Using advanced technology scientists at Aarhus University, in collaboration with Danish Crown, the Danish Meat Research Institute and a number of international partners have identified biomarkers that can be used to predict meat quality. The scientists found markers for meat quality that could be used, so now it is just a matter of developing tools for practical use.
Fishing through the genome
The results that scientists have generated so far are based on research carried out as part of a huge, five-year EU project – Q-PorkChains – which has involved 62 partners from a large number of countries. The project was launched in 2007 and was completed in December 2011.
In the part of the project we contributed to, we used the new technologies of proteomics and transcriptomics to identify suitable biomarkers for meat quality in pork.
The scientists received muscle biopsies from the slaughterhouses from different European countries and established a muscle library. And it was this library they used to fish for markers related to quality aspects of meat. When they found interesting links between genes and meat quality attributes they verified the results at the level of individual genes using a technique called RT-PCR. The results were then validated in other porcine lines. In this way the scientists could confirm if there was a link between a certain gene and a certain attribute.
The meat quality attributes that the scientists investigated were drip loss, colour, juiciness, flavour, intramuscular fat and tenderness. The investigations paid off, but require further development work.
- We have found 16-20 genes that are interesting in connection with drip loss, but the link between individual genes and the attribute is too weak, so the possibility for predicting meat quality is correspondingly weak. Now we would like to develop tools that look at, for example, 6-7 genes at a time. This will give a better expression for the attribute and make the prediction safer, explains Niels Oksbjerg.
January 2012/ Aarhus University/Denmark.