Salmon could be bred to be more resistant to sea lice by using genetic data in a relatively inexpensive manner, scientists say.
The technique could be used in selective breeding to help mitigate the impact of sea lice, which is the most costly disease for the salmon aquaculture industry. It also has potential to be used for improving other economically important traits, and in other aquaculture species around the world, including shrimp and tilapia.
Selective breeding, using genetic data from across the entire genome – called genetic markers, can help improve the innate resistance of farmed salmon to sea lice and reduce prevalence of this disease. However, collecting this type of genetic marker data from large numbers of fish through DNA sampling can be prohibitively expensive in many typical aquaculture settings.
The scientists, led by Dr Smaragda Tsairidou and Professor Ross Houston at the Roslin Institute, were able to predict the genetic resistance of salmon to sea lice using far fewer genetic markers than is typical.
This was achieved by optimising the use of a computational technique called genotype imputation, and looking at variation at specific positions in the genome – called low density single nucleotide polymorphism markers genotypes.
Their approach enabled a low-cost assessment of the genetic makeup of the population with regards to sea lice resistance, which can inform selective breeding decisions to choose more resistant parents for breeding the next generation.
Sea lice is the most costly disease-related problem for the global salmon industry worldwide, and has a severe negative impact on salmon health, welfare and performance. In this study we used low density genetic markers to predict the resistance of salmon to sea lice, which is potentially more cost-efficient. The results from this study can be used to help breed salmon with improved resistance to this and other diseases.
Professor Ross Houston, Chair of Aquaculture Genetics, The Roslin Institute
The study was a collaboration with scientists at the Universities of Edinburgh and Stirling, and Hendrix Genetics. It was funded by the Scottish Aquaculture Innovation Centre and is published in the journal G3.
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