BMC Genomics

official impact factor 4.21

Open Access Research article

Gene expression in the brain and kidney of rainbow trout in response to handling stress

Aleksei Krasnov1*, Heikki Koskinen1, Petri Pehkonen1, Caird E Rexroad2, Sergey Afanasyev3 and Hannu Mölsä1

  • * Corresponding author: Aleksei Krasnov krasnov@uku.fi

  • † Equal contributors

Author Affiliations

1 Institute of Applied Biotechnology, University of Kuopio, P.O.B. 1627, 70211 Kuopio, Finland

2 National Center for Cool and Cold Water Aquaculture, USDA-ARS, 11876 Leetown Road, Kearneysville, WV 25430, USA

3 Sechenov Institute of Evolutionary Physiology and Biochemistry, M.Toreza av. 44, Petersburg, 194223, Russia

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BMC Genomics 2005, 6:3 doi:10.1186/1471-2164-6-3

Published: 6 January 2005

Abstract

Background

Microarray technologies are rapidly becoming available for new species including teleost fishes. We constructed a rainbow trout cDNA microarray targeted at the identification of genes which are differentially expressed in response to environmental stressors. This platform included clones from normalized and subtracted libraries and genes selected through functional annotation. Present study focused on time-course comparisons of stress responses in the brain and kidney and the identification of a set of genes which are diagnostic for stress response.

Results

Fish were stressed with handling and samples were collected 1, 3 and 5 days after the first exposure. Gene expression profiles were analysed in terms of Gene Ontology categories. Stress affected different functional groups of genes in the tissues studied. Mitochondria, extracellular matrix and endopeptidases (especially collagenases) were the major targets in kidney. Stress response in brain was characterized with dramatic temporal alterations. Metal ion binding proteins, glycolytic enzymes and motor proteins were induced transiently, whereas expression of genes involved in stress and immune response, cell proliferation and growth, signal transduction and apoptosis, protein biosynthesis and folding changed in a reciprocal fashion. Despite dramatic difference between tissues and time-points, we were able to identify a group of 48 genes that showed strong correlation of expression profiles (Pearson r > |0.65|) in 35 microarray experiments being regulated by stress. We evaluated performance of the clone sets used for preparation of microarray. Overall, the number of differentially expressed genes was markedly higher in EST than in genes selected through Gene Ontology annotations, however 63% of stress-responsive genes were from this group.

Conclusions

1. Stress responses in fish brain and kidney are different in function and time-course. 2. Identification of stress-regulated genes provides the possibility for measuring stress responses in various conditions and further search for the functionally related genes.