|Hayes, B -|
|Bowman, A -|
|Chamberlain, A -|
|Savin, K -|
|Van Tassell, Curtis|
|Goddard, M -|
Submitted to: PLoS One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 7, 2009
Publication Date: August 18, 2009
Repository URL: http://hdl.handle.net/10113/37779
Citation: Hayes, B.J., Bowman, A.J., Chamberlain, A.J., Savin, K., Van Tassell, C.P., Sonstegard, T.S., Goddard, M.E. 2009. A validated genome wide association study to breed cattle adapted to an environment altered by climate change. PLoS One. Aug 18:4(8)e:6676. Interpretive Summary: In the coming decades, climate change will be a major challenge to continued production of food in many parts of the world. Certain regions of Australia and the U.S. where dairy production has been established are likely to be particularly badly affected. Another major challenge to milk production could be a scarcity of high energy feeds such as grain due to both reduction in the area of land suitable for cropping and competition with the biofuels industry. One way of preparing the dairy industry for these changes is to select for cattle that will be adapted to the new production systems. We made use of the large differences in climate and levels of feeding which already exist across Australian dairy farms to find genetic markers for the “sensitivity to environment” of milk production. The markers we discovered should aid more rapid selection for cows whose milk production is less affected by rising temperatures, and for cows which milk better on low quality feed.
Technical Abstract: Continued production of food in areas predicted to be most affected by climate change, such as dairy farming regions of Australia, will be a major challenge in coming decades. Along with rising temperatures and water shortages, scarcity of inputs such as high energy feeds is predicted. Genomic selection is a new technology that can be used to select animals that will produce more food under these difficult conditions than existing animals. We conducted a genome wide association study to detect SNPs associated with the sensitivity of milk production to environmental conditions. To do this we combined historical milk production and weather records with dense SNP genotypes on dairy sires with many daughters milking across a wide range of production environments in Australia. A cluster of significant SNPs on chromosome nine, validated in a different breed of dairy cattle, implicate a promising candidate gene The validated SNPs we have reported here will aid selection for high milk production under anticipated climate change scenarios, for example selection of sires whose daughters will be most productive at low levels of feeding.