Genetic chip will help salmon farmers breed better fish

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Atlantic salmon production could be boosted by a new technology that will help select the best fish for breeding. The development will enable salmon breeders to improve the quality of their stock and its resistance to disease. A chip loaded with hundreds of thousands of pieces of DNA — each holding a fragment of the salmon’s genetic code — will allow breeders to detect fish with the best genes. It does so by detecting variations in the genetic code of each individual fish — known as single nucleotide polymorphisms (SNPs). These variations make it possible to identify genes that are linked to desirable physical traits, such as growth or resistance to problematic diseases, for example sea lice infestations. Salmon breeders will be able to carry out the test by taking a small sample of fin tissue. The chip carries over twenty times more genetic information than existing tools. Similar chips have already transformed breeding programmes for land-farmed livestock including cattle and pigs. Salmon farming contributes around half a billion pounds to the UK economy each year and provides healthy, high quality food. Worldwide, approximately 1.5 million tonnes of Atlantic salmon are produced every year. Dr Ross Houston, of The Roslin Institute, said: “Selective breeding programmes have been used to improve salmon stocks since the 1970s. This new technology will allow the best breeding fish to be selected more efficiently and accurately, particularly those with characteristics that are difficult to measure such as resistance to disease” Dr Alan Tinch, director of genetics at Landcatch Natural Selection, said: “This development takes selective breeding programmes to a whole new level. It is an extension to the selective breeding of salmon allowing more accurate identification of the best fish to create healthier and more robust offspring.”

http://www.sciencedaily.com/  Science Daily March 4, 2014

http://www.sciencedaily.com/releases/2014/02/140213220427.htm  Original web page at Science Daily

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