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Individual identification and marking techniques for zebrafish

Author:
Delcourt, Johann, Ovidio, Michaël, Denoël, Mathieu, Muller, Marc, Pendeville, Hélène, Deneubourg, Jean-Louis, Poncin, Pascal
Source:
Reviews in fish biology and fisheries 2018 v.28 no.4 pp. 839-864
ISSN:
0960-3166
Subject:
Danio rerio, animal identification, aquaculture, color, durability, ecology, ecotoxicology, ethics, fish, genetic engineering, image analysis, managers, medicine, microchip technology, models, neurophysiology, researchers, transponders
Abstract:
In laboratory fish research, the zebrafish Danio rerio (Cyprinidae) represents the equivalent of the mouse in mammalian research. This species has become a major model for studies in developmental and behavioural genetics, neurophysiology, biomedicine, ecotoxicology, and behavioural and evolutionary ecology. To meet the need for accurate and reproducible data in both fundamental and applied sciences, it is of primary importance to be able to tag and/or recognize individual zebrafish. However, classic methods used in fish ecology and aquaculture are generally difficult to apply to such small fish. Recently, various new tagging methods have been developed. This paper presents a first review of current identification and marking methods applied to zebrafish, from external observation methods (such as skin pattern recognition, fin clipping, scale regeneration, colour and transgenic methods) to the most advanced technological developments in electronic (low- and high- radio-frequencies PIT tags, microchip) and image analysis methods (video tracking). This review aims to help researchers and zebrafish facility managers select the identification method (ID) best adapted to their needs. The main characteristics of each ID method are examined (including detection range, durability, speed and repetitiveness, ID code combination, size dependence and ethical considerations), and their pros and cons are summarized in a decision table to help select the most appropriate option for a research or management program. Finally, contextual applications of these ID methods and future developments are discussed.
Agid:
6207332