86 Building industry-academic collaborations to use genetic technologies for solving challenges in the beef industry.

Abstract From a genetic improvement perspective, the overarching challenge in the beef industry is its segmented nature, where there is limited flow of animal performance information from later to earlier stages of the production system. For instance, often there is limited animal performance information passed from the feedlot stage back to the commercial cow-calf producer (and to the backgrounder in between) and ultimately back to the seedstock supplier. In a perfect system, information would be transferred along with value signals from the end user up through the production chain to incentivize the genetic improvement of economically relevant traits. Except for a limited number of vertically integrated production and progeny test programs, most of the industry is subject to this data disconnect. This issue remains a concern for the Beef Improvement Federation, where producers, industry-affiliated professionals, and academics gather annually to facilitate the overall genetic improvement of the beef industry, providing a unique opportunity to develop cooperative research programs. Even with these efforts, the lack of data transfer makes the evaluation of emerging traits of economic relevance in late-stage segments of the production chain even more difficult to improve at the seedstock level—the driver of industry genetic improvement. Traits such as susceptibility to bovine respiratory disease, the more recent bovine congestive heart failure, and environmental sustainability-related traits remain challenging. Still, partnerships amongst these groups are helping to leverage information collected at later stages of production. While funding for these partnerships is challenging, relationships amongst academics, producer-centric industry organizations, and industry-service providers have increasingly provided a mechanism for the development of tools for the seedstock and commercial breeders to improve these late-stage traits, overall animal performance, and industry success. The transfer of data is being facilitated by the use of genomic technologies that are able to, at least partially, bridge the lack of data flow from one segment of the beef industry back to the previous segment. With that transfer of genomic information, individual animal performance information (e.g. bovine congestive heart failure incidence, methane emission rate, etc.) can contribute to selection tools used at the seedstock and commercial breeding levels, increasing ability to accurately select breeding animals and create genetic improvement for these new traits.