AQUA NEWS

EU PROJECT TO IMPROVE THE UNDERSTANDING OF THE EXPRESSION OF BIOLOGICAL TRAITS IN FISH

Infectious diseases are one of the main issues in sustainable farmed fish production in Europe, accumulating a yearly economic loss of €1,800 million. They are expected to increase even more because of climate change, pressing the need to breed more resilient farmed fish strains. Advanced understanding of the regulation of genes in fish may help understand and improve important traits such as disease resistance. The EU-funded project AQUA-FAANG is laying the foundation for improved selective breeding to help tackle the main issues in aquaculture production.  Recent developments in genomics have advanced innovation in European aquaculture.

However, the current understanding of genome function remains limited in major farmed fish species. Therefore, the project aims to understand better how the genes of fish are being expressed to influence traits of commercial importance. To achieve this, the genome will be studied to determine how genes are regulated under different biological conditions. The project’s key focus is to address the challenge of aquaculture infectious diseases, like viruses, bacteria, and parasites, a significant threat to sustainable fish farming. The AQUA-FAANG project will generate high-quality maps of fish genomes, revealing detailed information on the expression of biological traits. The project focuses on the six most important farmed species in Europe: turbot, European seabass, gilthead seabream, Atlantic salmon, rainbow trout, and common carp.  To understand how the genome is linked to biological traits, it is not sufficient to only sequence the genes. Several methods need to be performed, each providing different types of information on which parts of the genome are activated. By comparing results from these methods, it is possible to understand in more detail how the genome reacts to the environment and how it is linked to a biological trait. The knowledge obtained by annotation (e.g., gene expression) may be useful to help predict breeding values for disease resistance and other traits.