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ARS Home » Plains Area » Clay Center, Nebraska » U.S. Meat Animal Research Center » Genetics and Animal Breeding » Research » Publications at this Location » Publication #326665

Title: A reduced panel to determine beef cattle breed composition

item Kuehn, Larry
item Snelling, Warren
item Lindholm-Perry, Amanda

Submitted to: International Society for Animal Genetics (ISAG)
Publication Type: Abstract Only
Publication Acceptance Date: 4/22/2016
Publication Date: 7/23/2016
Citation: Kuehn, L.A., Snelling, W.M., Lindholm-Perry, A.K. 2016. A reduced panel to determine beef cattle breed composition [abstract]. International Society for Animal Genetics (ISAG). Abstract Book. p. 32 (Abstract #P1036). Available:

Interpretive Summary:

Technical Abstract: The advent of high density marker arrays has revolutionized genetic prediction and selection in beef cattle. In addition to genetic prediction, these marker arrays can be useful for deriving breed composition of cattle with unknown origins. Using marker arrays with thousands of markers, we are able to predict breed composition with high (>95%) accuracy using multiple regression on known breed frequencies for each marker. Knowledge of breed composition can help with traceback and management objectives, but the cost of buying a marker array can be prohibitive, especially for commercial animals. With low cost tools, such as genotyping by sequencing, it may be possible to estimate breed composition at a significantly lower cost using fewer markers. Our objective was to develop a reduced panel of markers (400 or less) that could accurately predict breed composition. This panel was a subset of markers from a large commercially available array with over 770,000 SNP; approximately 500 animals from 9 different breeds (Angus, Hereford, Red Angus, Shorthorn, Charolais, Simmental, Gelbvieh, Limousin, Brahman) that had been genotyped using this array. The markers for the reduced panel were selected as the marker with the highest FST over 20 Mb intervals. Because Hereford and Brahman were the most genetically distant breeds, they were excluded from FST calculations. In total, 350 SNP markers were selected for the panel. Efficacy of the marker set was tested on a set of crossbred animals with known pedigrees. The correlation between pedigree and panel-predicted breed composition was 0.96. Performance was similar for a panel of 145 SNP (r = 0.93-0.95) selected from these 350. A random set of 120 SNP markers from the 770,000 SNP array achieved a correlation of 0.88 with pedigree breed composition. A reduced panel of markers can effectively predict breed composition with lower overhead costs relative to high-density arrays. The USDA is an equal opportunity employer.