Summary
When making breeding decisions would you consider the views of a geneticist? Well, anyone using the Good Bulls Guide, Australian Breeding Values (ABVs) or the Balanced performance Index (BPI) is drawing upon genetics research going back more than 25 years in Australia.
And Dr Jennie Pryce has been at the centre of Australia’s dairy genetic advancements for nearly half that time. She heads up the animal program within DairyBio, a joint initiative between Agriculture Victoria, Dairy Australia and the Gardiner Dairy Foundation. The DairyBio team is based in purpose-built facilities at the AgriBio Centre for AgriBioscience in Bundoora. It’s home to Agriculture Victoria’s genetics research team, and is co-located with industry organisations such as DataGene, Holstein Australia, Jersey Australia and NHIA. It creates a unique mix of great scientific minds, cutting edge technology and real-world perspective.
It’s an ideal research environment for Jennie who grew up on a dairy farm at Shropshire, UK, breeding pedigree Holsteins under the registered prefix of Severnvale Holsteins. A love of science led Jennie to study at Edinburgh University, ultimately achieving a doctorate in genetics. So, it is not surprising that she enjoys working with Australian dairy farmers and using the latest advances in genomics to develop new Australian Breeding Values (ABVs).
Genomics uses DNA testing to find genetic markers associated with traits that can be observed and measured to produce a prediction of genetic merit, an Australian Breeding Value (ABV). It’s game-changing technology for Dr Pryce and her colleagues.
“The combination of genomics and the capacity for computers to analyse massive data sets is enabling us to find genetic markers for traits of commercial value to dairy farmers. Genomics is particularly useful for traits that are difficult to observe and measure,” said Dr Pryce.
For example, farmers don’t routinely measure or record the impact of hot, humid weather on milk production and fertility, but Australian dairy farmers were the first in the world to be able to breed for improved heat tolerance, thanks to genomics and the DairyBio team.
International collaboration plays a key role in their work. For example, developing the Feed Saved ABV involved evaluation of the individual feed intake of thousands of cows and heifers in Australia, the UK and Netherlands.
“Individual feed intake is difficult and expensive to measure. Our Australian dataset wasn’t enough to achieve a reliable ABV. Overseas data made it possible, and we were the first in the world to release a tool nationally for all farmers to breed for improved feed efficiency.”
It’s a similar story with developing breeding values for health traits. Most health records don’t enter DataGene’s genetic evaluation data base, so Jennie’s team struggles to access the data they need to develop health ABVs. While exploring ways of increasing data coming into the databases, they are also using milk screening technology (MIR) used in herd test centres to identify links between milk MIR results and genetic markers for subclinical health issues such as milk fever and ketosis.
“We’ve been collaborating with European researchers on this work, which has a number of exciting potential applications such as predicting future fertility of cows from a herd-test sample taken in early lactation.”
While the MIR research is ongoing, Dr Pryce said it was a good example of the important role of new technologies in genetic advances.
“Traditionally, dairy genetics focused on production traits like milk volume and solids content. But dairy farmers need cows that are more than just good producers; they need to be fertile, healthy and have a variety of other traits that enable them to last many years in the milking herd. It is very exciting to have new technologies that are enabling us to develop breeding values for a broader range of traits that are important to farmers,” Dr Pryce said.
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Caption: Agriculture Victoria’s Dr Jennie Pryce leads the DairyBio animal genetics team which is using genomics to identify gene markers for traits that are difficult to measure e.g. health. |