- Evolutionary developmental biology
- Cellular interactions and extracellular matrix
Skeletal anomalies in farmed fish are a continuous problem for global aquaculture, affecting fish welfare, performance, and product quality. Aquaculture research has made considerable progress in reducing the incidence of deformities, but new species, intensified production, the damned for sterile fish, delicate early life stages and new fish feed ingredients are a continuous challenge. The use of zebrafish (Danio rerio) and medaka (Oryzias latipes) as models for research into human skeletal diseases such as osteoporosis, osteopetrosis and degenerative joint diseases is increasing, however their potential as models for farmed fish has not been sufficiently explored. These models offer the possibility to obtain deeper insights into the fundamental mechanisms that can cause skeletal malformations in humans and in farmed fish. A framework for
communication and scientific exchange between the aquaculture and biomedical sectors would benefit all stakeholders and advance scientific understanding of the problem. We propose a joint inter-sectorial training network to increase the mobility and visibility of scientists between aquaculture research and the biomedical sector using small fish models. The proposed ESR programs will provide career development to young researchers in the field of skeletal biology through international and multidisciplinary training on innovative molecular, histological, biochemical and cell culture methodologies relevant to both sectors. The network combines stakeholders from 7 European Universities, a US research hospital, and one Biological Institute. Commercial interests are represented by two Economy departments, one aquaculture and a major fish feed
production company. This structure allows the flow of information and people between the biomedical and aquaculture sectors, and between academic and applied sectors, thus addressing several objectives of the Europe 2020 strategy and ensuring a direct route from knowledge to application.