Scientists in Spain Develop a Panel of Genetic Markers for Tracing Meat from Farm to Fork

Scientists at the Universitat Autònoma de Barcelona, Spain, have developed and validated an identity test that can be used to confirm the breed and origin of meat from farm animals. The test was developed in collaboration with Applied Biosystems, an Applera Corporation business, and uses a number of specific genetic markers to identify individual animals, providing complete meat traceability and ensuring protection for consumers. The findings are published in the December 2007 issue of the scientific journal, Animal Genetics, Vol. 6, issue 38.

Meat traceability is an important prerequisite for consumer safety, particularly in the event of infectious disease outbreak or accidental feed contamination. European Union (EU) regulations concerning animal production chains are becoming increasingly stringent, with greater emphasis now placed on being able to demonstrate exactly where animals have been raised, slaughtered and sold for consumption. However, reliable, rapid and cost-effective molecular tools for animal identification are not currently available.

Professor Armand Sánchez and his colleagues from the Department of Animal and Food Sciences, Universitat Autònoma de Barcelona, and scientists from Applied Biosystems have developed a panel of 46 genetic markers that are all single nucleotide polymorphisms (SNPs), which are single sites of variation in the animal’s DNA sequence. Regions of DNA variation are commonly used for identification purposes, such as in human paternity tests and genetic fingerprinting, but these methods have traditionally relied on larger areas of polymorphism in the DNA sequence known as microsatellite markers. Although microsatellite-based genotyping requires only a handful of markers to identify an individual with very high accuracy, the technique is prohibitively expensive for genotyping livestock. However, by selecting larger numbers of suitable SNPs, SNP-based genotyping can be equally accurate for larger scale testing.

This study validated 46 SNPs, chosen from a set of 120, for identifying pigs from five different purebred lines that are of major commercial importance. The 46 SNPs were investigated in each DNA sample taken from hundreds of pigs, using the SNPlex™ Genotyping System and two 3730 DNA Analyzers from Applied Biosystems. The pattern of SNPs in each pig’s sample allowed the scientists to identify individual pigs and their parentage for each of the five breeds examined.

“We have established that 46 SNPs are sufficient to identify individual pigs, using the SNPlex technique, with absolute confidence,” said Dr. Sánchez, professor of genetics at the university. “The SNPlex platform is ideal for analyzing larger numbers of markers, and additional markers can be easily added to the panel as required, such as when breeders wish to identify specific genetic traits.”
The tests could also be useful for animal breeders and farmers who wish to identify genetic markers associated with particularly desirable traits in terms of meat quality and flavor, and could be adapted for identification and traceability in other animal species, such as sheep, cows and poultry.

“The SNP-based test provides a convenient, affordable and automation-friendly tool that can be used by farmers, breeders and meat producers to prove the quality of their products,” said Lars Holmkvist, Applied Biosystems’ president for Europe. “This Applied Biosystems technology also has the potential to enable farmers and breeders to provide their livestock with personalized identity cards.”

The SNPlex Genotyping System allows the simultaneous genotyping of up to 48 SNPs against a single biological sample, and can be used with genetic analyzers from Applied Biosystems, which set the standard as the most robust line of capillary electrophoresis systems available in the market. This includes the 48-capillary 3730 DNA Analyzer for medium to high throughput genetic analysis.

This work was funded by a collaborative project with Hypor España G.P.