Beef researchers developing genomic prediction tool

Researchers with Agriculture Canada and the University of Alberta’s Livestock Gentec are working together to develop a genomic prediction tool that could help Canadian beef producers build more efficiency, carcass quality and profitability into the national herd.

Livestock Gentec research scientist Changxi Li said they’re asking producers to submit hair, tissue or blood samples as well as birth dates, birth weights and age from both crossbred and purebred animals for the trial.

“Beef genomics analyzes the relationship between genetic makeup of cattle and traits and uses the data to develop tools to assist in beef herd breeding and management,” Li said.

He said the process links DNA markers already on record with the accompanying traits.

“Then we use these DNA markers to predict another animal’s traits if they have the same or similar DNA markers,” he said.

Traditional expected progeny difference measurements are similar, but Li said the predicted values determined using molecular genetics are called molecular EPD.

Li said using Canadian cattle DNA is important.

“Accuracy improves if you use a reference population which is closely related to the animal you’re trying to predict,” he said.

“The more Canadian cattle test results that are available for study, the more accurate the Genomic Prediction tool for the Canadian herd will be.

“The accuracy of genomic prediction of most economically relevant traits in Canadian beef cattle ranges from .30 to .60 depending on how related an animal is to the reference population.… These prediction equations provide a means for producers/breeders to start improving important traits such as feed efficiency (residual feed intake, dry matter intake) and growth (average daily gain) as well as carcass traits including carcass weight, rib-eye area, lean meat yield, average back fat thickness and marbling, some of which are currently expensive and difficult to measure.”

Project research assistant Michael Vinsky said one of the greatest advantages of this tool is not needing a pedigree to predict an animal’s traits, which is the case with traditional EPDs.

“This means unregistered cattle, crossbred cattle or cattle with no performance records can have their traits predicted.”

He said commercial producers with unregistered animals would then be able to predict their cows’ feed efficiency, growth and carcass traits to some degree when they might otherwise have nothing.

Vinsky said producers will be able to collect data on trait prediction as early as a few weeks after birth and be able to make decisions faster about which animals to keep to optimize the traits they most want.

For more information, contact Vinsky at mvinsky@ualberta.ca.

About the author

Comments

explore

Stories from our other publications