The exceptionally fast growth that fish experience after periods of fasting has been called ‘compensatory growth’ or ‘catch‐up’ growth. This phenomenon, reported in a wide range of fish species, has been studied in intensive aquaculture as a means of enhancing feed conversion efficiency, but the mechanisms implicated are complex and not yet fully understood. In the present study, the authors describe the cloning and sequencing of the complete coding sequences of sea bass (Dicentrarchus labrax) insulin‐like growth factor‐I (IGF‐I) and insulin‐like growth factor‐II (IGF‐II), which are potent mitogens known to play important roles in growth and development. Sea bass IGF‐I has an open reading frame (ORF) of 561 bp that encodes a mature protein of 187 amino acids, whereas IGF‐II has an ORF of 648 bp encoding a mature protein of 216 amino acids. At the amino acid level, sea bass IGF‐I shares a 30% similarity with IGF‐II. The authors then report the pattern of IGF‐I and IGF‐II gene expression in liver and myotomal muscle in response to prolonged fasting and refeeding. Nutritional status significantly influenced IGF‐I messenger RNA copy number in both liver and muscle, inducing a down‐regulation during fasting and an up‐regulation during the recovery from fasting. The trend of IGF‐II response was similar, but different feeding regimens did not affect the amounts of transcript as sharply as in IGF‐I. Taken together these data indicate that IGF‐I and IGF‐II participate in promoting sea bass muscle compensatory growth induced by refeeding.

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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.