Making DNA Analysis Results Useful to Producers through the Development of EPDs that Incorporate Genomic and Performance Information

This project will develop a new approach to beef cattle selection, one that allows producers to use genomics in a way that ties results together with those of existing evaluations, making selection for profitable animals much more feasible.

Date of Submission:	July 15, 2010
Total Budget:	$677,820
Total Amount Requested from Genome Alberta/ALMA (less than $500k):	$464,600
Project Duration:	3 years

Project Leader(s)	Mike McMorris Beef Improvement Opportunities 205-660 Speedvale Ave. West Guelph Ontario, N1K 1E5	Zhiquan Wang University of Alberta 1400 College Plaza 8215 112 Street, Edmonton AB, T6G 2C8
Co-Applicant(s)	Name	Affiliation
	Stephen Miller	University of Guelph
	Stephen Moore	University of Alberta
	Stewart Bauck	Merial
	Bruce Holmquist	Canadian Simmental Association
	Anne Brunet-Burgess	Canadian Limousin Association
	Elisa Marques	Beefbooster Inc.

Project Summary
The next wave of technology available to livestock producers, including beef producers, is genomics. Genomics involves the analysis of a tissue sample (DNA) to estimate genetic merit for economically important traits. This new technology allows us to estimate genetic merit for existing traits earlier in life; for new traits; and more accurately for traits that we currently evaluate.

Beef producers, however, are faced with yet another set of numbers that do not integrate with existing genetic evaluations. Confusion and poor selection decisions will continue until someone makes sense of the numbers.This project will develop a new approach to beef cattle selection, one that allows producers to use genomics in a way that ties results together with those of existing evaluations, making selection for profitable animals much more feasible.
Genomic test results offer estimates of genetic merit for a number of traits. As do genetic evaluations derived from traditional performance measurement programs, these estimates carry an accuracy level of less than 100%. Accuracy can be expected to increase over time as panels are refined and perhaps developed for specific populations of cattle. Accuracy is important since it has a direct positive impact on genetic change that can be expected from selection. Combining the results of genomic tests with those of performance measurement will increase accuracy as well as genetic gain. Comprehensive genomic analysis of a population is cost prohibitive. Emerging methodology using imputation can provide near maximum results at a mere fraction of the cost.
This project will see key animals genotyped with the more fulsome 50K panel and an additional larger number with the 3K panel. Through imputation, we will build
a reference population allowing producers to use the cheaper panel while attaining excellent return on investment.