Disease outbreaks remain one of the greatest challenges facing modern aquaculture. Viral, bacterial and parasitic diseases continue to cause substantial economic losses, compromise animal welfare and threaten the sustainability of production systems worldwide. Over the past two decades, selective breeding has become one of the most effective tools available to tackle these challenges. Genetic improvement programmes have successfully increased disease resistance in several aquaculture species, enabling producers to reduce mortality and improve overall production performance. But as breeding technologies continue to advance, researchers and breeding organisations are asking an important question:
Can genetics help not only improve survival, but also reduce the spread of disease within a population?
While disease resistance has traditionally been measured through survival, disease outbreaks are driven by more complex biological processes. Understanding these processes will drive the development of the next generation of breeding programmes designed not only to improve survival, but also to enhance overall population resilience.
At Xelect, breeding programme design increasingly considers not only individual performance traits, but also how populations behave under real-world production conditions. Understanding disease dynamics is a key part of this broader Breeding Programme Management approach.
Image: Silvia Garcia-Ballesteros during a customer site visit.
Beyond Survival: Understanding Disease Resistance
Traditionally, disease resistance is evaluated through challenge tests in which relatives of selection candidates are exposed to a pathogen under controlled conditions. The most common traits recorded are survival status (dead or alive) or time-to-death following infection. These measurements have delivered substantial genetic gains and remain valuable tools for improving resistance to economically important diseases. However, survival is only the final outcome of a series of epidemiological processes that determine how pathogens spread within a population.
During a disease outbreak, some animals become infected more easily than others. Some may carry and spread pathogens more efficiently, while others may be less likely to transmit infections. As a result, two populations with similar survival rates may experience very different disease dynamics. In practical terms, this means that a population can be genetically more resilient not only because more animals survive, but also because the disease itself struggles to spread.
Why Disease Transmission Matters for Producers
For producers, reducing mortality is clearly important. However, long-term sustainability also depends on reducing the frequency, duration and severity of disease outbreaks. When diseases spread rapidly, outbreaks can last longer, affect more animals and require greater management efforts. By contrast, populations that are less likely to become infected or transmit pathogens, can help slow the progression of an outbreak.
This can be illustrated with a simple scenario. Imagine two groups of fish exposed to the same disease challenge. In both groups, survival at the end of the outbreak is similar. However, in one group the disease spreads quickly through the population, while in the other, it spreads more slowly. Although both populations may show similar mortality levels, the second population provides a much greater benefit from a health management perspective.
The key question is therefore whether genetic selection can contribute not only to improving survival but also to reducing outbreak risk. For producers, this means the benefits of genetic improvement could extend beyond reducing mortality during individual outbreaks. More resilient populations may help reduce disease pressure within production systems, supporting more stable performance and improving long-term farm sustainability.
Can We Select Against Disease Spread?
Advances in genomics, data analysis and disease modelling are helping researchers better understand the biological processes that influence disease spread. Recent research has highlighted that genetic differences between animals can influence not only survival following infection, but also how diseases spread through populations.
This is an exciting development because it means that breeding programmes may be able to contribute to disease control in new ways. Future breeding strategies may increasingly incorporate traits associated with disease transmission alongside traditional resistance measures, helping to improve population-level resilience. From a commercial perspective, this approach represents a shift from managing disease outbreaks after they occur towards developing populations that are better prepared to withstand health challenges from the beginning.
How Measurement Shapes Breeding Outcomes
An important lesson from recent studies is that the way disease resistance is measured can influence breeding outcomes. Different challenge test designs may identify different types of animals as being the most resistant. Some fish may survive because they are genuinely difficult to infect, while others may survive because they become infected later or cope better once infected.
Understanding these differences helps breeders identify which animals contribute most effectively to long-term population health. As breeding programmes continue to evolve, improving the design of disease challenge tests will remain an important area of research. Better measurements can lead to more accurate selection decisions and greater improvements in health-related traits.
Integrating Genetics and Epidemiology
Advances in genomics, computing power and data analysis are creating new opportunities to rethink how breeding programmes are designed and evaluated. Traditionally, breeding decisions have focused on predicted genetic gain for traits such as growth, survival, feed efficiency and product quality. While these remain fundamental objectives, there is growing recognition that disease resilience should also be evaluated from a population perspective.
By integrating epidemiological models with genetic simulation and prediction tools, it becomes possible to evaluate not only how animals are expected to perform individually, but also how breeding decisions may influence disease dynamics across entire production systems. This approach opens the door to addressing questions such as:
- Which breeding strategies are most effective at reducing outbreak risk?
- How should challenge tests be designed to maximise disease control?
- Which traits generate the greatest benefit at both individual and population levels?
- How might selection decisions influence long-term resilience and sustainability?
What This Means for Breeding Programme Design
For breeding programme managers, this evolving understanding of disease resilience highlights several important considerations:
- Challenge testing methods should capture infection dynamics as well as survival
- Genomic evaluations may increasingly consider traits linked to susceptibility and transmission
- Population-level performance should be considered alongside individual breeding values
- Epidemiological modelling should be integrated to support long-term selection decisions
As these approaches develop, breeding programmes will increasingly focus on delivering both immediate performance gains and improved system-level resilience.
Building More Resilient Aquaculture Populations
The aquaculture industry has already demonstrated the value of genetic improvement for reducing disease losses. Emerging research suggests that breeding programmes may be able to go a step further by selecting populations that not only survive disease challenges but also limit disease transmission.
As genomic technologies, epidemiological models and breeding tools continue to advance, programme managers will gain new opportunities to evaluate health traits from both individual and population perspectives. This will help support breeding decisions that improve animal health, reduce outbreak risk and strengthen the long-term sustainability of aquaculture production systems.
By combining genetics with epidemiological insight, the industry can build more resilient populations and take a more proactive approach to disease management.
About the Author
Dr Silvia García-Ballesteros is a Breeding Programme Manager at Xelect, specialising in the application of genomic tools to aquaculture breeding programmes. She holds a degree in Veterinary Medicine and a master’s in Biostatistics from the Complutense University of Madrid, where she also completed her PhD in Veterinary Science in collaboration with INIA-CSIC.
