<Back to projects listing

Detecting detrimental genetics in the Canadian dairy herd


molecules image

Project Overview

Dairy breeding programs have successfully increased production levels over the past decades, with novel technologies allowing efficient selection of animals with desirable physical and genetic characteristics. This selection process has increasingly led to the mating of related animals, and the long-term consequences of this approach remain unclear. Furthermore, young, genomically tested breeding stock may be widely used with far-reaching impacts on the genetic makeup of the Canadian dairy cattle population. There is a need to understand genetic mutation and recombination rates, and determine which characteristics are frequently inherited together (haplotypes) in managed breeding programs.

The overall objective of this project is to develop a national strategy to rapidly identify, understand and manage detrimental genetic mutations to prevent rapid spread across the Canadian dairy population. This research aims at improving detection and management of detrimental genetics in Canadian dairy cattle for greater efficiency and profitability.

What Will the Research Team Do?

The research team will; (i) develop a monitoring system for detrimental genetic mutations using industry partnerships to ensure confidentiality; (ii) undertake genetic analysis of frequently used Canadian bulls and use data simulations to predict genetic mutation, recombination rates, and their economic consequences; and (iii) develop knowledge transfer materials to ensure information is available to Canadian dairy industry stakeholders.

The objectives of this project are to:

  1. Develop a rapid-response feedback system in which detrimental haplotypes will be identified before their frequency in the population increases. 
  2. Develop a reference dataset of segments of chromosomes that are inherited more often, as well as of more common recombination points within the genomes of the dairy population using analysis of both actual and simulated data sets (genomic architecture of homozygosity). 
  3. Identify and quantify potential financial implications of implementing various strategies to manage homozygosity; Develop integrated system analysis tools to quantify the impacts and the trade-offs associated with various strategies.
  4. Integrate results into developing educational and extension materials and conduct training for future dairy production workforce, stakeholders, and public outreach. 

Principal Investigators

Christine Baes
University of Guelph


Filippo Miglior

Flavio Schenkel
University of Guelph 

Brad Eggink
Holstein Canada

Key Words

  • Genetic mutations, rapid detection, management, Holstein

Period: 2023-2028
Budget: $899,990

Last Updated: June 17, 2024

Funding Partners