Animal selection strategies have achieved outstanding results during the past decades allowing the identification of high-performing animals. However, traditional selection schemes rely on full pedigree records, which still represent a major challenge for commercial and in particular, extensive production systems common to Northern Australia.

High throughput DNA technology, such as genotyping, dispense the need for pedigree information and has added great value to genetic evaluations in the stud sector. The remaining challenge, and the goal of this project, is to make these cutting-edge technologies affordable to commercial beef cattle producers, introducing novel science-based information into decision-making processes and providing an opportunity for greenhouse gas mitigation and land sparing.
The productivity improvement of commercial herds in Northern Australia represents a significant greenhouse gas mitigation opportunity for the beef industry. While commercial beef herds managed on extensive rangelands in the North underpin the productivity of Australia’s beef industry, there is a large gap between the potential and realized yield from these herds.

Nearly 100% of Northern Australia’s herds are mated with multiple sires. Apart from being necessary to sire the calf crop from breeding herds, the choice of herd bulls is often the only way for beef enterprises to achieve genetic progress in their herds. The decision to invest in high-value bulls for a particular genetic improvement goal needs to be underpinned by the confidence that they will perform well as sires.

In this project, we propose to evaluate the performance of bulls by applying DNA-based approaches to pooled DNA samples from calves, collected at weaning. By analyzing pools instead of individual animals, we can evaluate the performance of sires at a fraction of the cost. The drawback of pooling is the loss in the accuracy of predictions. Therefore, we have been testing different strategies of pooling to deliver an optimal compromise between cost-savings and prediction accuracy. The expected outcome of this project is a cost-effective approach to 1) estimate the number of calves sired by each bull in a herd; 2) estimate the quality of calves sired by each bull in a herd; 3) assist/inform bull buying decisions.

Our first results that were published suggest that pooling ten DNA samples before profiling the DNA might represent an optimum strategy, which defines ten times cost savings, when compared to individually testing every animal, without major compromise on the accuracy of the predictions.

Alexandre, Pâmela A; Reverter, Antonio; Lehnert, Sigrid A; Porto-Neto, Laercio R; Dominik, Sonja. Short Communication: In-silico validation of pooled genotyping strategies for genomic evaluation in Angus cattle. Journal of Animal Science, v. skaa17, 2020.

Alexandre, Pâmela A; Porto-Neto, Laercio R; Karaman, Emre; Lehnert, Sigrid A; Reverter, Antonio. Pooled genotyping strategies for the rapid construction of genomic reference populations. Journal of Animal Science, v. 97, p. 4761-4769, 2019.

Bell A.M., Henshall J.M., Porto-Neto L.R., Dominik S., McCulloch R., Kijas J. & Lehnert S.A. Estimating the genetic merit of sires by using pooled DNA from progeny of undetermined pedigree. Genetics Selection Evolution 49, 28, 2017.

Reverter A., Porto-Neto L.R., Fortes M.R.S., McCulloch R., Lyons R.E., Moore S., Nicol D., Henshall J.M. & Lehnert S.A. Genomic analyses of tropical beef cattle fertility based on genotyping pools of Brahman cows with unknown pedigree. Journal of Animal Science 94, 4096-108, 2016.

Funding: CSIRO
Full name of project: The weakest link – using genomics to lift the productivity of Australia’s northern rangeland beef herds
Project Team: Pamela Alexandre, Laercio Porto-Neto, Sigrid Lehnert, Toni Reverter.
For more information: Toni Reverter-Gomez