Genotyping efforts in the Efficient Dairy Genome Project
The Efficient Dairy Genome Project (EDGP), led by Filippo Miglior at the University of Guelph and Paul Stothard at the University of Alberta, aims to reduce methane emissions (ME) and increase feed efficiency (FE) in dairy cattle by providing genomics-based tools to support selective breeding for these traits. Key to these efforts is collecting individual daily feed intake and methane emission data for cows and heifers in Canada as well in partner countries. With the addition of DNA information, genomic estimated breeding values (GEBVs) will be a much more impactful tool for producers in helping them reach their profitability and breeding goals.
At PAGXXVI, Stothard presented an update on the genotyping side of the project, focusing on work being done to add structural variants (SVs) to the picture. SVs contribute to a large proportion of the genetic variation in cattle but have been largely ignored because they are more difficult to detect than single nucleotide polymorphisms (SNPs). However, it is known from ongoing research, particularly in humans, that SVs have an important impact on phenotype. To begin to understand the influence of SVs on FE and ME, the team analyzed whole-genome sequences from over 500 dairy and beef cattle, the latter through a collaboration with the Sustainable Beef project led by John Basarab. Using high-performance computing and new software for detecting and visualizing SVs, the team has built one of the most complete and well-characterized SV collections to date. This resource will allow us to examine the influence of specific SVs on FE and ME, and could lead to the generation of more accurate GEBVs as well as a better understanding of which genes contribute to variation in these traits.
Amassing a large collection of phenotypic measurements is paramount to these efforts. An exciting recent development in this regard was the installation of 100 GrowSafe bins at Sunalta Farms in Ponoka, Alberta, which will provide the feed intake information on over 300 cows per year. Another important step towards delivering GEBVs was the creation of a centralized database for integrating the data from Sunalta Farms with similar information collected from research herds at the universities of Alberta and Guelph as well as by research partners in the US, UK, Denmark, Australia, and Switzerland. Over the next two years, the team expects to have FE and ME data on more than 8,000 and 3,500 cows, respectively. Although much work remains to be done, the project is well on track to deliver the tools needed to improve these challenging but important traits.