Queen’s University Belfast has secured more than €295,000 as part of a €1.2 million international research award to develop rapid, non-invasive methods for monitoring health and disease in farmed Atlantic salmon.
The five-year project, titled Environmental RNA-based Assessment of Fish Health (eRNA-FISH), is being delivered under the US-Ireland Research and Development Partnership and involves collaboration between Queen’s University Belfast, Dublin City University, and University of Maine.
The consortium aims to develop an early-warning system capable of detecting physiological stress and disease in salmon using water samples rather than direct fish handling. The approach is based on analysing environmental RNA (eRNA), genetic material shed by fish into surrounding water, which can provide near real-time insight into biological responses to environmental conditions and infection.
Researchers say the technology could address limitations in current diagnostic approaches, which often rely on invasive or lethal sampling and may only identify problems once disease has progressed.
At Queen’s University Belfast, the project will focus on applying genomics and bioinformatics tools to identify molecular signatures associated with stress and disease. Partners at Dublin City University will contribute molecular and CRISPR-Cas expertise, while the University of Maine will support experimental design, ecological informatics, and development of monitoring frameworks.
The total €1.2 million award is supported by funding bodies in all three jurisdictions, including Ireland’s Department of Agriculture, Food and the Marine, the US Department of Agriculture’s National Institute of Food and Agriculture, and Northern Ireland’s Department of Agriculture, Environment and Rural Affairs.
Atlantic salmon is the largest marine finfish species in global aquaculture by production volume, and disease and environmental stress are widely recognised as major cost drivers for the sector. The project partners say the goal is to move disease surveillance toward a more proactive and welfare-focused model based on routine water sampling rather than fish-level testing.