Sheep Industry News August 2023

A Journey in Sheep GEMS

RON LEWIS University of Nebraska-Lincoln T he GEMS in Sheep GEMS

WHERE ARE WE AT? Sheep GEMS is in its early days. It began about a year and half ago. To fully evaluate ewe performance across a production season, we need her records collected around breeding, lambing and weaning. With many flocks breeding in the fall, we are just now gathering our first full season of production data. Industry engagement has been good. Performance records on 17 Katahdin, eight Polypay, seven Rambouillet, and 11 Suffolk flocks have been received so far. We antici pate a few more NSIP flock owners in these breeds submit ting their data shortly. In addition, flock records on these same four breeds are being generated at three collaborating USDA/ARS facilities: the Dale Bumpers Small Farms Re search Center, the U.S. Meat Animal Research Center and the U.S. Sheep Experiment Station. We have also collected substantial genomic – molecular – information. Genotypes on more than 12,000 animals are already available, most substantially in Katahdin (10,231), Rambouillet (929), and Polypay (854) sheep. More than half of those genotypes were collected as part of Sheep GEMS. Most exciting is that during the next couple of years – as we complete our data collection – we will generate a large, unique dataset to thoroughly evaluate robustness, climatic resilience and other key novel traits in our American sheep flocks. WHAT ARE SOME EARLY OUTCOMES? Although using molecular information in genetic evalu ation has become routine in many livestock species, its uptake is more limited in sheep. In part, that is because of the higher cost of genotyping relative to the value of an in dividual animal. One way to save on costs is to use a single genotyping platform to generate more molecular-based information. In Sheep GEMS, the genotyping platform used is a medi um-density array with about 50,000 genetic markers. With the genomic information collected with this platform, we can achieve several aims. We can more accurately estimate breeding values – called genomic prediction. We can verify parentage. We can also determine genetic conditions. Using this 50K array, we have developed and validated a reliable way to

means Genetics, Environment, Management and Socioeco

nomics. The interplay amongst those elements of a produc tion system is the underpinning for this project. Our specif ic focus is to enhance the sustainability of these systems by genetically improving the robustness and climatic resilience of our sheep flocks. Why so? Our industry consists of a variety of breeds raised across a range of geographies that not only differ in their climatic conditions, but in their management practic es. Breeding robust animals that perform well under these conditions is thereby key. The challenge is that nearly half – 44 percent – of U.S. ewes are culled prematurely for reasons other than age. Approximately 7 percent of the total American lamb crop dies each year from non-predator related causes. Clinically healthy ewes yet with high somatic cell counts in their milk cause economic losses of $19 to $32 per ewe. More than 20 percent of mature ewes in most commercial flocks have been diagnosed with high somatic cell counts, emphasizing its consequences on ewe productivity. One way to reduce the impact of these challenges is to breed for greater sustainability. Currently, though, traits that define robustness and climatic resilience are largely ab sent in domestic genetic evaluations. By working with sheep producers engaged in the National Sheep Improvement Program and U.S. Department of Agriculture Agricultural Research Service facilities with sheep programs, through Sheep GEMS we intend to address this limitation. By evaluating traits indicative of robustness and climatic resilience – namely lamb survival, ewe longevity, udder health and gastrointestinal parasite resistance – in both in dustry and research flocks, we plan to develop tools Ameri can sheep producers can use to incorporate sustainability into their breeding goals. This includes using genomic information to estimate breeding values more accurately for these new traits, as well as those already included in NSIP.

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