GENETIC markers for productive traits in cattle have proved far more difficult to find than might be expected.
Unlike some specific genetic disorders and red or black coat colour, productive traits are rarely controlled by just one gene. In fact, they have been shown to be remarkably complex.
Beef CRC chief scientist, Professor Mike Goddard, professorial fellow in animal genetics with Melbourne University and DPI Victoria, says "we simply don't know'' what genes control the main traits.
"If we could identify the genes that made one animal more productive than another we could simply select for that gene based on a DNA test and be assured of productive improvement," he says.
Until recently breeders could only collect phenotype, or trait, data on breeding animals and their progeny. Then the discovery of genetic markers made it possible to identify individual genes that are responsible for major abnormalities and coat colour. More recently, it has become possible to use thousands of genetic markers to predict the breeding value of cattle and sheep for economically important, but complex, traits such as milk yield.
"The information from these thousands of genetic markers can now be combined with performance and pedigree data to improve the accuracy of Estimated Breeding Values," says Prof Goddard.
Speaking at the Genetics Conference held as part of the Beef Australia 2012 program in Rockhampton last week Prof Goddard announced the delivery of genomic breeding values for key beef production and market traits across Australian beef cattle breeds.
He said the prediction of genomic breeding values across cattle breeds was a world-first innovation, and would be integrated into the existing estimated breeding values (EBVs) in BREEDPLAN, the beef cattle industry's genetic database by July this year.
"We've developed genomic across-breed predictions for all the existing traits in BREEDPLAN, except birth and weaning traits, including traits such as feed efficiency, carcase and beef quality and female and male reproductive performance," Prof Goddard said.
The prediction equations have been developed to work in all breeds. However they will be most accurate for the breeds that were available in the training data (that is, Angus, Hereford, Shorthorn, Brahman and Brahman-derived composites such as the Santa Gertrudis, Belmont Red and pastoral company Tropical Composites).
"The critical thing is that these genomic predictions have been developed and tested on Australian cattle under Australian beef production systems," Prof Goddard said.
The accuracy of the CRC's predictions vary across traits. For example, the average accuracy of predictions for feed conversion efficiency is about 40% (0.4), for marbling and age at puberty in heifers and bulls it is about 30% but it is only about 20% (0.2) for eye muscle area.
The accuracy also varies across the cattle breeds, with the accuracy being highest in those breeds with the largest number of trait records.
The key advantage of the Beef CRC's genomic research was for breeders to gain a genetic insight into the qualities of young animals that do not have any performance data recorded.
"You can't at present, for example, measure days to calving on a young bull. But if you could use BREEDPLAN genomic EBVs to predict days to calving with improved accuracy, that would really improve the decision-making process for breeders and producers in selecting the top animals," Prof Goddard said.
The Beef CRC's genomic predictions draw upon the "genotype'' (derived from the animals' DNA) and "phenotype'' (physical measurements on hard-to-measure traits) records of 10,000 beef cattle and used the latest 700K SNP chips that were released in late 2010.
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