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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #361461

Research Project: Improving Dairy Animals by Increasing Accuracy of Genomic Prediction, Evaluating New Traits, and Redefining Selection Goals

Location: Animal Genomics and Improvement Laboratory

Title: Genomic predictions for crossbred dairy cattle

item Vanraden, Paul
item TOOKER, MELVIN - Former ARS Employee
item CHUD, TATIANE - Universidade Estadual Paulista (UNESP)
item NORMAN, H - Council On Dairy Cattle Breeding
item MEGONIGAL, JR, JOEL - Council On Dairy Cattle Breeding
item HAAGEN, ISAAC - Pennsylvania State University
item WIGGANS, GEORGE - Council On Dairy Cattle Breeding

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/14/2019
Publication Date: 2/1/2020
Citation: Van Raden, P.M., Tooker, M.E., Chud, T.C.S., Norman, H.D., Megonigal, Jr, J.H., Haagen, I.W., Wiggans, G.R. 2020. Genomic predictions for crossbred dairy cattle. Journal of Dairy Science. 103(2):1620–1631.

Interpretive Summary: Over 50,000 crossbred animals have been genotyped, and commercial producers want to test and select their whole herds based on genomic evaluation. Genomic breed base representation (BBR) was computed for all animals in the national database, imputation strategies for crossbred genotypes were compared, and crossbreds were evaluated using BBR to weight marker effects computed for each pure breed. Crossbred genomic PTA were correlated by about 0.91 compared with those from a common set of marker effects for all breeds. The methods developed allow more accurate genomic predictions for crossbred animals containing any of the 5 dairy cattle breeds routinely evaluated.

Technical Abstract: Genomic evaluations are useful for crossbred as well as purebred populations when selection is applied to commercial herds. Genomic breed composition was estimated from 60,671 markers using the known breeds of daughter-proven Holstein, Jersey, Brown Swiss, Ayrshire, and Guernsey bulls as the five traits (breed fractions) to be predicted. In initial research, genotypes of 6,296 crossbred animals were imputed from lower density chips together with either their 3,119 ancestors or all 834,367 genotyped animals. Estimates of breed composition were adjusted so that no percentages were negative or exceeded 100 and the breed percentages summed to 100. A final adjustment was applied to set percentages above 93.5% equal to 100% and the resulting value was termed breed base representation and implemented in 2016. The crossbreds included 733 Jersey x Holstein crossbreds with >40% of both breeds (F1 crosses), 55 Brown Swiss x Holstein F1, 2,300 Holstein backcrosses with >67% and <90% Holstein, 2,026 Jersey backcrosses, 27 Brown Swiss backcrosses and 502 other crossbreds of various combinations. Larger percentages of alleles were imputed by using a crossbred reference population rather than the closest purebred reference. Crossbred predictions were averages of genomic predictions computed using marker effects for each pure breed, weighted by the animal’s genomic breed composition. The marker and polygenic effects were estimated separately for each breed on the all-breed scale instead of the within-breed scales previously used. For crossbreds, genomic predictions weighted by breed base representation were more accurate than parent average and slightly more accurate than predictions using only the predominate breed. For purebreds, single-trait predictions using only within-breed data were as accurate as multiple-trait predictions treating allele effects in different breeds as correlated effects. The crossbred genomic predicted transmitting abilities will aid producers in managing their breeding programs and selecting replacement heifers.