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Integrating Genomic Approaches to Improve Dairy Cattle Resilience: a Comprehensive Goal to Enhance Canadian Dairy Industry Sustainability
Extended
Project Overview
Dairy is one of Canada's most important and dynamic industries, significantly contributing to the country’s GDP. Global demand for dairy products is set to expand further, while at the same time, the industry is facing several emerging issues, related to human and animal health, environmental impacts, sustainability, and social acceptability. This project looked to satisfy increasing demand and ensure the global competitiveness of Canada’s dairy cattle industry, while ensuring overall sustainability.
The overall objective of the project was to develop new datasets and genomic tools to deliver a more ‘resilient’ cow, i.e. an animal able to adapt rapidly to changing environmental conditions, without compromising its productivity, health or fertility while becoming more resource-efficient and reducing its environmental burden. Improvement in overall animal resilience will reduce costs for the Canadian dairy industry and provide wider benefits to society.
What Did the Research Team Do?
This project developed and implemented a set of new breeding tools for dairy farmers and the artificial insemination industry based on novel traits for resilience. An integrated multidisciplinary approach was used with seven research activities:
- Identified and implemented new “closer-to-biology” female phenotypes for fertility to enhance selection accuracy for estrous expression and embryo survival.
- Improved accuracy of genetic selection for various health traits and broaden disease resistance by adding new phenotypes to the health evaluation portfolio.
- Improved animal environmental efficiency by increasing the size of the reference population for genomic selection of improved feed efficiency and reduced methane emission.
- Clarified how the expression of the traits in Activity 1 to 3 interact and how they are impacted by environmental factors.
- Investigated potential epigenetic effects across lactation and generations for important traits.
- Identified other genomic and epigenetic markers for candidate genes or regions associated with the traits of interest.
- Defined the needs and values of both industry and consumers to identify optimal sets of traits that integrate farmer and consumer perspectives.
What Did the Research Team Do?
The research team delivered several impactful results including:
Closer to Biology Fertility
- Standardized phenotypes based on digital estrous behaviour events captured by automated sensors to be used for genetic selection of animals for optimal estrous expression.
- Linked estrous behaviour events with physiological processes, including circulating concentrations of progesterone in plasma and milk that are important for embryo survival.
- Identified Ano-genital distance as a key indicator trait for selection for improved fertility.
Enhanced Disease Resistance
- Developed routine phenotyping, protocols for data recording, and a data pipeline from farms to Lactanet to collect data for fertility disorders (cystic ovaries, retained placenta, and metritis), Johne’s Disease, calf health factors (respiratory disease, diarrhea, and calf survivability)
- Incorporated fertility disorders into routine genomic analyses leading to improved herd reproduction and profitability.
Feed Efficiency and Methane Reduction
- Enlarged the international reference populations for feed efficiency and methane emissions to 14,868 and 4,504 respectively, leading to higher accuracies of genomic evaluations.
- Incorporated feed efficiency and methane efficiency into routine genomic analyses allowing for improved environmental sustainability across the dairy industry.
Genetic and Environmental Relationships
- Identified how the expression of resilience traits are regulated and their relationship with other traits.
- Estimated genetic parameters for the resilience traits outlined above and identified favorable genetic parameters for the incorporation of these traits into routine genomic selection.
Multigenerational and Epigenetic Effects
- Quantified the effect of early maternal environment on resilience of daughters and discovered epigenetic markers related to resilience, providing information and tools to optimize management decisions and cow resilience.
Sustainability and Social Acceptance
- Identified farm level and market level outcomes from selection of resilience traits and public acceptance of dairy under different breeding strategies.
Principal Investigators
Christine Baes
University of Guelph
Co-Investigators
Ronaldo Cerri
University of British Columbia
Marc-André Sirard
Université Laval
Paul Stothard
University of Alberta
Key Words
- Resilience, fertility phenotypes, cow health, environmental efficiency, epigenetics
Period: 2018-2024
Budget: $12,058,736
Last Updated: July 10, 2024
Funding Partners
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LEARN MOREPROJECT PUBLICATIONS
- Houlahan, K., Schenkel, F. S., Hailemariam, D., Lassen, J., Kargo, M., Cole, J. B., Connor, E. E., Wegmann, S., Junior, O., Miglior, F., Fleming, A., Chud, T. C. S., & Baes, C. F. 2021. Effects of incorporating dry matter intake and residual feed intake into a selection index for dairy cattle using deterministic modeling. Animals. 11(4), 1157. https://doi.org/10.3390/ani11041157
- Tippenhauer, C. M., Plenio, J. L., Madureira, A. M. L., Cerri, R. L. A., Heuwieser, W., & Borchardt, S. 2021. Factors associated with estrous expression and subsequent fertility in lactating dairy cows using automated activity monitoring. J. Dairy. Sci. 104(5), 6267–6282. https://doi.org/10.3168/jds.2020-19578
- Tippenhauer, C. M., Plenio, J. L., Madureira, A., Heuwieser, W., & Borchardt, S. 2023. Timing of artificial insemination using sexed or conventional semen based on automated activity monitoring of estrus in Holstein heifers. Animals. 13(19), 2994. https://doi.org/10.3390/ani13192994
- Plenio, J.L., Bartel, A., Madureira, A.M.L., Cerri, R.L.A., Heuwieser, W., & Borchardt, S. 2021. Application note: Validation of BovHEAT — An open-source analysis tool to process data from automated activity monitoring systems in dairy cattle for estrus detection. Computers and Electronics in Agriculture. 188, 106323. https://doi.org/10.1016/j.compag.2021.106323
- Borchardt, S., Tippenhauer, C.M., Plenio, J.L., Bartel, A., Madureira, A.M.L., Cerri, R.L.A., & Heewieser, W. 2021. Association of estrous expression detected by an automated activity monitoring system within 40 days in milk and reproductive performance of lactating Holstein cows. J. Dairy. Sci. 104(8): P9195-9204. https://doi.org/10.3168/jds.2020-19705
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