The genetic sequence of the first bovine, a Hereford cow, was published in 2009. This milestone was achieved through an international collaboration with 300 scientists in 25 countries, taking over six years to complete, at a cost of more than $50 million. Since then thousands of bovine sequences have been completed as the cost of the technology continues to decline. Sequence information can be analyzed directly, used for comparing animals within a breed, or for comparing animals across breeds.
One category of genetic difference frequently used for comparison is ‘Single Nucleotide Polymorphisms’ or SNPs (pronounced ‘snips’). SNPs are used as genetic markers to track the ancestral heritage of regions of DNA or of individual animals. SNPs also can be used to predict the likelihood that a given animal will possess an individual or a series of trait(s). The latter can only occur once a SNP or a collection of SNPs is linked to a particular trait.
In our projects, genotype information from a wide range of beef and dairy breeds are used to develop accurate genomic predictions to assess the genetic potential of individual animals for various production, health, and quality traits. This information will, in turn, be used to make genetic improvement in Canada's cattle populations.
Low-density (and low-cost) tests have developed that allow an animal's entire genome to be inferred from a comparatively small number of SNPs, thereby giving valuable information as to its breeding value. Our projects work with scientists (and data) from around the world, as well as leading Canadian seedstock organizations.
Livestock Gentec is currently involved in more than 30 bovine projects, many of which include collaborations with scientists at leading institutions, nationally and internationally. For more information on the individual projects listed below, please contact our management team or the principal investigator(s) directly.
|Project Title||Principal Investigator||Duration||Research / Strategic Goal|
|Performance validation of RFI selected cattle under extensive cow/calf production systems. (Mattheis Ranch Project)||Bork, Edward||2014-2017||Efficiency|
|The practical application and development of easy to use genomic selection tools for breed improvement in the Canadian beef breed associations.||Crowley, John; Latimer, Michael (CBBC)||2014-2017||Knowledge Translation|
|Genetics of the eating quality of high connective tissue beef.||Bruce, Heather||2015-2017||Quality|
|Genomic approaches to the control of Bovine Respiratory Disease Complex.||Plastow, Graham; Orsel, Karin (UCVM)||2015-2017||Health|
|Incorporating genomic information to improve carcass quality and reproduction traits in beef cattle.||Plastow, Graham; Stewart-Smith, Jennifer (Beefbooster)||2015-2017||Efficiency, Quality|
|Improving the annotation of genetic variation associated with feed efficiency and methane yield in beef cattle.||Plastow, Graham||2016-2017||Efficiency|
|Improvement of cow feed efficiency and the production of consistent quality beef using molecular breeding values for RFI and carcass traits. (Kinsella Project)||Plastow, Graham||2013-2018||Knowledge Translation|
|DNA-based biomarkers for feed efficiency in beef cattle- Walsh Fellowship Program.||Li, Changxi||2014-2018||Efficiency|
|Identifying functional SNPs to enhance genomic prediction accuracy for feed efficiency and carcass merit traits in beef cattle.||Li, Changxi||2014-2018||Efficiency|
|Methane emissions from beef cattle bred for low RFI.||Basarab, John||2014-2018||Efficiency|
|Genetic improvement of feed efficiency and reducing methane emissions for dairy cows to support "green Alberta milk".||Wang, Zhiquan||2015-2018||Efficiency|
|Production and testing of PUFA-BHP in beef II: optimizing diets, NIRS predictions, rumen bacterial profiles, and human health implications.||Guan, Leluo (Co investigator)||2015-2018||Health|
|Systematic study on the relationship among rumen microbial lipid metabolism, meat beneficial fatty acids, and meat quality in beef cattle.||Guan, Leluo||2015-2018||Quality|
|Using predicted and residual ruminal volatile fatty acid concentrations to predict feed efficiency, carcass yield, and carcass composition in beef cattle.||Guan, Leluo||2015-2018||Efficiency, Quality|
|Breeding strategies for improving feed efficiency and reducing methane emissions in dairy cattle.||Baes, Christine (UofGueph)||2016-2018||Efficiency|
|Enhancing bioavailability of human inedible crop byproducts and lowering carbon footprint for sustainable dairy production.||Guan, Leluo||2016-2018||Efficiency|
|Genetic variations associated with feed efficiency and methane yield in beef cattle.||Plastow, Graham||2016-2018||Efficiency|
|Assessment of rumen microbiota in beef cattle with different feed efficiency on grazing rangeland.||Guan, Leluo||2017-2018||Efficiency|
|Evaluating the biological basis of feed efficiency to create tools that can assist selection for feed efficient lactating cows.||Wang, Zhiquan; Plastow, Graham||2017-2018||Efficiency|
|Producer Extension Sessions (EnVigour HX).||Stothard, Paul||2017-2018||Knowledge Translation|
|Testing for signatures of selection in Canadian BSE cases.||Plastow, Graham; Czub, Stephanie (AAFC)||2017-2018||Health|
|The application of genomics into the commercial cow/calf sector of the beef industry.||Stothard, Paul||2017-2018||Knowledge Translation|
|Canadian Agriculture Adaptation Program (CAAP2)||Crowley, John; Latimer, Michael (CBBC)||2015-2019||Knowledge Translation|
|Development and deployment of MBVs/gEPDs for feed efficiency and carcass traits that perform in commercial cattle.||Basarab, John||2015-2019||Efficiency, Quality|
|Increasing feed efficiency and reducing methane emissions through genomics: a new promising goal for the Canadian dairy industry.||Stothard, Paul; Miglior, Filippo (UofGuelph)||2015-2019||Efficiency|
|Development and application of functional genomic prediction for feed efficiency and carcass traits in beef cattle.||Li, Changxi||2016-2019||Efficiency, Quality|
|Development of an integrated model to predict longevity of beef cows.||Li, Changxi||2016-2019||Health|
|gGreenBeefcow: ldentifying and validating genomic and fecal microbiome markers for low methane emissions in beef cattle.||Fitzsimmons, Carolyn||2016-2019||Efficiency|
|Assessment of rumen microbiota in beef cattle with different feed efficiency on grazing rangeland.||Guan, Leluo||2017-2019||Efficiency|
|Evaluating a new tool (GGP-F250) for improving accuracies of gEPDs for production efficiency in commercial beef cattle.||Basarab, John; Plastow, Graham||2017-2019||Efficiency|
|Optimize heterozygosity in composite and crossbred beef populations using genetic and genomic tools.||Basarab, John; Plastow, Graham||2017-2019||Efficiency|
|Genetic analyses of feed intake, feed efficiency, female fertility, and cow lifetime productivity in beef cattle raised under two environments.||Basarab, John; Li, Changxi||2017-2023||Efficiency|
|Elucidating the biological basis of feed efficiency to create tools that can assist selection for feed efficient lactating dairy cows.||Plastow, Graham||2017-2020||Efficiency|