Abstract #275

# 275
Building a better cow: The Australian experience and what’s next.
J. E. Pryce*1,2, M. Shaffer3, 1Agriculture Victoria, Bundoora, VIC, Australia, 2La Trobe University, Bundoora, VIC, Australia, 3DataGene, Bundoora,VIC, Australia.

Genomic selection has opened up opportunities for developing new breeding values that rely on phenotypes that use dedicated reference populations of genotyped cows. There are also opportunities to advance phenotype collection through automation and identifying predictor traits that can be measured cost-effectively. One model is to identify the best phenotypes to measure in research herds and then increase observations (perhaps using predictors) in genotyped commercial herds. Further advances in the accuracy of genomic prediction can be gained from the use of sequence data, in addition to gene expression studies, which can lead to improved persistence of genomic breeding values across generations. In Australia integrating data collection with a research and implementation platform is the platform for delivering new methodologies and breeding values. For example, we have recently delivered the Feed Saved breeding values to industry and are soon to deliver genomic breeding values for Heat Tolerance. Identifying traits to include in the national objective will be the focus of future breeding value research, such as expanding the number of health traits breeding values available. However, industry, market and social drivers may see the emergence of new breeding values, such as cow level methane emissions, gestation length or niche milk products. To date, selection objectives have been similar globally, but it is possible that they may diverge into the future. Selection index methodology is still needed to ensure that the weights on each trait in the index are appropriate, although the weights are subtly altered to respond to respective industry and consumer requirements. So far nationwide indices remain standard practice, but this may change in the future, especially as tools to deliver information back to farmers become more sophisticated. Already bull selection tools and personalised genetic trends are available, but the capture of economic and farm data will see the emergence of even more tools. Increasing the rate of genetic gain in the genomics era remains a challenge in Australia, so industry engagement is paramount.

Key Words: genomic selection, novel traits, selection index

Speaker Bio
Dr Jennie Pryce is Principal Research Scientist of Agriculture Victoria and La Trobe University, located at AgriBio, where she leads a large team of scientists and supervises PhD students. Her main areas of interest are genetic improvement of functional traits in dairy cattle, optimising breeding scheme design under genomic selection and development of dairy selection indices.
Jennie is also a senior editor with the Journal of Dairy Science and a member of the ICAR (International Committee on Animal Recording) working group on functional traits. In Australia, Jennie is Lead Scientist of DataGene and also sits on several industry and research alignment groups that shape the future of dairy research in Australia.