Phenobank – improving fertility in Northern Australian beef herds
The female reproduction Phenobank project was undertaken to collect datasets to build a reference population to facilitate genomic selection in northern Australian cattle. A large reference population is needed for more accurate genomic Estimated Breeding Values (gEBVs). The Phenobank project used existing datasets from research herds and commercial producers with stored DNA samples create the database.
Phenobank is an initiative developed as a ‘warehouse’ for beef cattle data. It is free for producers to use and gives capacity for the data to be stored and shared. Phenobank is a valuable tool which will assist with herd management and decisions regarding breeding female selection.
Phenotypic data (data based on observable characteristics expressed from genes) collected from around 10,000 tropical cows and heifers, recording pregnancy, calving and rebreed data along with stored DNA samples was used to create the Phenobank. This reference population underpins the discovery and validation of using predictive genetic markers for female reproduction traits.
Method
After a working collaboration with University of Queensland, Meat and Livestock Australia, CSIRO and Northern Territory Department of Industry, Tourism and Trade was established, new software was developed to create the database of genetic information.
Data came from females from the Victoria River Research Station, Douglas Daly Research Farm, research stations in Queensland and commercial producers that collaborated in the project. Historic data from the CRC for Beef Genetic Technologies (Beef CRC) was also included as they had useful phenotype data and a retrievable DNA sample for genotyping.
Phenotypes that were recorded were the year that the female was born, her pregnancy status after first (PREG1), second and third mating, along with time between giving birth and beginning to cycle again (REB).
Results
The Phenobank database was successfully created and the reproduction phenotypes and genotypes of 10,507 cows across research and industry herds was added to the databank.
The administrator for this database is currently ABRI in collaboration with CSIRO. Pastoralists that shared their herd data were given a unique username and passcode to access their data. The Phenobank model has progressed to be able to accommodate the creation of new profiles and new cows can be added to allow for expansion.
Following the analysis of the genomic models, Preg1 and REB had heritability estimates of 0.17 and 0.21 respectively. These heritabilities were similar to the estimates for the same measured traits previously reported. Prediction accuracy estimates for these traits were high and demonstrate the potential for genomic technologies to improve reproductive efficiency and transform the productivity of Australia’s northern beef herd.
Conclusion
The Phenobank project has shown that it is possible to work directly with producers to collect useful datasets for female reproduction traits, which can boost reference populations, increase prediction accuracies, and facilitate the adoption of genomic technologies.
Heritability estimates and genomic correlations suggest that fertility can be improved through selection for the traits used in this project. Ultimately this would lead to better breeding rates in tropical herds and improved profitability.
Best Practise Management strategies to take away from this project
- Record wet/dry and pregnancy status of cows – cull cows that are dry (not lactating) and empty (not pregnant). Foetal aging data can be used to identify cows that will calve at desirable times of year and make management decision.
- Bull testing – make sure all bulls are fertile, fit and healthy
- EBV’s and gEBV’s for fertility traits can be used to select bulls that will improve herd fertility.
Contact details:
Project leader:
Dr. Marina Fortes, University of Queensland, email: m.fortes@uq.edu.au
Research officer:
Gretel Bailey-Preston, Katherine Research Station, email: gretel.baileypreston@nt.gov.au
