
Genetic matchmakers aim for a perfect pairing of oysters
Scientists seek best candidates to create most resilient and commercially viable offspring
Scientists from the University of Aberdeen and Native Aqua, a native oyster farm near Mull, have been awarded £14,300 to investigate how to improve the resilience of the native oyster, in a bid to boost the numbers of the species.
Researchers will use novel data-driven genetic approaches to inform a new breeding programme. By analysing the genetic fingerprint of each species in a breeding programme they can then optimise which oysters to breed together for the strongest offspring. This approach is common in agriculture and aquaculture farmed species, but has so far not been used to help the native oyster.
Dr Victoria Sleight, from the University of Aberdeen who is leading the project said: “The native oyster has suffered drastic decline due to overfishing of wild stocks and climate change. Because every healthy native oyster on a farm will release 1-2 million baby larvae into the ocean, farming and breeding this species to improve their resilience to climate change, will restore natural populations and enhance commercial shellfish aquaculture industries.”

Dr Tom Ashton is co-founder of Native Aqua and a former director of St Andrews aquaculture genetics company Xelect.
He said: “Native oysters are a notoriously difficult species to farm, they have poor robustness and slow growth.
“We aim to use scientific collaboration to develop a strong bloodline that performs well on commercial farms. The wonderful thing about native oysters is that they spawn naturally whilst being grown for the table market, so aquaculture operations improve wild stocks.
“Our collaboration with Aberdeen will advance the development of quality farmed oysters and will leave a permanent positive legacy on the UK’s marine ecosystem.”
This is the first time that modern genetic analysis and selection techniques have been used to study the species.
Funding for the one-year project has been awarded from Scottish Universities Life Sciences Alliance and The Data Lab.