Literature DB >> 18257394

EST-based identification of genes expressed in perch (Perca fluviatilis, L.).

Federica Rossi1, Valentina Chini, Anna Giulia Cattaneo, Giovanni Bernardini, Genciana Terova, Marco Saroglia, Rosalba Gornati.   

Abstract

Perch are promising species for freshwater aquaculture and, differently from other fish, have not yet been domesticated through artificial selection; therefore, they show a wide genetic variability that is undesirable for aquaculture. In addition to the more traditional methods of aquatic biotechnology, the most recently developed molecular biological techniques can augment the overall efficiency of aquaculture. To help these new molecular techniques find their place in the everyday management of fish farming, we should make an effort to reduce the gap in genomic resources that separates farming species from "model organisms." We performed single-pass sequencing on 1237 randomly selected clones from a perch liver cDNA expression library, 350 clones of a brain-minus-liver, and 639 clones of a liver-minus-brain subtraction library. The sequences were deposited in the NCBI Expressed Sequence Tags database (www.ncbi.nlm.nih.gov/projects/dbEST). In the three libraries we identified 108, 46, and 104 genes, respectively. EST cataloguing and profiling of perch will provide a basis for functional genomic research in this species, but will also promote studies in comparative and environmental genomics, for identifying polymorphic markers that are useful, for example, to survey the disease resistance of fish and for discovering of new molecular markers of exposure. Using these genomic resources, micro- and macroarrays can be produced that will give immediate and practical benefits in the field of aquaculture, allowing early diagnosis of the fish conditions and helping in the generation of new mechanistic data on the nature of fish responses to different farming conditions.

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Year:  2007        PMID: 18257394      PMCID: PMC6042039          DOI: 10.3727/105221607783417600

Source DB:  PubMed          Journal:  Gene Expr        ISSN: 1052-2166


  39 in total

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