X, Reece K, Warr GW: The case for sequencing the Pacific oyster genome. Journal of Shellfish research. 2005, 24 (2): 429-441.View ArticleGoogle Scholar
- Fabioux C, Huvet A, Lelong C, Robert R, Pouvreau S, Daniel JY, Minguant C, Le Pennec M: Oyster vasa-like gene as a marker of the germline cell development in Crassostrea gigas . Biochem Biophys Res Commun. 2004, 320 (2): 592-598. 10.1016/j.bbrc.2004.06.009.View ArticlePubMedGoogle Scholar
- Zhulidov PA, Bogdanova EA, Shcheglov AS, Vagner LL, Khaspekov GL, Kozhemyako VB, Matz MV, Meleshkevitch E, Moroz LL, Lukyanov SA, et al: Simple cDNA normalization using kamchatka crab duplex-specific nuclease. Nucleic Acids Res. 2004, 32 (3): e37-10.1093/nar/gnh031.PubMed CentralView ArticlePubMedGoogle Scholar
- Bonnet A, Iannuccelli E, Hugot K, Benne F, Bonaldo MF, Soares MB, Hatey F, Tosser-Klopp G: A pig multi-tissue normalised cDNA library: large-scale sequencing, cluster analysis and 9K micro-array resource generation. BMC Genomics. 2008, 9: 17-10.1186/1471-2164-9-17.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang Z, Schwartz S, Wagner L, Miller W: A greedy algorithm for aligning DNA sequences. J Comput Biol. 2000, 7 (1–2): 203-214. 10.1089/10665270050081478.View ArticlePubMedGoogle Scholar
- Huang X, Madan A: CAP3: A DNA sequence assembly program. Genome Res. 1999, 9 (9): 868-877. 10.1101/gr.9.9.868.PubMed CentralView ArticlePubMedGoogle Scholar
- Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M: KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007, W182-185. 10.1093/nar/gkm321. 35 Web ServerGoogle Scholar
- Mao X, Cai T, Olyarchuk JG, Wei L: Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics. 2005, 21 (19): 3787-3793. 10.1093/bioinformatics/bti430.View ArticlePubMedGoogle Scholar
- Rungis D, Berube Y, Zhang J, Ralph S, Ritland CE, Ellis BE, Douglas C, Bohlmann J, Ritland K: Robust simple sequence repeat markers for spruce (Picea spp.) from expressed sequence tags. Theor Appl Genet. 2004, 109 (6): 1283-1294. 10.1007/s00122-004-1742-5.View ArticlePubMedGoogle Scholar
- Conde L, Vaquerizas JM, Dopazo H, Arbiza L, Reumers J, Rousseau F, Schymkowitz J, Dopazo J: PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes. Nucleic Acids Res. 2006, 621-625. 10.1093/nar/gkl071. 34 Web ServerGoogle Scholar
- Herpin A, Lelong C, Becker T, Rosa F, Favrel P, Cunningham C: Structural and functional evidence for a singular repertoire of BMP receptor signal transducing proteins in the lophotrochozoan Crassostrea gigas suggests a shared ancestral BMP/activin pathway. Febs J. 2005, 272 (13): 3424-3440. 10.1111/j.1742-4658.2005.04761.x.View ArticlePubMedGoogle Scholar
- Lelong C, Mathieu M, Favrel P: Structure and expression of mGDF, a new member of the transforming growth factor-beta superfamily in the bivalve mollusc Crassostrea gigas . Eur J Biochem. 2000, 267 (13): 3986-3993. 10.1046/j.1432-1327.2000.01432.x.View ArticlePubMedGoogle Scholar
- Schneider JE: Energy balance and reproduction. Physiol Behav. 2004, 81 (2): 289-317. 10.1016/j.physbeh.2004.02.007.View ArticlePubMedGoogle Scholar
- Schneider JE: Metabolic and hormonal control of the desire for food and sex: implications for obesity and eating disorders. Horm Behav. 2006, 50 (4): 562-571. 10.1016/j.yhbeh.2006.06.023.View ArticlePubMedGoogle Scholar
- Fernandez-Fernandez R, Martini AC, Navarro VM, Castellano JM, Dieguez C, Aguilar E, Pinilla L, Tena-Sempere M: Novel signals for the integration of energy balance and reproduction. Mol Cell Endocrinol. 2006, 254–255: 127-132. 10.1016/j.mce.2006.04.026.View ArticlePubMedGoogle Scholar
- Wade GN, Jones JE: Neuroendocrinology of nutritional infertility. Am J Physiol Regul Integr Comp Physiol. 2004, 287 (6): R1277-1296.View ArticlePubMedGoogle Scholar
- Montagnani C, Labreuche Y, Escoubas JM: Cg-IkappaB, a new member of the IkappaB protein family characterized in the pacific oyster Crassostrea gigas . Dev Comp Immunol. 2008, 32 (3): 182-190. 10.1016/j.dci.2007.06.001.View ArticlePubMedGoogle Scholar
- Ghosh S, May MJ, Kopp EB: NF-kappa B and Rel proteins: evolutionarily conserved mediators of immune responses. Annu Rev Immunol. 1998, 16: 225-260. 10.1146/annurev.immunol.16.1.225.View ArticlePubMedGoogle Scholar
- Fabioux C, Corporeau C, Quillien V, Favrel P, Huvet A: In vivo RNA interference in oyster: vasa silencing inhibits germ cell development. FEBS Journal. 2009, 276: 2566-2573. 10.1111/j.1742-4658.2009.06982.x.View ArticlePubMedGoogle Scholar
- Yu H, Li Q: Exploiting EST databases for the development and characterization of EST-SSRs in the Pacific oyster (Crassostrea gigas). J Hered. 2008, 99 (2): 208-214. 10.1093/jhered/esm124.View ArticlePubMedGoogle Scholar
- Rafalski A: Applications of single nucleotide polymorphisms in crop genetics. Curr Opin Plant Biol. 2002, 5 (2): 94-100. 10.1016/S1369-5266(02)00240-6.View ArticlePubMedGoogle Scholar
- Curole JP, Hedgecock D: Estimation of preferential pairing rates in second-generation autotetraploid pacific oysters (Crassostrea gigas). Genetics. 2005, 171 (2): 855-859. 10.1534/genetics.105.043042.PubMed CentralView ArticlePubMedGoogle Scholar
- Quilang J, Wang S, Li P, Abernathy J, Peatman E, Wang Y, Wang L, Shi Y, Wallace R, Guo X, et al: Generation and analysis of ESTs from the eastern oyster, Crassostrea virginica Gmelin and identification of microsatellite and SNP markers. BMC Genomics. 2007, 8: 157-10.1186/1471-2164-8-157.PubMed CentralView ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.