Bull fertility update: historical data, new cohort and advanced genomics Final Report
Did you know, this project combined data from the CRC for Beef Genetic Technologies with new data, collected in partnership with producers, to create one of the most complete datasets on bull fertility traits with matched DNA profiles.
| Project start date: | 23 February 2019 |
| Project end date: | 28 July 2021 |
| Publication date: | 29 June 2022 |
| Project status: | Completed |
| Livestock species: | Grass-fed Cattle |
| Relevant regions: | National |
|
Download Report
(1.8 MB)
|
|
Summary
This project combined data from the CRC for Beef Genetic Technologies with new data, collected in partnership with producers, to create one of the most complete dataset on bull fertility traits with matched DNA profiles. The traits assessed are those recorded in the bull breeding soundness examination (BBSE). The assembled dataset included nearly 7,000 records in six tropical breed types.
Objectives
Update the Beed CRC legacy dataset to the latest technology. During the Beef CRC projects, especially Beef CRC III, an impressive dataset was collected on cattle fertility. The phenotypic records were paired with a SNP profile, mostly at around 50,000 SNP markers density. We proposed and successfully applied imputation approaches to fill in missing trait records and increase marker density from the original SNP chip up to the whole-genome sequence (around 22 million SNP).
• Expand the Beef CRC dataset on bull fertility and generate impactful outcomes. We achieved this objective by increasing the number of bulls evaluated from around 2,800 up to nearly 10,000 bulls with BBSE records. Around 7,000 of these bulls have a matching DNA profile. Using this newly combined dataset, we exploited the genetic architecture of BBSE traits to identify the most relevant genomic regions associated with the traits and we derived multibreed genomic breeding values with useful accuracies.
Key findings
Heritability estimates varied from low (0.17 body condition score and 0.19 sperm progressive motility) to moderate (0.46 scrotal circumference and 0.52 sheath score). Although some traits showed a few genomic regions with highly significant associations, all traits seem to be controlled by several genes (meaning they have a polygenic architecture). Surprisingly, the genomic correlation of the same trait when observed in different breeds was very low for most of the traits, except for scrotal circumference and sheath score. The interpretation of this result is that in different breeds, different genes or mutations maybe driving the studied traits.
A pleiotropy test was applied to identify markers relevant to several traits at the same time. This test allowed the identification of two key chromosomes (5 and X) that harbor most of the top makers, with additional markers on chromosomes 6, 8, 10, 21, and 24. These genomic regions can be prioritized and further explored to better understand the genes controlling bull fertility traits.
Using a multibreed genomic selection approach, estimated breeding values (GEBV) for fertility traits with useful accuracies were derived. Additionally, the importance of a breed to being represented within the reference population when estimating breeding values in a multibreed scheme was demonstrated.
Benefits to industry
• All traits observed followed a polygenic pattern, meaning that multiple regions across the genome were associated with the bull fertility traits studied in this project. Therefore, the best approach for bull fertility improvement would be via genomic selection approaches for which this project sets the basis.
• The reference population used was big and diverse enough to produce multibreed GEBV with useful accuracies for bull fertility traits for the Industry. The analyses highlighted the importance for the specific breed of interest to be part of the reference population when estimating multibreed breeding values. To estimate the most accurate GEBVs for the particular breed in question, this breed needs to be included in the reference dataset. By creating a multibreed dataset, this project paved the way for the development of GEBVs for bull fertility in multiple breed types.
MLA action
MLA continues to work with CSIRO to deliver data captured as part of the Livestock Genetics Program. Also to continue to expand and grow the reference for these traits and find a pathway to market through BREEDPLAN to make these traits available to producers.
Future research
• Working with Industry to grow the multibreed reference population used to investigate bull fertility traits. Suggest establishing a process to engage with Industry, to collect and compile BBSE records with matched DNA profiles to cement a multibreed population in our research arena. Importantly, many bull breeders already pay for BBSE and so it is of great value to leverage these existing records for genetic improvement.
• Undertaking further research on the genomic architecture of the bull fertility traits investigated in this project to a) better understand the genes controlling these traits, b) explore further avenues to assist in improving the accuracy of genomic prediction (GEBV), and c) investigate other potential uses of the defined functional mutations affecting these traits.
• Establishing a process for delivering multibreed genomic predictions for bull fertility traits to the Industry.
