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      Genomic resources for a commercial flatfish, the Senegalese sole (Solea senegalensis): EST sequencing, oligo microarray design, and development of the Soleamold bioinformatic platform

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          Abstract

          BackgroundThe Senegalese sole, Solea senegalensis, is a highly prized flatfish of growing commercial interest for aquaculture in Southern Europe. However, despite the industrial production of Senegalese sole being hampered primarily by lack of information on the physiological mechanisms involved in reproduction, growth and immunity, very limited genomic information is available on this species.ResultsSequencing of a S. senegalensis multi-tissue normalized cDNA library, from adult tissues (brain, stomach, intestine, liver, ovary, and testis), larval stages (pre-metamorphosis, metamorphosis), juvenile stages (post-metamorphosis, abnormal fish), and undifferentiated gonads, generated 10,185 expressed sequence tags (ESTs). Clones were sequenced from the 3'-end to identify isoform specific sequences. Assembly of the entire EST collection into contigs gave 5,208 unique sequences of which 1,769 (34%) had matches in GenBank, thus showing a low level of redundancy. The sequence of the 5,208 unigenes was used to design and validate an oligonucleotide microarray representing 5,087 unique Senegalese sole transcripts. Finally, a novel interactive bioinformatic platform, Soleamold, was developed for the Senegalese sole EST collection as well as microarray and ISH data.ConclusionNew genomic resources have been developed for S. senegalensis, an economically important fish in aquaculture, which include a collection of expressed genes, an oligonucleotide microarray, and a publicly available bioinformatic platform that can be used to study gene expression in this species. These resources will help elucidate transcriptional regulation in wild and captive Senegalese sole for optimization of its production under intensive culture conditions.

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          Most cited references 57

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          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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            Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

            The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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              Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research.

              We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. Blast2GO is freely available via Java Web Start at http://www.blast2go.de. http://www.blast2go.de -> Evaluation.
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                Author and article information

                Affiliations
                [1 ]Laboratory of the Institut de Recerca i Tecnologia Agroalimentàries (IRTA)-Institut de Ciències del Mar, Consejo Superior de Investigaciones Científicas (CSIC), 08003 Barcelona, Spain
                [2 ]Oryzon Genomics, Scientific Parc University of Barcelona, 08028 Barcelona, Spain
                [3 ]CIBERehd, Hospital Clínic, 08036 Barcelona, Spain
                [4 ]IFAPA Centro "El Toruño", Junta de Andalucía, 11500 El Puerto de Santa María, Cádiz, Spain
                [5 ]Instituto de Ciencias Marinas de Andalucía, CSIC, 11510 Puerto Real, Cadiz, Spain
                [6 ]Institut de Ciències del Mar, CSIC, 08003 Barcelona, Spain
                [7 ]Department of Physiology, Faculty of Biology, University of Barcelona, 08028 Barcelona, Spain
                Contributors
                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2008
                30 October 2008
                : 9
                : 508
                2612027
                1471-2164-9-508
                18973667
                10.1186/1471-2164-9-508
                Copyright © 2008 Cerdà et al; licensee 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.

                Categories
                Research Article

                Genetics

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